The pursuit of carbon neutrality in China demands a rapid, spatially informed scale-up of renewable energy, including biomass, yet high-resolution, policy-aware data for site-specific planning remain scarce. To bridge this gap, we develop China's high-resolution spatially explicit biomass resource potential dataset, which integrates five biomass categories (agricultural residues, forestry residues, energy crops, animal manure, and municipal waste) at 1 km resolution for 2020, with projections to 2050. This dataset incorporates key constraints such as food security, ecological conservation, and land use suitability. It provides heat value potential distribution maps in GeoTIFF and PDF formats, and heat value potential data in Excel format. By combining multi-source geospatial data, statistical downscaling, and machine learning, this dataset enables precise assessment of resource conditions and provides forward-looking planning for biomass power deployment, rural revitalization, and carbon reduction strategies, thereby meeting China's critical need for integrated, location-aware open data in energy and land-use decision-making.
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.
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.
3-Hydroxypropionic acid (3-HP) is an important platform chemical for a circular bioeconomy since it is a precursor for the production of several high-value derivatives such as acrylic acid as well as biodegradable plastics. Escherichia coli is a promising host for 3-HP biosynthesis due to its well-characterized metabolic network and ease of genetic manipulation. In E. coli, 3-HP is produced from glycerol via a two-step pathway involving glycerol dehydratase and an NAD⁺-dependent aldehyde dehydrogenase. However, a major limitation in this process is redox imbalance, as both glycerol catabolism and 3-HP biosynthesis generate excess NADH, thereby restricting NAD⁺ availability and limiting product formation. In this study, we systematically evaluated the influence of cosubstrate selection to enhance 3-HP production by decoupling biomass formation from product synthesis while achieving redox balance. An engineered E. coli strain, with knockouts of glycerol kinase (glpK) and glycerol dehydrogenase (gldA) to prevent glycerol catabolism, was employed to redirect glycerol flux exclusively toward 3-HP biosynthesis. A secondary carbon source was supplied to support cell growth and promote NAD⁺ regeneration. Six different sugars were evaluated as growth substrates to assess their impact on redox balance and 3-HP production. Among the tested secondary substrates, sucrose and xylose enabled high 3-HP titers of 61 and 50 g/L, respectively, significantly surpassing the 30 g/L titer obtained using glycerol as the sole carbon source. The strategy was successfully extended to renewable feedstocks such as molasses and pretreated lignocellulosic liquor hydrolysate in combination with crude glycerol, achieving 3-HP titers in the range of ~ 35-40 g/L. KEY POINTS: • Redox imbalance limits glycerol-based 3-HP biosynthesis in E. coli. • Redox-optimized dual-substrate feeding enhances 3-HP titer, yield and productivity. • Validation with renewable substrates provides feasibility for a circular bioeconomy.
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.
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.
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.
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.
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.
Salinity gradient energy, which exists widely between two solutions with different concentrations, represents a substantial and renewable energy resource. Currently, harvesting the salinity gradient energy is largely confined to river estuaries, which significantly limits its applicability for island communities. To address this challenge, a three-compartment device that couples freshwater production with full-day electricity generation is developed, utilizing a carbonized biomass evaporator and electric double layer capacitive mixing technology. In the device, a Rattan-based solar-driven interfacial evaporator continuously concentrates the seawater during solar-driven interfacial evaporation, establishing a sustained salinity gradient between the generated high-concentration brine and the original seawater. Concurrently, the salinity gradient energy is converted into electricity by the biomass-derived ion bridges and electrodes. The system can achieve a maximum peak power density of 19.47 mW m-2 under a 10-fold concentration salinity gradient and 4.79 W m-2 under a 1000-fold salinity gradient.
The increasing demand for sustainable materials in additive manufacturing has driven the development of bioplastics derived from renewable biomass, including microalgae. In this study, the rheological behavior of a 20 wt.% aqueous gel prepared from native Chlorella vulgaris (C. vulgaris) starch, plasticized with 30 wt.% glycerol, was investigated to assess its suitability for extrusion-based 3D printing (direct-ink-writing, DIW). Steady shear analysis revealed a pronounced yield stress (τ0 = 271.93 Pa) and strong shear-thinning behavior, described by the Herschel-Bulkley model (K = 59.47 Pa·sn, n = 0.67), indicating structural stability at rest and efficient flow under shear. Oscillatory measurements confirmed a predominantly elastic response, with storage modulus (G' ≈ 13,500 Pa) greatly exceeding loss modulus (G″) and a low loss factor (tan δ≈ 0.1), demonstrating gel integrity and shape retention. Temperature-dependent analysis indicated enhanced network strength without thermal softening, while thixotropic recovery tests showed rapid structural rebuilding after shear removal. Notably, a ~50% increase in G' during recovery highlights improved interlayer adhesion potential. These results show that C. vulgaris starch exhibits the key rheological characteristics required for DIW-type extrusion printing, including yield stress, shear-thinning behavior, viscoelastic stability, and rapid recovery, making it a promising candidate for this application.
The transition toward circular economy practices and CO2 reduction goals is driving the development of new sound absorption technologies. Traditional absorbers made from mineral wool or foams provide broadband absorption; however, their production is associated with intensive energy consumption and non-renewable resources. This is why the focus has been shifting from the mere substitution of materials to integrated solutions that combine sustainability with structure. This paper reviews recent innovations in sustainable absorbers based on bio-based and recycled materials. The acoustic performance of porous materials depends on such factors such as pore structure, airflow resistivity and geometric parameters such as thickness, multi-layer structure and resonances. At the same time, additive manufacturing (AM) allows creating geometry-controlled absorbers providing advanced acoustic properties. Despite many sustainable absorbers demonstrating sufficient sound absorption properties at medium and high frequencies, their use at low frequencies remains challenging. Additionally, concerns regarding durability, flame retardance, and environmental consistency continue to limit their broader application. Yet, hybrid, multi-material strategies, particularly those combining geopolymer matrices with bio-based or recycled fillers, are identified as a promising route to address these limitations. This review outlines current trends and highlights key challenges and future directions in the design of sustainable sound-absorbing systems.
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.
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 growing need for renewable energy resources has brought small-molecule organic solar cells into focus as one of the potential candidates for future generation photovoltaics owing to their easy manufacturing process, flexibility, and lightweight nature. This paper presents the theoretical investigation carried out through density functional theory (DFT) and time-dependent DFT (TDDFT) methods for designing and characterizing a series of five novel donor materials (CA1-CA5) based on carbazole core, thiophene spacer, and various functionalized terminal electron-withdrawing acceptors. Analysis of the results obtained from frontier molecular orbitals suggests that functionalization of the terminal acceptor can modulate the electronic properties, such as the energy level and band gap of these molecules. Remarkably, CA2 and CA1 possess lower band gaps (2.71 eV and 2.81 eV, respectively) than the reference material (3.48 eV) and are therefore expected to have higher charge transfer efficiency. Strong intramolecular charge transfer (ICT) is observed in all molecules using transition density matrix and molecular electrostatic potentials. Additionally, CA1 and CA2 are identified to have high oscillator strength and absorption at the longest wavelength, implying high light-harvesting ability.
Since the Industrial Revolution, the large-scale extraction and utilization of fossil fuels have driven the rapid development of human society while causing an exponential increase in CO2 emissions. Photocatalysis and electrocatalysis are regarded as some of the most promising strategies for carbon neutralization due to their ability to utilize renewable solar energy and electricity to drive the CO2 reduction reaction (CO2RR), respectively. Binary alloy and high-entropy catalysts have shown excellent ability to precisely modulate geometrical configurations on the atomic scale, which can be used to construct additional CO2RR active sites, and have attracted much attention as commonly used photo/electrocatalytic catalysts. In this review, we systematically review various synthesis strategies for binary alloy and high-entropy catalysts, analyze the synergistic effects of the elements in binary alloys and high-entropy materials in the photo/electrocatalytic CO2RR to generate a variety of energy materials, and focus on the mechanism of the CO2RR in binary alloys and high-entropy materials, which achieves a simultaneous enhancement in the activity, selectivity and durability. In addition, we have deeply examined the opportunities and major challenges for the development of binary alloy and high entropy catalysts. Binary alloys and high-entropy materials are becoming the centerpiece of the development of next-generation high-efficiency carbon-recycling catalysts due to their unique electronic structure tunability, synergistic active sites, and excellent stability.
Solar radiation forecasting is a complex task since the radiation signal is nonlinear, intermittent and is significantly influenced by meteorological variability, which makes it vital for PV planning, renewable energy planning and stability of the smart grid. In this work, a replicable comparison between CNN-LSTM and CNN-BiLSTM models for one-step ahead solar clearness-index forecasting based on multivariate climate variables from NASA POWER dataset for Delhi, India, is presented. Under identical preprocessing, windowing, chronological splitting, and training conditions, CNN-LSTM achieved MAE = 0.0880, RMSE = 0.1100, R2 = 0.3100, EVS = 0.3154, WI = 0.6317, and APB = 1.89%, whereas CNN-BiLSTM obtained MAE = 0.1015, RMSE = 0.1224, R2 = 0.1456, EVS = 0.1998, WI = 0.5261, and APB = 5.98%. The Skill Scores shown and the negative values for direct clearness-index prediction do not imply that the persistence reference was unattainable, but rather reveal that the results are a controlled model-to-model comparison and not evidence of state-of-the-art superiority. Reconstructed all-sky irradiance produced stronger agreement with observations (MAE = 0.4353, RMSE = 0.5417, R2 = 0.7884, EVS = 0.7965, WI = 0.9299, and APB = 3.90%). The main task of CNN-LSTM is to provide a practical balance between accuracy and efficiency in this experimental context, and further testing with other locations, more powerful baselines and probabilistic forecasting techniques is needed.
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.
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.