ACS ES&T engineering最新文献

{"title":"Oxygen Vacancies-Mediated Z-Scheme Mechanism Promotes Synergistic Photoelectrocatalysis for Hydroxyl Radical and Singlet Oxygen-Cooperating on Selective Pollutant Degradation","authors":"Duoduo Fang, Di Luo, Han Xiao, Jiaxing Li, Lin Ma, Jiangzhi Zi, Zichao Lian","doi":"10.1021/acsestengg.4c00453","DOIUrl":"https://doi.org/10.1021/acsestengg.4c00453","url":null,"abstract":"Achieving high effective degradation of organic pollutants in sewage having adverse effects on human health and ecosystems remains a major challenge. In this study, an oxygen vacancy (O_v)-mediated Z-scheme Co₃O₄/O_v-TiO₂ heterojunction was first reported for simultaneous selective photoelectrocatalytic pollutant degradation and hydrogen production under visible light irradiation. The optimized Co₃O₄/O_v-TiO₂ exhibited excellent photoelectrocatalytic performance in the degradation of the organic pollutants under visible light irradiation due to the formation of a Z-scheme heterojunction for the utilization of highly reductive photogenerated electrons and oxidative holes. The mechanistic investigation suggested that the synergistic effects of hydroxyl radical and singlet oxygen as the dominant reactive species facilitated the ring-open reactions of the rhodamine B for the mineralization processes. This work provides a deep understanding of designing Z-scheme heterojunction photoelectrocatalysts through defect engineering technologies for sewage treatment.","PeriodicalId":7008,"journal":{"name":"ACS ES&T engineering","volume":"14 1","pages":""},"PeriodicalIF":7.1,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142204231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhanced Selectivity in PMS Activation via Non-Metal Doping for Efficient 1O2 Generation in Emerging Organic Pollutants Degradation","authors":"Yi Shen, Mingzheng Yang, Chao Zhu, Haizhong Zhang, Renlan Liu, Jun Wang, Qile Fang, Shuang Song, Baoliang Chen","doi":"10.1021/acsestengg.4c00400","DOIUrl":"https://doi.org/10.1021/acsestengg.4c00400","url":null,"abstract":"The activation of peroxymonosulfate (PMS) to generate singlet oxygen (¹O₂) for the removal of emerging organic pollutants (EOPs) from complex aqueous environments has garnered widespread attention. However, the low efficiency and selectivity of current PMS activation for ¹O₂ generation result in suboptimal EOP degradation. To enhance the selectivity of PMS activation and promote the non-radical pathway, non-metal heteroatoms with varying electronegativities were introduced to disrupt the symmetrical coordination structure of Fe active sites in Fe single-atom catalysts. The results showed that, in the B-Fe₁/GLCNs/PMS system, the pseudo-first-order kinetic rate for bisphenol A (BPA) degradation reached 4.435 min^–1, which is 7.4 times higher than that of the unmodified control group. Experimental and theoretical calculations demonstrated that the doping of non-metal heteroatoms altered the electron density and distribution at the Fe active sites, thereby modulating the adsorption configuration of HSO₅^– and increasing the selectivity for PMS activation to generate ¹O₂. Additionally, the degradation of EOPs by ¹O₂ produced intermediate products with lower biological toxicity, and ¹O₂ demonstrated strong anti-interference capability. The change in HSO₅^– morphology improved the rate of ¹O₂ generation. This study provides deep insights into designing high-performance PMS activation catalysts via non-metal doping to regulate the electronic structure of active sites for a selective non-radical pathway.","PeriodicalId":7008,"journal":{"name":"ACS ES&T engineering","volume":"18 1","pages":""},"PeriodicalIF":7.1,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142204233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Visualization Isolation of Electrochemically Active Bacteria by Using a Gelled Electrode-Based Electrochemical Plate","authors":"Bo Cao, Yuxuan Zang, Beizhen Xie, Ting Zhao, Hongyu Zhao, Yanhong Ge, Hong Liu, Yue Yi","doi":"10.1021/acsestengg.4c00308","DOIUrl":"https://doi.org/10.1021/acsestengg.4c00308","url":null,"abstract":"Electrochemically active bacteria (EAB) are catalysts of microbial electrogenesis and electrosynthesis, showing great prospects in wastewater treatment and biochemical engineering. However, isolating EAB is difficult, and only a few pure-cultured EAB have been reported. In this study, a novel gelled electrode based on an electrochemical plate is established, which for the first time realizes the selective screening of EAB strains and visible colony formation. A new EAB, <i>Rhodococcus qingshengii</i> C6, is isolated by using the method. <i>R. qingshengii</i> C6 is capable of electricity generation with a wide range of substrate spectra and is capable of reducing common electron acceptors by consuming electricity. The bidirectional extracellular electron transfer mechanism is preliminarily investigated, and exogenous redox mediators play an important role in extracellular electron transfer. This study provides an easy and simple method for the isolation and purification of EAB, contributing to the valuable bacterial resources exploration.","PeriodicalId":7008,"journal":{"name":"ACS ES&T engineering","volume":"37 1","pages":""},"PeriodicalIF":7.1,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142204232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Catalytic Methane Mitigation Over Mesoporosity-Engineered Hierarchically Porous Pd/SSZ-13 Zeolites","authors":"Gaozhou Liang, Anqi Guo, Wuwan Xiong, Dongdong Chen, Ulrich Simon, Daiqi Ye, Haibao Huang, Peirong Chen","doi":"10.1021/acsestengg.4c00347","DOIUrl":"https://doi.org/10.1021/acsestengg.4c00347","url":null,"abstract":"Palladium-zeolites are active catalysts for abating methane (CH₄), the second largest greenhouse gas contributing to climate change, via catalytic combustion. Yet, it remains challenging to improve the activity of Pd-zeolites in CH₄ combustion, in particular under humid conditions. Here, using small-pore SSZ-13 zeolite as a showcase, we demonstrate mesoporosity engineering as an effective approach to boost the CH₄ combustion performance of Pd-zeolites. A newly designed gemini quaternary ammonium surfactant, namely C_18–4N₂MP, was fabricated using inexpensive reagents and employed as a mesoporogen in the hydrothermal synthesis of hierarchically micro–meso–macro–porous SSZ-13 product. High-dispersion Pd catalysts were achieved by using the hierarchically porous SSZ-13 zeolites as supports. Physicochemical characterization and reaction kinetics disclosed that rational mesoporosity engineering of the hierarchically porous SSZ-13, simply by optimizing C_18–4N₂MP addition in the precursor gel prior to hydrothermal crystallization, favored the formation of highly dispersed PdO<i>_x</i> active phase and, in turn, the CH₄ combustion without noticeable accumulation of carbonaceous intermediates on the surface. Additionally, mesoporosity-optimized Pd/SSZ-13 displayed improved durability and outstanding moisture resistance during CH₄ combustion. This study sheds new light on the fabrication of high-performance Pd-zeolite catalysts for CH₄ emission abatement by facile engineering of zeolite mesoporosity.","PeriodicalId":7008,"journal":{"name":"ACS ES&T engineering","volume":"452 1","pages":""},"PeriodicalIF":7.1,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142226150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Confined Manganese-Based Catalysts for Gaseous Pollutant Removal: A Critical Review","authors":"Jialin Li, Zhijian Xiao, Jingling Yang, Mingshan Zhu","doi":"10.1021/acsestengg.4c00355","DOIUrl":"https://doi.org/10.1021/acsestengg.4c00355","url":null,"abstract":"Manganese-based materials are widely applied as catalysts for catalytic removal of gaseous pollutants due to their low cost and excellent redox performance. However, existing challenges such as unsatisfactory activity and stability hinder the application of manganese-based catalysts. Confining manganese-based materials into specific regions has the potential to influence intermolecular arrangement and mass diffusion and lower the activation energy barrier, thereby enhancing reaction stability and the catalyst’s activity. In this critical review, we briefly summarize the common reported nanoconfined manganese-based analogues for gaseous pollutant elimination including nitrogen oxides (NO_<i>x</i>) and volatile organic compounds (VOCs). Details of the commonly reported hosts for confined catalysts and their impact on catalytic behavior and an in-depth discussion of the related mechanism are included. Through this critical review, we aim to raise the research attention on using confined catalysis as a fundamental guide or even tool to improve the catalytic performance of gaseous pollutant elimination.","PeriodicalId":7008,"journal":{"name":"ACS ES&T engineering","volume":"61 1","pages":""},"PeriodicalIF":7.1,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142226153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Confined Manganese-Based Catalysts for Gaseous Pollutant Removal: A Critical Review","authors":"Jialin Li,&nbsp;Zhijian Xiao,&nbsp;Jingling Yang* and Mingshan Zhu*,&nbsp;","doi":"10.1021/acsestengg.4c0035510.1021/acsestengg.4c00355","DOIUrl":"https://doi.org/10.1021/acsestengg.4c00355https://doi.org/10.1021/acsestengg.4c00355","url":null,"abstract":"<p >Manganese-based materials are widely applied as catalysts for catalytic removal of gaseous pollutants due to their low cost and excellent redox performance. However, existing challenges such as unsatisfactory activity and stability hinder the application of manganese-based catalysts. Confining manganese-based materials into specific regions has the potential to influence intermolecular arrangement and mass diffusion and lower the activation energy barrier, thereby enhancing reaction stability and the catalyst’s activity. In this critical review, we briefly summarize the common reported nanoconfined manganese-based analogues for gaseous pollutant elimination including nitrogen oxides (NO_<i>x</i>) and volatile organic compounds (VOCs). Details of the commonly reported hosts for confined catalysts and their impact on catalytic behavior and an in-depth discussion of the related mechanism are included. Through this critical review, we aim to raise the research attention on using confined catalysis as a fundamental guide or even tool to improve the catalytic performance of gaseous pollutant elimination.</p>","PeriodicalId":7008,"journal":{"name":"ACS ES&T engineering","volume":"4 9","pages":"2078–2096 2078–2096"},"PeriodicalIF":7.4,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142228402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spectral-Based Machine Learning Enables Rapid and Large-Scale Adsorption Capacity Prediction of Heavy Metals in Soil","authors":"Chongchong Qi, Tao Hu, Mengting Wu, Yong Sik Ok, Han Wang, Liyuan Chai, Zhang Lin","doi":"10.1021/acsestengg.4c00325","DOIUrl":"https://doi.org/10.1021/acsestengg.4c00325","url":null,"abstract":"Accurate and large-scale estimation of the soil adsorption capacity of heavy metals (HMs) is vital to tackle soil HM contamination. Here, a novel framework has been developed to evaluate the adsorption capacity of HMs in soil using visible and near-infrared spectroscopy. Soil attributes were accurately estimated without any spectral preprocessing using a combined autoencoder (AE) and deep neural network (DNN) approach. Soil HM adsorption capability was then evaluated based on spectral-derived soil attributes, using 2,416 data points on Cd(II), Pb(II), and Cr(VI). The proposed AE-DNN models offer accurate estimations of soil attributes with an average <i>R</i>² of 0.811 on the independent testing sets. The trained AE-DNN models can reveal patterns typically used by experts to identify bond assignments and promote data-driven knowledge discovery. By comparison with adsorption capacity maps based on actual and estimated soil attributes, we show that the spectral-based soil adsorption capacity evaluation is statistically reliable. Our adsorption capacity maps for the EU and USA identify known soil contamination sites and undocumented areas of high contamination risk. Our framework enables rapid and large-scale prediction of the adsorption capacity of HMs in soil and showcases important guidance for further soil contamination testing, soil management, and industrial planning.","PeriodicalId":7008,"journal":{"name":"ACS ES&T engineering","volume":"27 1","pages":""},"PeriodicalIF":7.1,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142204236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Low-Cost and Point-of-Use Sensing Device Based on 2D Diffusion-Controlled Colorimetric Sensing Array for Continuous and Multiplexed Air Pollution Monitoring","authors":"Jingjing Yu, Wei Ding, Francis Tsow, Chinmay Chandrakant Dixit, Vishal Varun Tipparaju, Erica Forzani, Xiaojun Xian","doi":"10.1021/acsestengg.4c00416","DOIUrl":"https://doi.org/10.1021/acsestengg.4c00416","url":null,"abstract":"The development of a low-cost and point-of-use sensing device capable of continuously and simultaneously detecting various air pollutants is essential for enhancing air pollution monitoring in communities and workplaces. This technology would enable real-time monitoring, facilitating prompt interventions to mitigate the impact of air pollution on human health and the environment. Colorimetric gas sensors are often used to detect different air pollutants owing to their high selectivity and sensitivity, low cost, and compact size. Nevertheless, continuous and multiplexed detection of gas with a colorimetric sensor often requires lifetime-extension methods and an expensive, space-demanding, and power-hungry optical imaging system as the signal transducer. To address these challenges, we introduce a fully integrated portable gas sensing device that uses cheap, miniaturized, and power-efficient electronic and sensing components. This device enables continuous and multiplexed monitoring of air pollutants through a two-dimensional (2D) diffusion-controlled colorimetric sensor array. By selecting sensing probes with specific colorimetric chemical reactions for different gas analytes, the 2D sensor array ensures specificity across a range of analytes. The test results demonstrate that our 2D diffusion-based colorimetric sensing device can be used for sensitive, selective, and multiplexed monitoring of different air pollutants (ammonia, carbon monoxide, carbon dioxide, and nitrogen dioxide) in a continuous manner. This device has proven effective in monitoring pollutants released from car exhaust. Our innovative chemical sensing approach has facilitated the creation of a compact, cost-effective, and easily deployable sensing device. This device offers continuous and multiplexed sensing capabilities, making it ideal for air pollution monitoring in communities and workplaces to provide evidence-based environmental data for effective air pollution management strategies.","PeriodicalId":7008,"journal":{"name":"ACS ES&T engineering","volume":"66 2 1","pages":""},"PeriodicalIF":7.1,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142204237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pipe Failure Prediction in the Water Distribution System Using a Deep Graph Convolutional Network and Temporal Failure Series","authors":"Yanran Xu, Zhen He","doi":"10.1021/acsestengg.4c00234","DOIUrl":"https://doi.org/10.1021/acsestengg.4c00234","url":null,"abstract":"Ensuring the safety and reliability of the water distribution system (WDS) manifests significant importance for residential, commercial, and industrial needs and may benefit from the structure deterioration models for early warning of water pipe breaks. However, challenges exist in model calibration with limited monitoring data, unseen underground conditions, or high computing requirements. Herein, a novel deep learning-based DeeperGCN framework was proposed to predict pipe failure by cooperating with graph convolutional network (GCN) models for graph processing. The DeeperGCN model achieved much deeper architectures and was designed to utilize spatial and temporal data simultaneously. Two graph representation methods and three GCN models were compared, showing the best predictions with the “Pipe_as_Edge” method and the DeeperGEN model. To identify the priority of pipe maintenance directly, the prediction targets were assigned as a binary classification question to determine break or not over 1-, 3-, and 5-year periods, with prediction accuracies of 96.91, 96.73, and 97.23%, respectively. The issue of data imbalance was observed and addressed through varied evaluation metrics, resulting in the weighted F1 scores &gt;0.96. The DeeperGCN framework demonstrated potential applications in visualizing pipe failure prediction with high accuracies of 97.09, 96.31, and 97.81% across three periods in 2015, for example.","PeriodicalId":7008,"journal":{"name":"ACS ES&T engineering","volume":"4 1","pages":""},"PeriodicalIF":7.1,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142204234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pipe Failure Prediction in the Water Distribution System Using a Deep Graph Convolutional Network and Temporal Failure Series","authors":"Yanran Xu,&nbsp; and ,&nbsp;Zhen He*,&nbsp;","doi":"10.1021/acsestengg.4c0023410.1021/acsestengg.4c00234","DOIUrl":"https://doi.org/10.1021/acsestengg.4c00234https://doi.org/10.1021/acsestengg.4c00234","url":null,"abstract":"<p >Ensuring the safety and reliability of the water distribution system (WDS) manifests significant importance for residential, commercial, and industrial needs and may benefit from the structure deterioration models for early warning of water pipe breaks. However, challenges exist in model calibration with limited monitoring data, unseen underground conditions, or high computing requirements. Herein, a novel deep learning-based DeeperGCN framework was proposed to predict pipe failure by cooperating with graph convolutional network (GCN) models for graph processing. The DeeperGCN model achieved much deeper architectures and was designed to utilize spatial and temporal data simultaneously. Two graph representation methods and three GCN models were compared, showing the best predictions with the “Pipe_as_Edge” method and the DeeperGEN model. To identify the priority of pipe maintenance directly, the prediction targets were assigned as a binary classification question to determine break or not over 1-, 3-, and 5-year periods, with prediction accuracies of 96.91, 96.73, and 97.23%, respectively. The issue of data imbalance was observed and addressed through varied evaluation metrics, resulting in the weighted F1 scores &gt;0.96. The DeeperGCN framework demonstrated potential applications in visualizing pipe failure prediction with high accuracies of 97.09, 96.31, and 97.81% across three periods in 2015, for example.</p>","PeriodicalId":7008,"journal":{"name":"ACS ES&T engineering","volume":"4 9","pages":"2252–2262 2252–2262"},"PeriodicalIF":7.4,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142228130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}