Bioinspired Tandem Electrode for Selective Electrocatalytic Synthesis of Ammonia from Aqueous Nitrate.

The electrocatalytic nitrate reduction reaction (NO3RR) has recently emerged as a promising technique for readily converting aqueous nitrate (NO3-) pollutants into valuable ammonia (NH3). It is vital to thoroughly understand the mechanism of the reaction to rationally design and construct advanced electrocatalytic systems that can effectively and selectively drive the NO3RR. There are several natural enzymes that incorporate molybdenum (Mo) and that can activate NO3-. Based on this, a cadmium (Cd) single-atom anchored Mo2TiC2Tx electrocatalyst (referred to as CdSA-Mo2TiC2Tx) through the NO3RR to generate NH3 was rationally designed and demonstrated. In an H-type electrolysis cell and at a current density of 42.5 mA cm-2, the electrocatalyst had a Faradaic efficiency of >95% and an impressive NH3 yield rate of 48.5 mg h-1 cm-2. Moreover, the conversion of NO3- to NH3 on the CdSA-Mo2TiC2Tx surface was further revealed by operando attenuated total reflection Fourier-transform infrared spectroscopy and an electrochemical differential mass spectrometer. The electrocatalyst significantly outperformed Mo2TiC2Tx as well as reported state-of-the-art catalysts. Density functional theory calculations revealed that CdSA-Mo2TiC2Tx decreased the ability of the d-p orbital to hybridize with NH3* intermediates, thereby decreasing the activation energy of the potential-determining step. This work not only highlights the application prospects of heavy metal single-atom catalysts in the NO3RR but also provides examples of bio-inspired electrocatalysts for the synthesis of NH3.

Selective Nitrate Electroreduction to Ammonia on CNT Electrodes with Controllable Interfacial Wettability.

The development of electrocatalysts that can efficiently reduce nitrate (NO3-) to ammonia (NH3) has garnered increasing attention due to their potential to reduce carbon emissions and promote environmental protection. Intensive efforts have focused on catalyst development, but a thorough understanding of the effect of the microenvironment around the reactive sites of the catalyst is also crucial to maximize the performance of the electrocatalysts. This study explored an electrocatalytic system that utilized quaternary ammonium surfactants with a range of alkyl chain lengths to modify an electrode made of carbon nanotubes (CNT), with the goal of regulating interfacial wettability toward NO3- reduction. Trimethyltetradecylammonium bromide with a moderate alkyl chain length created a very hydrophobic interface, which led to a high selectivity in the production of NH3 (∼87%). Detailed mechanistic investigations that used operando Fourier-transform infrared (FTIR) spectroscopy and online differential electrochemical mass spectrometry (DEMS) revealed that the construction of a hydrophobic modified CNT played a synergistic role in suppressing a side reaction involving the generation of hydrogen, which would compete with the reduction of NO3-. This electrocatalytic system led to a favorable process for the reduction of NO3- to NH3 through a direct electron transfer pathway. Our findings underscore the significance of controlling the hydrophobic surface of electrocatalysts as an effective means to enhance electrochemical performance in aqueous media.

SEB-YOLO: An Improved YOLOv5 Model for Remote Sensing Small Target Detection.

Due to the limited semantic information extraction with small objects and difficulty in distinguishing similar targets, it brings great challenges to target detection in remote sensing scenarios, which results in poor detection performance. This paper proposes an improved YOLOv5 remote sensing image target detection algorithm, SEB-YOLO (SPD-Conv + ECSPP + Bi-FPN + YOLOv5). Firstly, the space-to-depth (SPD) layer followed by a non-strided convolution (Conv) layer module (SPD-Conv) was used to reconstruct the backbone network, which retained the global features and reduced the feature loss. Meanwhile, the pooling module with the attention mechanism of the final layer of the backbone network was designed to help the network better identify and locate the target. Furthermore, a bidirectional feature pyramid network (Bi-FPN) with bilinear interpolation upsampling was added to improve bidirectional cross-scale connection and weighted feature fusion. Finally, the decoupled head is introduced to enhance the model convergence and solve the contradiction between the classification task and the regression task. Experimental results on NWPU VHR-10 and RSOD datasets show that the mAP of the proposed algorithm reaches 93.5% and 93.9%respectively, which is 4.0% and 5.3% higher than that of the original YOLOv5l algorithm. The proposed algorithm achieves better detection results for complex remote sensing images.

Improved Machine Learning Models by Data Processing for Predicting Life-Cycle Environmental Impacts of Chemicals.

Machine learning (ML) provides an efficient manner for rapid prediction of the life-cycle environmental impacts of chemicals, but challenges remain due to low prediction accuracy and poor interpretability of the models. To address these issues, we focused on data processing by using a mutual information-permutation importance (MI-PI) feature selection method to filter out irrelevant molecular descriptors from the input data, which improved the model interpretability by preserving the physicochemical meanings of original molecular descriptors without generation of new variables. We also applied a weighted Euclidean distance method to mine the data most relevant to the predicted targets by quantifying the contribution of each feature, thereby the prediction accuracy was improved. On the basis of above data processing, we developed artificial neural network (ANN) models for predicting the life-cycle environmental impacts of chemicals with R2 values of 0.81, 0.81, 0.84, 0.75, 0.73, and 0.86 for global warming, human health, metal depletion, freshwater ecotoxicity, particulate matter formation, and terrestrial acidification, respectively. The ML models were interpreted using the Shapley additive explanation method by quantifying the contribution of each input molecular descriptor to environmental impact categories. This work suggests that the combination of feature selection by MI-PI and source data selection based on weighted Euclidean distance has a promising potential to improve the accuracy and interpretability of the models for predicting the life-cycle environmental impacts of chemicals.

Prospective Life Cycle Assessment for the Electrochemical Oxidation Wastewater Treatment Process: From Laboratory to Industrial Scale.

Electrochemical oxidation (EO) is a promising technology for water purification, but indirect environmental burdens may arise in association with consumption of materials and energy during electrode preparation and process operation. This study evaluated the life cycle environmental impacts of emerging EO technology from laboratory scale to industrial scale using prospective life cycle assessment (LCA) on a quantitative basis. Environmental impacts of EO technology were assessed at laboratory scale by comparing three representative anode materials (SnO2, PbO2, and boron-doped diamond) and other two typical processes (adsorption and Fenton method), which verified the competitiveness of the EO process and identified the key factors to environmental hotspots. Thereafter, LCA of scale-up EO was performed to offer guidance for practical application, and the life cycle inventory was compiled upon thermodynamic and kinetic simulations, empirical calculation rules, and similar technical information. Results demonstrated EO to be effective for destructing recalcitrant organic pollutants, but visible direct benefits might be outweighed by increased indirect environmental burdens associated with the preparation of anode materials, use of electrolytes, and energy consumption during the operation stage at both laboratory scale and larger scale. This necessitated attention to overall life cycle profiles by taking into account reactor design, anode materials, electrolyte and flow pattern, and decentralized location with a large share of renewable power station and rigorous contamination control strategies for wastewater treatment plants.

Water Flow-Driven Coupling Process of Anodic Oxygen Evolution and Cathodic Oxygen Activation for Water Decontamination and Prevention of Chlorinated Byproducts.

Electrochemical advanced oxidation process (EAOP) is a promising technology for decentralized water decontamination but is subject to parasitic anodic oxygen evolution and formation of toxic chlorinated byproducts in the presence of Cl-. To address this issue, we developed a novel electrolytic process by water flow-driven coupling of anodic oxygen evolution reaction (OER) and cathodic molecular oxygen activation (MOA). When water flows from anode to cathode, O2 produced from OER is carried by water through convection, followed by being activated by atomic hydrogen (H*) on Pd cathode to produce •OH. The water flow-driven OER/MOA process enables the anode to be polarized at low potential (1.7 V vs SHE) that is lower than that of conventional EAOP whose •OH is produced from direct water oxidation (>2.3 V vs SHE). At a flow rate of 30 mL min-1, the process could achieve 94.8% removal of 2,4-dichlorophenol (2,4-DCP) and 71.5% removal of chemical oxygen demand (COD) within 45 min at an anode potential of 1.7 V vs SHE and cathode potential of -0.5 V vs SHE. To achieve the comparable 2,4-DCP removal performance, 4.3-fold higher energy consumption was needed for the conventional EAOP with titanium suboxide anode (anode potential of 2.9 V vs SHE), but current efficiency declined by 3.5 folds. Unlike conventional EAOP, chlorate and perchlorate were not detected in the OER/MOA process, because low anode potential <2.0 V vs SHE was thermodynamically unfavorable for the formation of chlorinated byproducts by anodic oxidation, indicated by theoretical calculations and experimental data. This study provides a proof-in-concept demonstration of water flow-driven OER/MOA process, representing a paradigm shift of electrochemical technology for water decontamination and prevention of chlorinated byproducts, making electrochemical water decontamination more efficient, more economic, and more sustainable.

Fluidic MXene Electrode Functionalized with Iron Single Atoms for Selective Electrocatalytic Nitrate Transformation to Ammonia.

The growth of renewable energy industries and the ongoing need for fertilizer in agriculture have created a need for sustainable production of ammonia (NH3) using low-cost, environment-friendly techniques. The electrocatalytic nitrate (NO3-) reduction reaction (NO3RR) has the potential to improve both the management of environmental nitrogen and the recycling of synthetic nutrients. However, NO3RR is frequently hindered by the incomplete NO3- conversion, sluggish reaction kinetics, and suppression of the hydrogen evolution reaction (HER). Inspired by specific local electronic structures that are adjustable for single-atom catalysts, this work presents a nanohybrid electrocatalytic filter with iron single atoms (FeSA) immobilized on MXene. The fabricated FeSA/MXene filter exhibited maximum NH3 Faradaic efficiency and selectivity (82.9 and 99.2%, respectively) that were higher than those for filters made of Fe nanoparticles anchored on MXene (FeNP/MXene) (69.2 and 81.3%, respectively) and MXene alone (32.8 and 52.4%, respectively), measured at an initial pH of 7 and an applied potential of -1.4 V vs Ag/AgCl. Density functional theory calculations revealed that, compared to the FeNP/MXene filter, the FeSA/MXene filter prevented the competition from the HER and reduced the activation energy of the potential-limiting step (*NO to *NHO) that made the NH3 synthesis thermodynamically favorable . This work highlights an alternative strategy for achieving a synergistic NO3- removal and nutrient recovery with durable catalytic activity and stability.

Machine Learning Models for Inverse Design of the Electrochemical Oxidation Process for Water Purification.

In this study, a machine learning (ML) framework is developed toward target-oriented inverse design of the electrochemical oxidation (EO) process for water purification. The XGBoost model exhibited the best performances for prediction of reaction rate (k) based on training the data set relevant to pollutant characteristics and reaction conditions, indicated by Rext2 of 0.84 and RMSEext of 0.79. Based on 315 data points collected from the literature, the current density, pollutant concentration, and gap energy (Egap) were identified to be the most impactful parameters available for the inverse design of the EO process. In particular, adding reaction conditions as model input features allowed provision of more available information and an increase in the sample size of the data set to improve the model accuracy. The feature importance analysis was performed for revealing the data pattern and feature interpretation by using Shapley additive explanations (SHAP). The ML-based inverse design for the EO process was generalized to a random case for tailoring the optimum conditions with phenol and 2,4-dichlorophenol (2,4-DCP) serving as model pollutants. The resulting predicted k values were close to the experimental k values by experimental verification, accounting for the relative error lower than 5%. This study provides a paradigm shift from conventional trial-and-error mode to data-driven mode for advancing research and development of the EO process by a time-saving, labor-effective, and environmentally friendly target-oriented strategy, which makes electrochemical water purification more efficient, more economic, and more sustainable in the context of global carbon peaking and carbon neutrality.

Copper Nanowire Networks: An Effective Electrochemical Peroxymonosulfate Activator toward Nitrogenous Pollutant Abatement.

Herein, we developed an electrochemical filtration system for effective and selective abatement of nitrogenous organic pollutants via peroxymonosulfate (PMS) activation. Highly conductive and porous copper nanowire (CuNW) networks were constructed to serve simultaneously as catalyst, electrode, and filtration media. In one demonstration of the CuNW network's capability, a single pass through a CuNW filter (τ < 2 s) degraded 94.8% of sulfamethoxazole (SMX) at an applied potential of -0.4 V vs SHE. The exposed {111} crystal plane of CuNW triggered atomic hydrogen (H*) generation on sites, which contributed to effective PMS reduction. Meanwhile, with the involvement of SMX, a Cu-N bond was formed by the interactions between the -NH2 group of SMX and the Cu sites of CuNW, accompanied by the redox cycling of Cu2+/Cu+, which was facilitated by the applied potential. The different charges of the active Cu sites made it easier to withdraw electrons and promote PMS oxidation. Theoretical calculations and experimental results were combined to suggest a mechanism for pollution abatement with CuNW networks. The results showed that system efficacy for the degradation of a wide array of nitrogenous pollutants was robust across a broad range of solution pH and complex aqueous matrices. The flow-through operation of the CuNW filter outperformed conventional batch electrochemistry due to convection-enhanced mass transport. This study provides a new strategy for environmental remediation by integrating state-of-the-art material science, advanced oxidation processes, and microfiltration technology.

Enhanced visible light photo-Fenton catalysis by lanthanum-doping BiFeO3 for norfloxacin degradation.

Efficient photo-Fenton removal of antibiotic effluent is a widely followed and significant attempt to deal with the growing environmental pollution. In this study, BiFeO3 and lanthanum doped BiFeO3 catalysts were synthesized via one-step hydrothermal method as hydrogen peroxide activator for mineralization of norfloxacin (NOR). Various characterization measurements were used to verify La was successfully doped into the lattice of perovskite and investigated the effect of La doping molar ratio on BiFeO3 through the characterization of the morphology and physicochemical properties. The degradation experiment and reaction rate constants showed that the La-doped BiFeO3 particle exhibited superior photo-Fenton catalytic performance to undoped BiFeO3. Especially, the degradation efficiency of 15% La-doped BiFeO3 could reach up to 84.94%. And the first order kinetic constant of optimized conditions was 0.01638 min-1, which was about 6.9 times than that of undoped BiFeO3.The influence of pH, oxidizer content and catalyst dosage in photo-Fenton reaction were investigated detailedly. Besides, the synthetic catalyst possessed favorable stability and reusability with little metal leaching after many cycles of use. Radical scavenger experiments and electron spin resonance tests were carried out to conclude that the ·OH and holes were regarded as the dominate active species in the catalytic process. The narrow band gap and excellent electron transfer efficiency were the key factors for La-doped BiFeO3 to have high catalytic efficiency in the photo-Fenton system. Current works demonstrated the great promise of La-doped BiFeO3 in the elimination of antibiotic organics.

SiamHSFT: A Siamese Network-Based Tracker with Hierarchical Sparse Fusion and Transformer for UAV Tracking.

Due to high maneuverability as well as hardware limitations of Unmanned Aerial Vehicle (UAV) platforms, tracking targets in UAV views often encounter challenges such as low resolution, fast motion, and background interference, which make it difficult to strike a compatibility between performance and efficiency. Based on the Siamese network framework, this paper proposes a novel UAV tracking algorithm, SiamHSFT, aiming to achieve a balance between tracking robustness and real-time computation. Firstly, by combining CBAM attention and downward information interaction in the feature enhancement module, the provided method merges high-level and low-level feature maps to prevent the loss of information when dealing with small targets. Secondly, it focuses on both long and short spatial intervals within the affinity in the interlaced sparse attention module, thereby enhancing the utilization of global context and prioritizing crucial information in feature extraction. Lastly, the Transformer's encoder is optimized with a modulation enhancement layer, which integrates triplet attention to enhance inter-layer dependencies and improve target discrimination. Experimental results demonstrate SiamHSFT's excellent performance across diverse datasets, including UAV123, UAV20L, UAV123@10fps, and DTB70. Notably, it performs better in fast motion and dynamic blurring scenarios. Meanwhile, it maintains an average tracking speed of 126.7 fps across all datasets, meeting real-time tracking requirements.

Mo Vacancy-Mediated Activation of Peroxymonosulfate for Ultrafast Micropollutant Removal Using an Electrified MXene Filter Functionalized with Fe Single Atoms.

Developing advanced heterogeneous catalysts with atomically dispersed active sites is an efficient strategy to boost the kinetics of peroxymonosulfate (PMS) activation for micropollutant removal. Here, we report a binary Mo2TiC2Tx MXene-based electroactive filter system with abundant surface Mo vacancies for effective activation of PMS. The Mo vacancies assumed two essential roles: (i) as anchoring sites for Fe single atoms (Fe-SA) and (ii) as cocatalytic sites for the Fenton-like reaction. Fe-SA formed strong metal-oxygen bonds with the Mo2TiC2Tx support, stabilizing at the sites previously occupied by Mo. The resulting Fe-SA/Mo2TiC2Tx nanohybrid filter achieved 100% degradation of sulfamethoxazole (SMX) in the single-pass mode (hydraulic retention time <2 s) when assisted by an electric field (2.0 V). The rate constant (k = 2.89 min-1) for SMX removal was 24 and 67 times greater than that of Fe nanoparticles immobilized on Mo2TiC2Tx and the pristine Mo2TiC2Tx filter, respectively. Operation in the flow-through configuration outperformed the conventional batch reactor model (k = 0.17 min-1) due to convection-enhanced mass transport. The results obtained from experimental investigations and theoretical calculations suggested that atomically dispersed Fe-SA, anchored on Mo vacancies, was responsible for the adsorption and activation of PMS to produce sulfate radicals (SO4•-) in the presence of an electric field. This study provides a proof-of-concept demonstration of an electroactive Fe-SA/Mo2TiC2Tx filter for broader application in the treatment of water contaminated by emerging micropollutants.

Electrochemical removal of 4-chlorophenol in water using a porous Magnéli-phase (Ti4O7) electrode.

Electro-oxidation is a promising technology for removal of refractory organic pollutants. While the appeal of this technology lies in its chemical-free nature, commercially scale-up application may be limited by the availability of electrode materials and mass transport. Here we report the development of a flow-through electro-oxidation system for removal of chlorophenols in water using Magnéli-phase (Ti4O7) tubular anode and a 304 stainless steel (SS) tubular cathode. The key to this system was the porous and conductive Magnéli-phase Ti4O7 anode, the structure and composition of which was confirmed by scanning electron microscopy, X-ray diffraction and X-ray photoelectron spectroscopy. System efficacy was evaluated by using 4-chlorophenol (4-CP) as a typical refractory contaminant and model chlorophenol. Under optimized conditions, a complete removal of 4-CP could be obtained within 120 min in 0.04 mol L-1 Na2SO4 solution. Electro-produced HO• and direct electron transfer were both shown to contribute to the 4-CP electro-oxidation process due to the high selectivity and oxygen evolution potential of the Ti4O7 anode. The intermediates of 4-CP degradation were identified and a pathway for its electro-oxidation was proposed. When challenged with industrial wastewater containing 4-CP, chemical oxygen demand (COD) and total organic carbon removal efficiencies of 67.5% and 63.1% respectively could be obtained, accounting for energy consumption of 85.1 kWh·kg COD-1 for degradation of 1 kg of COD in industrial wastewater. This study provides an effective and robust solution for the removal of refractory emerging contaminants from industrial wastewaters using a continuous-flow electro-oxidation system.

Sources, fates and treatment strategies of typical viruses in urban sewage collection/treatment systems: A review.

The ongoing coronavirus pandemic (COVID-19) throughout the world has severely threatened the global economy and public health. Due to receiving severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from a wide variety of sources (e.g., households, hospitals, slaughterhouses), urban sewage treatment systems are regarded as an important path for the transmission of waterborne viruses. This review presents a quantitative profile of the concentration distribution of typical viruses within wastewater collection systems and evaluates the influence of different characteristics of sewer systems on virus species and concentration. Then, the efficiencies and mechanisms of virus removal in the units of wastewater treatment plants (WWTPs) are summarized and compared, among which the inactivation efficiencies of typical viruses by typical disinfection approaches under varied operational conditions are elucidated. Subsequently, the occurrence and removal of viruses in treated effluent reuse and desalination, as well as that in sewage sludge treatment, are discussed. Potential dissemination of viruses is emphasized by occurrence via aerosolization from toilets, the collection system and WWTP aeration, which might have a vital role in the transmission and spread of viruses. Finally, the frequency and concentration of viruses in reclaimed water, the probability of infection are also reviewed for discussing the potential health risks.

Amyloid-Templated Palladium Nanoparticles for Water Purification by Electroreduction.

Electrocatalysis offers great promise for water purification but is limited by low active area and high uncontrollability of electrocatalysts. To overcome these constraints, we propose hybrid bulk electrodes by synthesizing and binding a Pd nanocatalyst (nano-Pd) to the electrodes via amyloid fibrils (AFs). The AFs template is effective for controlling the nucleation, growth, and assembly of nano-Pd on the electrode. In addition, the three-dimensional hierarchically porous nanostructure of AFs is beneficial for loading high-density nano-Pd with a large active area. The novel hybrid cathodes exhibit superior electroreduction performance for the detoxification of hexavalent chromium (Cr6+ ), 4-chlorophenol, and trichloroacetic acid in wastewater and drinking water. This study provides a proof-of-concept design of an AFs-templated nano-Pd-based hybrid electrode, which constitutes a paradigm shift in electrocatalytic water purification, and broadens the horizon of its potential engineered applications.

China Tongxinluo Study for myocardial protection in patients with Acute Myocardial Infarction (CTS-AMI): Rationale and design of a randomized, double-blind, placebo-controlled, multicenter clinical trial.

Acute ST-segment elevation myocardial infarction (STEMI) remains a serious life-threatening event. Despite coronary revascularization, patients might still suffer from poor outcomes caused by myocardial no-reflow and ischemic/reperfusion injury. Tongxinluo (TXL), a traditional Chinese medicine, has been preliminarily demonstrated to reduce myocardial no-reflow and ischemic/reperfusion injury. We further hypothesize that TXL treatment is also effective in reducing clinical end points for the patients with STEMI. METHODS AND RESULTS: The CTS-AMI trial is a prospective, randomized, double-blind, placebo-controlled, multicenter clinical study in China. An estimated 3,796 eligible patients with STEMI from about 120 centers are randomized 1:1 ratio to TXL or placebo groups. All enrolled patients are orally administrated a loading dose of 8 capsules of TXL or placebo together with dual antiplatelet agents on admission followed by 4 capsules 3 times a day until 12 months. The primary end point is 30-day major adverse cardiovascular and cerebrovascular events, a composite of cardiac death, myocardial reinfarction, emergency coronary revascularization, and stroke. Secondary end points include each component of the primary end point, 1-year major adverse cardiovascular and cerebrovascular events, and other efficacy and safety parameters. CONCLUSIONS: Results of CTS-AMI trial will determine the clinical efficacy and safety of traditional Chinese medicine TXL capsule in the treatment of STEMI patients in the reperfusion era.

Electron Spin Resonance Evidence for Electro-generated Hydroxyl Radicals.

Electro-generated hydroxyl radicals (•OH) are of fundamental importance to the electrochemical advanced oxidation process (EAOP). Radical-specific electron spin resonance (ESR) evidence is still lacking in association with the direct electron transfer (DET) reaction of spin trap (e.g., 5,5-dimethyl-1-pyrroline-N-oxide; DMPO) and side reactions of the DMPO-OH adduct in the strongly oxidative environment offered by anodic polarization. Herein, we showed ESR identification of electro-generated •OH in EAOP based on the principle of kinetic selection. Excessive addition of a DMPO agent and fast spin trapping allowed suitable kinetic conditions to be set for effective spin trapping of electro-generated •OH and subsequent ESR identification. Otherwise, interferential triplet signals would emerge due to formation of paramagnetic dimer via dehydrogenation, DET oxidation, and dimerization reactions of the DMPO-OH adduct. The results demonstrate that •OH formation during spin-trapping on the titanium suboxide (TiSO) anode could be quantified as 47.84 ± 0.44 µM at current density of 10 mA cm-2. This value revealed a positive dependence on electrolysis time, current density, and anode potential. The effectiveness of ESR measurements was verified by the results obtained with the terephthalic acid probe. The ESR identification not only provides direct evidence for electro-generated •OH from a fundamental point of view, but also suggests a strategy to screen effective anode materials.

Low-Temperature Removal of Refractory Organic Pollutants by Electrochemical Oxidation: Role of Interfacial Joule Heating Effect.

Low temperature presents a challenge to wastewater treatment in the winters of cold regions. In the electrochemical oxidation (EO) process, the interfacial Joule heating (IJH) effect results in interfacial temperature higher than that of bulk electrolytes, which would alleviate the negative impact of low water temperature on organic oxidation occurring within the boundary layer of the anode. This study investigated the electrochemical oxidation of the representative recalcitrant organic pollutant, i.e., phenol, p-chlorophenol (p-CP), and 2,4-dichlorophenoxyacetic acid (2,4-D) on titanium suboxide (TiSO) anode at a low water temperature (8.5 ± 1 °C). At a low current density of 2 mA cm-2, the IJH effect was insignificant and thus had a slight impact on interfacial temperature, leading to a low-efficiency and incomplete organic removal via direct electron transfer (DET) oxidation. Increasing the current density to 20 mA cm-2 promoted the working up of the IJH effect and thus resulted in a dramatic increase in the interfacial temperature from 8.1 to 38.7 °C. This almost eliminated the negative impact of low temperature on the abatement of organic pollutants as though the low temperature of the bulk solution did not interact with interfacial reactions at all. This was indicated by the oxidation rates of 0.158 min-1 (phenol), 0.084 min-1 (p-CP), and 0.070 min-1 (2.4-D) at a temperature of 8.5 ± 1 °C, the values being almost comparable to that obtained at room temperature (23.5 ± 1 °C). Both theoretical and experimental results demonstrated that the extent to which the low- and room-temperature cases deviated from each other was positively correlated with the activation energy of organic pollutants when reacting with •OH. The improvement of organic oxidation at low temperature should result from the compensation of the IJH effect, giving rise to higher •OH reactivity, more activated organic molecules, and enhanced mass transfer. This study may prompt new possibilities to develop an IJH effect-based electrochemical manner for decentralized water decontamination in cold regions.

Low-Tortuosity Water Microchannels Boosting Energy Utilization for High Water Flux Solar Distillation.

Solar distillation through photothermal evaporators has approached solar light energy (E1) limit under no solar concentration but still suffers from modest vapor and clean water production. Herein, a nature-inspired low-tortuosity three-dimensional (3D) evaporator is demonstrated to significantly improve water production. The solar evaporator, prepared from polypyrrole-modified maize straw (PMS), had upright vascular structures enabling high water lifting and horizontal microgaps facilitating broad water distribution to the out-surface. Consequently, this novel PMS evaporator dramatically enhanced the utilization of the solar heat energy stored in the environment (E2) for promoting evaporation. The maximum vapor generation rate of a single PMS respectively increases 2.5 and 6 times compared with the conventional 3D evaporators and the planar evaporators of an identical occupied area. Consequently, a scaled-up PMS array achieved a state-of-the-art vapor generation rate of 3.0 L m-2 h-1 (LMH) under a simulated condition and a record-high clean water production of 2.2 LMH for actual seawater desalination under natural conditions (1 sun intensity). This breakthrough reveals great potentials for cost-effective freshwater production as well as the rational design of high-performance photothermal evaporators for solar distillation.

Volatile-Organic-Compound-Intercepting Solar Distillation Enabled by a Photothermal/Photocatalytic Nanofibrous Membrane with Dual-Scale Pores.

Solar distillation is emerging as a robust and energy-effective tool for water purification and freshwater production. However, many water sources contain harmful volatile organic compounds (VOCs), which can evaporate through the photothermal evaporators and be collected together with distilled water, or even be enriched in the distilled water. In view of the penetration of volatile organic compounds, herein, we rationally demonstrate a dual-scale porous, photothermal/photocatalytic, flexible membrane for intercepting volatile organic compounds during solar distillation, which is based on a mesoporous oxygen-vacancy-rich TiO2-x nanofibrous membrane (m-TiO2-x NFM). The dual-scale porous structure was constructed by micrometer-sized interconnected tortuous pores formed by the accumulation of m-TiO2-x nanofibers and nanometer-sized pores in the m-TiO2-x individual nanofibers. Consequently, the membrane can sustainably in situ intercept VOCs by providing more photocatalytic reactive sites for collision (mainly by mesopores) and longer tortuous channels for prolonging VOC retention (mainly by micrometer-sized pores); thus, it results in less than 5% of phenol residual in distilled water. As a proof of concept, when the m-TiO2-x NFM is employed to purify practical river water in an evaporation prototype under real solar irradiation, complex volatile natural organic contaminants can be effectively intercepted and the produced distilled water meets the drinking water standards of China. This development will promote the application prospects of solar distillation.