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Correction: materials laboratories of the future for alloys, amorphous, and composite materials (MRS Bulletin, (2025), 50, 2, (190-207), 10.1557/s43577-024-00846-y)

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MRS Bulletin 2025年 1-2页

作者： Banerjee, Sarbajit Meng, Y. Shirley Minor, Andrew M. Zhang, Minghao Zaluzec, Nestor J. Chan, Maria K.Y. Seidler, Gerald McComb, David W. Agar, Joshua Mukherjee, Partha P. Melot, Brent Chapman, Karena Guiton, Beth S. Klie, Robert F. McCue, Ian D. Voyles, Paul M. Robertson, Ian Li, Ling Chi, Miaofang Destino, Joel F. Devaraj, Arun Marquis, Emmanuelle A. Segre, Carlo U. Liu, Huinan H. Yang, Judith C. Momeni, Kasra Misra, Amit Abdolrahim, Niaz Medvedeva, Julia E. Cai, Wenjun Sehirlioglu, Alp Dizbay-Onat, Melike Mehta, Apurva Graham-Brady, Lori Maruyama, Benji Rajan, Krishna Warner, Jamie H. Taheri, Mitra L. Kalinin, Sergei V. Reeja-Jayan, B. Schwarz, Udo D. Simon, Sindee L. Brown, Craig M. Department of Chemistry and Department of Materials Science & Engineering Texas A & M University College Station United States Pritzker School of Molecular Engineering The University of Chicago Chicago United States Department of Materials Science & Engineering University of California Berkeley Berkeley United States National Center for Electron Microscopy Molecular Foundry Lawrence Berkeley National Laboratory Berkeley United States Center for Nanoscale Materials Argonne National Laboratory Lemont United States Department of Physics University of Washington Seattle United States Department of Materials Science & Engineering The Ohio State University Columbus United States Department of Mechanical Engineering and Mechanics Drexel University Philadelphia United States School of Mechanical Engineering Purdue University West Lafayette United States Department of Chemistry University of Southern California Los Angeles United States Department of Chemistry Stony Brook University The State University of New York Stony Brook United States Department of Chemistry University of Kentucky Lexington United States Department of Physics University of Illinois at Chicago Chicago United States Department of Materials Science & Engineering Northwestern University Evanston Bangladesh Department of Materials Science & Engineering University of Wisconsin–Madison Madison United States Department of Materials Science and Engineering University of Pennsylvania Philadelphia United States Department of Mechanical Engineering and Materials Science Duke University Durham United States Department of Chemistry Creighton University Omaha United States Physical and Computational Sciences Directorate Pacific Northwest National Laboratory Richland United States Department of Materials Science & Engineering University of Michigan–Ann Arbor Ann Arbor United States Department of Physics Illinois Institute of Technology Chicago United States Department of Bioengineering and the Mater

This article was updated to correct Minghao Zhang’s affiliation from "Pritzker School of Molecular engineering, The University of Chicago, Chicago, USA" to "Pritzker School of Molecular engineering, The University of Chicago, Chicago, USA;Argonne National laboratory, Lemont, USA." Argonne National laboratory was left off the original publication. © The Author(s) 2025.

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A Semisupervised Soft-Sensor of Just-in-Time Learning With Structure Entropy Clustering and Applications for Industrial Processes Monitoring

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2023年第4期4卷 722-733页

作者： Li, Dong Liu, Yiqi Huang, Daoping Xu, Chong South China University of Technology Key Laboratory of Autonomous Systems and Networked Control Ministry of Education School of Automation Science and Engineering Guangzhou510640 China Technical University of Denmark Process and Systems Engineering Center Department of Chemical and Biochemical Engineering Lyngby2800 Denmark South China University of Technology School of Automation Science and Engineering Guangzhou510640 China Gannan Normal University School of Physics and Electronic Information Ganzhou341000 China

To monitor industrial processes properly, soft-sensors are widely used to predict significant but difficult-to-measure quality variables. However, the prediction performances of traditional data-driven soft-sensors are usually unacceptable once suffering from high-nonlinear, high-dimension, and imblance data issues. Therefore, a semisupervised soft-sensor, which is learned by a just-in-time method with structure entropy clustering (SS-JITL-SEC), is proposed aiming to improve prediction performance with a simpler way. Inspired by a divide and conquer strategy, a novel SEC method is proposed to achieve several clusters and then to translate the highly complex and nonlinear modeling problems into simple and linear ones. Moreover, the training dataset is extended through a mixed SS labeling approach. Finally, dissimilarity-based JITL works together with the resulting clustering subdatasets to formulate a local adaptive prediction model. Two datasets from different types of wastewater treatment plants are used to verify the effectiveness of the proposed soft-sensor. The results show that the SS-JITL-SEC soft-sensor can achieve better prediction performance than other standard counterparts, and even for effective process monitoring with the resulted residuals. © 2020 IEEE.

关键词： Entropy

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Advancing electrochemical impedance analysis through innovations in the distribution of relaxation times method

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Joule 2024年第7期8卷 1958-1981页

作者： Maradesa, Adeleke Py, Baptiste Huang, Jake Lu, Yang Iurilli, Pietro Mrozinski, Aleksander Law, Ho Mei Wang, Yuhao Wang, Zilong Li, Jingwei Xu, Shengjun Meyer, Quentin Liu, Jiapeng Brivio, Claudio Gavrilyuk, Alexander Kobayashi, Kiyoshi Bertei, Antonio Williams, Nicholas J. Zhao, Chuan Danzer, Michael Zic, Mark Wu, Phillip Yrjänä, Ville Pereverzyev, Sergei Chen, Yuhui Weber, André Kalinin, Sergei V. Schmidt, Jan Philipp Tsur, Yoed Boukamp, Bernard A. Zhang, Qiang Gaberšček, Miran O'Hayre, Ryan Ciucci, Francesco Department of Mechanical and Aerospace Engineering The Hong Kong University of Science and Technology Hong Kong Metallurgical and Materials Engineering Colorado School of Mines Golden80401 United States Beijing Key Laboratory of Green Chemical Reaction Engineering and Technology Department of Chemical Engineering Tsinghua University Beijing China Green Energy Storage Trento38123 Italy Department of Manufacturing and Production Engineering Faculty of Mechanical Engineering and Ship Technology Institute of Machine and Materials Technology Gdańsk University of Technology Gdańsk Poland Electrode Design for Electrochemical Energy Systems University of Bayreuth Bayreuth Germany School of Chemistry University of New South Wales Sydney Australia School of Advanced Energy Sun Yat-Sen University Shenzhen China Sustainable Energy Center CSEM Neuchâtel2002 Switzerland Interdisciplinary Faculty of Science and Engineering Shimane University Matsue Japan Centre for Electronic and Optical Materials National Institute for Materials Science Tsukuba Japan Department of Civil and Industrial Engineering University of Pisa Pisa Italy Department of Materials Imperial College London Exhibition Road LondonSW7 2AZ United Kingdom Department of Chemical Engineering Massachusetts Institute of Technology Cambridge02139 United States Electrical Energy Systems University of Bayreuth Bayreuth Germany Ruder Boskovic Institute Zagreb Croatia Department of Materials and Minerals Resources Engineering National Taipei University Taipei Taiwan Finland Johann Radon Institute for Computational and Applied Mathematics Linz Austria School of Science and Engineering Nanjing Tech. University Nanjing China Karlsruhe Germany Department of Materials Science and Engineering University of Tennessee KnoxvilleTN37996 United States Physical Science Division Pacific Northwest National Laboratory RichlandWA99354 United States Systems Engineering for Electrical Energy Storage University of B

Electrochemical impedance spectroscopy (EIS) is widely used in electrochemistry, energy sciences, biology, and beyond. Analyzing EIS data is crucial, but it often poses challenges because of the numerous possible equivalent circuit models, the need for accurate analytical models, the difficulties of nonlinear regression, and the necessity of managing large datasets within a unified framework. To overcome these challenges, non-parametric models, such as the distribution of relaxation times (DRT, also known as the distribution function of relaxation times, DFRT), have emerged as promising tools for EIS analysis. For example, the DRT can be used to generate equivalent circuit models, initialize regression parameters, provide a time-domain representation of EIS spectra, and identify electrochemical processes. However, mastering the DRT method poses challenges as it requires mathematical and programming proficiency, which may extend beyond experimentalists’ usual expertise. Post-inversion analysis of DRT data can be difficult, especially in accurately identifying electrochemical processes, leading to results that may not always meet expectations. This article examines non-parametric EIS analysis methods, outlining their strengths and limitations from theoretical, computational, and end-user perspectives, and provides guidelines for their future development. Moreover, insights from survey data emphasize the need to develop a large impedance database, akin to an impedance genome. In turn, software development should target one-click, fully automated DRT analysis for multidimensional EIS spectra interpretation, software validation, and reliability. Particularly, creating a collaborative ecosystem hinged on free software could promote innovation and catalyze the adoption of the DRT method throughout all fields that use impedance data. © 2024 Elsevier Inc.

关键词： Electrochemical impedance spectroscopy

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Humidity Sensing Elements Based on Silica-Graphene Surface Layers 15

Humidity Sensing Elements Based on Silica-Graphene Surface L...

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15th International Scientific and Practical Conference on Environment. Technology. Resources, ETR 2024

作者： Nedev, Nedyu Nenova, Zvezditza Kozhukharov, Stephan Ivanov, Stefan Nenov, Toshko Fundamentals of Electrical and Power Engineering Technical University of Gabrovo Gabrovo Bulgaria LAMAR Laboratory for Advanced Materials Research University of Chemical Technology and Metallurgy Sofia Bulgaria Automation Information and Control Systems Technical University of Gabrovo Gabrovo Bulgaria

ISBN: (纸本)9781713899570

The paper presents humidity sensing elements based on silica-graphene surface layers, prepared via a sol-gel method. The samples were sintered at temperatures of 400 °C, 600 °C and 800 °C. Tetraethoxysilane was used as a precursor of SiO2 and as a dopant - graphene aggregates of nanoplatelets. A description of the sample preparation procedure is provided. Using a precise impedance analyzer and a calibrator for humidity and temperature, the changes in their resistance R were investigated with variations in relative humidity in the range of 30% to 90% at a temperature of 25 °C and at a frequency of 20 Hz. Morphological observations and map data analyses were carried out by Scanning Electron Microscopy (SEM) and Energy Dispersion Spectroscopy (EDX). The developed sensor elements have a good sensitivity to the humidity, and the resistance change reaches two orders of magnitude. Additions of graphene improve the sensitivity of the elements. The characteristics of the sensing elements at different sintering temperatures and different amounts of graphene dopant were modeled using an artificial neural network. © 2024 Nedyu Nedev, Zvezditza Nenova, Stephan Kozhukharov, Stefan Ivanov, Toshko Nenov.

关键词： Silica

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Multi-frequency formation mechanism and modulation strategy of self-priming enhanced submerged pulsed waterjet

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International Journal of Mining Science and Technology 2025年第2期35卷 175-189页

作者： Haojie Jia Yanwei Liu Weiqin Zuo Hongkai Han Ping Chang Mohammad Waqar Ali Asad Guozhong Hu Jian Miao Hani SMitri College of Safety Science and Engineering Henan Polytechnic UniversityJiaozuo 454003China Henan International Joint Laboratory of Coal Mine Safety and Occupational Hazards Prevention and Control Jiaozuo 454003China Zhengzhou Institute for Advanced Research of Henan Polytechnic University Zhengzhou 451464China WA School of Mines:Minerals Energy and Chemical EngineeringCurtin UniversityKalgoorlie WA 6430Australia School of Mines China University of Mining and TechnologyXuzhou 221116China School of Intelligent Engineering Shandong Management UniversityJinan 250357China Department of Mining and Materials Engineering McGill UniversityMontreal H3A0E8Canada

Under submerged conditions, compared with traditional self-excited oscillating pulsed waterjets(SOPWs), annular fluid-enhanced self-excited oscillating pulsed waterjets(AFESOPWs) exhibit a higher surge pressure through self-priming. However, their pressure frequency and cavitation characteristics remain unclear, resulting in an inability to fully utilize resonance and cavitation erosion to break coal and rock. In this study, high-frequency pressure testing, high-speed photography, and large eddy simulation(LES) are used to investigate the distribution of the pressure frequency band, evolution law of the cavitation cloud, and its regulation mechanism of a continuous waterjet, SOPW, and AFESOPW. The results indicated that the excitation of the plunger pump, shearing layer vortex, and bubble collapse corresponded to the three high-amplitude frequency bands of the waterjet pressure. AFESOPWs have an additional self-priming frequency that can produce a larger amplitude under a synergistic effect with the second high-amplitude frequency band. A better cavitation effect was produced after self-priming the annulus fluid, and the shedding frequency of the cavitation clouds of the three types of waterjets was linearly related to the cavitation number. The peak pressure of the waterjet and cavitation erosion effect can be improved by modulating the waterjet pressure oscillation frequency and cavitation shedding frequency.

关键词： Multi-frequency Modulation Self-priming Submerged waterjet Cavitation

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Pressure swing adsorption process modeling using physics-informed machine learning with transfer learning and labeled data

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Green chemical engineering 2025年第2期6卷 233-248页

作者： Zhiqiang Wu Yunquan Chen Bingjian Zhang Jingzheng Ren Qinglin Chen Huan Wang Chang He School of Materials Science and Engineering Sun Yat-Sen UniversityGuangzhou510275China Guangdong Engineering Center for Petrochemical Energy Conservation Guangzhou510275China Department of Industrial and Systems Engineering The Hong Kong Polytechnic UniversityHong Kong Special Administrative RegionChina School of Chemical Engineering and Technology Sun Yat-sen UniversityZhuhai519082China State Key Laboratory of Heavy Oil Processing China University of Petroleum-BeijingBeijing102249China CNNC No.7 Research and Design Institute Co.Ltd. Taiyuan030012China

Pressure swing adsorption(PSA)modeling remains a challenging task since it exhibits strong dynamic and cyclic *** study presents a systematic physics-informed machine learning method that integrates transfer learning and labeled data to construct a spatiotemporal model of the PSA *** approximate the latent solutions of partial differential equations(PDEs)in the specific steps of pressurization,adsorption,heavy reflux,counter-current depressurization,and light reflux,the system's network representation is decomposed into five lightweight *** this basis,we propose a parameter-based transfer learning(TL)combined with domain decomposition to address the long-term integration of periodic PDEs and expedite the network training ***,to tackle challenges related to sharp adsorption fronts,our method allows for the inclusion of a specified amount of labeled data at the boundaries and/or within the system in the loss *** results show that the proposed method closely matches the outcomes achieved through the conventional numerical method,effectively simulating all steps and cyclic behavior within the PSA processes.

关键词： Physics-informed machine learning Pressure swing adsorption Transfer learning Labeled data Partial differential equations

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Dynamic asymmetric mechanical responsive carbon nanotube fiber for ionic logic gate

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Chinese chemical Letters 2024年第6期35卷 249-253页

作者： Pei Cao Yilan Wang Lejian Yu Miao Wang Liming Zhao Xu Hou State Key Laboratory of Physical Chemistry of Solid Surfaces College of Chemistry and Chemical EngineeringXiamen UniversityXiamen 361005China Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province(IKKEM) Xiamen 361005China The Higher Educational Key Laboratory for Biomedical Engineering of Fujian Province Department of BiomaterialsResearch Center of Biomedical Engineering of XiamenCollege of MaterialsXiamen UniversityXiamen 361005China Key Laboratory of Multifunctional Nanomaterials and Smart Systems Advanced Materials DivisionSuzhou Institute of Nano-Tech and Nano-BionicsChinese Academy of SciencesSuzhou 215123China Institute of Artificial Intelligence Xiamen UniversityXiamen 361005China Department of Physics Research Institute for Biomimetics and Soft MatterFujian Provincial Key Laboratory for Soft Functional Materials ResearchJiujiang Research InstituteCollege of Physical Science and TechnologyXiamen UniversityXiamen 361005China Engineering Research Center of Electrochemical Technologies of Ministry of Education Xiamen UniversityXiamen 361005China

Inspired by biological ion channels,numerous artificial asymmetric ion channels have been synthesized to facilitate the fabrication of ionic ***,the creation of biomimetic asymmetric ion channels necessitates expensive scientific apparatus and intricate material processing procedures,which constrains its advancement within the realm of ionic *** this study,we have devised dynamic asymmetric ion channels with mechanical responsiveness by combining polymers of varying elastic modulus along the longitudinal axis of carbon nanotube fiber(CNTF).The ion rectification can be modulated via the disparate response of CNTF-based ion channels to mechanical *** have effectively employed these asymmetric ion channels with mechanical sensitivity in the design of a logic gate device,achieving logic operations such as“AND”and“OR”.The conception of these dynamic asymmetric ion channels with mechanical sensitivity offers a straightforward,cost-effective,and versatile approach for generating ion channels,highlighting their potential application in intricate,highly integrated ionic circuits.

关键词： Carbon nanotubes fibers Mechanical response Rectification effect Ionic logic gate

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Boosting Peroxymonosulfate Activation via Co-Based LDH-Derived Magnetic Catalysts:A Dynamic and Static State Assessment of Efficient Radical-Assisted Electron Transfer Processes

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Energy & Environmental materials 2024年第5期7卷 301-312页

作者： Wenhan Yang Junming Xia Fanfan Shang Ge Ge Yang Bin Wang Hairui Cai Lingyun Jing Hao Zhu Shengchun Yang Chao Liang Guosheng Shao MOE Key Laboratory for Nonequilibrium Synthesis and Modulation of Condensed Matter School of PhysicsNational Innovation Platform(Center)for Industry-Education Integration of Energy Storage TechnologyXi'an Jiaotong UniversityXi'an 710000China State Key Laboratory of Organic Electronics and Information Displays&Institute of Advanced Materials(1AM) Nanjing University of Posts&Telecommunications9 Wenyuan RoadNanjing 210023China College of Petroleum and Chemical Engineering Lanzhou University of TechnologyLanzhou 730050China Key Laboratory of Western China's Environmental Systems(Ministry of Education)and Gansu Engineering Research Center of Fine Particles Pollution Control Technology and Equipment College of Earth and Environmental SciencesLanzhou UniversityLanzhou 730000China State Center for International Cooperation on Designer Low-Carbon&Environmental Materials(CDLCEM) School of Materials Science and EngineeringZhengzhou UniversityZhengzhou 450001China

Heterogeneous catalysts promoting efficient production of reactive species and dynamically stabilized electron transfer mechanisms for peroxomonosulfates(PMS)still lack systematic ***,a more stable magnetic layered double oxides(CFLDO/N-C),was designed using self-polymerization and high temperature carbonization of *** CFLDO/N-C/PMS system effectively activated PMS to remove 99%(k=0.737 min^(-1))of tetracycline(TC)within 10 *** CFLDO/N-C/PMS system exhibited favorable resistance to inorganic anions and natural organics,as well as satisfactory suitability for multiple *** magnetic properties of the catalyst facilitated the separation of catalysts from the liquid phase,resulting in excellent reproducibility and effectively reducing the leaching of metal *** electronic bridge was constructed between cobalt(the active platform of the catalyst)and PMS,inducing PMS to break the O-O bond to generate the active *** combination of static analysis and dynamic evolution confirmed the effective adsorption of PMS on the catalyst surface as well as the strong radical-assisted electron transfer ***,we further identified the sites where the reactive species attacked the TC and evaluated the toxicity of the *** findings offer innovative insights into the rapid degradation of pollutants achieved by transition metals in SR-AOPs and its mechanistic elaboration.

关键词： advanced oxidation process degradation mechanisms electron transport layered double hydroxide reactive species

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Designing MPC controller for a Heat Exchanger Equipped with Thermoelectric Generators 11

Designing MPC Controller for a Heat Exchanger Equipped with ...

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2022 11th International Conference on Information and Electronics engineering, ICIEE 2022

作者： Kemjariya, Sucha Daosud, Wachira Weerachaipichasgul, Weerawun Kittisupakorn, Paisan Control and Systems Engineering Research Laboratory Department of Chemical Engineering Faculty of Engineering Chulalongkorn University Bangkok10330 Thailand Department of Chemical Engineering Faculty of Engineering Burapha University Chonburi20130 Thailand Division of Chemical Engineering Department of Industrial Engineering Faculty of Engineering Naresuan University Phitsanulok65000 Thailand

A thermoelectric generator (TEG) is a solid-state semiconductor device that can convert temperature differences and heat flow into electrical energy. Nowadays, industries with high-temperature production processes tend to experience unavoidable heat loss. Heat exchangers are therefore the most widely used equipment to recover these waste heat. The researcher therefore saw the benefits of bringing TEG devices to be installed in heat exchangers. It is thought that in addition to the heat exchanger being a device that helps the heat transfer of one fluid to another fluid. Can also generate electricity back to use as well. This will be of great benefit in increasing the efficiency of waste heat recovery and reducing production costs. In this research, 36 plates of Bismuth Telluride (Bi2Te3) TEG devices were installed in plate and fin heat exchangers and studied the effect of changes in the inlet flow rate of cold water at 20 °C on the effect of heat exchange and the electrical power produced by TEG. The hot water inlet flow rate was constant at 1 l/min and the temperature was constant at 85 °C. Then mathematical model was created to predict the results of the outlet hot water temperature, outlet cold water temperature, current and voltage produced. The model can predict accurately the least squares value (R2) with values of 0.949, 0.859, 0.707 and 0.749, respectively. In addition, a multiple input, multiple output (MIMO) using model predictive controller (MPC) was designed to control the output current, and temperature can control into the setpoint effectively. © Published under licence by IOP Publishing Ltd.

关键词： Heat transfer

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Partially charged single-atom Ru supported on ZrO_(2) nanocrystals for highly efficient ethylene hydrosilylation with triethoxysilane

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Nano Research 2022年第7期15卷 5857-5864页

作者： Mingyan Li Shu Zhao Jing Li Xiao Chen Yongjun Ji Haijun Yu Dingrong Bai Guangwen Xu Ziyi Zhong Fabing Su Key Laboratory of Resources Chemicals and Materials(Shenyang University of Chemical Technology) Ministry of EducationShenyang 110142China State Key Laboratory of Multiphase Complex Systems Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China Faculty of Materials and Manufacturing Institute of Advanced Battery Materials and DevicesBeijing University of TechnologyBeijing 100124China Department of Chemical Engineering Beijing Key Laboratory of Green Chemical Reaction Engineering and TechnologyTsinghua UniversityBeijing 100084China School of Light Industry Beijing Technology and Business UniversityBeijing 100048China Institute of Industrial Chemistry and Energy Technology Shenyang University of Chemical TechnologyShenyang 110142China Department of Chemical Engineering Guangdong Technion-Israel Institute of Technology(GTIIT)Shantou 515063China Technion-Israel Institute of Technology(IIT) Haifa 32000Israel

Homogeneous noble metal catalysts used in alkene hydrosilylation reactions to manufacture organosilicon compounds commercially often suffer from difficulties in catalyst recovering and recycling,undesired disproportionation reactions,and energyintensive purification of ***,we report a heterogeneous 0.5Ruδ+/ZrO_(2) catalyst with partially charged single-atom Ru(0.5 wt.%Ru)supported on commercial ZrO_(2) nanocrystals synthesized by the simple impregnation method followed by H2 *** used in the ethylene hydrosilylation with triethoxysilane to produce the desired ethyltriethoxysilane,0.5Ruδ+/ZrO_(2) showed excellent catalytic performance with the maximum Ru atom utilization and good recyclability,even superior to homogeneous catalyst(RuCl3·H2O).Structural characterizations and density functional theory calculations reveal the atomic dispersion of the active Ru species and their unique electronic properties distinct from the homogeneous *** reaction route over this catalyst is supposed to follow the typical Chalk-Harrod *** highly efficient and supported singleatom Ru catalyst has the potential to replace the current homogeneous catalyst for a greener hydrosilylation industry.

关键词： single-atom Ru heterogeneous catalysts hydrosilylation reaction high performance

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