Electrochemical reduction of nitrate (NO3-) to ammonia (NH3) represents a sustainable route for wastewater treatment and ammonia synthesis. Copper (Cu)-based catalysts, although effective for nitrate reduction, are limited by two major challenges: pronounced structural reconstruction and a strong tendency for ammonia adsorption, which causes active-site poisoning and rapid deactivation. To address these issues, we developed a Cu/Fe(OH)3 heterostructure catalyst using a facile controlled chemical deposition method. This composite architecture is designed to stabilize the active sites and mitigate NH3-induced poisoning, thereby enhancing both catalytic durability and performance. Density functional theory (DFT) calculations demonstrated that the hybridization between the d orbitals of Cu and Fe(OH)3 induced a downshift of the Cu D-band center from-2.079 eV to-2.086 eV, leading to a reduction in the adsorption energy barrier for reaction intermediates. Moreover, the DFT calculations indicated that the presence of Fe(OH)3 facilitated the adsorption of NO3-, while Cu promoted the desorption of NH3, collectively forming an efficient tandem electrocatalytic system. This synergistic tandem effect contributed to an exceptional nitrate reduction performance, achieving a current efficiency of 75.90 % and a high NH4+ selectivity of 98.22 % within 1 h of electrolysis, significantly outperforming both bare NF and Fe(OH)3/NF catalysts.

In this study, a facile CO2 etching method is employed to modify microcrystalline graphite (MG), successfully introducing abundant structural defects and pores, increasing the surface area to 58.54 m2 g-1, approximately five times that of pristine MG. This material (MG-CO2-4h) exhibits excellent rate capability: it delivers an initial discharge capacity of 630.72 mAh g-1 with an initial Coulombic efficiency (ICE) of 79.78%, and a discharge specific capacity of 258.9 mAh g-1 at 1 A g-1, representing a 3.1-fold enhancement compared to pristine MG. Moreover, the electrode delivers a stable capacity of 550.08 mAh g-1 over 400 cycles with a Coulombic efficiency (CE) of 99.43% at 0.1 A g-1; even at 1 A g-1, it retains 264.8 mAh g-1 after 1500 cycles with 99.54% CE. These results highlight the material's superior rate capability and cycling stability. This work provides a straightforward and effective modification method, demonstrating that the CO2-etched microcrystalline graphite holds promising potential as an advanced lithium-ion battery (LIB) anode material.

Molecular-based crystalline conductors, with their highly ordered structures, are highly valuable for clarifying how molecular arrangements determine electronic properties. However, conventional zero-dimensional cluster materials generally exhibit low conductivity due to the difficulty in establishing efficient conductive networks within their isolated systems. In this study, we constructed an electron-rich dimeric molecular conductor by introducing the aromatic metal-cluster building block {MoIV3py3} as a stereogenic unit while encapsulating rare-earth ions. This design enables the formation of a novel d-π•••π-d conjugated conductive pathway between otherwise isolated clusters. Among the systems, the hexagonal phases embedded with Sm and Eu ions exhibit the shortest π•••π contact distance (3.65 Å) and possess the highest in-plane (ab-axis) conductivity of 3.17 × 10⁻5 S•m⁻1 and 2.94 × 10⁻5 S•m⁻1, respectively—more than 105 times higher than that of conventional polyoxometalates. The incorporation of rare-earth ions not only induces the formation of a semiconducting hexagonal phase and a metallic-like tetragonal phase but also enables the modulation of anisotropic charge transport in single crystals. This work provides an important design strategy and synthetic pathway for the tailored construction of cluster-based crystalline materials with targeted electrical properties.

Progressive freeze concentration (PFC) is a promising freeze-based separation technology for concentrating solutes while producing purified ice. However, its separation efficiency is often limited by the increasing thermal resistance of the growing ice layer, which weakens heat extraction, slows ice-front propagation, and promotes solute entrapment within the ice phase. In this study, an internal thermal-bridge strategy was proposed to intensify PFC by inserting high-conductivity metal rods into the freezing system. The rods provided an additional low-resistance heat-transfer pathway between the cold environment and the liquid interior, thereby strengthening internal thermal transport and promoting temperature-gradient-guided Cu(II) migration. Systematic experiments, heat-transfer calculations, temperature-field simulations, and response surface methodology were combined to evaluate the effects of rod configuration, freezing temperature, and initial Cu(II) concentration on separation performance. Compared with conventional PFC, metal-rod insertion increased the total heat flux by up to 12.9 times and reduced the complete freezing time by 34.5–37.0%. The enhanced thermal transport generated a more favorable axial and radial temperature distribution, which, together with ice-front solute rejection, facilitated directional Cu(II) enrichment toward the bottom concentrated zone. Under the optimized conditions of 258 K, two 15-cm rods with a 5 cm exposed and 10 cm immersed configuration, and an initial Cu(II) concentration of 300 mg/L, the bottom Cu(II) concentration reached 2341 mg/L, corresponding to a concentration factor of 7.80. These results demonstrate that internal thermal-bridge engineering can effectively couple heat transfer and solute migration in PFC, offering a practical process-intensification strategy for freeze-concentration separation of ion-containing aqueous streams.

Chlorine-mediated flow-through electrode systems (Cl-FES) are considered a promising method for water treatment. However, the transformation and distribution of various reactive species in the Cl-FES remain unclear. In this study, the active chlorine (AC) distribution and electro-oxidation performance of oxidation-reduction (Oxred) mode (anode-cathode) were systematically investigated. The pH distribution and linear sweep voltammetry curve revealed that the acid-to-alkaline transition zone in the Ox-red mode is conducive to suppressing the side reaction of oxygen evolution. The Ox-red mode achieved a 2.16-fold enhancement in AC generation rate compared to the reduction-oxidation (Red-ox) mode (cathode-anode). Meanwhile, SHapley Additive exPlanation (SHAP) analysis confirmed that flow rate was the predominant electrolytic parameter in the AC generation, with an optimal output of 92.31 mg/L achieved at 1.5 mL/min. The AC distribution at different flow rates indicated that an increased flow rate promotes the formation of hypochlorous acid (HClO) in the vicinity of the anode and inhibits the formation of chlorates. Furthermore, the ammonia electro-oxidation results demonstrated that the Ox-red mode exhibited a 2.38-fold improvement in ammonia removal rate and a high nitrogen selectivity of 94.51 %. Additionally, the chloramine byproducts generated in the interelectrode region decreased by 98.33 % after passing the cathode region. The overall findings offer insights into reactive species and byproducts regulation for effective and environmental-friendly electro-oxidation applications in flow-through electrode systems.

The rapid growth of the electronic chip industry, fueled by the rise of artificial intelligence, is driving increasing demand for high-quality electrolytic copper foil (ECF). A major challenge for ECF production is achieving highquality output in a cost-effective and low-carbon manner. In this study, a Composite-Feature-Multi-ObjectiveInterpretation (CFMI) framework based on machine learning (ML) was developed to simultaneously optimize energy consumption and CF surface roughness during ECF production. The results show that the eXtreme Gradient Boosting (XGBoost) model outperforms the other seven ML algorithms in predicting both energy consumption (RMSE = 50.39 kWh.t(-1) , R-2 = 0.93) and CF surface roughness (RMSE = 0.30 mu m, R-2 = 0.73). SHapley Additive exPlanations (SHAP) analysis identifies current density, temperature, and sulfuric acid con-centration as primary factors influencing energy consumption, while deposition time, current density, and copper ion predominantly affect CF surface roughness. Moreover, SHAP-based feature clustering effectively reduces dimensionality while maintaining model accuracy, with XGBoost showing less than 1 parts per thousand R-2 degradation. Furthermore, the proposed multi-objective Non-dominated Sorting Genetic Algorithm-II (NSGA-II) outperforms the traditional Response Surface Methodology (RSM), achieving 59.63 kWh.t(-1) energy savings (equivalent to a 33.63 kg CO2.t(-1) reduction) at a target CF roughness of 0.60 mu m. The Pareto front further confirms the excellent dual-optimization capability of NSGA-II, which achieved a 10.15 % energy reduction while maintaining product quality. This study provides new insights for intelligent copper foil production and enables greener manufacturing paradigms.

The application of electro-oxidation (EO) technology in organic dyes is restricted by the drawbacks, such as the expensive electrode materials, high energy consumption, and narrow pH applied range. Herein, a natural manganese sand (NMS)-catalyzed in situ electro-generated active chlorine (e.g., HClO) system was proposed to remove methyl orange (MO). The results show that MO can be efficiently removed by the NMS/EO system over a wide pH range (pH 3-12). Radicals (e.g., HO center dot, Cl center dot) and non-radical active species (e.g., 1O2, Mn4+) are involved in the removal of MO by the NMS/EO system. The effects of important parameters, including the initial solution pH, NMS dosage, current density, electrolyte type, and electrode space, on MO degradation by the NMS/EO system were investigated. The kinetic model of MO removal confirmed that the degradation rate of MO was mainly affected by the dosage of NMS compared with the NaCl concentration. Moreover, the NMS/EO system exhibited a significant reduction in energy consumption for MO removal. This work provides new insights into the degradation of organic dyes by NMS-catalyzed in situ electrogenerated active chlorine.

The metal with highly occupied d-orbitals and unclosed d-orbitals shells (Cu, Pd and Pt) was widely used as catalyst in electrochemical NO3 - reduction reaction (NO3-RR), but the production ammonia adsorped on active sites of surface hinders NO3-RR. Herein, a series of CuxFey electrodes (Cu75Fe25, Cu50Fe50 and Cu25Fe75) were prepared through electrochemical co-deposition of Cu and Fe on nickel foam (NF) as a cathode. The CuxFey/NF electrodes showed nearly 100 % NO3-RR efficiency in 3 h and excellent durability. Meanwhile Cu75Fe25 had high current efficiency (98.01 %) in 30 min and a good stability of nitrate reduction activity after 8 cyclic experiments. The improved electrocatalytic activity on nitrate reduction is attributed to the high electron transfer rate, high adsorption capacity of electroactive species, high electrochemically active surface areas (ECSA) and double layer capacitance (Cdl) of the Cu75Fe25 electrode. Nitrate was first converted to nitrite, followed by acceptance of sixelectron to produce NH3. Density functional theory (DFT) calculations confirmed that the Fe-shifted Cu d-band center contributed to weak adsorption energies of ammonia, and thus resulted in superior activity and selectivity toward NO3 - reduction to NH3. Taking together, results showed the promising application of CuxFey/NF electrodes in electrocatalytic denitrification and ammonia production from wastewater.

Nitrate pollution in water contributes to harmful eutrophication and ecological degradation. Electrochemical nitrate reduction to ammonia (NRA) provides a promising method for both removing nitrate pollutants and recovering ammonia. However, the hydrogen evolution reaction (HER) at the cathode hinders nitrate reduction efficiency. The use of porous solid electrolytes (PSE) combined with metal cations can suppress HER through the cation shielding effect, but the impact of different alkali metal cations, anions, and PSE on this effect remains underexplored. This study investigated the synergistic effects of alkali metal cations and PSE on the cation shielding effect for NRA. The results demonstrated that the inclusion of PSE significantly enhanced NRA efficiency compared to conventional membrane electrode assembly. Nitrate reduction efficiency with various alkali metal cations followed the order: Cs+ > K+ > Na+ > Li+, with Cs+ showing the strongest cation shielding effect, as confirmed by the increased double layer capacitance value and enhanced current density. The influence of interlayer alkali metal cation concentrations and anion types on NRA in the PSE system was evaluated as well. Moreover, comparing to different PSE type of D001, IRC, and S-DVB, FPC achieved the highest nitrate reduction (63.31 %) and NH4+-N generation (41.41 mg L-1) through providing the optimal cation channels. Additionally, the presence of OH- and K+ in the cathode chamber optimized cathode-interlayer synergy for NRA. When applied to nitrate-containing silver production wastewater, the PSE system achieved 96.03 % nitrate reduction and 396.38 mg L-1 NH4+-N production in 420 min. These findings highlight the practical potential of PSE systems for efficient nitrate removal and sustainable ammonia synthesis, offering a promising framework for wastewater treatment.

The electrochemical two-electron oxygen reduction reaction (2e- ORR) plays an important role in the electrosynthesis of hydrogen peroxide (H2O2). Nonetheless, the conventional configuration of the electrode or reactor limited the 2e- ORR kinetics, resulting in low H2O2 yields. Additionally, the high costs associated with these systems hinder practical applications. Herein, we proposed a new strategy to simultaneously improve the mass transfer and interfacial reaction microenvironment through the surface and aeration modification of the simple submerged electrode for high-performance H2O2 production. The three-phase interfaces (TPIs) on electrode for 2e- ORR were first modulated under the internally aerated conditions with superior mass transfer. The design of aeration from the interior of the surface-modified cathode facilitated the mass transfer, promoted uniform oxygen concentration distribution across the cathode surface, and improved the interfacial reaction microenvironment, thereby boosting the H2O2 production. Under optimal conditions, the undoped electrocatalytic system achieved a remarkable H2O2 yield of 9.91 mg h- 1 cm- 2 (644.53 mg L-1h- 1) with a 51.6 % faradaic efficiency at a low current density of 40 mA cm- 2 and a small airflow rate of 0.1 L min- 1. The long-term electrolysis stability and more than 99 % degradation of methyl orange demonstrated the great potential of the synergistic interfacial enhancement of electrode modification and internal aeration for cost-effective H2O2 production and environmental remediation applications.

The waste acid generated in the production of expanded graphite by “chromium method” has the characteristics of high acid concentration and high chromium content. The Cr(Ⅲ) can be oxidized to Cr(Ⅵ) by electro-oxidation in membrane system to realize the regeneration of waste acid containing chromium. Since it was difficult to achieve real-time detection of Cr(Ⅵ) content in this highly acidic system, a study based on artificial neural network was conducted to accurately predict the electro-oxidation regeneration effect of chromium-containing waste acid. Based on the regeneration of chromium-containing waste acid experiments, the key characteristic parameters of hexavalent chromium regeneration including time, sulfuric acid concentration, and electrolyte volume were determined by correlation analysis. Then, through hyperparameter optimization, the relatively optimal topology structure of the artificial neural network was obtained as follows: Neurons=35, Batch size=30, Layers=4. The coefficient of determination(R2) between predicted value and experimental value was greater than 0.97, and the root-mean-square error(RMSE) was less than 0.04. Finally, the average relative error between predicted value and experimental value was 0.14%, which indicated that the model had good generalization ability. The artificial neural network model overcame the difficulty of predicting electrochemical processes due to multi-parameter, nonlinearity and time variability, and could realize the prediction of Cr(Ⅵ) regeneration under complex mapping conditions, which was of great significance for the optimization and control of electrochemical processes.

Electrochemical nitrate reduction to nitrogen gas is considered as an alternative strategy to address water pollution problem, but the high cost and poor product selectivity of electrode limit its application. Here, Ni3P loaded nickel foam was fabricated via one-step eletrodeposition as cathode for electrochemical nitrate reduction. Due to the improvement of electron transfer rate and electrochemically active surface area, current efficiency and reaction rate constant enhanced 20.4-flod and 40-fold, respectively. Batch experiments revealed the remarkable nitrate reduction performance (similar to 97.53 %) after the optimization of potential, initial NO3- concentration and pH. Presence of chlorine induced electrochlorination will tune N-2 (selectivity up to similar to 100 %) to become the dominant products. Mechanism study suggested that the atomic H*-mediated indirect reduction, meanwhile properties of Ni3P to strengthen NO3- adsorption and prevent desorption of NO and NO2 are responsible for the enhancement of nitrate reduction. This work is meaningful for water environment protection and energy sustainable development.

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Electro-assisted catalytic wet air oxidation (ECWAO) is an environmentally-friendly pollutant removal process with energy-saving and mild reaction properties. However, it requires an electrode with high catalytic capacity and stability, and the catalytic mechanism behind the process still needs to be further clarified. Herein, we report a graphite felt (GF)-supported PbOx catalyst which can chemically adsorb oxygen and activate it into free radicals by an anodic electric field to promote wet air oxidation. XRD, SEM, EDS, XPS, BET and TG measurements indicated that PbO and PbO2 were successfully doped and loaded onto the GF, increasing the specific surface area and number of active sites. The best RhB degradation efficiencies achieved were 91.26 % over 15 min and 96.68 % over 90 min. The PbOx@C/GF maintained good catalytic performance over eight cycles in the pH range of 3-11 with negligible metal leaching. The RhB degradation pathway of RhB was analyzed through GC-MS results. A free radical quenching experiment, a contrast experiment, and an electrochemical test revealed the process of oxygen being adsorbed by Pb(II) and activated to degrade organic matter was revealed. Five kinds of dyes were degraded by the electrode via the ECWAO process, and the degradation rate reached over 93.7 % within 90 min. The degradation specific energy consumption (SEC) of probe pollutant RhB is 48.70 kW & sdot;h/kg-COD. The industrial practical dye wastewater COD removal rate was close to 100 %, and the SEC was 24.44 kW & sdot;h/kg-COD. Therefore, it can be concluded that a graphite felt (GF)-supported PbOx catalyst can act as an anode for ECWAO to chemically adsorb oxygen and activate it into free radicals using an anodic electric field to promote wet air oxidation.

Wastewater reclaim in industrial parks can effectively reduce the dependence on external water resources, few literatures evaluated the reclaim system from perspectives of economy, technology, and environmental impact. It is very popular across China that a constructed wetland is linked with a wastewater plant and then discharged the tailwater into surface waters, based on current situation, pilot experiment, and other available techniques, six scenarios for wastewater reclaim system were designed for Shanghai Chemical Industrial Park. Using life cycle assessment, it was found that in scenario of pilot experiment, most environmental impact was derived from wastewater plant and ultra filtration - reverse osmosis, in which ultra filtration - reverse osmosis accounted >20 % for POCP, AP, and EP, Wastewater plant accounted >86 % for ADP, ODP. It was showed that electricity and sludge were most important parameters affecting LCA, when electricity consumption was reduced by 20 %, total standardized environmental impact would be changed in the range of 1.40 %-1.65 %, the most significant change was HTP (6.12 %-6.32 %) when 20 % up and downward change in sludge amount, followed by MAETP (5.27 %-5.36 %). A multi-criteria decision-making analysis was conducted on all the scenarios based on environmental impact, life cycle cost, technical efficiency, it was showed that the scenario designed for pilot experiment was the best available technique, which was consisted of wastewater plant, hybrid constructed wetland, ultra-filtration and reverse osmosis, and reused as desalted water. A wastewater reclaim plant is suggested from the result of this paper. It was believed that this study could provide references for construction of wastewater reclaim system in industrial parks of the world.

Although sodium hypochlorite acting as an oxidant has been investigated for the role it plays in the degradation of organic contaminants, little attention has been paid to its activation and efficient utilization. In this study, natural manganese sand (NMS) was verified to be effective for activation of sodium hypochlorite (NaClO). Due to the generation of O2−, the removal efficiency of ionic organic contaminants in NMS/NaClO system was 1.9–4.1 times higher than that in NMS or NaClO alone. Hence, NMS activated NaClO system performed ~96.6 % contaminants removal efficiency at a wide pH range (pH 5–9). Kinetic modeling yielded that the NMS dosage was more important than NaClO dosage. Long-term stability was observed in the presence of various salts (bicarbonate, sulfate, phosphate, and chloride). Characterization results revealed that electron transfer among NMS, NaClO, and organic contaminants was responsible for NaClO activation. Then NaClO-based Fenton-like process was proposed by tracing the degradation intermediates of methyl orange (MO) and generations of reactive oxygen species in the MO/NMS/NaClO system. This study presents the potential of NMS to activate NaClO and enhance ionic organic contaminants removal from aquatic environments.

Titanium-based flow-through electrode achieved high Cr(VI) reduction efficiency. ● Flow-through pattern enhanced the mass transfer and reduced cathodic polarization. ● BPNN predicted the optimal electroreduction conditions of flow-through cell. Flow-through electrodes have been demonstrated to be effective for electroreduction of Cr(VI), but shortcomings are tedious preparation and short lifetimes. Herein, porous titanium available in the market was studied as a flow-through electrode for Cr(VI) electroreduction. In addition, the intelligent prediction of electrolytic performance based on a back propagation neural network (BPNN) was developed. Voltametric studies revealed that Cr(VI) electroreduction was a diffusion-controlled process. Use of the flow-through mode achieved a high limiting diffusion current as a result of enhanced mass transfer and favorable kinetics. Electroreduction of Cr(VI) in the flow-through system was 1.95 times higher than in a parallel-plate electrode system. When the influent (initial pH 2.0 and 106 mg/L Cr(VI)) was treated at 5.0 V and a flux of 51 L/(h·m2), a reduction efficiency of ~99.9% was obtained without cyclic electrolysis process. Sulfate served as the supporting electrolyte and pH regulator, as reactive CrSO72− species were formed as a result of feeding HSO4−. Cr(III) was confirmed as the final product due to the sequential three-electron transport or disproportionation of the intermediate. The developed BPNN model achieved good prediction accuracy with respect to Cr(VI) electroreduction with a high correlation coefficient (R2 = 0.943). Additionally, the electroreduction efficiencies for various operating inputs were predicted based on the BPNN model, which demonstrates the evolutionary role of intelligent systems in future electrochemical technologies.

以能源化工行业常见产物甲醇作为溶析剂,研究了在低温条件下(≤0℃)溶析结晶回收高盐废水中氯化钠的调控方法,并结合氯化钠回收率与能耗分析优化了工艺条件.结果表明,当温度从20℃降低至-25℃时,氯化钠回收率由35.02%～52.07%提高到44.20%～62.81%,低温条件显著提高了氯化钠回收率.同时,随着温度降低,溶析结晶氯化钠晶体粒径变小,晶体形状由长方体逐渐变为正方体.当温度为-25℃,初始浓度300 g/L,搅拌速率500 r/min,搅拌时间60 min,醇水体积比2∶1时,低温溶析结晶法氯化钠回收率可达57.97%,能耗仅为三效蒸发的69%.本文研究甲醇溶析剂低温溶析工艺,为能源化工行业高浓度氯化钠废水的资源化利用提供了参考.

Electrochemical is a promising approach for the removal of ammonia nitrogen, but the challenge is to achieve better performance under lower energy consumption. In this study, a new electrochemical system hybrid with intelligent optimization algorithms was developed for the efficient removal of ammonia nitrogen and energy saving. Ammonia removal performance and energy consumption were recorded when the traditional electrochemical system operated at various parameters. As the premise of model training, the data were processed through Scatter diagram matrix, Box plot, Principal Component Analysis, Spearman correlation and Shapley Additive Explanations to evaluate the redundancy and independence of parameters. Backpropagation neural network based on deep learning was used as surrogate model of non-dominated sorted genetic algorithm-II, meanwhile, the range of electrochemical parameters was used as the constraint for multi-objective optimization. The optimized result is the Pareto front and the optimal solution was obtained by combining the Technique for Order Preference by Similarity to an Ideal Solution. This new hybrid system achieved an increase of 11.75 % ~ 13.61 % in ammonia removal and a reduction of 21.31 % ~ 36.84 % in energy consumption. The optimal solution represents a better ammonia removal performance at low energy consumption, which is meaningful for the concept of a real-time controlled electrochemical system.