Search Results (1,329)

Cobalt has emerged as a strategic critical metal due to its essential role in rechargeable batteries, high-performance alloys, catalysts, and clean energy technologies. However, its supply chain remains heavily dependent on cobalt produced as a by-product of copper and nickel mining and is geographically concentrated, particularly in the Democratic Republic of Congo. This review provides a comprehensive assessment of cobalt geology, mineralogy, global reserves, market trends, primary extraction routes, and emerging secondary recovery strategies. Unlike previous reviews that address these topics separately, this work integrates geological occurrence, mineralogical characteristics, extraction technologies, and resource circularity within a unified framework aimed at evaluating future cobalt supply resilience. The main cobalt-bearing deposit types of sediment-hosted Cu–Co deposits, Ni–Co laterites, and magmatic Ni–Cu–Co sulphide deposits are compared in terms of their mineralogical characteristics and processing requirements. Hydrometallurgy is identified as the dominant industrial route, typically combining high-pressure acid leaching (HPAL) with downstream purification and recovery processes such as solvent extraction and electrowinning (SX–EW). Emphasis is placed on the relationship between ore mineralogy and process selection, as well as on the growing integration of secondary resources, including tailings, slags, and spent batteries, into existing cobalt production chains. Despite promising recovery rates at laboratory scale, challenges remain in impurity control, economic scalability, and integration into established refining infrastructure. This review demonstrates that secondary resources are evolving from supplementary feedstocks to strategically important contributors to cobalt supply. Future supply security will depend on feedstock diversification, more flexible refining systems, improved impurity management, and the implementation of sustainable circular-economy strategies. Full article

Due to increasing demand and consumption of electricity, as well as the need to decarbonize and mitigate climate change, solar energy is an important factor in the transition to emission-free energy sources. This study focuses on identifying the most suitable locations for the construction of large solar photovoltaic (PV) power plants while respecting environmental, economic, and technical standards. The study area covers the mainland part of Southeastern Europe (796,039 km²), including the following countries: Slovenia, Croatia, Bosnia and Herzegovina, Serbia, Montenegro, North Macedonia, Albania, Greece, Bulgaria, Romania, Moldova, and Türkiye. Using geographic information systems (GIS) and remote sensing methods, nine factors (topographic, climatic, hydrological, ecological, vegetation, and anthropogenic) were analyzed with a spatial resolution of 100 m. A fuzzy analytic hierarchy process (F-AHP) pairwise comparison matrix was constructed to quantify the relative importance of the selected criteria. The F-AHP weighting results indicate that photovoltaic output (17.9%) and land use (15.7%) are the most important among the evaluated criteria. The results show that 6.7% of Southeastern Europe is very highly suitable for installing solar PV plants, with the most suitable areas located in Moldova (14.5%) and Greece (10.5%). Through spatial analysis of the final results, 24 of the most suitable locations for large-scale solar PV power plant development were identified, with a potential to generate approximately 30.2 TWh of electricity annually. In such a scenario, the forecast indicates that 24 large-scale solar power plants would supply electricity to more than 6.7 million households, corresponding to over 17 million inhabitants. The final spatial patterns provide decision-makers at the international level with a significantly more effective basis for planning solar energy development in order to increase the share of green energy and clean technologies in this part of Europe. Full article

Trace water is one of the most critical matrix contaminants in ultra-high-purity (UHP) process gases, like argon (Ar), nitrogen (N₂), and many others. Even trace amounts can severely degrade the quality of many products that are reliant on these gases. Despite its importance to advanced technology sectors, notably semiconductor manufacturing, it has proven quite difficult to realize preparative or analytical trace water metrology over the full amount fraction range needed or in the broad spectrum of industrially relevant matrix gases. Within the EU-funded PROMETH2O project consortium, this challenge has been addressed through the development or significant improvement of traceable measurement methods and standards spanning 5 nmol⋅mol⁻¹ to 5 µmol⋅mol⁻¹, tailored for use in UHP process gas production, such as Ar, N₂ and clean dry air (CDA). The measurement ranges were extended and the uncertainties were improved while being consistent with the current best practice at primary humidity standard laboratories. The developed standards provide combined standard uncertainties ranging from approximately 0.4 % to 1.5 % in water vapor amount fraction and from 0.03 °C to 0.07 °C in frost-point temperature, while the comb-assisted CRDS system achieves detection limits in the sub-ppb to ppt range. These capabilities were validated in applications that are relevant to process instrumentation and the gas industry. A distributed metrological infrastructure at various European national metrology institutes and partner sites now provides SI-traceable trace water measurements in UHP gases, strongly supporting and extending the calibration capabilities for the gas and semiconductor industries and the associated stakeholders. Full article

The efficient removal of tenacious oxide scales from hot-rolled steel surfaces represents a persistent challenge in advanced manufacturing, as traditional manual grinding methods exhibit poor efficiency and environmental compatibility. This investigation develops an innovative methodology, i.e., a “coarse-to-fine” hierarchical cleaning paradigm consisting of dual-stepwise laser cleaning with variable parameters that successfully addresses the restrictive process window inherent to conventional single-parameter techniques. Through a strategically designed sequential treatment protocol—employing initial low-frequency (20 kHz), high-energy-density (200 mm/s) laser irradiation for primary oxide ablation, succeeded by high-frequency (60 kHz), low-energy-density (4000 mm/s) processing for residual scale elimination—we demonstrate an optimal synergy between ablative and thermomechanical vibration mechanisms. Rigorous multi-modal characterization incorporating SEM-EDS microscopy, oxygen content quantification, and metallographic analysis confirms exceptional performance metrics, including 98.7% oxide removal efficiency and 43.2% reduction in substrate surface roughness relative to standard methods. The developed protocol achieves a 2.8-fold expansion of the operational parameter space while establishing a novel “coarse-to-fine” hierarchical cleaning paradigm. These findings offer fundamental insights into laser–matter interactions while delivering a transferable technological framework for high-value manufacturing sectors, particularly in automotive and aerospace component production. Full article

Hydrogen peroxide (H₂O₂) is widely used in semiconductor cleaning and etching, where ultralow levels of metallic, anionic, organic, and particulate impurities must be strictly controlled. Industrially produced H₂O₂ therefore requires extensive downstream purification before it can meet electronic-grade specifications. Conventional purification routes based on distillation or rectification, adsorption, ion exchange, and final filtration are technically mature, but they remain constrained by substantial energy consumption, multiple treatment stages, chemical regeneration, secondary waste generation, and safety risks associated with H₂O₂ decomposition. This review critically evaluates membrane technologies for purifying and concentrating electronic-grade H₂O₂. Microfiltration and ultrafiltration are discussed as front-end clarification processes, nanofiltration as an intermediate impurity-load-reduction step, and reverse osmosis as the membrane process with the strongest direct experimental for ionic-impurity removal from concentrated H₂O₂. Pervaporation and membrane distillation are assessed as emerging water-removal technologies, although their industrial applicability remains insufficiently validated. Membrane material strategies, including oxidation-resistant polymers, inorganic and hybrid membranes, antioxidant-containing composites, and emerging MOF- and two-dimensional-material-based membranes, are also evaluated. Particular attention is paid to the limited direct evidence available for emerging materials and to the risks of H₂O₂ decomposition, material leaching, particle release, and deterioration of membrane selectivity. The available evidence indicates that membrane processes are currently more appropriately regarded as complementary clarification, purification, polishing, or concentration units rather than complete replacements for established industrial technologies. Future studies should prioritize long-term oxidative stability, ppb- and ppt-level impurity validation, low H₂O₂ loss, module-material compatibility, process safety, and continuous pilot-scale techno-economic assessment. Full article

Among numerous atmospheric-pressure plasma jets (APPJs), high industrial acceptability has been reached for the ones based on high-voltage, low-current, vortex-stabilized arc, typically operated with kHz DC-pulses. This review explores the interrelations between the “process” in a chemical–physical sense and “process”, or to better differentiate, “processing” in the sense of technological treatment, with respect to such APPJs. The mutual dependence of the processing requirements (e.g., high processing speed, compatibility with robotic processing, low total cost of ownership, reliability, and long service intervals) and the physical and chemical processes in the plasma jet are analyzed. The focus is on the hybrid character of the produced plasma, comprising a non-equilibrium arc and a diffuse plasma. Different operation modes of the gliding arc discharge (GAD) are discussed. The reviewed chemical processes are the generation of reactive oxygen–nitrogen species (RONS), oxidation and reduction reactions, and interactions with vapors, solids, and liquids. The considered processing examples are established applications, such as surface activation, cleaning, oxide reduction, film removal, and coating, as well as emerging applications for sterilization and plasma-activated water (PAW) production. Full article

The dairy industry is increasingly seeking natural alternatives to synthetic additives to meet the growing demand for clean-label and functional foods. Bee-derived products (BDPs), including propolis, honey, bee pollen, bee bread, and royal jelly, represent a promising class of bioactive ingredients due to their antimicrobial, antioxidant, and immunomodulatory properties. This review critically examines their integration across the dairy value chain, adopting a farm-to-product perspective. At the farm level, BDPs can modulate rumen fermentation, influence microbial populations, and contribute to improved feed efficiency and reduced enteric methane emissions. These effects may translate into modifications in milk composition and functional properties. At the processing and product levels, the incorporation of BDPs into dairy matrices such as yogurt, cheese, and fermented milk enables the development of functional foods enriched with bioactive compounds and supports probiotic viability in synbiotic systems. However, their application is associated with technological and sensory challenges, including variability in chemical composition, dose-dependent antimicrobial effects, and potential impacts on texture and flavour. By bridging animal and food science, this review highlights the multifunctional role of BDPs in enhancing sustainability, safety, and nutritional value in dairy systems, while identifying current limitations and future research directions for their effective industrial implementation. Full article

Offshore wind is expanding globally, driven by energy security and decarbonization goals. Brazil’s world-class potential for this resource is challenged by its unique context: an already clean electricity matrix and abundant, low-cost onshore alternatives, which reduce the immediate urgency for deployment. This paper starts with a global offshore wind market analysis, understanding why the main countries pursue this technology, in contrast with Brazil’s already high share of renewable generation. The following examination focuses on Brazil’s recently approved new offshore wind framework and the governance-related issues, revealing that the legislative process was distorted by unrelated riders mandating costly, non-competitive energy procurement. These riders threatened to absorb future market growth, undermining competition and jeopardizing the emergence of the entire offshore wind industry. While presidential vetoes of these riders were essential to preserve this opportunity, remaining market distortions still favor mature technologies. The study concludes that Brazil’s primary barrier to offshore wind is not technical or resource-based but institutional: the need for stable, transparent governance to foster a truly competitive and predictable policy environment. Full article

Breakthrough innovation—central to industrial competitiveness and the ongoing clean-energy transition—remains persistently constrained by information homogenization and weak cross-domain integration in single-layer innovation networks. Technology Innovation Composite Networks (TICNs) have therefore been advocated as dual-layer platforms coupling knowledge and collaboration networks, yet the cross-layer mechanism through which they generate breakthrough outputs has not been specified. This paper specifies and tests how knowledge-layer structural holes open access to heterogeneous information that must cross into the collaboration layer to be recombined into breakthroughs. Two distinct boundaries shape the outcome. Inventors’ finite cognitive processing capacity makes integration returns decay along an inverted U-shape; separately, excessive degree and closeness centrality drive the collaboration layer into homogenization and localization, narrowing the range of structural holes it can productively absorb and shifting the breakthrough peak toward lower structural-hole levels. Together, they delineate an optimal cross-layer integration zone. Using panel data on 10,681 patents, 948 inventors, and 5631 inventor-year observations from new energy (2004–2018), a fixed-effects negative binomial model confirms the inverted U-shape and the steepening, peak-shifting moderations of degree and closeness centrality; a Lind–Mehlum test places the turning point inside the observed data range, and negative binomial (robust SE), Poisson and zero-inflated Poisson specifications—together with a stricter top-1% breakthrough threshold—yield consistent results. The study moves multilayer network research from structural description toward mechanism-level identification and offers actionable network-design guidance. Full article

This manuscript will present an advancement of transformative research that has been conducted at Oak Ridge National Laboratory (ORNL) over a 25-year period (2000–2025) on a variety of environmental and biological matrices. These investigations derived a fundamental understanding of how elemental detection and analysis of these matrices led to the knowledge and discovery of natural processes in plants and the environment. Each project led to the initiation of a new research area which unearthed awesome and novel breakthroughs. Highlights are listed below: 1. The preliminary research at ORNL centered on the detection of aerosols utilizing Laser-induced Breakdown Spectroscopy (LIBS) technology. The Clean Air Act Amendment (CAAA) of 1990 highlighted the importance of identifying hazardous air pollutants (HAPs) due to their impact on environmental and human health, thereby underscoring the need to detect various toxic elements. Research in aerosol chemistry aimed to identify these harmful elements released by factories during periods of increased emissions in their manufacturing processes. LIBS emerged as the most effective method for real-time, in situ measurements of metal species in both gaseous and aerosol phases. 2. An understanding of the presence of total carbon in soils gives perspective on how to develop carbon sequestration strategies. The recognition that carbon sinks can evolve back to carbon sources to emit back to the atmosphere was an important consideration. Also, the concentration of carbon in soil indicates the health of land areas for growing crops successfully. 3. The direct detection of most of the elements in a wood sample in a single emission spectrum, without sample preparation, encouraged the research to use the LIBS technique for preservative treated wood coupled with use of multivariate statistical methodology. Additionally, it encouraged the researchers to try to differentiate natural woods from different parts of the country, and it was successfully demonstrated that LIBS coupled with MVA analysis could differentiate wood of different species from each other and of similar species grown in different environments based on their elemental spectra. This was a breakthrough since it revealed a systematic approach to connect elemental scarcity and abundance to either drought or typical rainfall conditions for the hardwood trees grown in specific areas. 4. Furthermore, the research progressed to reveal physiological and developmental processes contributing to biomass production such that the variation in leaf elemental composition increases our understanding of terrestrial nutrient cycles, as well as tracking the transfer of toxic elements from soils to living organisms. 5. Recently another breakthrough viz., ionomics initiated the correlation of elements to specific genes, uncovering the function that the element performed in the plant. More recently, this has been extended from plants to fungi as well as fungi growing in symbiotic relations with plants. Full article

This study presents a comprehensive bibliometric analysis of research trends in grain cleaning devices from 1998 to 2025. Grain cleaning equipment plays a critical role in post-harvest processing by improving grain quality, reducing losses, and enhancing overall efficiency in agricultural systems. The analysis is based on bibliographic data retrieved from the Scopus database. Various bibliometric tools and indicators, including publication trends, citation analysis, co-authorship networks, and keyword co-occurrence, were employed to identify patterns of development, major contributors, and emerging research themes in this field. The results reveal a significant growth in publications in recent years, reflecting increasing global interest in advanced cleaning technologies, including energy-efficient systems, intelligent sorting, and automation. Key research hotspots include vibration-based separation, pneumatic systems, and smart sensor-based cleaning technologies. This study provides a systematic overview of the intellectual structure and evolution of grain cleaning device research, offering valuable insights for researchers and practitioners. The findings also highlight existing research gaps and suggest future directions for the development of more efficient, sustainable, and intelligent grain processing technologies. Full article

Liquid storage tanks are widely used in sectors such as water treatment, oil and gas, food processing, and chemical manufacturing. Knowing the exact amount of liquid in a tank is essential for ensuring safety, preventing spills, and optimizing process control; therefore, the liquid level in a tank must be maintained at a precise reference point. This is where liquid level control for tanks becomes crucial and constitutes a fundamental problem in the industrial sector due to nonlinearities, multivariable coupling, and stochastic disturbances. Given the drawbacks of available control methods, such as classical Model Predictive Control (MPC), which are highly dependent on model accuracy and struggle to reject complex stochastic noise, predicting random disturbances represents a major technological challenge. A new approach is proposed to specifically address the problem and challenge of the four-tank system, where water levels in two lower tanks must be controlled by two pumps, often with varying delays and significant parameter disturbances. To establish a relationship between expected performance and MPC parameters, this approach uses a novel hybrid nonlinear MPC, Extended State Observer, and Physics-Informed Neural State Estimation (NMPC-ESO-PINSE) architecture. A Physics-Informed Neural State Estimation (PINSE) layer, chosen for its learning capacity, is designed to filter sensor noise by applying Bernoulli’s physical laws, while an Extended State Observer (ESO) is integrated to capture and compensate for unmodeled uncertainties in the process. Finally, a proposed hybrid (NMPC-ESO-PINSE) strategy leverages these clean, physically consistent state estimations to solve a non-convex optimization problem via Sequential Quadratic Programming (SQP), computing optimal pump voltages. Extensive numerical simulations demonstrate the superior resilience of this decoupled framework against parametric drifts and continuous noise sequences, yielding a $+27.36\%$ reduction in global Root Mean Square Error (RMSE) compared to standard NMPC, accelerating the closed-loop settling time to $15.2 \mathrm{s}$, and restricting transient overshoot to just $0.18\%$. Full article

In the Arabian Gulf region, saltwater desalination is considered to be a significant process in producing clean water. This paper presents a sustainable, combined process for upgrading a Doha reverse osmosis (RO) plant in Kuwait. A pilot-scale microbial desalination cell (MDC) stack is proposed as a pre-treatment unit prior to the RO process in order to improve plant performance. A cost–benefit analysis is conducted for the combined system to emphasize the significance of the MDC–RO process. In RO, the expected energy consumption is 2.6–13 kWh per m³ of desalinated water, whereas using MDC can reduce this to about 0.52–5.3 kWh/m³. Moreover, this new technology using catalytic MDCs can help in improving electric current production and reducing the amount of rejected brine and membrane fouling in the RO process. The electric current is improved by reducing MDCs’ internal resistance using a reduced graphene oxide/polyaniline composite-coated stainless steel mesh cathode electrode. Layer-by-layer electro-deposition can be applied to achieve these coatings. An intermediate zeolite filter is proposed to mitigate RO membrane fouling. The combined system’s natural zeolite-membrane filter improves water purification. In this study, we assessed the combined MDC–RO process for upgrading the Doha plant’s performance in terms of quality, cost, and time. The suggested catalytic MDC, using efficient, low-cost materials as cathode electrodes with an equivalent daily cost of 0.01 USD/m³ and a desalination efficiency of about 40%, acts as an alternative to high-cost platinum metal electrodes. The results also indicate that the equivalent daily cost of energy consumption using the MDC process is about 0.03 USD/m³, whereas the investment cost is about 0.4 USD/m³ daily for one year of cell operation. Full article

Waste cooking oils (WCO) are large-scale residual streams from domestic and industrial food processing. Their improper disposal poses severe environmental risks, yet their integration into the oleochemical sector offers a strategic opportunity for the green transition by substituting fossil-based feedstocks. This systematic review provides a comprehensive assessment of WCO valorization as a sustainable precursor for high-value products, specifically biopolymers, bioplasticizers, and biolubricants. The study followed the PRISMA 2020 guidelines, searching PubMed, Scopus, and MDPI databases (up to September 2025). The search strategy utilized combinations of keywords present in the title. Inclusion criteria focused on peer-reviewed chemical and biotechnological conversion pathways published in English within the last decade. Studies addressing biofuel production, patents, and review were excluded. Screening, data extraction, and qualitative risk of bias assessment, centered on experimental reproducibility and reporting transparency, were performed independently by multiple reviewers. From an initial pool of 2637 records, 87 studies met the eligibility criteria. The analysis reveals that polyhydroxyalkanoates (PHAs) represent the most extensively researched pathway, followed by WCO-derived epoxides and innovative biolubricant formulations. While several studies report high conversion yields under optimized conditions, the transition from bench-scale to industrial implementation remains hindered by the heterogeneous composition of WCO and a lack of standardized pre-treatment protocols. WCO valorization shows transformative potential for the circular economy, offering a dual benefit of waste mitigation and sustainable material synthesis. However, future research must address scalability challenges and feedstock variability. This review identifies emerging trends and provides a roadmap for the industrial adoption of WCO-based processes in the framework of clean technologies. Full article