Search Results (29)

Tokamak technology, as the cornerstone of nuclear fusion energy, holds immense potential in achieving efficient plasma confinement and high energy densities. To comprehensively map the rapidly evolving landscape of this field, this study employs bibliometric analysis to systematically examine the research and development trends of tokamak technology from 2014 to 2024. The data are drawn from 7702 academic publications in the Scopus database, representing a global research effort. Additionally, the study incorporates 2299 tokamak-related patents from Google Patents over the same period, analyzing their technological trends to highlight the growing significance of tokamak devices. Using the R language and the Bibliometric package, the analysis explores research hotspots, institutional influences, and keyword evolution. The results reveal a multifaceted global landscape: China leads in publication output, and the United States maintains a leading role in citation impacts and technological innovation, with other notable contributions from Germany, Japan, South Korea, and various European countries. Patent trend analysis further reveals the rapid expansion of tokamak applications, particularly with significant innovations in high-temperature superconducting magnets and plasma control technologies. Nevertheless, the study identifies major challenges in the commercialization process, including plasma stability control, material durability, and the sustainability of long-term operations. To address these, the study proposes concrete future directions, emphasizing international collaboration and interdisciplinary integration. These efforts are crucial in accelerating tokamak commercialization, thereby providing a strategic roadmap for researchers, policymakers, and industry stakeholders to advance the global deployment of clean energy solutions. Full article

Heterologous expression of caseins in non-mammalian systems offers a sustainable and scalable alternative for producing milk proteins, with potential applications in the food and biopharmaceutical industries. However, a significant challenge in these systems is achieving proper phosphorylation, a critical post-translational modification required for casein functionality and stability. This review explores the current state of research on heterologous casein production, with a particular focus on the biological and technical hurdles associated with phosphorylation. Specifically, we examine the absence of the mammalian-specific kinase Fam20C in plant and yeast systems and the broader lack of secretory kinase machinery in bacteria, which collectively contribute to impaired phosphorylation fidelity. While some endogenous kinases may partially compensate, they are typically insufficient to replicate the phosphorylation pattern required for functionality. We evaluate potential strategies to address these limitations, analyze the role of phosphorylation in casein functionality, provide insights into existing patents and experimental approaches, and highlight ongoing research efforts. By synthesizing current knowledge and proposing new avenues for innovation, this review aims to provide a roadmap for the successful production of functional heterologous caseins. Full article

Technology roadmapping is conducted by systematic mapping of technological evolution through patent analytics to inform innovation strategies. This study proposes an integrated framework combining hierarchical Latent Dirichlet Allocation (LDA) modeling with multiphase technology lifecycle theory, analyzing 113,449 Derwent patent abstracts (2008–2022) across three dimensions: technological novelty, functional applications, and competitive advantages. By segmenting innovation stages via logistic growth curve modeling and optimizing topic extraction through perplexity validation, we constructed dynamic technology roadmaps to decode latent evolutionary patterns in AI-powered programmable manipulators (B25J classification) within an innovation trajectory. Key findings revealed: (1) a progressive transition from electromechanical actuation to sensor-integrated architectures, evidenced by 58% compound annual growth in embedded sensing patents; (2) application expansion from industrial automation (72% early stage patents) to precision medical operations, with surgical robotics growing 34% annually since 2018; and (3) continuous advancements in adaptive control algorithms, showing 2.7× growth in reinforcement learning implementations. The methodology integrates quantitative topic modeling (via pyLDAvis visualization and cosine similarity analysis) with qualitative lifecycle theory, addressing the limitations of conventional technology analysis methods by reconciling semantic granularity with temporal dynamics. The results identify core innovation trajectories—precision control, intelligent detection, and medical robotics—while highlighting emerging opportunities in autonomous navigation and human–robot collaboration. This framework provides empirically grounded strategic intelligence for R&D prioritization, cross-industry investment, and policy formulation in Industry 4.0. Full article

Solid-state batteries (SSBs) hold the potential to revolutionize energy storage systems by offering enhanced safety, higher energy density, and longer life cycles compared with conventional lithium-ion batteries. However, the widespread adoption of SSBs faces significant challenges, including low charge mobility, high internal resistance, mechanical degradation, and the use of unsustainable materials. These technical and manufacturing hurdles have hindered the large-scale commercialization of SSBs, which are crucial for applications such as electric vehicles, portable electronics, and renewable energy storage. This study systematically reviews the global SSB patent landscape using a cross-sectional bibliometric and thematic analysis to identify innovations addressing key technical challenges. The study classifies innovations into key problem and solution areas by meticulously examining 244 patents across multiple dimensions, including year, geographic distribution, inventor engagement, award latency, and technological focus. The analysis reveals significant advancements in electrolyte materials, electrode designs, and manufacturability. This research contributes a comprehensive analysis of the technological landscape, offering valuable insights into ongoing advancements and providing a roadmap for future research and development. This work will benefit researchers, industry professionals, and policymakers by highlighting the most promising areas for innovation, thereby accelerating the commercialization of SSBs, and supporting the transition toward more sustainable and efficient energy storage solutions. Full article

In the dynamic field of robotics engineering, nanorobot technology has witnessed rapid advancements. Developing a technology roadmap is essential for quickly identifying the trends and key technological aspects of nanorobotics from an array of multi-source data. Traditional research methods, such as Delphi surveys, bibliometrics, patent analysis, and patent paper citation analyses, often fail to capture the rich semantic information available. Moreover, these approaches generally provide a unidimensional perspective, which restricts their capacity to depict the complex nature of technological evolution. To overcome these shortcomings, this paper introduces a novel framework that utilizes the ALBERT method combined with multi-source data for critical theme extraction. It integrates varied data sources, including academic papers and patents, to explore the interrelation within the nanorobot technology roadmap. The methodology begins with text feature extraction, clustering algorithms, and theme mining to identify dominant technological themes. Subsequently, it applies semantic similarity measures to connect multiple themes, employing a “multi-layer ThemeRiver map” for a visual representation of these inter-layer connections. The paper concludes with a comprehensive analysis from both the technological research and industrial application perspectives, underscoring the principal developmental themes and insights of nanorobot technology, and projecting its future directions. Full article

There is a clear target and roadmap for the peaking of carbon emissions and achievement of carbon neutrality, and prior to this target being reached, penalties have been formulated to supervise enterprises and prompt green innovation. This study aimed to investigate the transmission mechanism between environmental penalties and green innovation using an empirical econometrical model and two sets of samples—punished firms and heavily polluting listed firms—amounting to 520 punished firms and 6043 firm-year observations. The main conclusions were threefold. Firstly, regarding the panel data, of the three parameters, namely, the times of penalties, the number of penalty fines, and the intensity of the penalty, only the number of penalty fines were statistically significant in terms of green innovation, indicating that only the hypothesis that, the higher the number of environmental penalties, the greater the green innovation that could be supported. Secondly, from a longitudinal perspective, there was one spontaneous effect on green patents, but the effect faded quickly in the second year after the punishment, indicating that firms did not seek green innovation as the solution for environmental penalties from a long-term perspective. Thirdly, the case number of external penalties in a province was significantly statistically associated with green innovation under an intertwined effect of the actual controller and shareholders. Therefore, there was a spillover of the deterrence effect from external penalties, with a higher number of penalty cases in a province corresponding to greater green innovation but with a very subtle coefficient. In addition, taking the median as the benchmark for group division, the group smaller than the median was statistically significant, while the group with a higher number of external penalties was not statistically significant, suggesting that firms were used to the penalties issued by environmental authorities. Full article

The increasing density of urban populations has spurred interest in utilizing underground space. Underground logistics systems (ULS) are gaining traction due to their effective utilization of this space to enhance urban spatial efficiency. However, research on technological advancements in related fields remains limited. To address this gap, we applied a data-driven approach using patent data related to the ULS to develop a technology roadmap for the field. We employed Latent Dirichlet Allocation (LDA), a machine learning-based topic modeling technique, to categorize and identify six specific technology areas within the ULS domain. Subsequently, we conducted portfolio analytics to pinpoint technology areas with high technological value and to identify the major patent applicants in these areas. Finally, we assessed the technology market potential by mapping the technology life cycle for the identified high-value areas. Among the six technology areas identified, Topic 1 (Underground Material Handling System) and Topic 4 (Underground Transportation System) showed significant patent activity from companies and research institutions in China, the United States, South Korea, and Germany compared to other countries. These areas have the top 10 patent applicants, accounting for 20.8% and 13.6% of all patent applications, respectively. Additionally, technology life cycle analytics revealed a growth trajectory for these identified areas, indicating their rapid expansion and high innovation potential. This study provides a data-driven methodology to develop a technology roadmap that offers valuable insights for researchers, engineers, and policymakers in the ULS industry and supports informed decision-making regarding the field’s future direction. Full article

This study explores the implementation of an interdisciplinary curriculum in product and media design education and its impact on knowledge innovation and competency development. The curriculum is based on scaffolding theory, incorporating design proposals, workshops, digital design, marketing tests, and marketing activities guided by teachers and mentors from a branded ceramic workshop. The research findings demonstrate that the interdisciplinary curriculum facilitates knowledge innovation and fosters the development of students’ professional skills, creativity, and problem-solving skills. The study also highlights the importance of stable scaffolding, including artefact-, peer-, and teacher support, which significantly contributes to cultivating transformational competencies, as outlined in the 2030 OECD Learning Compass. Additionally, the collaboration with Shanshing Four Seasons Celadon Studio on a patented ceramic product, “Funny Monkey”, is a tangible example of the journey towards a triple-helix knowledge economy. This research underscores the importance of interdisciplinary curricula in promoting knowledge innovation and integrating transformational competencies in education. Scaffolding theory provides practical guidance for student learning and teaching strategies, presenting a sustainable roadmap for developing interdisciplinary curricula and offering a concrete and transferable pedagogical prototype for educational innovation. Full article

The semi-automatic construction and analysis of technology roadmaps are at the forefront of applying artificial intelligence techniques. To clarify the development path of the core technologies in the field of agricultural machinery, we propose a core technology evolution path analysis method based on patent text semantic mining. First, the key sentences in the text were extracted, and the BERT model was used to represent the topic’s key sentences in semantic vectorization. Then, the technology roadmap was constructed through the unsupervised LDA topic clustering method, and the main fields of activity, blank fields, and fields of agricultural machinery were visually analyzed. Next, investment in research fields was strengthened. Finally, we mapped the technology roadmap and patent IPC codes and found that the evolution of core technologies in the field of agricultural machinery could be divided into the technology development stage, technology focus stage, and technology transformation stage; this allows us to analyze the evolution and integration of these core technologies. The internal laws of the technology evolution provide a reference for future research plans of governments, enterprises, and institutions, aiding in the patent portfolio planning by revealing the microlevel process of technology integration and the technological trends in agricultural machinery. Full article

This multi-disciplinary paper aims to provide a roadmap for the development of an integrated, process-intensified technology for the production of H₂, NH₃ and NH₃-based symbiotic/smart fertilizers (referred to as target products) from renewable feedstock with CO₂ sequestration and utilization while addressing environmental issues relating to the emerging Food, Energy and Water shortages as a result of global warming. The paper also discloses several novel processes, reactors and catalysts. In addition to the process intensification character of the processes used and reactors designed in this study, they also deliver novel or superior products so as to lower both capital and processing costs. The critical elements of the proposed technology in the sustainable production of the target products are examined under three-sections: (1) Materials: They include natural or synthetic porous water absorbents for NH₃ sequestration and symbiotic and smart fertilizers (S-fertilizers), synthesis of plasma interactive supported catalysts including supported piezoelectric catalysts, supported high-entropy catalysts, plasma generating-chemical looping and natural catalysts and catalysts based on quantum effects in plasma. Their performance in NH₃ synthesis and CO₂ conversion to CO as well as the direct conversion of syngas to NH₃ and NH₃—fertilizers are evaluated, and their mechanisms investigated. The plasma-generating chemical-looping catalysts (Catalysts, 2020, 10, 152; and 2016, 6, 80) were further modified to obtain a highly active piezoelectric catalyst with high levels of chemical and morphological heterogeneity. In particular, the mechanism of structure formation in the catalysts BaTi_1−rM_rO_3−x−y{#}_xN_z and M₃O_4−x−y{#}_xN_z/Si = X was studied. Here, z = 2y/3, {#} represents an oxygen vacancy and M is a transition metal catalyst. (2) Intensified processes: They include, multi-oxidant (air, oxygen, CO₂ and water) fueled catalytic biomass/waste gasification for the generation of hydrogen-enriched syngas (H₂, CO, CO₂, CH₄, N₂); plasma enhanced syngas cleaning with ca. 99% tar removal; direct syngas-to-NH₃ based fertilizer conversion using catalytic plasma with CO₂ sequestration and microwave energized packed bed flow reactors with in situ reactive separation; CO₂ conversion to CO with BaTiO_3−x{#}_x or biochar to achieve in situ O₂ sequestration leading to higher CO₂ conversion, biochar upgrading for agricultural applications; NH₃ sequestration with CO₂ and urea synthesis. (3) Reactors: Several patented process-intensified novel reactors were described and utilized. They are all based on the Multi-Reaction Zone Reactor (M-RZR) concept and include, a multi-oxidant gasifier, syngas cleaning reactor, NH₃ and fertilizer production reactors with in situ NH₃ sequestration with mineral acids or CO₂. The approach adopted for the design of the critical reactors is to use the critical materials (including natural catalysts and soil additives) in order to enhance intensified H₂ and NH₃ production. Ultimately, they become an essential part of the S-fertilizer system, providing efficient fertilizer use and enhanced crop yield, especially under water and nutrient stress. These critical processes and reactors are based on a process intensification philosophy where critical materials are utilized in the acceleration of the reactions including NH₃ production and carbon dioxide reduction. When compared with the current NH₃ production technology (Haber–Bosch process), the proposed technology achieves higher ammonia conversion at much lower temperatures and atmospheric pressure while eliminating the costly NH₃ separation process through in situ reactive separation, which results in the production of S-fertilizers or H₂ or urea precursor (ammonium carbamate). As such, the cost of NH₃-based S-fertilizers can become competitive with small-scale distributed production platforms compared with the Haber–Bosch fertilizers. Full article

In the digital era, companies have experienced a progressive change in their business models, which has led them to develop greater agility to adapt to changing environments, and the necessity to properly manage the group decision making in these companies is patent. This paper shows how fuzzy models are utilized in group decision making. In this context, one of the most important group decisions to be adopted is how to manage the digital transformation of the company, drawing up the best possible roadmap. To achieve this goal, this paper proposes a new methodology improvement of group decision making based on a fuzzy 2-tuple linguistic model and the analytic hierarchy process (AHP) method. The suggested methodology proposes the calculation of the digital maturity level (DML) of companies based on five of the most cited and agreed upon criteria in the existing literature. The methodology proposed in this paper was tested and validated for the business case of Spanish SMEs through three different clusters to derive global recommendations tailored to each specific cluster and company segments, using a sample of 1428 companies. The main fundings reveal that the digital maturity level directly impacts on the size of the company and its digital mindset in the sense of driving change management processes. As future works, authors recommend extending the model to any industry using the proposed methodology and evaluate disruptive technologies such as artificial intelligence (AI) in supporting the digital transformation of SMEs. Full article

This study aims to predict new technologies by analyzing patent data and identifying key technology trends using a Temporal Network. We have chosen big data-based smart logistics technology as the scope of our analysis. To accomplish this, we first extract relevant patents by identifying technical keywords from prior literature and industry reports related to smart logistics. We then employ a technology prospect analysis to assess the innovation stage. Our findings indicate that smart logistics technology is in a growth stage characterized by continuous expansion. Moreover, we observe a future-oriented upward trend, which quantitatively confirms its classification as a hot technology domain. To predict future advancements, we establish an IPC Temporal Network to identify core and converging technologies. This approach enables us to forecast six innovative logistics technologies that will shape the industry’s future. Notably, our results align with the logistics technology roadmaps published by various countries worldwide, corroborating our findings’ reliability. The methodology presents in this research provides valuable data for developing R&D strategies and technology roadmaps to advance the smart logistics sector. Full article

The content of the China-US CCUS technology development roadmap is summarized based on the roadmap update in 2019. Qualitative analysis and evaluation were conducted from the perspectives of running CCUS demonstrations or industrial projects, CO₂ pipeline infrastructure, established regulatory frameworks, policy support, research and development capabilities, and geological storage resources. A simple analysis of the development status of carbon capture, storage, and utilization technology through relevant patent data is provided. Future planning by China and the United States in terms of planning volume, investment funds, related industries, transportation methods, geological storage, geological utilization, other utilization methods, and incentive policies is compared. Overall, US CCUS technology development is in the leading position in the world; it has entered the stage of small-scale commercial promotion, while the overall development level of China’s CCUS technology is still behind the international advanced level in a small-scale experimental demonstration period, and is still in the catch-up stage. However, as the Chinese government has put forward the strategy of “carbon peaking and carbon neutralization”, CCUS has ushered in a golden opportunity for development in China, and some large-scale industrial demonstration projects have been carried out. This study analyzes China’s advantages and challenges in developing CCUS and gives some suggestions on the direction that China’s CCUS development should take in the future. Full article

Hyperuricemia is a metabolic disease with an increasing incidence in recent years. It is critical to identify potential technology opportunities for hyperuricemia drugs to assist drug innovation. A technology roadmap (TRM) can efficiently integrate data analysis tools to track recent technology trends and identify potential technology opportunities. Therefore, this paper proposes a systematic data-driven TRM approach to identify potential technology opportunities for hyperuricemia drugs. This data-driven TRM includes the following three aspects: layer mapping, content mapping and opportunity finding. First we deal with layer mapping. The BERT model is used to map the collected literature, patents and commercial hyperuricemia drugs data into the technology layer and market layer in TRM. The SAO model is then used to analyze the semantics of technology and market layer for hyperuricemia drugs. We then deal with content mapping. The BTM model is used to identify the core SAO component topics of hyperuricemia in technology and market dimensions. Finally, we consider opportunity finding. The link prediction model is used to identify potential technological opportunities for hyperuricemia drugs. This data-driven TRM effectively identifies potential technology opportunities for hyperuricemia drugs and suggests pathways to realize these opportunities. The results indicate that resurrecting the pseudogene of human uric acid oxidase and reducing the toxicity of small molecule drugs will be potential opportunities for hyperuricemia drugs. Based on the identified potential opportunities, comparing the DNA sequences from different sources and discovering the critical amino acid site that affects enzyme activity will be helpful in realizing these opportunities. Therefore, this research provides an attractive option analysis technology opportunity for hyperuricemia drugs. Full article

Hydrogen energy, one of the energy sources of the future, represents a substantial issue which affects the industries and national technologies that will develop in the future. In order to utilize hydrogen energy, a hydrogen supply chain is required so that hydrogen can be processed and transported to vehicles. It is helpful for technology and policy development to analyze technologies necessary to charge the hydrogen energy generated into vehicles through the supply chain to discover technologies with high potential for future development. The purpose of this paper is to identify promising technologies required in storing, transporting, and charging vehicles generated by the hydrogen fuel supply chain. Afterward, the promising technologies identified are expected to help researchers set a direction in researching technologies and developing related policies. Therefore, we provide technology information that can be used promisingly in the future so that researchers in the related field can utilize it effectively. In this paper, data analysis is performed using related patents and research papers for technical analysis. Promising technologies that will be the core of the hydrogen fuel supply chain in the future were identified using the published patents and research paper database (DB) in Korea, the United States, Europe, China, and Japan. A text mining technique was applied to preprocess data, and then a generic topographic map (GTM) analysis discovered promising technologies. Then, a technology roadmap was identified by analyzing the promising technology derived from patents and research papers in parallel. In this study, through the analysis of patents and research papers related to the hydrogen supply chain, the development status of hydrogen storage/transport/charging technology was analyzed, and promising technologies with high potential for future development were found. The technology roadmap derived from the analysis can help researchers in the field of hydrogen research establish policies and research technologies. Full article