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Lignin is the most abundant renewable source of aromatic carbon, and yet it remains a mostly underutilized byproduct of the biorefinery and paper industries. Factors such as complexity and a heterogeneous structure make lignin recalcitrant to conventional valorization, the utility of which often requires harsh conditions and expensive catalysts. Electrochemical conversion has emerged as a highly promising, sustainable alternative due to the use of electricity produced by renewable sources to drive depolymerization under mild, ambient conditions. This review summarizes recent progress in this field and provides a comprehensive overview of the primary electrochemical pathways used to promote the valorization of lignin. Herein, we critically examine oxidative strategies that include both direct electrooxidation at the anode surface and indirect oxidation using redox mediators, and provide details of the key challenges of electrode deactivation and product overoxidation. We then discuss reductive strategies with a focus on electrocatalytic hydrogenolysis for C-O bond cleavage. Furthermore, we explore advanced integrated systems that combine electrochemistry with microbial, enzymatic, and photochemical processes to enhance selectivity and efficiency. Finally, this review addresses persistent challenges and offers future perspectives and suggests opportunities with an emphasis on the critical need for innovations in electrocatalyst design, green electrolytes, and integrated reactor engineering to unlock the full potential of lignin as a renewable feedstock for a circular carbon economy.

The decarbonization of urban energy communities increasingly requires coordinated integration of hydrogen, electricity, heat, and mobility under market-regulated environments. This study develops a hydrogen-driven digital transactions market embedded within a clustered, integrated energy hub architecture, where digital transactions markets, such as carbon emission trading (CET) and green certificate trading (GCT) mechanisms, are endogenously incorporated into operational scheduling. The framework coordinates hydrogen-diversified utilization, dual electric-hydrogen transportation systems, multi-vector storage, and renewable generation under carbon accounting constraints and social multi-stakeholder interactions. A decentralized multi-carrier optimization model is formulated to minimize system-wide scheduling cost while integrating CET/GCT revenues directly into dispatch decisions. Uncertainties in renewable generation, demand, and electricity prices are modeled using an inexact probabilistic stochastic programming approach with scenario generation and reduction. To extend evaluation beyond economic performance, a hydrogen-centric eco-social welfare layer comprising ten normalized indicators is introduced, quantifying emission mitigation, accessibility, equity, cost relief, and public acceptance. The model is validated on a four-hub clustered configuration under baseline and stress-test scenarios, including demand surges, renewable shortfalls, hydrogen price shocks, and market price fluctuations. Results demonstrate effective coordination between hydrogen production, storage, and mobility demand, with demand-side flexibility reducing operational costs by more than 16% in selected hubs. Carbon and certificate oracles market participation improves financial performance while enhancing emission compliance. Sensitivity analysis confirms robustness under combined worst-case disturbances. The proposed framework establishes a unified operational market structure that links hydrogen diversification, digital carbon-regulated transactions, and measurable eco-social welfare within sustainable urban energy systems.

The optimal power flow (OPF) problem is essentially about finding the cheapest and safest way to operate a power system without breaking any of the operational limits that govern it. In this paper, we introduce a new Modified Newton-Raphson-Based Optimizer (MNRBO) specifically designed to tackle real-world OPF problems, integrating renewable photovoltaic sources. The NRBO integrates gradient-inspired search using the NR search rule and the trap avoidance strategy. Our MNRBO extends this framework by adding two adaptive components. An Adaptive Crossover Mechanism (ACM) is added that lets solutions dynamically exchange useful information with each other, keeping the population diverse and preventing everyone from getting stuck in the same mediocre spot too soon. Also, a Sigmoid decay mode that smoothly and gradually shifts the algorithm from broad exploration (looking around the whole search space) in the early stages to careful fine-tuning (exploitation) toward the end. This gives much steadier and more predictable convergence than the original abrupt or polynomial decay. The resulting MNRBO algorithm forms a self-evolving optimization framework that automatically adjusts its learning strategy as the search progresses. We thoroughly tested MNRBO on the standard IEEE 30-bus system across a wide range of realistic scenarios: minimizing fuel costs (with smooth quadratic models, valve-point ripples, and multi-fuel options), handling generators with prohibited operating zones, and minimizing transmission losses under normal, peak, and light-load conditions. In every single case, MNRBO delivered better solutions, faster and more consistent convergence, and dramatically lower variation across multiple runs compared to the original NRBO and several other state-of-the-art algorithms. The results clearly show that MNRBO is not only more accurate but also far more robust and dependable, exactly what operators need when solving OPF in real power systems where reliability really matters. To further validate the applicability of the proposed approach under renewable energy uncertainty, a probabilistic OPF framework incorporating photovoltaic renewable generation is developed. In this case study, the integration of renewable solar photovoltaic energy in conditions of variable irradiance is examined using the Point Estimate Method (PEM) with lognormal irradiance modeling. In addition, an ablation study is conducted to quantify the individual contributions of the ACM and sigmoid decay strategy in the presence of renewable photovoltaic sources, demonstrating their significant impact on convergence stability, robustness, and optimization accuracy.

India has grown increasingly dependent on imported foreign fossil fuels to fuel an expanding population and economy, thereby placing considerable strain on the economy, society, and environment. Transitioning from fossil fuels to renewable sources of energy is necessary for India to continue developing and prospering as a nation in the future. One approach to realize energy goals (SDG-7) for India and assist it in transitioning to renewable energy is using photovoltaic (PV) technology. Despite having gained significant traction in India, many barrierss still exist beyond improving effectiveness. A systematic approach will be presented in this paper to overcome these barriers using the spherical fuzzy (SF) technique for decision-making. The SF decision-making technique is designed to help reduce uncertainty when making decisions and to minimize bias when evaluating procedures and regulations related to solar energy. To support the SF framework proposed, three different methodologies will be utilized: SF-SWARA for determining subjective criterion weights; SF-CRITIC for finding objective weights; and SF-CODAS for ranking strategic alternatives. Based on a literature review and recommendations from the authors, twelve main barriers will be identified and ranked according to their relative importance in achieving success with PV technology in India. Furthermore, it is suggested that funding be allocated for additional research and development to boost domestic production of PV equipment. An evaluation of the proposed methodology confirms its reliability, particularly through comprehensive sensitivity analysis. The authors provide thorough evidence to support the recommendation of using this methodology to evaluate the expected economic and environmental impacts of PV technology in India.

Among renewable energy sources, hydropower has been the most economical and well-established technology for decades. However, the construction of hydropower plants (HPPs) may have (unknown) cumulative ecological and socioeconomic ramifications in the short and long term. In Africa, 673 large HPPs are proposed. If implemented, they will alter all major river networks through dam construction and reservoir inundation, although the actual extent remains unknown. This study conducts an integrated assessment of the impacts of all proposed HPPs at both basin and continental scales. Projected reservoir areas were overlaid with spatially explicit datasets on megafauna abundance, protected areas, cropland, and human resettlement. We further calculated indices of river regulation and fragmentation, as well as potential sediment entrapment and evaporation associated with the projected reservoirs. By integrating these indicators, we identified 102 HPPs that fall within the top quarter of projects with the greatest potential overall impact. HPP capacity size alone proved to be an inadequate impact indicator, as underlined by the highest- and lowest-ranked HPPs, both of which exhibited comparably low capacities. A sensitivity analysis revealed that the ranking depends on both the number of HPPs considered and the selection of indicators included in the analysis. This study provides evidence-based information to support decision-making when balancing renewable electricity needs against the environmental and socioeconomic impacts of HPP development at basin and continental scales.

Many strategies to create a circular bioeconomy have been proposed. To be successful, CO2 must be reduced with renewable energy into chemical building blocks, from which the chemical industry can be supported. Circular strategies include leveraging photosynthesis to produce sugar and lipid intermediates or renewable electricity to produce hydrogen or other electron carriers to support CO2 reduction. Acetogens can anaerobically reduce CO2 with H2 to produce mixtures of small organic molecules in gas fermentations. We previously demonstrated that acetate, a common product of gas fermentation, can be converted to the model oleochemical dodecanol in engineered Escherichia coli. Here, we explored the conversion of ethanol and mixtures of ethanol and acetate to the same model oleochemicals. Co-feeding ethanol can supply both carbon and additional reducing power relative to acetate alone. In this work, we engineered E. coli to catabolize ethanol and expressed two distinct ethanol metabolism pathways in different operons and combined them with improved engineered acetate activation. We evaluated the performance of these operons in dodecanol-producing strains when fed ethanol or acetate and found ethanol to be a better carbon source when judged by product titers. The engineered strains fed ethanol produced about 2-fold more dodecanol than the strains fed acetate. This increase was in part, due to change in product distribution. Cells fed ethanol produced predominantly dodecanol, whereas cells fed acetate generated a mixture of dodecanol and dodecanoic acid. Dodecanol titers were further improved by employing feeding strategies in controlled bioreactors.

In the context of the circular bioeconomy and environmental protection trends, the efficient use of renewable resources has become a driving force for industry, and lignin represents precisely a renewable carbon resource, abundant in terrestrial biomass that could become a sustainable substitute for fossil resources, under conditions of full exploitation. This study systematically evaluates the biosorption of Manganese (Mn(II)) from aqueous media using unmodified Tripidium bengalense (Sarkanda grass) lignin. Under optimal operating conditions (adsorbent dosage of 5 g/L, pH 6.5, and 20 °C), a highly competitive experimental adsorption capacity of 12.52 mg/g was achieved. Kinetic studies revealed exceptionally rapid uptake rates, with thermodynamic equilibrium established within the first 30 min, fitting perfectly with the pseudo-second-order (Ho-McKay) model (R2 ≥ 0.9998). Equilibrium data were best described by the Freundlich isotherm (R2 ≥ 0.9886), confirming chemisorption via preferential inner-sphere complexation on a heterogeneous surface. Thermodynamic analysis verified that the process is spontaneous (ΔG ranging from -13.24 to -26.19 kJ/mol) and endothermic (ΔH from 11.21 to 14.83 kJ/mol). FTIR, SEM-EDX, and TG/DTG analyses confirmed successful Mn-O coordination involving phenolic hydroxyl and carboxylic groups. Furthermore, the lignin showed excellent recyclability, maintaining a retention efficiency over 70% (70.7-85.8%) after three desorption-resorption cycles using 1N HCl. Ecotoxicological validation via Sorghum bicolor L. germination tests confirmed the complete detoxification of the post-adsorption filtrates (up to 100% germination capacity), while the Mn(II)-loaded lignin completely suppressed seed germination (0%), proving secure metal immobilization. These findings establish raw Sarkanda grass lignin as an efficient, scalable, and ecologically sustainable biosorbent for heavy metal remediation.

Power-to-X strategies are a key approach for coupling renewable energy generation with storage and utilization pathways. Because renewable sources such as solar and wind are intermittent, surplus electricity must be converted into chemical energy carriers, including hydrogen, fuels, and chemical feedstocks. In this context, the capture and electrochemical conversion of CO2 into valuable products is particularly attractive, as it supports a circular carbon economy and mitigates greenhouse gas emissions. Herein, we report the solvochemical and mechanochemical synthesis and implementation of a triazine-based ligand system, 2,4,6-tri-(1H-pyrazol-1-yl)-1,3,5-triazine (TPT-1), and its silver(I) complexes for electrochemical CO2 reduction. TPT-1 was synthesized via heteroaryl nucleophilic substitution of chlorine on a 1,3,5-triazine ring by pyrazolate. Subsequent metalation yielded the silver complexes Ag(TPT-1)2 and polymeric Ag2(TPT-1)2, which were characterized by nuclear magnetic resonance (NMR), ultraviolet/visible (UV/vis), Fourier-transform infrared (FT-IR), X-ray photoelectron spectroscopy (XPS), and high-resolution mass spectrometry (HRMS). Electrocatalytic activity was first investigated by homogeneous cyclic voltammetry in CH3CN and subsequently under heterogeneous conditions in H-type and custom-built zero-gap electrochemical cells. The silver(I) complexes exhibited stable and selective CO2-to-CO conversion, achieving Faradaic efficiencies of ∼80%, energy efficiencies of 24%, and single-pass conversions of 20% at a constant current density of 200 mA cm-2.

This study reports the strategic molecular design of a range of novel multi-acrylate monomers derived from the terpenoids nopol and verbenol, and their successful use in two-photon polymerization (2PP). This design process allowed the identification of structures most appropriate for use in additive manufacturing (AM) resins. This was achieved by deriving new synthesis routes that enabled the fabrication of monomers with bespoke numbers and placements of vinyl groups, which were then shown to dictate the level of success achieved in resin-based AM processing. By identifying the correct molecular design, it was demonstrated via 2PP that structures with uniform composition, smooth surfaces, and finely resolved features could be printed, as confirmed by scanning electron microscopy (SEM). 2PP is a high-precision 3D-printing technique for fabricating complex micro- and nano-scale structures. Despite its potential in functional devices, advanced manufacturing, and biomedical applications, the range of biobased monomers suitable for 2PP remains limited, and they are typically derived from petrochemical sources. This study also demonstrated that terpene and terpenoid reagents, which are abundant and renewable natural compounds, offer a promising platform for developing biobased, multifunctional monomers for AM.

The increasing global demand for fossil fuels, driven by rapid population growth, has led to resource depletion and rising energy costs, prompting the search for renewable alternatives such as bioethanol. This study aimed to isolate, screen, and characterize potent yeast strains from selected fruits and evaluate their bioethanol production using molasses as a substrate. Eighteen fruit samples were randomly collected from Gondar City, Tikil Dingay, and Kola Diba in the Amhara Regional State, Ethiopia. Yeasts were isolated using the serial dilution technique and screened based on gas production and medium color change. Identification was conducted through morphological, physiological, biochemical, and molecular analyses, including sequencing of the ITS1, ITS2, and 5.8 S rRNA regions. A total of 22 yeast isolates were obtained, of which four (ASMS2, A1IS3, AS2M2, and AS3M10) demonstrated strong fermentation potential. Optimal growth was observed at 37 °C and pH 5. All selected isolates tolerated up to 5% ethanol and 30% glucose concentrations and fermented glucose, sucrose, and maltose, but not galactose or lactose. Ethanol concentrations ranged from 0.780 to 1.218%, with fermentation efficiencies between 36.0% and 47.0%, and ethanol productivity from 0.16 to 0.23 g/L/h. Molecular identification revealed A1IS3 as Pichia kudriavzevii and AS2M2 as Pichia species. The findings indicate that mango and avocado fruits are promising sources of ethanol-producing yeasts, and further optimization of fermentation conditions is recommended.

Coumarins are privileged scaffolds in medicinal chemistry, chemical biology, and functional materials, yet their synthesis remains dominated by classical condensations and metal-dependent methods that limit structural diversity and sustainability. This review reframes coumarin construction through energy-driven activation, highlighting photochemical, electrochemical, and biochemical strategies as sustainable alternatives. Visible-light processes enable access to three-dimensional, sp3-rich, and fused architectures that are inaccessible by conventional routes, while electrochemical methods replace stoichiometric oxidants with electrical input under metal-free conditions. Biocatalytic and biosynthetic platforms further extend coumarin synthesis into aqueous, selective, and renewable regimes. Collectively, these paradigms align molecular innovation with modern sustainability and design principles.

Green hydrogen is central to many decarbonization strategies, yet its water footprint is often reduced to the water consumed by electrolysis itself. As electrolyzer plants scale up, cooling can become a hidden water demand, especially in hot and water-stressed regions where many renewable hydrogen projects are planned. Here we combine a thermodynamic cooling model with climate reanalysis, global water-stress data and renewable capacity-factor maps to quantify evaporative-cooling water demand for electrolysis across regions and seasons. We show that cooling can dominate total water use and that high solar-resource regions frequently coincide with high water stress and high cooling demand. Wind-rich regions, in contrast, are more often located in cooler or more water-abundant settings. A composite Water Risk Index identifies where freshwater-based evaporative cooling is likely to require alternatives such as dry or hybrid cooling, desalination or reclaimed-water supply. Our results show that cooling technology and water sourcing are central to water-sustainable hydrogen planning.

Under weak grid scenarios, wide variations of grid impedance distort resonance characteristics of LCL-type grid-connected inverters. Digital control delays introduce phase lag, which easily causes damping polarity reversal in conventional capacitor-current-feedback active damping strategies. From the perspective of impedance stability, this paper reveals that control delays produce frequency-dependent resistive components in equivalent damping impedance. The analytical boundary of positive-negative resistance transition is derived, which dominates the weak-grid adaptability of inverters. Accordingly, an impedance reshaping strategy based on phase-lead delay compensation is proposed. Embedded in the feedback loop, the phase-lead network extends the valid positive-resistance frequency region and decouples the inherent coupling between LCL resonance frequency and sampling frequency. The critical frequency is lifted from [Formula: see text] to above [Formula: see text], and the system maintains a stability margin over 45° within 0-10 mH grid inductance range. A quasi-proportional-resonant cascaded current regulator is further designed to suppress background harmonic interference. Simulation and experimental tests on a 5 kW prototype verify the superior performance. When grid inductance steps from 0 to 8 mH, grid-connected current THD remains below 2.8%, and transient response completes within two fundamental cycles. This study provides theoretical guidance and practical solution for stable grid integration of high-penetration renewable energy systems.

Driven by the growing demand for sustainable polymers, polylactic acid (PLA) has attracted increasing attention due to its renewable origin and biodegradability. Lactide, the key cyclic monomer for PLA production via ring-opening polymerization (ROP), plays a decisive role in determining the molecular weight, stereoregularity, and final performance of PLA materials. However, current lactide synthesis processes still face significant challenges, including competing side reactions under high-temperature and high-vacuum conditions, difficulties in controlling stereochemical purity, and relatively high energy consumption. In this review, recent advances in lactide synthesis are systematically analyzed by examining the two principal industrial routes: the one-step process based on the direct dehydration-cyclization of lactic acid (LA), and the two-step process involving prepolymerization of LA followed by depolymerization/cyclization of oligomeric intermediates. The reaction mechanisms, key intermediates, and major side reactions-including racemization, transesterification, and deep polycondensation-are discussed, together with the regulatory roles of catalytic systems and reaction-separation coupling strategies. Comparative analysis reveals that the one-step route offers advantages in process integration and potential energy efficiency, whereas the two-step route provides superior control over stereochemical purity and process stability. Future research directions focusing on green catalysts, process intensification, and sustainable lactide production are also highlighted.

Polysaccharide structural assignment via nuclear magnetic resonance (NMR) spectroscopy remains an analytical challenge due to spectral overlap because of limited chemical shift dispersion. This challenge is exacerbated by the wide-spread use of proton (1H) detection. Progress has also been hindered by the dispersed nature of carbohydrate databases and the restricted applicability of most prediction tools, which provide limited atom-specific residue discrimination in larger polymers. These limitations hamper the efficient characterization of glycosyltransferase (GT) activity, which depends on defining donor-acceptor substrate pairs and accurately identifying corresponding products. Here, we demonstrate the utility of high field 13C-detected NMR for the assignment of two homohexamers. Laminarihexaose and xylohexaose were analyzed using 2D heteronuclear correlation and correlation via long-range coupling (COLOC) experiments to evaluate whether complete residue level assignments could be achieved. The COLOC experiment revealed long range correlations that were not resolved using heteronuclear multiple bond correlation, and the 1D 13C spectra provided exceptional resolution, including distinct shoulders corresponding to residue specific chemical shift differences previously assumed to be indistinguishable. These findings suggest that high field 13C NMR can provide the nuanced atom level information required to train machine learning models for predicting chemical shift assignments of large, complex, and highly degenerate polysaccharides. Such models offer a promising framework for rapid structural identification of GT reaction products, enabling progress of high throughput characterization of plant derived polysaccharides central to renewable biomaterial development.

Utilizing abundant and renewable lignocellulose to develop advanced functional materials is a cornerstone of sustainable engineering. However, when applied to solar-driven interfacial water evaporation, challenges such as low vapor escape efficiency and the difficulty in achieving simultaneous pollutant degradation persist. To address these obstacles, a cellulose-based Janus membrane integrating efficient water transport channels with photocatalytic Fenton functionality was biomimetically engineered. The membrane was synthesized via an in-situ interfacial reaction between dissolved cellulose and multiple metal ions, enabling in-situ polymetallic hydroxide formation and poly(dopamine)-modified MXene incorporation into the regenerated cellulose matrix. Meanwhile, hydrophobically modified ramie fibers constructed a fibrous "synaptic" architecture on the surface. The asymmetric wettability interface-hydrophobic on the upper surface and hydrophilic on the lower-facilitated directional water transport and rapid vapor escape. MXene and polymetallic hydroxides served as active components for photothermal conversion and photocatalytic Fenton reactions. The membrane demonstrated degradation efficiencies of 100%, 60.5%, and 64.4% for 200 mg·L-1 Rhodamine B, 40 mg·L-1 bisphenol A, and 40 mg·L-1 oxytetracycline within 60 min, with a high water evaporation rate of 2.15 kg·m-2·h-1. Overall, this study demonstrates that biomimetic structural design and synergistic interfacial engineering of biomass-based materials offer new insights and strategies for the solar-powered water purification.

The transition toward a circular economy is accelerating the development of high-performance, sustainable polymeric materials derived from renewable resources. Medium-chain-length polyhydroxyalkanoates (mcl-PHAs) represent a versatile class of biodegradable polyesters with inherent flexibility and tunable side-chain chemistry, making them attractive candidates for advanced polymer applications. Here, we report a novel class of bio-based polyurethanes (PUs) incorporating mcl-PHAs as soft segments, marking their first application in polyurethane synthesis and shifting towards greener PU synthesis. Polyurethane networks were prepared using castor oil (CO) and mcl-PHAs as polyols, with hexamethylene diisocyanate (HMDI) as a hard segment. Material properties were systematically tuned by varying the mcl-PHA/CO ratio (100/0 to 0/100), enabling precise control over structure-property relationships. Comprehensive characterization confirmed urethane bond formation and revealed predominantly amorphous materials with tunable thermal and mechanical behavior. Increasing mcl-PHA content enhanced elasticity and influenced phase organization, underscoring its role as a flexible, bio-derived soft segment. The resulting materials exhibited competitive mechanical performance alongside adjustable swelling behavior and morphology. Importantly, in vitro biocompatibility (MRC-5 fibroblasts) and eco-toxicological evaluation (Caenorhabditis elegans) confirmed the absence of toxicity. These findings highlight the potential of mcl-PHAs as sustainable building blocks for advanced polyurethane systems.

Second-generation bioethanol technology is based on renewable raw materials with an unlimited potential for replenishment. However, the production cost of second-generation bioethanol is still higher than that of the first-generation. Biomass pretreatment is a key challenge, and solving it will improve the technology efficiency. In this study, Miscanthus × giganteus from the Russian breeding stock was subjected to pretreatments with dilute HNO3 under atmospheric pressure. Pretreatments were carried out either as a single stage (HNO3) or as two stages ((i) HNO3 followed by NaOH, and (ii) NaOH followed by HNO3). Classical delignification with NaOH was also performed for comparison. Simultaneous saccharification and fermentation with delayed inoculation (dSSF) was then performed under identical conditions, with Saccharomyces cerevisiae Y-3136 as the microbial producer. Two-stage pretreatments were found to excel in purity, pulp composition, pulp conversion, bioethanol yield during fermentation, and raw bioethanol purity (impurities decreased by a factor of 21 compared to NaOH delignification). However, fermentation indicators are not the only critical aspect in bioethanol production technology. The complete cycle from Miscanthus × giganteus feedstock to the target bioethanol product was evaluated. The single-stage pretreatment with HNO3 performed best among the tested conditions. The HNO3 pretreatment achieved a 50% yield of pulps and a maximal bioethanol yield of 267 L/t, which is 44% higher compared to NaOH delignification. Furthermore, the HNO3 pretreatment enables savings in resources and electric power, as well as full commercial utilization of all polymers of the lignocellulosic matrix of the feedstock.

Lignocellulosic biomass has long been recognized as the most abundant renewable source of organic matter on Earth [...].