Mapping Research Trends in Pulsed Electric Field Technology Applied to Biogas Production: A Comprehensive Bibliometric Analysis

Abstract

This study provides a comprehensive review of the application of pulsed electric field (PEF) technology as a pretreatment method for enhancing biogas production from various organic substrates. A comparative bibliometric analysis was conducted using four databases, Web of Science Core Collection, Scopus, Dimensions, and Google Scholar, to evaluate research activity, interdisciplinarity, and geographic distribution of PEF-related literature. The results show that, although biomass pretreatment research has grown considerably over the past two decades, the number of studies focused specifically on PEF remains extremely low, accounting for less than 0.5% in each database. A detailed overview of 66 studies further confirms PEF’s potential to improve methane yield through substrate disintegration and microbial community enhancement, yet highlights the need for standardization and scalability. Optimization studies reveal promising outcomes, particularly for sludge and algal substrates, though most were limited to laboratory scale. Two full-scale studies demonstrated economic feasibility, yet long-term stability, energy balance, and integration into existing anaerobic digestion systems remain underexplored. The analysis of author countries and institutions shows that research is concentrated in China, Sweden, and France. Overall, this review identifies major research gaps and outlines future directions aimed at including a more diverse range of substrates, improving comparability, and validating PEF in real-scale biogas production systems.

1. Introduction

A continuous rise in global demand for additional energy sources has triggered a search for alternatives, and biogas has emerged as a promising option. Biogas, a renewable and sustainable energy source, is produced from organic material through a process called anaerobic digestion (AD) [1]. AD is a biochemical process in which complex organic matter is biodegraded through a series of phases to simpler forms employing microorganisms in the absence of oxygen, producing a gaseous blend comprising mainly methane (50–75%) [1,2]. Digestate, a secondary product of AD, is rich in macronutrients, such as nitrogen and phosphorus, in both organic and inorganic forms. Also, digestate may contain micronutrients that can improve soil fertility and functionality. Such digestate properties could cover plant needs over a longer time compared to mineral fertilizers [3]. A wide range of substrates can be utilized for biogas production. The selection of substrate directly influences the biogas yield and quality. Depending on the substrate type, different processing and pretreatment methods can be applied. Generally, feedstock can be classified into two categories: lignocellulosic and non-lignocellulosic biomass. Non-lignocellulosic biomass comprises different wastes of animal, organic industrial, and domestic origin. These feedstocks are easily degradable but can contain contaminants, such as pathogens, toxic compounds, antibiotics, and heavy metals, which can negatively impact the performance and survival of microorganisms in the AD reactor [4]. Lignocellulosic biomass is primarily composed of three fractions, cellulose (40–50%), hemicellulose (25–35%), and lignin (15–20%) [5], which are interconnected in a matrix resistant to biodegradation. The quantity of all three constituents varies from plant to plant, as well as their origin. Generally, lignin is the most resistant to degradation among cellulose and hemicellulose. If present in large quantities, lignin may represent an issue in the biogas production process, as it hinders the bioconversion of lignocellulose to methane. An essential aspect of biogas production efficiency from lignocellulose biomass lies in the application of pretreatment methods before AD. To be considered effective, a pretreatment method must incur minimal investment and operating costs and must be economically viable and environmentally friendly, and sustainable. Also, an important aspect of the pretreatment step is aimed at reducing or eliminating fermentation inhibitors, e.g., lignin-derived compounds that may hinder microbial activity and inhibit AD [6]. Among the various pretreatment methods being researched, pulsed electric field (PEF) technology has gained increasing attention due to its potential to improve the efficiency of biogas production [7,8]. PEF processing applications are increasingly growing in the domain of electro-magnetic technologies for use in medicine, environmental, and food applications [9]. In the food industry, where it is increasingly being commercially utilized, PEF is a non-thermal alternative to traditional pasteurization. Its ability to preserve nutritional properties while effectively inactivating microorganisms makes PEF a technology that is gaining momentum in the industrial production of liquid foods [10,11]. PEF involves the conduction of electric currents through food materials with semiconducting properties, which are in direct contact with electrodes to modify, treat, or process foods while preserving quality, enhancing functionality, ensuring safety, and extending shelf life [10]. As a non-thermal and environmentally friendly method, PEF offers several advantages over conventional pretreatment techniques, including lower energy consumption, minimal chemical use, and reduced production of inhibitory by-products [12].

Numerous studies have confirmed the broad applicability of PEF in food and environmental processing, demonstrating its capacity to induce electroporation in plant, animal, and microbial cells with relatively low energy inputs and short treatment times. For instance, PEF has been successfully applied to enhance mass transfer in meat and vegetable products, increase juice extraction yields, and reduce drying times, while preserving product quality and meeting regulatory standards. These industrial-scale applications demonstrate the scalability and versatility of PEF, providing a strong technological foundation for exploring its integration into AD systems. Although microbial inactivation via PEF requires higher energy inputs than plant tissue disintegration, the associated benefits, such as improved substrate permeability and accelerated bioconversion, may offer valuable advantages for biogas production [13].

During PEF treatment, biological membranes are exposed to short-duration, high-intensity electrical pulses that form an electric field. A sufficiently high electric field (E = 10–100 kVcm⁻¹) leads to a rapid increase in the electric conductivity and permeability of the membrane, which causes membrane electroporation—a physical phenomenon that forms pores in the cell membrane. This effect can be either reversible or irreversible [9,14]. The research is mostly focused on irreversible electroporation, including thermal pasteurization, increased extraction yields [12], tissue softening, enhanced drying [15], electrochemotherapy [16], and tumor ablation [17]. Reversible electroporation is usually applied in molecular biology for the introduction of specific molecules in vivo (e.g., plasmids and antibodies) [18,19].

Recent studies have demonstrated the effectiveness of PEF in improving biogas production from various substrates. However, while these studies highlight the benefits of PEF, the field still faces challenges in standardizing operating parameters and optimizing energy efficiency, which are crucial for large-scale applications [7,20,21]. To address these challenges and gain a comprehensive understanding of the development of the field, this review conducts a bibliometric analysis of the literature on PEF pretreatment for biogas production.

Bibliometrics play an important role in academic research by helping to explore the overall state of a research field, its developments, and its evolution. It aids in gathering and categorizing knowledge about that field and identifying gaps. The significant increase in scientific knowledge production, such as congress and journal publications, available in international databases, has created a need for such investigations across research disciplines [22,23]. Bibliometrics allows scientists to systematically analyze publication counts and gain concrete insight from extensive unstructured data. It helps map and understand the accumulation of scientific knowledge [24,25]. Furthermore, the continuous rise in scientific publications makes it challenging for researchers to stay up-to-date with newly created knowledge [22]. Therefore, well-executed bibliometric analysis can form a strong foundation in all research areas [24,25,26,27]. This approach is especially useful for tracking the development of innovative technologies, such as PEF, and evaluating their progress over time. In the context of PEF technology for biogas production, bibliometric analysis helps assess how research in this field has evolved, which areas have advanced most, and where further research is necessary. For instance, previous studies have shown that PEF’s effectiveness in enhancing biogas production varies depending on the substrate type, the PEF operational parameters (e.g., electric field strength, pulse duration, frequency, etc.), and specific process conditions [21,28,29]. By analyzing the trends in these studies over time, this approach can reveal shifts in focus, such as the growing interest in optimizing energy efficiency or comparing PEF with other pretreatment technologies [21,30]. Additionally, bibliometric analysis can uncover the geographical distribution of research, highlighting the most active regions and institutions involved in the area. Such analysis also provides valuable information that can help researchers connect and collaborate [31]. Understanding the global landscape of PEF research can provide insights into international collaborations, regional expertise, and potential opportunities for future partnerships. This is particularly relevant for a technology like PEF, which holds the potential for widespread industrial adoption but requires collaboration across different sectors and disciplines to achieve large-scale integration.

This work builds upon the author’s previous review article on the role of PEF in biogas production research [28], which provided an overview of experimental research and mechanisms of action of PEF. Expanding on that foundation, the present study employs a bibliometric approach using four major scientific databases (Scopus, WoS, Google Scholar, and Dimensions) to quantitatively explore publication trends, research domains, and global interest in this emerging topic. To date, no such bibliometric analysis has been conducted, making this study a novel contribution to the scientific development of sustainable energy technologies in biogas production.

Therefore, the specific objectives of this study are as follows:

(i)

To categorize the research output by scientific disciplines to gain insight into the degree of disciplinarity of the PEF method, understand the dominant research areas contributing to this field, and gain insight into the evolution of the field over the years.

(ii)

To evaluate and compare the bibliometric potential of four scientific databases (WoSCC, Scopus, Dimensions, and Google Scholar) with regard to their coverage, classification systems, and data overlap, and to reflect on their suitability for bibliometric research.

(iii)

To map the evolution of research activity on PEF in biogas production over time, identify publication trends, and growth. This includes a comparative analysis with other substrate pretreatment methods to show how common PEF applications are in biogas research.

(iv)

To analyze the application of PEF pretreatment among different substrate types and assess its effects on microbial community structure and activity, to understand how PEF influences both substrate degradability and microbial processes relevant to AD, and to identify under-represented substrate types in the current research field.

(v)

To examine research efforts aimed at optimizing operational parameters of PEF pretreatment for enhanced AD performance, and to evaluate the scalability of this technology across batch-, pilot, and full-scale applications, with emphasis on treatment efficiency and energy performance, and to identify gaps related to insufficiently explored parameters and underrepresented system scales.

(vi)

To compare the performance of PEF pretreatment with other pretreatment methods in terms of methane yield, substrate solubilization, and energy efficiency.

By fulfilling these objectives, this review aims to guide future research directions, contribute to cross-disciplinary dialogue and integration, and support the strategic development of sustainable bioenergy technologies.

2. Comparative Overview and Selection Criteria for Bibliometric Databases

Analysis and visualization are two basic processes that comprise the science mapping procedure [32]. The analysis part, which can be conducted by utilizing various scientific databases, calculates similarity matrices and relationships between items such as authors, words, papers, journals, etc. Afterward, the relationships and networks between the relevant items can be visualized and interpreted effectively with different interactive platforms [25,33]. Several scientific databases are available today, but they have been developed for various purposes and exhibit diverse characteristics [23]. Many studies have compared scientific databases and examined their size, the number of publications they cover, their accuracy, etc. The WoS and Scopus databases are today the two most comprehensive databases predominantly represented in the bibliometric analysis [22,23,24,31,34,35], while some authors also include Google Scholar in this group.

WoS was the first broad-based international bibliographic database. Over time, it has become the most influential bibliographic data source commonly used for journal selection, research evaluation, bibliometric analyses, and similar purposes [35]. For more than 40 years, WoS was the only source of bibliographic data [36]. WoS is a multidisciplinary citation and abstract database covering 256 fields [22]. As a citation database, it enables users to view the frequency and identity of citations for a paper or author. WoS also provides tools for identifying journal impact factors and institutional performance rankings. WoS is a selective, structured, and balanced database with complete citation links and enhanced metadata designed for various informational needs [37]. It may deliver focused results from reputable journals, resulting in a smaller search dataset compared to Scopus, which offers broader coverage [38]. Scopus is a multidisciplinary database similar to WoS. It is among the largest curated abstract and citation databases, with extensive global and regional scientific coverage. It also provides detailed author and institution profiles, generated through advanced profiling algorithms and manual curation. The reliability of Scopus has made it a popular choice for bibliometric analyses in research evaluations, landscape studies, science policy assessments, and university rankings [36].

However, the widespread recognition of WoS and Scopus has led to increased access costs, making it difficult for organizations to afford subscriptions to both [39]. Consequently, organizations often have to choose between these data sources [40]. Typically, the organization’s decision to subscribe to a particular database is mainly influenced by the metrics used in national and institutional research evaluation policies [41]. Additionally, bibliographic databases serve as the main data sources for leading global university ranking organizations. Despite frequent skepticism about the validity of these rankings, their results continue to have a significant impact on the overall prestige of universities and are essential in guiding future developments [42,43,44].

Google Scholar was launched as a search engine. Unlike WoS and Scopus, Google Scholar automatically includes any academic-looking document it finds online, even those behind paywalls through agreements with publishers [45]. According to some studies [25,46,47], Google Scholar provides broader coverage than WoS and Scopus [22], but the quality of data in Google Scholar remains a challenge, and extracting data is difficult, making it challenging to use for bibliometric analysis [22,48]. Specifically, Google Scholar was designed as a search tool, not as a data source for bibliometrics. Moreover, there are several limitations to using Google Scholar for bibliometric analysis, such as unstable data, ease of manipulation with data, limitation of advanced search form to 4 search dimensions (keywords from the title of the document or anywhere in the text, authors, source and year of publication), limitation to displaying the first 1000 search results that can be sorted only according to relevance and publication date, it does not offer any features to analyze results, etc. [46].

In addition to the well-known scientific search databases such as Scopus, WoS, and Google Scholar, many other databases are becoming increasingly popular and useful for researchers. These newer platforms offer unique features, such as access to open data, advanced analytics, or integration with modern tools for scientific communication. Examples of such databases include the following: Dimensions, Scilit, Crossref, OpenAlex, Lens, Semantic Scholar, etc.

Dimensions database is similar to WoS, Scopus, and Google Scholar in terms of indexing a wide range of content types across several research fields. Like these databases, Dimensions provides citation metrics, but also extends them to include altmetrics. With the Dimensions platform, users can quickly gain insight into connections between scholarly objects, researchers, funders, and institutions; retrieve specific article metrics, such as citation counts; and discover which fields of research are active and growing. These features may be attractive to stakeholders who are interested in tracking the impact of research output.

Web of Science, Scopus, Google Scholar, and Dimensions share a common goal of facilitating literature searches and citation analysis, but differ in terms of indexing depth, search sophistication, metadata quality, and transparency of updates.

Table 1. Comparison of key features of selected bibliometric databases.

Database	Established	Approximate Coverage (Millions)	Access	Search Capabilities	Citation Export Support	References
WoS	1964	182	Subscription	Advanced	Full support	[37,49,50]
Scopus	2004	100	Subscription	Advanced	Full support	[36,51,52]
Google Scholar	2004	389 *	Free	Not supported	Not available	[45,46,47,48,53]
Dimensions	2018	147	Partially free **	Limited	Basic support	[54,55,56]

* These data are from 2019 and may have increased since then. ** Basic search and limited metrics are freely available, while full analytical tools and advanced data require a subscription.

provides a comparative overview of the main characteristics of these four bibliometric databases, including their scope, access model, and analytical capabilities. Other databases, such as Scilit, Crossref, OpenAlex, Lens, and Semantic Scholar, offer broader coverage but lack advanced search functionalities and standardized analytical tools, making them less suitable for rigorous systematic reviews.

The author of [33] suggests in his review paper several criteria to guide researchers in choosing a database for bibliometric research, such as (i) the number of journals covered in the research field; (ii) access to the database (e.g., institutional memberships, free access, etc.); (iii) journal impact factors and their field-leading potential; (iv) the ability to download data in a format compatible with bibliometric analysis software; (v) the ability to filter data by the software that can address research questions; and (vi) the number of records that can be exported from the database. Researchers often recommend searching multiple databases. However, this frequently results in data overlap because most journals are indexed in multiple databases simultaneously, which makes the results ambiguous. Additionally, since the downloaded file formats vary from one database to another, and the downloaded information is often in different formats, it is usually not technically feasible to merge datasets and compare them.

Based on these criteria, the selection of databases for this review paper was made with careful consideration of their suitability for systematic bibliometric analysis. While initial exploratory searches were also conducted in the mentioned databases, such as Scilit or Crossref, these databases did not allow for the application of consistent and advanced search filters or could not export data in formats compatible with bibliometric tools. Therefore, due to these technical limitations and inconsistent metadata structures, they were excluded from the final analysis.

3. Search Strategy and Methodology

The research presented is non-experimental but exploratory and descriptive in scope. It involves a systematic literature search, evaluation, and synthesis of information to assess the significance of the topic and its impact on biogas research and development. The literature search was conducted using four scientific databases, as follows: Web of Science Core Collection (WoSCC), which is a part of the broader WoS database platform that includes peer-reviewed literature from multiple scientific fields; Scopus; Google Scholar; and Dimensions. Searches were performed in July 2025, focusing on records containing the specified terms within fields such as title, abstract, and author keywords. In the case of WoSCC, the search included Keywords Plus, an additional indexing feature unique to that database. It should be noted that Google Scholar does not support structured searches by title, abstract, or author keywords to the same extent as Scopus and Web of Science. Due to this limitation, Google Scholar was used in this research primarily as a supplementary database to complement the more advanced and reproducible searches performed in WoSCC, Scopus, and Dimensions. This approach acknowledges that Google Scholar’s limited search functionality makes it less suitable for systematic and fully transparent literature reviews, but valuable for capturing additional relevant publications. Boolean operators (AND, OR, NOT) were applied in the search syntax to define logical relationships between search terms, enabling a comprehensive and structured retrieval of relevant literature. However, due to differences in the search functionalities and indexing practices across the databases, search strategies were adapted accordingly. For example, WoSCC and Scopus offer advanced field-specific search capabilities and Boolean operators, including the combined use of title, abstract, and keyword fields (e.g., TS in WoSCC and TITLE-ABS-KEY in Scopus). Dimensions supports Boolean operators and enables field-specific searches primarily through its advanced query language, whereas Google Scholar provides more limited Boolean functionality and does not support structured field-specific searches to the same extent. In Google Scholar, search queries relied on the use of exact phrase matching with quotes and basic Boolean operators to approximate title-specific searches, after which all results were screened and included or excluded from analysis depending on whether they met the search criteria. To minimize potential bias arising from the less-structured nature of Google Scholar data, all retrieved records were read in full and critically evaluated, and only those directly relevant to PEF pretreatment before AD were retained for analysis. This approach ensured a broad yet focused collection of the relevant scientific literature for subsequent bibliometric analysis and qualitative synthesis. To facilitate quick reference and improve transparency, the exact search data retrieved from each database at every stage of the literature search are summarized in

Table 2. Summary of search data and records retrieved per database at each stage of the literature search.

Search Focus	Search Date	Final Number of Records Retrieved	Note
General search on PEF/electroporation (all fields)	July 2025	WoSCC: 23,922; Scopus: 38,790; Dimensions: 30,524	Provides an overview of overall PEF research activity across scientific fields
Biomass pretreatment before AD (any type of pretreatment)	July 2025	WoSCC: 11,323; Scopus: 9172; Dimensions: 6054	Allows comparison between the total number of pretreatment studies and the subset focused on PEF
PEF pretreatment before AD	July 2025	WoSCC: 27; Scopus: 25; Dimensions: 19; Google Scholar: not available—manual screening	Represents the final dataset of PEF-related studies selected for detailed analysis
Manual screening and duplicate removal	July 2025	Total relevant studies included: 66	Both the peer-reviewed and grey literature

. This tabular overview complements the detailed description provided above and offers a clear comparison across the four databases used.

First, a bibliometric analysis of published studies using PEF in different scientific fields was designed to include both the terms pulsed electric field and electroporation, combined using Boolean operators to ensure coverage of all the relevant literature. This search considered the presence of these terms in the title, abstract, and/or keywords, depending on the database. Boolean operators were used to connect related terms. In WoSCC, the search was performed using the TS field (Topic), which included the title, abstract, author keywords, and Keywords Plus. The following query was applied: TS = (“pulsed electric field” OR “electroporation”). In Scopus, the search was performed using the TITLE-ABS-KEY field, which included the title, abstract, and author keywords. The following query was applied: TITLE-ABS-KEY(“pulsed electric field” OR electroporation). In Dimensions, the search was performed using the general search interface and included both the Title and Abstract fields. The following query was applied: “pulsed electric field” OR electroporation. While Dimensions allows for more precise field-specific queries through its Domain-Specific Language (DSL), the general interface was used in this paper to maximize accessibility and replicability. Google Scholar was not utilized for this analysis due to the absence of a result count display.

In the second stage of the literature search, the focus was placed on identifying studies in which substrate pretreatment was applied before AD. To ensure comprehensive coverage, the following search terms were used in combination: biogas, anaerobic digestion, anaerobic co-digestion, anaerobic fermentation, and pretreatment. Boolean operators were used to connect related terms. In WoSCC, the TS field (Topic) was used: TS = ((biogas OR “anaerobic digestion” OR “anaerobic co-digestion” OR “anaerobic fermentation”) AND (pretreat* OR pre-treat*)). To capture all possible word variants related to pretreatment, the truncation symbol * was used. This allowed the retrieval of records containing different forms of the word, such as pretreat, pretreated, pretreating, pretreatment, and pretreatments, as well as pre-treat, pre-treated, pre-treating, pre-treatment, and pre-treatments. By applying the * wildcard after the root “pretreat”, the search strategy ensured broader results while maintaining relevance to the topic. In Scopus, the search targeted the TITLE-ABS-KEY((biogas OR “anaerobic digestion” OR “anaerobic co-digestion” OR “anaerobic fermentation”) AND (pretreat* OR pre-treat*)). In Dimensions, the general search interface was used, and it was restricted to the Title and Abstract fields. The applied query was as follows: (“biogas” OR “anaerobic digestion” OR “anaerobic co-digestion” OR “anaerobic fermentation”) AND (pretreatment OR pretreated OR pretreating OR pretreat OR pre-treatment OR pre-treated OR pretreating OR pre-treat). Google Scholar was not utilized for this analysis due to the absence of a result count display.

The third stage of the literature search aimed at studies focusing on the application of PEF specifically as a pretreatment method for substrates intended for AD. The search was designed using two conceptual groups of terms (PEF and biogas) connected via Boolean operators to ensure comprehensive coverage. Depending on the database, these terms were searched within the title, abstract, and/or keywords. In WoSCC, the search was performed using the TS (Topic) field, and the applied query was as follows: TS = (“pulsed electric field” OR “electroporation”) AND TS = (biogas OR “anaerobic digestion” OR “anaerobic co-digestion” OR “anaerobic fermentation”). In Scopus, the TITLE-ABS-KEY field was used, and the applied query was as follows: TITLE-ABS-KEY((“pulsed electric field” OR electroporation) AND (biogas OR “anaerobic digestion” OR “anaerobic co-digestion” OR “anaerobic fermentation”) AND (pretreat* OR pre-treat). In WoSCC, the search query did not include the term pretreat* to avoid excluding relevant studies that describe the application of PEF before AD without explicitly using pretreatment-related terminology. Including the truncation-based term was found to restrict the results overly, omitting studies that were otherwise topically relevant. In Dimensions, the search was performed using the general interface, and results were filtered by limiting the query to the Title and Abstract fields. The following query was used: (“pulsed electric field” OR electroporation) AND (biogas OR “anaerobic digestion” OR “anaerobic co-digestion” OR “anaerobic fermentation”). In this search, the Google Scholar database was also included. The query was structured using quotation marks for phrases and Boolean operators to combine terms. Although the platform does not fully support Boolean logic or parentheses, the following formulation was used to maximize relevance: (“biogas” OR “anaerobic digestion” OR “anaerobic co-digestion” OR “anaerobic fermentation”) AND (“pulsed electric field” OR “electroporation”). The search yielded a substantial number of results, but the exact number could not be determined, as the Google Scholar database does not provide a function to display the total number of retrieved records. As a result, all retrieved entries were manually screened, and only those directly relevant to the defined scope of the study were selected for further analysis.

In addition to the primary databases used in this review, the Scilit platform was also considered for inclusion. However, a preliminary search on the target topic yielded only 11 records, of which 2 were duplicates from the Dimensions database and 9 from Scopus. Thus, Scilit did not contribute any unique records beyond those already identified in other databases. Given its limited added value and overlap with more comprehensive databases, Scilit was excluded from the final systematic search strategy.

A bibliometric analysis was also performed to assess the worldwide research activities related to the use of PEF technology in biogas production. The analysis included a mapping of the geographical distribution of publications, which made it possible to identify the countries that are leading in the application and study of PEF as a biomass pretreatment method. A world map was created to visually represent these key contributing countries and highlight global research patterns in this area.

4. Results and Discussion

4.1. Comparative Bibliometric Analysis of PEF Research Across Databases

The first search, which encompassed results related to the utilization of PEF across various scientific fields, resulted in a considerable variation in coverage: a total of 38,790, 23,922, and 30,524 records in the Scopus, WoSCC, and Dimensions databases, respectively. These differences may indicate variations in the scope and indexing practices of the databases. WoS and Scopus both offer extensive coverage of engineering and applied science journals; however, multiple studies have shown that Scopus offers wider coverage [35,38], which is in accordance with this search. WoSCC, with a more selective database access and journal inclusion policy that prioritizes high-impact journals, returned fewer records [40]. Dimensions provided an intermediate number of records, which could be due to its broad indexing in the publications with a DOI registration [47]. These results indicate that there is strong overall PEF research activity, whereas the total number of indexed publications differs considerably across databases. For further analysis, the option to classify publications by research area was selected in each database, allowing for comparison of the PEF disciplinarity across these three databases (Figure 1).

As many studies are interdisciplinary, the software assigned multiple research areas to several studies. Although the database export revealed a wide range of research areas, only the four most prominent broader domains are presented in this paper. Numerous specific subfields were summed under these broad categories to ensure clarity and readability, as listing all individual areas would be excessive and less informative for comparative purposes. The results show that biomedical and medical sciences dominate in the Scopus database, while in both WoSCC and the Dimensions databases, biochemical and biological sciences dominate. In total, the engineering research area appears as moderately represented, while agricultural and food sciences remain the least represented.

Further analysis revealed both the historical scope and the recent acceleration of research on PEF (Figure 2). The earliest record dates back to 1955 and is found in the Scopus database. In contrast, the first record in WoSCC appears in 1960, while in Dimensions it is from 1975. However, the Dimensions database provides access to publications only from the past 50 years. From the 1990s onward, there has been a clear upward trend in the number of publications across all three databases, indicating increasing scientific interest in PEF research. The most significant growth occurs from around 2010, with Scopus showing the steepest increase. In 2024, Scopus reached nearly 3000 records. Dimensions and WoSCC show similar trends, though with lower total counts, likely due to different indexing policies and journal coverage. The apparent drop in 2025 is because the year is still ongoing, and indexing is not complete yet. It is also clear that Scopus continues to have the highest number of records to date in 2025. Overall, the data demonstrate substantial and accelerating growth in PEF research over the past two decades.

In summary, PEF has a wide range of applications, from food processing to medical treatments, environmental applications, and materials science. However, its role in biogas production is still at an early stage, and many aspects are still unexplored.

The following bibliometric analysis was conducted to present the total number of scientific publications published in WoSCC that address biomass pretreatment for enhancing AD. The goal was to compare the proportion of studies in which some form of biomass pretreatment was investigated (Figure 3a) and to compare this number with the number of scientific papers in which PEF pretreatment of biomass was applied before AD (Figure 3b). Regarding the first graph (number of publications in which any type of biomass pretreatment was conducted before AD), a significant and consistent increase in published papers is evident, particularly from 2010 onwards, with the number of publications exceeding 1000 per year in the most active period (2019–2022). The second graph that shows the annual number of WoSCC-indexed publications that specifically investigated PEF pretreatment of biomass for AD reveals a very limited number of publications, with the first publication appearing in 2011. The annual number of publications did not exceed five in any year, while the most active period occurred between 2015 and 2023. Despite the overall increase in interest in biomass pretreatment before AD in the WoSCC database, the number of studies focusing on PEF pretreatment remains exceptionally low; only 27 publications out of 11,323 were identified for any type of pretreatment. This corresponds to a mere 0.24% of the total, emphasizing a significant under-representation of PEF within the broader scientific representation. In absolute terms, the bibliometric searches retrieved only 27 PEF-related studies out of 11,323 papers related to any type of biomass pretreatment in WoSCC, 25 out of 9172 in Scopus, and 19 out of 6054 in Dimensions. By contrast, bibliometric data from [57] show that ultrasound, microwave, and steam explosion, which represent the most studied pretreatment methods for lignocellulosic biomass in the 2010–2023 period, have a substantially higher representation in the literature. Although the time frame differs from the present review, this comparison clearly highlights the marginal position of PEF relative to other emerging pretreatment technologies. These findings highlight a notable research gap and suggest strong potential for future studies aimed at validating and scaling up PEF technology in biogas production systems.

Additionally, an analysis of the publication type was conducted. Among the 27 publications retrieved from the WoSCC database, the majority were original research articles (n = 17), followed by review papers (n = 8) and conference proceedings (n = 2). This distribution indicates that most contributions in this field are based on experimental investigations, with an increasing number of review articles emerging in recent years to synthesize findings and highlight future directions. This trend may reflect a growing recognition among researchers that there is a lack of clear guidelines and frameworks in this highly interdisciplinary, promising, yet complex area of research. Notably, the majority of these publications appear in high-impact, well-ranked journals, which underscores both the scientific relevance and the increasing interest in this research domain.

To complement the absolute publication counts shown in Figure 3a,b, the data were also normalized to illustrate the relative share of PEF-related publications within the total number of pretreatment studies indexed in WoSCC. The results (Figure 3c) demonstrate that, despite a slight increase after 2009, the proportion of PEF studies consistently remains below 1% of all pretreatment research. This confirms that PEF is still a marginally represented technology in the scientific literature related to biogas production.

Following the analysis conducted using the WoSCC, a corresponding bibliometric assessment was performed in the Scopus database. The aim was to determine the total number of scientific publications related to biomass pretreatment for enhanced biogas production and to compare this number with the publications specifically focused on PEF pretreatment before AD (Figure 4). This comparative analysis provides further insight into the extent to which the PEF pretreatment method is represented in the broader context of biomass pretreatment research within the Scopus-indexed literature.

The number of publications related to any type of biomass pretreatment in Scopus (Figure 4a) exhibits a clear upward trend over the past two decades, reflecting the growing interest in optimizing biogas production processes. In contrast, Figure 4b illustrates the number of publications specifically dealing with PEF pretreatment of biomass before AD. While the total number of such publications remains relatively low, the presence of papers each year since 2009 demonstrates a steady, although modest, research interest. Despite the overall increase in interest in biomass pretreatment before AD in the Scopus database, the number of studies focusing on PEF pretreatment remains low; 25 publications out of 9172 were identified for any type of pretreatment. This corresponds to 0.27% of the total, highlighting a marked underrepresentation of PEF technology in the current research landscape. Despite its technological advantages, the low number of publications highlights the need for further research.

Further analysis of all 25 publications revealed that the majority were original research articles (n = 16), followed by a smaller number of review articles (n = 5) and conference papers (n = 4). This distribution confirms that the field is predominantly driven by experimental research, with a few reviews that synthesize results and guide future studies. Notably, the number of conference papers is higher than that in WoSCC, which may reflect broader indexing of conference proceedings in Scopus. This suggests that PEF-related research is not only being disseminated through peer-reviewed journals but is also presented and discussed within scientific and professional communities, possibly indicating a growing but still maturing area of interest.

To complement the absolute publication counts presented in Figure 4a,b, the data were also normalized to show the relative share of PEF-related publications within the total number of pretreatment studies indexed in Scopus. As illustrated in Figure 4c, the proportion of PEF studies has consistently remained below 1% throughout the entire period, with only a slight increase observed after 2008. This further confirms that, despite gradual growth in absolute numbers, PEF continues to represent a marginal research direction when compared to other biomass pretreatment approaches.

As in previous databases, the bibliometric analysis was also conducted in the Dimensions database. Although it lacks the advanced filtering capabilities and precision of WoSCC and Scopus databases, its vast content and inclusion of a wider variety of publication types, such as project reports, conference abstracts, preprints, etc., make it a valuable supplementary resource in bibliometric research. The total number of scientific publications related to biomass pretreatment for enhanced biogas production indexed in the Dimensions database was quantified. These results were then compared to the number of publications specifically focused on PEF pretreatment before AD (Figure 5). The purpose of this comparison is to assess the visibility and representation of PEF-related research within the broader context of the biomass pretreatment literature and to identify trends specific to the Dimensions database.

The data in Figure 5a show a steady and gradual increase from the late 1980s, followed by a sharp rise beginning around 2010. This growth trend continues, reaching its highest values between 2020 and 2023, which may reflect the increasing global focus on optimizing AD processes. Despite a decline in 2025, which is likely due to incomplete indexing for the current year, the overall upward trend indicates strong and growing research interest in biomass pretreatment strategies. The data in Figure 5b present the annual number of publications that specifically focus on the application of PEF as a pretreatment method before AD. The first publication occurrence appears in 2008, but consistent publishing activity begins only around 2014. The highest number of PEF-related papers was recorded in 2015 (three papers), but the trend remains uneven, with several years showing only one or no publications at all. This disparity between these two figures (Figure 5a,b) highlights the limited representation of PEF applications in the broader body of research on biomass pretreatment before AD. Despite the overall increase in interest in biomass pretreatment before AD in the Dimensions database, the number of studies specifically addressing PEF pretreatment remains low; only 19 publications out of 6054 were identified for any type of pretreatment. This accounts for 0.31% of the total, further underscoring the marginal representation of PEF technology within the broader scientific discourse. The irregular publication pattern suggests that, while scientific interest in PEF is present, it has not yet translated into sustained or large-scale research output in the Dimensions-indexed literature.

The analysis of publication types in the Dimensions database reveals that the majority of contributions related to the application of PEF pretreatment for enhancing biogas production are original research articles (n = 9), indicating emphasis on experimental studies. Additionally, seven review articles suggest an interest in synthesizing knowledge and identifying research trends in this emerging area. The presence of two conference papers suggests that the topic is still rarely featured in academic or professional events.

In addition to the absolute publication counts shown in Figure 5a,b, the data were normalized to present the relative share of PEF-related publications within the total number of pretreatment studies in the Dimensions database. As illustrated in Figure 5c, this proportion has remained consistently below 1% throughout the entire period, with only occasional fluctuations observed after 2009. These results further reinforce the finding that PEF research, despite some recent growth, continues to represent a marginal field within the broader biomass pretreatment literature.

The comparative analysis of publication trends in WoSCC, Scopus, and Dimensions databases reflects the growing research interest in biomass pretreatment before AD. All three databases show a slow and almost negligible publication rate before the year 2000, followed by a gradual increase during the 2000s, and a sharp rise after 2010, which corresponds to the global shift toward renewable energy and sustainable waste valorization. It should be noted that the Dimensions database contains publication records only from 1976 onwards, which must be taken into account when interpreting early-year trends. The peak publication period in all three databases is between 2017 and 2023. This demonstrates strong alignment in the overall scientific output across databases, reinforcing the reliability of the observed trend. Although WoSCC and Scopus both show similar patterns in terms of the shape of growth, Scopus generally presents slightly higher publication counts, especially in the 2020–2023 years. This might be attributed to the broader indexing of conference papers and regional journals. Dimensions also follows the same path, but with somewhat lower numbers before 2010. However, from 2015 onward, the publication count in Dimensions rises steeply, eventually reaching similar output levels to Scopus, particularly in 2021–2023.

The comparative visualization of PEF-related publications across these three databases reveals a consistent pattern of low research output, underscoring the niche status of this specific pretreatment approach within the broader context of biomass valorization. Two databases (WoSCC and Dimensions) show that the earliest publications addressing PEF in the context of AD appear only after 2009, with no prior entries recorded, whereas the first publication addressing PEF pretreatment of biomass aimed at AD appears in 2008. This late emergence is indicative of the relatively recent application of PEF technology in this field. The period from 2014 to 2023 marks the most active phase of publishing across all datasets, though with modest annual outputs, rarely exceeding 3–5 papers per year in any single database. Peaks occur in slightly different years depending on the platform: 2021 in WoSCC, 2018 in Scopus, and 2015 in Dimensions. It is also notable that, despite methodological and indexing differences among databases, the overall shape and timeline of PEF-related publication trends remain aligned. This convergence enhances the credibility of the observed pattern and supports the conclusion that PEF pretreatment, while promising, remains underrepresented in the scientific literature compared to more established methods. As of 2025, no entries have yet been recorded for PEF pretreatment of biomass before AD in any of the databases, likely due to indexing delays or ongoing publication processes.

In addition to these three databases, a supplementary search was conducted using Google Scholar. Despite its limitations, Google Scholar revealed a greater number of relevant publications not indexed in the other three databases. Due to the specificity of the Google Scholar database, a manual screening of all search results was performed to extract only those publications that directly address the application of PEF pretreatment for enhancing biogas production. Figure 6 presents the annual distribution of these manually selected publications.

While isolated publications appeared as early as 2004 and sporadically in the following years, a more consistent publishing activity began in 2012. A notable increase is observed from 2014 onward, with peak outputs in 2015 and 2022 (both with six publications). The years 2023 and 2024 show a slight decline compared to peak years, but maintain a relatively stable output of 4 to 5 publications per year. In contrast to curated databases such as WoSCC, Scopus, and Dimensions, Google Scholar returns a higher total number of results. This broader coverage is expected, as it includes not only peer-reviewed journal articles but also the grey literature such as technical reports, conference papers, theses, dissertations, and book chapters [58]. This inclusiveness allows for a more comprehensive overview of research engagement with PEF pretreatment. Despite the limitations of indexing precision, Google Scholar reveals that the interest in this topic has grown steadily over the past decade. Importantly, the data for 2025, although still incomplete, already shows continued activity. Compared to WoSCC, Scopus, and Dimensions, the Google Scholar dataset shows a notably broader variety of publication types, with a significantly higher number of review papers (n = 23) and the inclusion of doctoral (n = 2) and master’s theses (n = 2), which are typically not indexed in curated databases. While the number of original research articles (n = 17) is comparable to other sources, the presence of seven conference papers, along with student theses, suggests that Google Scholar captures early-stage research and informal dissemination routes more effectively. This broader representation highlights Google Scholar’s strength in mapping the full spectrum of scientific communication, particularly in emerging or interdisciplinary fields such as PEF pretreatment for AD. However, the higher number of different paper categories may also reflect looser inclusion criteria and potential overlaps, which should be interpreted with caution when conducting quantitative assessments.

4.2. Overview of the Published Studies on PEF Pretreatment Before AD

To map the scope and direction of current research on PEF pretreatment in the context of AD, a total of 66 scientific publications were manually selected from four major databases, WoSCC, Scopus, Dimensions, and Google Scholar, based on predefined relevance criteria. Each record was individually screened for relevance, and duplicates were removed. This manual search allowed the inclusion of both peer-reviewed articles and the relevant grey literature (e.g., conference papers, theses, technical reports, etc.), thereby providing a more comprehensive overview of the research field. The selected studies differ in terms of substrates, pretreatment conditions, and scale of implementation. They also reflect an increasing interest in microbial responses to PEF, comparative evaluation of PEF with other pretreatment technologies, process optimization, and scalability. Therefore, the following sections synthesize these findings across three thematic areas: (a) application of PEF to different substrates, including microbial responses to PEF pretreatment; (b) optimization of PEF parameters, scalability, and energy performance; and (c) comparisons between PEF and other pretreatment methods.

4.2.1. Substrate Types and Microbial Community Responses

The studies reviewed highlight the use of PEF technology as a pretreatment method to improve biogas production from diverse types of organic waste. These include animal manure, municipal sewage sludge, algae, lignocellulosic materials (such as straw and crop residues), and other agricultural and industrial organic residues. Research involving different manure types, such as pig slurry [20], chicken manure [21], and cow manure [59], shows promising results, with increased biogas yields compared to untreated controls. Besides manure, PEF has been tested on other substrates with positive outcomes. Many studies on municipal sewage sludge [30,60,61,62,63,64,65,66] report improved solubilization and increased substrate bioavailability, resulting in higher methane production. Lignocellulosic biomass [67,68,69,70] has also been frequently studied, with findings indicating that PEF can partially break down cell wall structures and enhance digestibility, although usually less effectively than some thermochemical methods. Algae [71,72] and food waste [65,73] have been less extensively studied, but the results suggest that PEF may boost biogas production, especially when combined with other treatments.

Many studies agree that PEF enhances the solubilization of organic matter by increasing cell membrane permeability through electroporation. This electroporation effect facilitates the release of intracellular compounds and improves substrate accessibility for anaerobic microorganisms, thereby enhancing the hydrolysis phase of AD [62,72,74]. In several experimental studies, the effects of electroporation have been visually confirmed using scanning electron microscopy (SEM), which revealed significant structural disintegration at the cellular level. Additionally, chemical analyses of lignocellulosic substrates have confirmed the disruption of fiber structure and reduction in lignocellulose recalcitrance, further supporting the role of PEF in improving substrate biodegradability [59,68,69].

An increasingly recognized aspect of PEF pretreatment is its effect on microbial communities. Since AD depends on the coordinated activity of diverse microbial populations, understanding how PEF influences microbial dynamics is essential, especially in long-term and large-scale systems. Emerging evidence indicates that PEF not only enhances substrate solubilization but can also positively affect microbial structure and function, supporting more efficient biogas production. The effects of PEF pretreatment on microbial communities have been investigated in both batch-scale and pilot-scale studies, providing insight into how microbial structure and activity respond to this technology under different operational conditions.

Several batch-scale studies have demonstrated the beneficial effects of PEF on sludge digestibility and biogas yield. For example, refs. [75,76] showed that PEF enhances the solubilization of organic matter and increases methane production. The authors of [65] performed a batch-scale AD using low-voltage PEF pretreatment (0.3–0.9 V) with biochar derived from anaerobically digested biogas residue. The results indicate that an external voltage of 0.3 V, coupled with 5 gL⁻¹ of biochar, elevates methane yield by 45.5% compared to biogas residue biochar alone, and the coupled approach increased biogas production by up to 143% within 10 days. Microbial analysis revealed an enrichment of hydrogenotrophic methanogens, particularly Methanobacterium, facilitating more efficient direct interspecies electron transfer (DIET). The approach also improved biogas quality, accelerated volatile fatty acid utilization, and enhanced ammonia nitrogen removal during start-up. These results highlight the potential of electro-stimulated biochar to intensify methanogenic activity, valorize digestion residues, and support scalable improvements in AD performance. These insights further highlight the relevance of understanding microbial shifts induced by PEF and their implications for process optimization. In addition to conventional PEF studies, related research has also explored the impact of other types of electric fields on microbial communities. For example, ref. [77] investigated extremely low-frequency (ELF) electric fields (1–500 Hz) applied to activated sludge from wastewater treatment plants. Their results demonstrated that exposure to low-intensity fields (4–6 Vm⁻¹) stimulated microbial metabolism and accelerated pollutant removal, suggesting that electric field stimulation can enhance microbial activity even outside the context of AD. Although this study did not focus on biogas production, it supports the broader notion that electric fields can modulate microbial processes and thereby provide valuable insights into the mechanisms underlying PEF-enhanced AD.

Several pilot-scale studies have also examined microbial responses to PEF pretreatment under more realistic operational conditions, providing further insight into its applicability in scaled-up AD systems. The authors of [78] conducted a pilot-scale study investigating the effect of PEF pretreatment on thickened WAS. Although the study did not include a detailed microbial analysis, it reported a 16% increase in methane production compared to untreated sludge, along with improvements in the solubilization of organic matter. Notably, the authors also emphasized the energetic performance of the system, which achieved an energy return on energy invested (EROEI) greater than 30, meaning that, for every unit of energy consumed by the PEF system, over 30 units were recovered as energy in the form of methane. These findings demonstrate the strong potential of PEF as an energy-efficient pretreatment technology for enhancing AD in wastewater treatment facilities.

A unique and notable contribution comes from the full-scale study by [79], who applied a focused pulsed (FP) pretreatment system, which is based on PEF technology, at the Mesa Northwest Water Reclamation Plant in Arizona, USA. The system was integrated between sludge thickening and anaerobic digesters to treat a blend of primary and secondary sludges. This commercial unit was one of the first examples of PEF technology applied continuously at full operational scale. According to the New York State Energy Research and Development Authority (NYSERDA), the FP unit began regular operation in April 2007, processing up to 85% of the daily sludge flow. The results were notable: soluble chemical oxygen demand (SCOD) increased by 158%, dissolved organic carbon (DOC) rose by 117%, and biogas production improved by up to 40% compared to the baseline operation. Additionally, the volume of biosolids sent for disposal was reduced by approximately 17–30%, depending on operating conditions. Importantly, the study also examined the microbial response to FP pretreatment. Fluorescence in situ hybridization (FISH) analysis revealed that, while total bacterial populations remained relatively stable, there was a notable increase in acetoclastic methanogens, particularly those from the Methanosaeta genus, suggesting that FP treatment may selectively favor key microbial groups responsible for methane production. This indicates that the pretreatment enhanced substrate bioavailability without negatively impacting the core methanogenic community. Despite these encouraging results, there is no publicly available evidence indicating that the system remained active beyond 2009. The most recent public sources, including fact sheets from the U.S. Environmental Protection Agency (EPA) and NYSERDA, do not indicate that the FP system is currently active [80].

Among the limited studies that investigated microbial responses to electrical pretreatment, ref. [81] reported a full-scale application of pulsed electrical treatment, referred to as focused pulsed pretreatment, at a municipal digester treating sewage sludge. The study demonstrated increased bacterial diversity and a clear shift in methanogenic populations toward acetoclastic Methanosaeta, accompanied by lower effluent acetate concentrations. These findings suggest more efficient volatile fatty acid utilization and point to a potential improvement in process stability under continuous operating conditions. Importantly, this is one of the few full-scale studies that link pulsed electric treatment directly to microbial community changes in AD, providing rare evidence beyond the batch-scale observations that dominate the literature.

Studies investigating microbial community responses to PEF remain limited, but related evidence from broader AD research helps to contextualize potential mechanisms. A systematic review by [82] demonstrated that different pretreatment technologies often induce shifts toward hydrogenotrophic methanogens, which are typically more resilient under inhibitory or fluctuating conditions. Such shifts are considered beneficial for process stability, as they can prevent the accumulation of volatile fatty acids. In addition, ref. [83] highlighted in their review that DIET, which can be stimulated by electrical environments, represents an important pathway that stabilizes methanogenic consortia and enhances methane production efficiency. These insights support the hypothesis that PEF, by altering substrate availability and electrochemical conditions, may indirectly promote DIET-enabled pathways. Furthermore, ref. [84] emphasized that microbial community composition is strongly shaped by operational and environmental parameters in AD, and that stability is closely linked to the balance between acetoclastic and hydrogenotrophic methanogenesis. Collectively, these studies suggest that, even though direct evidence for PEF-specific microbial shifts is scarce, the related literature indicates plausible pathways through which PEF could contribute to more robust and stable microbial consortia in long-term operation.

4.2.2. Optimization and Scalability

To move from experimental validation toward practical deployment, it is essential to optimize the operational parameters of PEF pretreatment. Studies have investigated a variety of factors, including electric field strength, number of pulses, pulse duration, energy input, etc., to determine conditions that maximize methane yield while maintaining energy efficiency. These optimization efforts are typically conducted at the batch scale, but some have been expanded to include energy analyses and simulations relevant to full-scale application. This section highlights selected studies that specifically focus on optimizing PEF parameters, with emphasis on treatment efficiency, process integration, and potential scalability. Table 3 provides an overview of selected studies, summarizing their key findings and operational conditions related to PEF pretreatment. While not all studies listed in the table are discussed in detail in the text, they were included to provide a broader context and highlight relevant research trends. As this review builds upon the work of [28], studies already covered in that paper have been excluded.

A growing number of studies have examined optimizing process conditions and pretreatment parameters of PEF technology to improve biogas production. Most investigations are performed at the batch scale, providing controlled settings to evaluate how pretreatment variations impact substrate solubilization, degradation, and methane output. These lab-scale results can guide pilot- and full-scale applications, offering key insights into integrating PEF technology into industrial AD systems. In a batch study, ref. [85] investigated using PEF technology as a sludge pretreatment to enhance AD efficiency. The study focused on optimizing voltage intensity (up to 54 kV), sludge conductivity (4–8.86 mScm⁻¹), and flow rate (5 mLmin⁻¹), with a custom-designed lab-scale reactor and electric field simulations performed in the CST Studio software. The optimal conditions (54 kV, 23 mm electrode gap, and 8.86 mScm⁻¹ conductivity) significantly increased soluble COD and improved sludge disintegration. Under these conditions, methane production increased by 1.36 times compared to untreated sludge. These results show that precise adjustments of PEF parameters can significantly enhance biogas yield and AD efficiency. Another batch study by [30] assessed PEF pretreatment on WAS before AD. The authors applied the Box–Wilson statistical experimental design to study the effects of conductivity, flow rate, and temperature on SCOD in PEF-treated WAS. Simulations verified the experimental results. After optimization, authors reported 1.70 times increase in methane yield, an 18% rise in soluble COD, and a 19% increase in VSS, implying better solubilization of organic matter. The author of [86] conducted a comprehensive batch-scale study on the application of PEF pretreatment on ley crop silage, focusing on the optimization of treatment parameters to enhance biogas production. The experimental design included variations in pulse number, current intensity, treatment vessel size, and particle size distribution of the substrate. The results showed a significant increase in methane yield, by up to 108% compared to untreated silage, under specific treatment conditions, highlighting the importance of selecting the fine fraction particle sizes and reactor configuration. Although some configurations (e.g., large vessels with high pulse numbers) reduced biogas yields, likely due to poor energy distribution rather than limits of PEF technology. Importantly, energy balance analysis showed that methane energy output was 2 to 6 times greater than electrical input, confirming the energy viability. These findings provide useful insights into how physical and electrical parameters of PEF treatment influence performance and support scaling up PEF as a pretreatment method in biogas production.

Only a few studies have tested the technology at full operational scale, yet their results are promising and provide valuable insights into industrial-scale feasibility. In a full-scale study at the Växtkraft co-digestion plant, ref. [87] evaluated the potential of PEF pretreatment together with membrane filtration of recirculated process water to enhance overall AD performance. The plant processes a mixture of organic waste from households and restaurants together with ley crop biomass. Mechanical pretreatment of the ley crop silage was the most energy-efficient, while electroporation also significantly increased methane yield, resulting in over 30% more biogas. The study included several optimization strategies, with electroporation being particularly notable as it was tested in real operating conditions and confirmed to be feasible at full scale. A follow-up study by [88] further assessed the impact of PEF pretreatment on the performance of the Växtkraft full-scale AD plant. Initial batch tests on ley crop silage showed up to a 9.2% increase in methane yield. Full-scale evaluation of electroporation, combined with membrane filtration of recirculated process water, estimated a total methane increase of more than 30%. This study represents the first and, to date, only known example of PEF application to a solid lignocellulosic substrate under full-scale operational conditions. It demonstrates both the technical feasibility and the potential process benefits of using PEF in large-scale biogas plants treating recalcitrant biomass. Building on previous studies focused on solid substrates, additional optimization work [29] has also been conducted on lignocellulosic energy crops. One such example is the use of high-voltage PEF treatment to improve the AD performance of hybrid Pennisetum, a fast-growing biomass resource. In a batch-scale study, the effects of high-voltage PEF pretreatment were systematically evaluated under varying process conditions, including voltage intensity (up to 15 kV), pulse frequency (60–120 Hz), and treatment duration (20–60 min). Among 9 tested combinations, the condition of 15 kV/120 Hz/60 min yielded the highest cumulative biogas production, around a 27% increase compared to the untreated control. The study also reported increased peak gas production and an extended peak production period. Variance analysis revealed that voltage had the greatest influence on biogas production, followed by treatment time and frequency. These results confirm that PEF pretreatment can enhance the biodegradability of lignocellulosic substrates such as hybrid Pennisetum and shorten the digestion cycle, making it a promising strategy for improving AD performance.

In a combined batch and continuous study by [88], PEF was applied to the organic fraction of municipal solid waste to improve AD performance. The authors explored how variations in electric field strength and pulse frequency influenced methane yield and process efficiency. BMP tests showed a 40% increase in biogas potential compared to the control, while continuous experiments reported a 20–40% increase in methane yield. Notably, the study included an energy balance assessment, finding that the ratio of energy input to additional methane energy output ranged from 2% to 8%, with some configurations yielding even better results.

Moving beyond lab-scale investigations, several studies have evaluated PEF pretreatment in pilot-scale setups to explore its performance under more realistic conditions. In a study conducted by [89], the effects of PEF pretreatment on the AD of WAS were evaluated at both laboratory and pilot scales. At the lab scale, a wide range of treatment intensities was tested to assess disintegration efficiency and the release of intracellular components. Following these trials, a long-term semi-continuous pilot-scale experiment was performed using two parallel 50 L completely mixed digesters: one fed with untreated sludge and the other with PEF-treated sludge. Over approximately two months, a comprehensive monitoring protocol was applied, including total and soluble COD, carbohydrates, proteins, lipids, volatile fatty acids (C2–C5), and biogas production. The study demonstrated that PEF effectively disrupted rigid cell structures, enhancing sludge solubilization and methane production. These results support the scalability of PEF as a pretreatment method and underscore its potential for integration in full-scale AD systems, especially for WAS.

In another pilot-scale study combining PEF pretreatment with shock wave technology, the authors of [90] evaluated the process performance using a parallel fermentation setup with identically structured 200 L digesters and 100 L secondary digesters. One line received the treated substrate, while the other served as an untreated control. This design enabled direct comparison of treatment effects under identical and fluctuating substrate conditions. Although the study encountered some operational disturbances, both reactor lines produced comparable biogas yields under stable conditions, indicating that process variability was primarily associated with treatment, rather than inherent substrate fluctuations. While external factors limited a clear quantification of treatment effects, the approach demonstrates a promising methodology for validating PEF pretreatment under pilot-scale operational conditions, bridging the gap between laboratory trials and full-scale implementation.

These studies collectively demonstrate that optimization of PEF parameters is a crucial step toward improving both the efficiency and scalability of this technology. The use of experimental designs and modeling software further enhances the reliability of such findings, especially when transitioning from batch to larger operational scales.

Table 3. Operational settings and parameters of studies of PEF pretreatment of different substrates (The table includes only those parameters provided by the original authors; missing data highlight the lack of standardized reporting in the literature.)

Research Size	Substrates	Pretreatment Parameters	Results	Ref.
Batch scale	Pig slurry	PEF pretreatment: Stainless-steel electrodes 20 cm long, 0.5 cm wide, and 7 cm high. Exponential decay waveform. delectrode = 1 cm; f = 1.7 Hz; τ = 4 µs; treatment duration = 83 and 90 min; TI = 0, 15, 30, 50 kWhm−3; slurry dosed with circulation pump at a rate of 350 mlmin−1; E = 20 kVcm−1 BMP assay: 1 L batch reactors; T = 37 °C; IS ratio = 1 (based on VS); t = 22 days.	COD removal and CH4 yield increased linearly with higher pretreatment TI—pretreatment TI of 50 kWhm−3 resulted in 58% higher CH4 production and 44% improvement in COD removal as compared to the control.	[20]
Batch scale	Chicken manure	PEF pretreatment: Stainless-steel reactor with a coaxial electrode. Rectangular electrical pulses. delectrodes = 2 cm; U = 40 kV; τ = 50 µs; f = 5 kHz; E = 11.66 to 38.66 kVcm−1 BMP assay: T = 37 °C; t = 24 days; mixing: 30 s at 100 rpm every 10 min; IS ratio = 5 (based on VS).	The highest increase in the COD (increased from 5957 ± 71 to 6973 ± 85 mgL−1) and TOC (increased from 1922 ± 48 to 2252 mgL−1) was obtained after pretreatment with specific energy input 0.26 Whg−1 TS. Increased BMP from 210.42 ± 7.92 to 248.90 ± 9.29 mlg−1 VS. Negative energy balance in all pretreatment conditions.	[21]
Batch scale	Microalgae Auxenochlorella protothecoides	PEF pretreatment: Plane-parallel stainless-steel electrodes. delectrodes = 4 mm; E = 40 kVcm−1; f = 3 Hz; τ = 1 µs; Wspec. = 150 kJkg−1 BMP assay: T = 38 °C; t = 38 days; IS ratio = 0.36 to 0.38 (based on VS).	If compared to untreated, PEF pretreated microalgae showed a 10% increased CH4 yield (467 mLnormg−1 VS). PEF pretreated microalgae subjected to extraction and removal of aqueous fraction showed a 23% increase in CH4 yield (558 mLnormg−1 VS). PEF pretreated microalgae subjected to extraction and removal of aqueous fraction and lipids achieved 41% of CH4 potential (205 mLnormg−1 VS)	[72]
Batch scale	WAS and pig manure	PEF pretreatment: Cylindrical treatment chamber. U = 10 kV; τ = 10 µs; f = 1000 Hz; σ = 0.1 Sm−1; L = 0.01 m; HRT = 0.01 s WAS: TI = 4.0, 9.9, 19.8 kWhm−3; E = 24.5 kVcm−1 Manure: TI = 7.0, 10.5 kWhm−3; E = 19.7 kVcm−1 BMP assay: t = 30 days; T = 35 °C.	PEF pretreatment solubilized approximately 10% of the total COD, increasing SCOD from as low as 20 mgL−1 to more than 1000 mgL−1. BMP was increased for pig manure by 80%, and for WAS by 100%	[76]
Batch scale	WAS	PEF pretreatment: Co-linear cylindrical stainless-steel treatment chamber. U = 0–36 kV; f = 0.1–50 Hz BMP assay: t = 37 days; T = mesophilic conditions.	The CH4 production increased 1.70 times. An 18% improvement in SCOD and a 19% improvement in VSS were observed when compared to the control.	[30]
Batch scale	Maize silage	PEF pretreatment: Coaxial 500 mL chamber, stainless-steel electrodes. delectrodes = 2 cm; U = 40 kV; τ = 50 µs; f = 10 kHz; rectangular pulse shape; Emin = 11.66 kVcm−1; Emax = 38.61 kVcm−1; tPEF = 0, 30, 60, 90, 120, 150, 180, 210, 240, and 270 s BMP assay: IS ratio = 5; T = 35 °C; t = 24 days.	A 14% higher biogas yield (at tPEF 180 s for 751.97 mLg−1 VS) compared to the control.	[91]
Batch scale	Grass silage	PEF pretreatment: Coaxial 500 mL chamber, stainless-steel electrodes. delectrodes = 2 cm; U = 40 kV; τ = 50 µs; f = 5 kHz; Emin = 11.66 kVcm−1; Emax = 38.66 kVcm−1 BMP assay: IS ratio = 5; T = 35 °C; t = 24 days.	A 20% higher biogas yield compared to the control.	[68]
Batch scale	Rapeseed straw	PEF pretreatment: Coaxial 500 mL chamber, stainless steel electrodes. delectrodes = 2 cm; U = 40 kV; τ = 50 µs; f = 5 kHz; rectangular pulse shape; Emin = 11.66 kVcm−1; Emax = 38.61 kVcm−1; tPEF = 0, 1, 2, 3, 4, 5, 6, 7, 8 min. BMP assay: IS ratio = 5; T = 37 °C; t = 24 days.	A 5-min PEF pretreatment resulted in about 14% higher biogas yield compared to the control sample. The biogas productivity for this sample was 478.0 ± 27.5 NmLg−1 VS, approximately 15% higher than the control sample. Due to the energy gain, the sample disintegrated for 4 min was the most effective, yielding 0.06 Whg−1 TS.	[69]
Full scale	WAS + thickened primary sludge	PEF pretreatment: full-scale OpenCELTM FP unit installed at the water reclamation plant between the centrifuges and the two digesters to treat the mixture sludges; E = 20–30 kV AD: HRT = 30–35 days; T = 35–38 °C.	FP pretreatment of a mixture of sludges increased the SCOD by 160% and the DOC by 120% over the control. FP pretreatment of 63% of the input sludge increased biogas production by over 40% and reduced biosolids requiring disposal by 30% when compared to the control.	[79]
Pilot scale	A mixture of 55%TS corn silage and 45%TS cattle manure	PEF combined with shock waves. PEF pretreatment: continuous PVC chamber; τ = 1 μs; U = 30 kV; pulse repetition rate: 15 pulses/s; pulse duration: 5–20 μs. Electrophoresis power supply: 1000 V, 250 W voltage source and a transistorized full bridge (H-bridge) connected downstream. The shock wave generated by a high-performance piezo ceramic using a high-voltage pulse at ~36 kHz. The piezo disks diameter: 5 cm, thickness: 8 mm. The breakdown field strength: 1 kVmm−1. AD: loading increased from 2.5 kg0TSm−3d−1 to 3.5 kg0TSm−3d−1 in daily steps of 0.2 kg0TSm−3d−1; HRT = 30 days; T = 37–38 °C Pilot plant: 2 digesters (2 × 200 L fermentation volume) and 2 secondary digesters (2 × 100 L fermentation volume).	No significant increase in specific biogas or methane production was observed with PEF + shock wave treatment in comparison to control; no biological instability or inhibition; frequent clogging occurred, mostly in the untreated line; the authors suppose that the benefits could be more pronounced with homogeneous or less fibrous substrates.	[90]
Batch scale	Wastewater sludge	PEF pretreatment: TI = 4, 20, 70, and 95 kJ/kg BMP assay: continuous stirred-tank reactors (CSTR) of 10 L capacity; T = 55 °C; HRT = 10.5 days.	Increases of 7.3% in cumulative biogas production and 7% in VS reduction were obtained from the AD of mixed primary and secondary sludge pretreated with an intensity of 95 kJ/kg.	[92]
Batch scale	Degreased food waste + sewage sludge (ratio 1:1); addition of biochar to enhance AD	PEF pretreatment: carbon felt electrodes (4 × 4 × 0.5 cm). The electric field was supplied in three stages, 0–10, 11–20, and 21–30 days, and connected to a stabilized voltage of U = 0.3, 0.6, and 0.9 V, respectively. BMP assay: T = 55 °C; shaking incubator at 100 rpm; t = 30 days.	Under U = 0.3 V, coupled with 5 gL−1 of biochar, resulted in a 143% growth in biogas production. Increased methane production (by 45.5% compared to the biochar-only test) by enriching hydrogenotrophic methanogens such as Methanobacterium, enhancing DIET associated with electroactive bacteria, and weakening acetolactate methanogenic capacity. Efficient utilization of VFA and accelerated ammonia nitrogen removal in the early stages, thereby improving the start-up efficiency of AD.	[65]
Batch scale	Source-separated food waste	PEF pretreatment: E = 24 kVcm−1; f = 12.5 Hz. BMP assay: continuous reactors; T = 37 °C; t = 98 days.	BMP tests indicated up to a 50% increase in the total biogas potential. The largest amount of energy used was 500 J (kg TS)−1 per pulse. The methane formation increased from 222 to 338 Lkg−1 TS.	[88]
Batch scale	Biological sludge from the pulp and paper wastewater treatment	PEF pretreatment: Substrate was poured into a 250 mL cylinder cuvette (length 20 cm, diameter 4 cm); U = 36 kV; I = 40 mA; f = ~10.5 Hz. E = ~10 kVcm−1; n = 2000 (2 × 1000, due to equipment limitation), each pulse corresponding to an energy consumption of 54.4 J. BPM assay: semi-continuous digester; HRT = 20 days; T = 37 °. The digesters were fed once a day (200 mL substrate) and stirred 15 min every hour (400–500 rpm).	No or little effect on the initial methane production rate or methane potential was achieved.	[93]
Batch scale	Food waste	HVPD pretreatment: The ground plate electrode is a stainless-steel disc (with a diameter of 90 mm and a thickness of 1.5 mm). The pulse peak voltage amplitude = 50 kV; f = 100, 200, 200 and 400 Hz; storage capacitance (Cp) = 2 nF; delectrodes = 5, 7, 9, 12 mm; tPEF = 5, 10, 15, 20, 30 min BMP assay: shaking incubator at 100 r/min, T = 35 °C.	The total cumulative methane production of the HVPD pretreated substrate was 134% higher than that of the control. The final VS transformation rates with and without HVPD pretreatment were 54.3% and 32.3%, respectively. Comparison of HVPD pretreatment with acid, alkali, and ultrasonic pretreatments showed that the methane production and COD removal rates with HVPD were more than 100% higher than the control, whereas about 50% higher can be obtained with other pretreatments.	[73]

d_electrodes—distance between the electrodes; f—pulse frequency; τ—pulse width; TI—treatment intensity; E—electric field strength; U—voltage; T—temperature; t—BMP test duration; t_PEF—treatment time; W_spec.—energy input; σ—conductivity; L—length of the treatment chamber; HRT—resident time (hydraulic retention time) in a treatment chamber; VS—volatile solids; COD—chemical oxygen demand; TOC—total organic carbon; SCOD—soluble chemical oxygen demand; VSS—volatile suspended solid; OLR—organic loading rate; BMP—biochemical methane potential; DIET—direct interspecies electron transfer; n—number of pulses; WAS—waste-activated sludge; FP—focus pulsed; DOC—dissolved organic carbon; VFA—volatile fatty acid.

Table 3. Operational settings and parameters of studies of PEF pretreatment of different substrates (The table includes only those parameters provided by the original authors; missing data highlight the lack of standardized reporting in the literature.)

Research Size	Substrates	Pretreatment Parameters	Results	Ref.
Batch scale	Pig slurry	PEF pretreatment: Stainless-steel electrodes 20 cm long, 0.5 cm wide, and 7 cm high. Exponential decay waveform. delectrode = 1 cm; f = 1.7 Hz; τ = 4 µs; treatment duration = 83 and 90 min; TI = 0, 15, 30, 50 kWhm−3; slurry dosed with circulation pump at a rate of 350 mlmin−1; E = 20 kVcm−1 BMP assay: 1 L batch reactors; T = 37 °C; IS ratio = 1 (based on VS); t = 22 days.	COD removal and CH4 yield increased linearly with higher pretreatment TI—pretreatment TI of 50 kWhm−3 resulted in 58% higher CH4 production and 44% improvement in COD removal as compared to the control.	[20]
Batch scale	Chicken manure	PEF pretreatment: Stainless-steel reactor with a coaxial electrode. Rectangular electrical pulses. delectrodes = 2 cm; U = 40 kV; τ = 50 µs; f = 5 kHz; E = 11.66 to 38.66 kVcm−1 BMP assay: T = 37 °C; t = 24 days; mixing: 30 s at 100 rpm every 10 min; IS ratio = 5 (based on VS).	The highest increase in the COD (increased from 5957 ± 71 to 6973 ± 85 mgL−1) and TOC (increased from 1922 ± 48 to 2252 mgL−1) was obtained after pretreatment with specific energy input 0.26 Whg−1 TS. Increased BMP from 210.42 ± 7.92 to 248.90 ± 9.29 mlg−1 VS. Negative energy balance in all pretreatment conditions.	[21]
Batch scale	Microalgae Auxenochlorella protothecoides	PEF pretreatment: Plane-parallel stainless-steel electrodes. delectrodes = 4 mm; E = 40 kVcm−1; f = 3 Hz; τ = 1 µs; Wspec. = 150 kJkg−1 BMP assay: T = 38 °C; t = 38 days; IS ratio = 0.36 to 0.38 (based on VS).	If compared to untreated, PEF pretreated microalgae showed a 10% increased CH4 yield (467 mLnormg−1 VS). PEF pretreated microalgae subjected to extraction and removal of aqueous fraction showed a 23% increase in CH4 yield (558 mLnormg−1 VS). PEF pretreated microalgae subjected to extraction and removal of aqueous fraction and lipids achieved 41% of CH4 potential (205 mLnormg−1 VS)	[72]
Batch scale	WAS and pig manure	PEF pretreatment: Cylindrical treatment chamber. U = 10 kV; τ = 10 µs; f = 1000 Hz; σ = 0.1 Sm−1; L = 0.01 m; HRT = 0.01 s WAS: TI = 4.0, 9.9, 19.8 kWhm−3; E = 24.5 kVcm−1 Manure: TI = 7.0, 10.5 kWhm−3; E = 19.7 kVcm−1 BMP assay: t = 30 days; T = 35 °C.	PEF pretreatment solubilized approximately 10% of the total COD, increasing SCOD from as low as 20 mgL−1 to more than 1000 mgL−1. BMP was increased for pig manure by 80%, and for WAS by 100%	[76]
Batch scale	WAS	PEF pretreatment: Co-linear cylindrical stainless-steel treatment chamber. U = 0–36 kV; f = 0.1–50 Hz BMP assay: t = 37 days; T = mesophilic conditions.	The CH4 production increased 1.70 times. An 18% improvement in SCOD and a 19% improvement in VSS were observed when compared to the control.	[30]
Batch scale	Maize silage	PEF pretreatment: Coaxial 500 mL chamber, stainless-steel electrodes. delectrodes = 2 cm; U = 40 kV; τ = 50 µs; f = 10 kHz; rectangular pulse shape; Emin = 11.66 kVcm−1; Emax = 38.61 kVcm−1; tPEF = 0, 30, 60, 90, 120, 150, 180, 210, 240, and 270 s BMP assay: IS ratio = 5; T = 35 °C; t = 24 days.	A 14% higher biogas yield (at tPEF 180 s for 751.97 mLg−1 VS) compared to the control.	[91]
Batch scale	Grass silage	PEF pretreatment: Coaxial 500 mL chamber, stainless-steel electrodes. delectrodes = 2 cm; U = 40 kV; τ = 50 µs; f = 5 kHz; Emin = 11.66 kVcm−1; Emax = 38.66 kVcm−1 BMP assay: IS ratio = 5; T = 35 °C; t = 24 days.	A 20% higher biogas yield compared to the control.	[68]
Batch scale	Rapeseed straw	PEF pretreatment: Coaxial 500 mL chamber, stainless steel electrodes. delectrodes = 2 cm; U = 40 kV; τ = 50 µs; f = 5 kHz; rectangular pulse shape; Emin = 11.66 kVcm−1; Emax = 38.61 kVcm−1; tPEF = 0, 1, 2, 3, 4, 5, 6, 7, 8 min. BMP assay: IS ratio = 5; T = 37 °C; t = 24 days.	A 5-min PEF pretreatment resulted in about 14% higher biogas yield compared to the control sample. The biogas productivity for this sample was 478.0 ± 27.5 NmLg−1 VS, approximately 15% higher than the control sample. Due to the energy gain, the sample disintegrated for 4 min was the most effective, yielding 0.06 Whg−1 TS.	[69]
Full scale	WAS + thickened primary sludge	PEF pretreatment: full-scale OpenCELTM FP unit installed at the water reclamation plant between the centrifuges and the two digesters to treat the mixture sludges; E = 20–30 kV AD: HRT = 30–35 days; T = 35–38 °C.	FP pretreatment of a mixture of sludges increased the SCOD by 160% and the DOC by 120% over the control. FP pretreatment of 63% of the input sludge increased biogas production by over 40% and reduced biosolids requiring disposal by 30% when compared to the control.	[79]
Pilot scale	A mixture of 55%TS corn silage and 45%TS cattle manure	PEF combined with shock waves. PEF pretreatment: continuous PVC chamber; τ = 1 μs; U = 30 kV; pulse repetition rate: 15 pulses/s; pulse duration: 5–20 μs. Electrophoresis power supply: 1000 V, 250 W voltage source and a transistorized full bridge (H-bridge) connected downstream. The shock wave generated by a high-performance piezo ceramic using a high-voltage pulse at ~36 kHz. The piezo disks diameter: 5 cm, thickness: 8 mm. The breakdown field strength: 1 kVmm−1. AD: loading increased from 2.5 kg0TSm−3d−1 to 3.5 kg0TSm−3d−1 in daily steps of 0.2 kg0TSm−3d−1; HRT = 30 days; T = 37–38 °C Pilot plant: 2 digesters (2 × 200 L fermentation volume) and 2 secondary digesters (2 × 100 L fermentation volume).	No significant increase in specific biogas or methane production was observed with PEF + shock wave treatment in comparison to control; no biological instability or inhibition; frequent clogging occurred, mostly in the untreated line; the authors suppose that the benefits could be more pronounced with homogeneous or less fibrous substrates.	[90]
Batch scale	Wastewater sludge	PEF pretreatment: TI = 4, 20, 70, and 95 kJ/kg BMP assay: continuous stirred-tank reactors (CSTR) of 10 L capacity; T = 55 °C; HRT = 10.5 days.	Increases of 7.3% in cumulative biogas production and 7% in VS reduction were obtained from the AD of mixed primary and secondary sludge pretreated with an intensity of 95 kJ/kg.	[92]
Batch scale	Degreased food waste + sewage sludge (ratio 1:1); addition of biochar to enhance AD	PEF pretreatment: carbon felt electrodes (4 × 4 × 0.5 cm). The electric field was supplied in three stages, 0–10, 11–20, and 21–30 days, and connected to a stabilized voltage of U = 0.3, 0.6, and 0.9 V, respectively. BMP assay: T = 55 °C; shaking incubator at 100 rpm; t = 30 days.	Under U = 0.3 V, coupled with 5 gL−1 of biochar, resulted in a 143% growth in biogas production. Increased methane production (by 45.5% compared to the biochar-only test) by enriching hydrogenotrophic methanogens such as Methanobacterium, enhancing DIET associated with electroactive bacteria, and weakening acetolactate methanogenic capacity. Efficient utilization of VFA and accelerated ammonia nitrogen removal in the early stages, thereby improving the start-up efficiency of AD.	[65]
Batch scale	Source-separated food waste	PEF pretreatment: E = 24 kVcm−1; f = 12.5 Hz. BMP assay: continuous reactors; T = 37 °C; t = 98 days.	BMP tests indicated up to a 50% increase in the total biogas potential. The largest amount of energy used was 500 J (kg TS)−1 per pulse. The methane formation increased from 222 to 338 Lkg−1 TS.	[88]
Batch scale	Biological sludge from the pulp and paper wastewater treatment	PEF pretreatment: Substrate was poured into a 250 mL cylinder cuvette (length 20 cm, diameter 4 cm); U = 36 kV; I = 40 mA; f = ~10.5 Hz. E = ~10 kVcm−1; n = 2000 (2 × 1000, due to equipment limitation), each pulse corresponding to an energy consumption of 54.4 J. BPM assay: semi-continuous digester; HRT = 20 days; T = 37 °. The digesters were fed once a day (200 mL substrate) and stirred 15 min every hour (400–500 rpm).	No or little effect on the initial methane production rate or methane potential was achieved.	[93]
Batch scale	Food waste	HVPD pretreatment: The ground plate electrode is a stainless-steel disc (with a diameter of 90 mm and a thickness of 1.5 mm). The pulse peak voltage amplitude = 50 kV; f = 100, 200, 200 and 400 Hz; storage capacitance (Cp) = 2 nF; delectrodes = 5, 7, 9, 12 mm; tPEF = 5, 10, 15, 20, 30 min BMP assay: shaking incubator at 100 r/min, T = 35 °C.	The total cumulative methane production of the HVPD pretreated substrate was 134% higher than that of the control. The final VS transformation rates with and without HVPD pretreatment were 54.3% and 32.3%, respectively. Comparison of HVPD pretreatment with acid, alkali, and ultrasonic pretreatments showed that the methane production and COD removal rates with HVPD were more than 100% higher than the control, whereas about 50% higher can be obtained with other pretreatments.	[73]

d_electrodes—distance between the electrodes; f—pulse frequency; τ—pulse width; TI—treatment intensity; E—electric field strength; U—voltage; T—temperature; t—BMP test duration; t_PEF—treatment time; W_spec.—energy input; σ—conductivity; L—length of the treatment chamber; HRT—resident time (hydraulic retention time) in a treatment chamber; VS—volatile solids; COD—chemical oxygen demand; TOC—total organic carbon; SCOD—soluble chemical oxygen demand; VSS—volatile suspended solid; OLR—organic loading rate; BMP—biochemical methane potential; DIET—direct interspecies electron transfer; n—number of pulses; WAS—waste-activated sludge; FP—focus pulsed; DOC—dissolved organic carbon; VFA—volatile fatty acid.

4.2.3. Comparative Analysis of PEF with Other Pretreatment Methods

To assess the practical relevance of PEF technology for AD, it is essential to compare its performance, energy efficiency, and scalability with other pretreatment methods. Comparative studies offer valuable insights into the relative advantages and limitations of each method and help identify contexts in which PEF may be more suitable or complementary. This section outlines comparative analyses in which PEF is assessed alongside other pretreatment methods, with emphasis on biogas yield improvement, energy efficiency, and operational feasibility.

In a comparative laboratory-scale study on grass silage [68], the effectiveness of PEF pretreatment was evaluated against microwave-induced disintegration, with both methods operated under equal energy input. The highest methane yield obtained from PEF-pretreated samples was 364.95 ± 17.76 NLkg⁻¹ VS, corresponding to a 20.1% increase compared to the untreated control. In contrast, microwave pretreatment led to a maximum increase of 10%. SEM imaging confirmed that PEF caused significant structural deformation of cell walls, which was not observed after microwave treatment. Furthermore, COD was substantially higher in PEF-treated samples than in microwave-treated samples, supporting improved substrate solubilization. These results demonstrate that PEF is more effective than microwave disintegration for lignocellulosic biomass when assessed under equivalent energy conditions, both in terms of methane yield and substrate disintegration efficiency. In another comparative batch study [21], PEF pretreatment was evaluated against ultrasonic disintegration for enhancing AD of chicken manure with a high straw content, representing a lignocellulosic substrate. Both methods led to increased methane yields and solubilization of organic matter, with PEF increasing the BMP from around 210 mLg⁻¹ VS to around 248 mLg⁻¹ VS and biogas production from around 307 mLg⁻¹ VS to around 367 mLg⁻¹ VS. Comparable improvements were achieved with ultrasound pretreatment, though the methane production rate and reaction kinetics were more favorable in PEF-treated samples. COD and total organic carbon (TOC) values were also higher after PEF, indicating more effective substrate disintegration. An energy balance analysis revealed that, while ultrasound pretreatments resulted in net energy losses across all tested series, PEF achieved a net energy gain in one configuration. These results highlight the potential of PEF as a more energy-efficient alternative to ultrasonic pretreatment for manures mixed with a high straw content. In a doctoral dissertation investigating pretreatment strategies for biological sludge from pulp and paper mills, ref. [93] compared the effects of alkali, thermal, and PEF pretreatments on methane production. Eleven sludge samples from six Swedish mills were subjected to batch BMP tests. Among the methods tested, alkali pretreatment had the most substantial effect on the initial methane production rate, followed by thermal treatment. However, PEF showed little or no effect on either the methane production rate or potential. In the semi-continuous digester, neither thermal nor alkali pretreatment improved methane yield, although alkali pretreatment caused acetate accumulation and decreased biogas production. The findings suggest that, while certain pretreatments can enhance the initial hydrolysis rate, PEF in this case was the least effective, highlighting the importance of substrate type and pretreatment–substrate compatibility in assessing PEF’s suitability compared to conventional methods.

A closely related method to PEF, high-voltage pulsed discharge (HVPD), was used in the following study, which applies short, high-energy electrical pulses that, in addition to electroporation, can induce plasma channels and shockwaves within the medium. Although the physical setup and underlying mechanisms differ slightly from conventional PEF systems, HVPD similarly enhances cell disruption and substrate solubilization, making it suitable for biogas production applications. In a batch-scale study using food waste as the substrate [73], HVPD pretreatment resulted in a 134% increase in cumulative methane production and significantly enhanced COD removal compared to the untreated control. When benchmarked against acid, alkali, and ultrasonic pretreatments under identical conditions, HVPD outperformed all three, yielding more than 100% improvement in methane output over the control. In contrast, the other methods achieved gains of approximately 50% or less. These results suggest that HVPD may offer superior substrate solubilization and biodegradability enhancement, particularly for heterogeneous organic waste streams.

These two studies [73,93] provide contrasting insights into the effectiveness of pulsed power-based pretreatments. While [93] found that PEF had a negligible impact on methane production from pulp and paper mill sludge, highlighting the importance of substrate-specific responsiveness, ref. [73] reported a dramatic increase in methane yield from food waste using the related HVPD technique. Notably, HVPD also outperformed acid, alkali, and ultrasonic pretreatments under identical conditions. The discrepancy may be attributed to both the inherent differences in substrate complexity and to the more disruptive physical mechanisms of HVPD, which include not only electroporation but also localized plasma generation and micro-shockwaves that may enhance solubilization more effectively than conventional PEF systems.

4.3. Global Research Distribution and Key Contributors to PEF Pretreatment in Biogas Research

The following analysis presents the geographic distribution of PEF utilization in biogas research (Figure 7). By understanding where PEF is being researched and the underlying reasons, one can gain a deeper appreciation for the factors that influence the global development and deployment of technologies aimed at improving sustainable energy production and waste management. This information can also help identify potential areas for future investment and collaboration. Future collaborations among these countries could significantly enhance the development and application of PEF technology in biomass pretreatment, facilitating the exchange of ideas, technologies, and methodologies to promote biogas production on a global scale.

The bibliographic analysis revealed that the highest number of publications originates from China, Sweden, and France, each contributing seven or more papers to the field. These countries stand out not only in terms of publication volume but also in the diversity of publication types and temporal distribution. While Sweden and the United States exhibit early involvement in the research area, with publications dating back to 2008 and 2009, respectively, China and France have demonstrated strong and sustained interest, particularly over the past decade. Notably, China shows a balanced output of both original research and review papers, whereas France and India display a predominance of review articles, potentially indicating a focus on knowledge synthesis and theoretical advancement. In contrast, countries such as Italy and Spain contribute exclusively with review papers, suggesting limited experimental engagement. The United States, although represented solely by original research articles, has not shown recent activity in this area, with the most recent publication dating back to 2015. Countries including Poland, Greece, Croatia, and Turkey, with three publications each, illustrate emerging research activity, often combining both review and original contributions. The remaining countries, each contributing one or two publications, reflect a geographically dispersed but limited engagement with the investigated method. Overall, the geographical distribution of publications indicates a globally expanding interest in the method, with notable research hubs concentrated in East Asia and Western Europe, and growing activity observed in Central and Southern Europe.

China is a leader in renewable energy research and waste-to-energy technologies [94]. China’s strong emphasis on sustainable solutions in the management of agricultural waste, meeting energy demands, and environmental policies may drive the adoption of innovative pretreatment technologies such as PEF [95]. A detailed analysis of institutional affiliations in China revealed a broad but structured distribution of research activity related to PEF pretreatment. Leading institutions include the Harbin Institute of Technology, Beijing University of Chemical Technology, and Shanghai University, as well as regional universities such as Yunnan Agricultural University and Tianjin University. Notably, several national key laboratories and research centers, such as the State Key Laboratory of Urban Water Resource and Environment in Harbin, the State Key Laboratory of Multiphase Flow in Power Engineering in Xi’an, and the Chinese National Engineering Research Center in Hong Kong, are actively engaged in this field, indicating strategic prioritization of PEF research in water, energy, and environmental engineering domains. Research activity is not confined to academic institutions alone: industry-linked centers, such as the Tianjin Capital Environment Protection Group and Jiangsu-based environmental technology companies, also contribute to scientific output. This interplay between academia and industry may reflect an emerging trend towards applied research and technology transfer in the field of AD and biowaste valorization.

In Sweden, research on PEF pretreatment is distributed across a range of institutions that reflect both academic depth and strong industry collaboration. Notable contributors include Luleå University of Technology, Mälardalen University (Västerås), Lund University, and Linköping University. Several studies also involved industry partners, such as Arc Aroma Pure, Anox Kaldnes AB, Mercatus Engineering AB, and Svensk Växtkraft AB, highlighting the translational and applied nature of Swedish research in this field. The active engagement of both universities and technology-oriented companies indicates a strong focus on innovation and commercialization, particularly in the context of sustainable waste management. The collaborative projects frequently involve regional actors, suggesting that Sweden fosters locally anchored research ecosystems that support technology transfer and full-scale implementation of PEF-based processes.

In France, research on PEF pretreatment is distributed across a network of both academic institutions and national research bodies. Notable contributors include the National Research Institute for Agriculture, Food and Environment (INRAE)—The Laboratory of Environmental Biotechnology, the University of Technology of Compiègne, and institutes affiliated to the French National Centre for Scientific Research (CNRS), such as the Institute of Pharmacology and Structural Biology in Toulouse. These institutions are actively involved in environmental sustainability and energy transition, indicating that the application of PEF technology is being explored within established environmental and process engineering frameworks [96,97]. Furthermore, the University of Bretagne Sud (Pontivy) appears multiple times, suggesting a localized concentration of interest. The involvement of both INRAE and CNRS highlights a strong presence of national-level research infrastructure, which is characteristic of French scientific policy [98]. Additionally, the involvement of French institutions in joint research with organizations abroad, such as the Polytechnic University of Catalonia in Barcelona, demonstrates active international collaboration and integration in PEF-related research.

5. Conclusions and Future Directions

This bibliometric review provides a comprehensive overview of PEF-related research, with a focus on its application in biomass pretreatment for enhanced biogas production. Although PEF has been widely explored across various scientific domains, including food processing, biomedicine, and environmental engineering, its use in AD remains limited and underrepresented. Across the four databases (WoSCC, Scopus, Dimensions, and Google Scholar) utilized for this study, publications on PEF as a pretreatment method for AD account for less than 0.5% of all biomass pretreatment studies, highlighting a clear research gap. Importantly, when normalized against the total number of pretreatment publications per year, the relative share of PEF studies in WoSCC, Scopus, and Dimensions consistently remained below 1% throughout the entire observation period. This finding confirms that PEF continues to represent a marginal approach compared to other pretreatment technologies of biomass aimed at biogas production. Nevertheless, a steady increase in publications is observed after 2010, particularly between 2017 and 2023, suggesting growing interest. Scopus provides the broadest coverage, while WoSCC offers high-quality metadata. Dimensions captures a variety of publication types, and Google Scholar offers the widest range of sources, including the grey literature and student theses, making it a valuable supplementary resource, especially in emerging fields like PEF in AD.

Nevertheless, several limitations of the bibliometric analysis should be acknowledged. The results are influenced by language and indexing biases, as English-language publications dominate the major databases, while the coverage and inclusion criteria differ between WoSCC, Scopus, Dimensions, and Google Scholar. Database coverage is also dynamic and continuously updated, which may result in slight variations if searches are repeated at a later time. These factors should be kept in mind when interpreting the quantitative findings of this review.

The reviewed studies confirm that PEF can significantly improve biogas yield across a wide range of organic substrates, such as animal manure, sewage sludge, microalgae, food waste, and lignocellulosic residues. These improvements stem primarily from electroporation-induced cell disruption, enhanced substrate solubilization, and facilitated hydrolysis. Additionally, emerging research indicates that PEF can alter microbial community structures, particularly methanogenic populations. However, microbial responses to PEF remain insufficiently studied, especially in long-term, pilot-, and full-scale systems.

While promising results have been achieved, most optimization studies remain confined to the batch scale. Full-scale and techno-economic analyses are rare, and operational parameters are often poorly described or overlooked. There is also a lack of standardization in experimental setups and reporting, which hampers reproducibility and cross-study comparisons. Despite their considerable energy potential, lignocellulosic feedstocks have received limited attention in process optimization studies.

The geographic distribution of PEF research shows that a few countries, particularly China, Sweden, and France, lead in terms of publication volume and institutional involvement. These nations often combine academic and industrial capacities, supported by national research infrastructure. While countries like the USA, India, and several EU members show moderate activity, global engagement remains uneven, suggesting significant room for expanded international collaboration and knowledge exchange.

Although several studies, including a limited number of full-scale studies, have demonstrated the feasibility and economic potential of PEF-assisted AD, substantial gaps remain. Most existing research focuses on specific substrates, such as sewage sludge or liquid organic waste, while lignocellulosic biomass and heterogeneous feedstocks remain underexplored.

Several limitations of the current PEF technology in biogas production research should also be noted. Although a few studies, including limited full-scale applications, have demonstrated the feasibility and potential of PEF-assisted AD, the vast majority of work has been performed under batch conditions. Most studies focus on sewage sludge, manure, and other liquid substrates, while lignocellulosic biomass and heterogeneous feedstocks remain largely underexplored. In addition, the lack of standardized reporting of PEF parameters, such as field strength, number of pulses, and energy input, restricts reproducibility and makes cross-study comparisons challenging. The predominance of short-term experiments further limits the ability to assess long-term process stability, while energy balances are rarely presented in detail, making it difficult to evaluate the overall feasibility of PEF-assisted AD. Another limitation is that potential mechanisms, such as DIET, remain largely unexplored in the context of PEF-assisted AD. DIET, a process in which microorganisms exchange electrons directly through conductive structures or particles, is known to stabilize methanogenic consortia and enhance methane production efficiency. However, its role under PEF stimulation has not yet been systematically investigated, representing an important gap for future studies. These limitations point to the need for harmonized methodologies, extended pilot- and full-scale trials, and systematic techno-economic assessments.

Future investigations should include a more diverse range of substrates to assess the broader applicability of PEF pretreatment with key priorities including:

• Extending full-scale validations across various feedstocks and digester configurations to evaluate process robustness and long-term performance.
• Enhancing process standardization, particularly in the reporting of key PEF parameters and treating chamber specifications, to enable comparability across studies.
• Expanding microbial analysis beyond lab-scale conditions to monitor community dynamics, functional gene expression, and pathway regulation in complex microbial consortia.
• Developing hybrid or synergistic pretreatment strategies, combining PEF with different pretreatment methods optimized for specific substrate characteristics. For example, PEF could be integrated with enzymatic hydrolysis to enhance accessibility of lignocellulosic biomass, with ultrasound to intensify cell disruption, or with mild alkaline or chemical pretreatments to improve solubilization of recalcitrant substrates.
• Conducting comprehensive techno-economic assessments and life cycle analyses to evaluate energy efficiency, cost-effectiveness, and environmental impacts under scaled-up conditions. A major gap identified in the reviewed literature is the lack of standardized and comparable energy balance assessments. Only a few PEF studies report input–output energy data, and often in inconsistent formats, which prevents fair benchmarking against alternative pretreatment methods. Future work should therefore prioritize systematic energy analyses to evaluate the true efficiency and competitiveness of PEF relative to other approaches.

The currently limited adoption of PEF in AD research can likely be attributed to a combination of technical barriers, such as the lack of suitable and affordable equipment, and limited awareness within the AD community, as the method has only recently begun to transition from other fields (e.g., medicine, molecular biology, food processing) into the context of biogas production. To achieve broader applicability and commercial readiness, interdisciplinary and international collaboration will be crucial, especially efforts integrating engineering, microbiology, economics, and sustainability assessment in unified research frameworks.