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Cover Feature: Design of a Metal–Organic Framework-Derived Co9S8/S Material for Achieving High Durability and High Performance of Lithium–Sulfur Batteries (ChemElectroChem 16/2021)

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ChemElectroChem 2021年第16期8卷

作者： Arif I. Inamdar Nahid Kaisar Saqib Kamal Tzuoo-Tsair Luo Prof. Dr. Shyankay Jou Prof. Dr. Chih-Wei Chu Prof. Dr. Ming-Hsi Chiang Prof. Dr. Kuang-Lieh Lu Institute of Chemistry Academia Sinica 115 Taipei Taiwan Department of Applied Chemistry National Yang Ming Chiao Tung University 300 Hsinchu Taiwan Sustainable Chemical Science and Technology Taiwan International Graduate Program Institute of Chemistry Academia Sinica 115 Taipei Taiwan Department of Materials Science and Engineering National Taiwan University of Science and Technology 106 Taipei Taiwan Research Center for Applied Sciences Academia Sinica 115 Taipei Taiwan Molecular Science and Technology Taiwan International Graduate Program Institute of Atomic and Molecular Science Academia Sinica 115 Taipei Taiwan Department of Chemistry Fu Jen Catholic University 242 New Taipei City Taiwan Department of Chemistry National Tsing Hua University 300 Hsinchu Taiwan Department of Medicinal and Applied Chemistry Kaohsiung Medical University 807 Kaohsiung Taiwan

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Bridging particle deformability and collective response in soft solids

arXiv

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arXiv 2020年

作者： Treado, John D. Wang, Dong Boromand, Arman Murrell, Michael P. Shattuck, Mark D. O’Hern, Corey S. Department of Mechanical Engineering & Materials Science Yale University New HavenCT06520 United States Integrated Graduate Program in Physical and Engineering Biology Yale University New HavenCT06520 United States Department of Biomedical Engineering Yale University New HavenCT06520 United States Department of Physics Yale University New HavenCT06520 United States Systems Biology Institute Yale University West HavenCT06516 United States Benjamin Levich Institute and Physics Department The City College of New York New YorkNY10031 United States Department of Applied Physics Yale University New HavenCT06520 United States

Soft, amorphous solids such as tissues, foams, and emulsions are composed of deformable particles. However, the effect of single-particle deformability on the collective behavior of soft solids is still poorly understood. We perform numerical simulations of two-dimensional jammed packings of explicitly deformable particles to study the mechanical response of model soft solids. We find that jammed packings of deformable particles with excess shape degrees of freedom possess low-frequency quartic vibrational modes that stabilize the packings even though they possess fewer interparticle contacts than the nominal isostatic value. Adding intra-particle constraints can rigidify the particles, but these particles undergo a buckling transition and gain an effective shape degree of freedom when their preferred perimeter is above a threshold value. We find that the mechanical response of jammed packings of deformable particles with shape degrees of freedom differs significantly from that of jammed packings of rigid-shape particles, which emphasizes the importance of particle deformability in modelling soft solids. © 2020, CC BY.

关键词： Degrees of freedom (mechanics)

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Advances of machine learning in molecular modeling and simulation

arXiv

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arXiv 2019年

作者： Haghighatlari, Mojtaba Hachmann, Johannes Department of Chemical and Biological Engineering University at Buffalo State University of New York BuffaloNY14260 United States Computational and Data-Enabled Science and Engineering Graduate Program University at Buffalo State University of New York BuffaloNY14260 United States New York State Center of Excellence in Materials Informatics BuffaloNY14203 United States

In this review, we highlight recent developments in the application of machine learning for molecular modeling and simulation. After giving a brief overview of the foundations, components, and workflow of a typical supervised learning approach for chemical problems, we showcase areas and state-of-the-art examples of their deployment. In this context, we discuss how machine learning relates to, supports, and augments more traditional physics-based approaches in computational research. We conclude by outlining challenges and future research directions that need to be addressed in order to make machine learning a mainstream chemical engineering tool. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning

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Cover Picture: Addressing Environmental Challenges of Porphyrin Mixtures Obtained from Statistical Syntheses (Chemistry - Methods 3/2021)

Chemistry–Methods

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Chemistry–Methods 2021年第3期1卷

作者： Helen Hölzel Maximilian Muth Prof. Dr. Dominik Lungerich Prof. Dr. Norbert Jux Department of Chemistry and Pharmacy & Interdisciplinary Center for Molecular Materials (ICMM) Friedrich-Alexander-University Erlangen-Nuernberg Nikolaus-Fiebiger-Str. 10 91058 Erlangen Germany Center for Nanomedicine Institute for Basic Science (IBS) 50 Yonsei-ro Seodaemun-gu Seoul 03722 South Korea Graduate Program for Nano Biomedical Engineering (NanoBME) Advanced Science Institute Yonsei University 50 Yonsei-ro Seodaemun-gu Seoul 03722 South Korea

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Identifying irregularity electricity usage of customer behaviors using logistic regression and linear discriminant analysis 3

Identifying irregularity electricity usage of customer behav...

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3rd International Conference on science in Information Technology, ICSITech 2017

作者： Lawi, Armin Wungo, Supriyadi La Manjang, Salama Department of Computer Science Post-graduate Program of Electrical Engineering Dept. Electrical Engineering Universitas Hasanuddin Makassar Indonesia

ISBN: (纸本)9781509058662

This study aims to implement a machine learning technique in identifying the irregularities of customer behavior on the use of prepaid electricity pulses. The methods used are Linear Discriminant Analysis and Logistic Regression. The performance of the classification system will be evaluated using the 10-fold cross-validation technique. Validation results are measured using accuracy, precision and recall values. In this research shows that the use of machine learning technique has a good performance in classification of electrical consumption behavior. Experimental results with the different amount of data testing indicate that Logistic Regression method has high accuracy, precision, and recall value when compared with Linear Discriminant Analysis that is 100%. This is due to Logistic Regression method can predict irregularities accurately because the addition of the amount of data does not affect the performance of the method. © 2017 IEEE.

关键词： Regression analysis

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Correction: The structural, vibrational, and mechanical properties of jammed packings of deformable particles in three dimensions

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Soft matter 2022年第19期18卷 3815页

作者： Dong Wang John D Treado Arman Boromand Blake Norwick Michael P Murrell Mark D Shattuck Corey S O'Hern Department of Mechanical Engineering & Materials Science Yale University New Haven Connecticut 06520 USA. corey.ohern@yale.edu. Integrated Graduate Program in Physical and Engineering Biology Yale University New Haven Connecticut 06520 USA. Department of Physics Yale University New Haven Connecticut 06520 USA. Department of Biomedical Engineering Yale University New Haven Connecticut 06520 USA. Systems Biology Institute Yale University West Haven Connecticut 06516 USA. Benjamin Levich Institute and Physics Department The City College of New York New York New York 10031 USA. Department of Applied Physics Yale University New Haven Connecticut 06520 USA.

Correction for 'The structural, vibrational, and mechanical properties of jammed packings of deformable particles in three dimensions' by Dong Wang , , 2021, , 9901-9915, DOI: 10.1039/D1SM01228B.

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Cover Feature: Chemo-Biological Upcycling of Poly(ethylene terephthalate) to Multifunctional Coating materials (ChemSusChem 19/2021)

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ChemSusChem 2021年第19期14卷

作者： Prof. Hee Taek Kim Mi Hee Ryu Ye Jean Jung Sooyoung Lim Hye Min Song Prof. Jeyoung Park Prof. Sung Yeon Hwang Dr. Hoe-Suk Lee Prof. Young Joo Yeon Dr. Bong Hyun Sung Prof. Uwe T. Bornscheuer Prof. Si Jae Park Prof. Jeong Chan Joo Prof. Dongyeop X. Oh Department of Food Science and Technology Chungnam National University Daejeon 34134 (Republic of Korea Research Center for Bio-based Chemicals Korea Research Institute of Chemical Technology Daejeon 34114 & Ulsan 44429 (Republic of Korea Department of Chemical Engineering and Materials Science Graduate Program in System Health Science & Engineering Ewha Womans University Seoul 03760 (Republic of Korea Advanced Materials and Chemical Engineering University of Science and Technology (UST) Daejeon 34113 (Republic of Korea Department of Biochemical Engineering Gangneung-Wonju National University Gangneung-si Gangwon-do 25457 (Republic of Korea Synthetic Biology and Bioengineering Research Center Korea Research Institute of Bioscience and Biotechnology Daejeon 34141 (Republic of Korea Department of Biotechnology & Enzyme Catalysis Institute of Biochemistry University of Greifswald 17487 Greifswald Germany Department of Biotechnology The Catholic University of Korea Bucheon-si Gyeonggi-do 14662 (Republic of Korea

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Control of microswimmers by spiral nematic vortices: transition from individual to collective motion and contraction, expansion, and stable circulation of bacterial swirls

arXiv

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arXiv 2020年

作者： Koizumi, Runa Turiv, Taras Genkin, Mikhail M. Lastowski, Robert J. Yu, Hao Chaganava, Irakli Wei, Qi-Huo Aranson, Igor S. Lavrentovich, Oleg D. Advanced Materials and Liquid Crystal Institute Materials Science Graduate Program Kent State University KentOH44242 United States Cold Spring Harbor Laboratory 1 Bungtown Rd Cold Spring HarborNY11724 United States Department of Chemistry University of Scranton ScrantonPA18510 United States Institute of Cybernetics of Georgian Technical University TbilisiGA0186 United States Georgian State Teaching University of Physical Education and Sport TbilisiGA0162 United States Department of Physics Kent State University KentOH44242 United States Department of Biomedical Engineering Pennsylvania State University University ParkPA16802 United States

Active systems comprised of self-propelled units show fascinating transitions from Brownian-like dynamics to collective coherent motion. Swirling of swimming bacteria is a spectacular example. This study demonstrates that a nematic liquid crystal environment patterned as a spiral vortex controls individual-to-collective transition in bacterial swirls and defines whether they expand or shrink. In dilute dispersions, the bacteria swim along open spiral trajectories, following the pre-imposed molecular orientation. The trajectories are nonpolar. As their concentration exceeds some threshold, the bacteria condense into unipolar circular swirls resembling stable limit cycles. This collective circular motion is controlled by the spiral angle that defines the splay-to-bend ratio of the background director. Vortices with dominating splay shrink the swirls towards the center, while vortices with dominating bend expand them to the periphery. 45o spiraling vortices with splay-bend parity produce the most stable swirls. All the dynamic scenarios are explained by hydrodynamic interactions of bacteria mediated by the patterned passive nematic environment and by the coupling between the concentration and orientation. The acquired knowledge of how to control individual and collective motion of microswimmers by a nematic environment can help in the development of microscopic mechanical systems. Copyright © 2020, The Authors. All rights reserved.

关键词： Vortex flow

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Real-time optimization using gradient adaptive selection and classification from infrared sensors measurement for esterification oleic acid with glycerol

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International Journal of Intelligent Computing and Cybernetics 2017年第2期10卷 130-144页

作者： Iwan Aang Soenandi Taufik Djatna Ani Suryani Irzaman Post Graduate Program of Agro-industrial Technology Bogor Agricultural UniversityBogorIndonesia and Faculty of Engineering and Computer ScienceKrida Wacana Christian UniversityJakartaIndonesia Post Graduate Program of Agro-industrial Technology Bogor Agricultural UniversityBogorIndonesia Department of Physics Faculty of Mathematics and Natural SciencesBogor Agricultural UniversityBogorIndonesia

Purpose-The production of glycerol derivatives by the esterification process is subject to many constraints related to the yield of the production target and the lack of process *** accurate monitoring and controlling of the process can improve production yield and *** purpose of this paper is to propose a real-time optimization(RTO)using gradient adaptive selection and classification from infrared sensor measurement to cover various disturbances and uncertainties in the ***/methodology/approach-The integration of the esterification process optimization using self-optimization(SO)was developed with classification process was combined with necessary condition optimum(NCO)as gradient adaptive selection,supported with laboratory scaled medium wavelength infrared(mid-IR)sensors,and measured the proposed optimization system indicator in the batch *** Process Modeling and Notation(BPMN 2.0)was built to describe the tasks of SO workflow in collaboration with NCO as an abstraction for the conceptual ***,Stateflow modeling was deployed to simulate the three states of gradient-based adaptive control combined with support vector machine(SVM)classification and Arduino microcontroller for ***-This new method shows that the real-time optimization responsiveness of control increased product yield up to 13 percent,lower error measurement with percentage error 1.11 percent,reduced the process duration up to 22 minutes,with an effective range of stirrer rotation set between 300 and 400 rpm and final temperature between 200 and 210℃ which was more efficient,as it consumed less *** limitations/implications-In this research the authors just have an experiment for the esterification process using glycerol,but as a development concept of RTO,it would be possible to apply for another chemical reaction or *** implications-This research introduces new development of an RTO approach to optimal con

关键词： Gradient technique Infrared sensor Real-time optimization Simulation and modelling Support vector machine

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Void distributions reveal structural link between jammed packings and protein cores

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Physical Review E 2019年第2期99卷 022416-022416页

作者： John D. Treado Zhe Mei Lynne Regan Corey S. O'Hern Department of Mechanical Engineering & Materials Science Yale University New Haven Connecticut 06520 USA Integrated Graduate Program in Physical & Engineering Biology Yale University New Haven Connecticut 06520 USA Department of Chemistry Yale University New Haven Connecticut 06520 USA Department of Molecular Biophysics & Biochemistry Yale University New Haven Connecticut 06520 USA Department of Physics Yale University New Haven Connecticut 06520 USA Department of Applied Physics Yale University New Haven Connecticut 06520 USA Program in Computational Biology and Bioinformatics Yale University New Haven Connecticut 06520 USA

Dense packing of hydrophobic residues in the cores of globular proteins determines their stability. Recently, we have shown that protein cores possess packing fraction ϕ≈0.56, which is the same as dense, random packing of amino-acid-shaped particles. In this article, we compare the structural properties of protein cores and jammed packings of amino-acid-shaped particles in much greater depth by measuring their local and connected void regions. We find that the distributions of surface Voronoi cell volumes and local porosities obey similar statistics in both systems. We also measure the probability that accessible, connected void regions percolate as a function of the size of a spherical probe particle and show that both systems possess the same critical probe size. We measure the critical exponent τ that characterizes the size distribution of connected void clusters at the onset of percolation. We find that the cluster size statistics are similar for void percolation in packings of amino-acid-shaped particles and randomly placed spheres, but different from that for void percolation in jammed sphere packings. We propose that the connected void regions are a defining structural feature of proteins and can be used to differentiate experimentally observed proteins from decoy structures that are generated using computational protein design software. This work emphasizes that jammed packings of amino-acid-shaped particles can serve as structural and mechanical analogs of protein cores, and could therefore be useful in modeling the response of protein cores to cavity-expanding and -reducing mutations.

关键词： Jamming Protein structure Packing & jamming problems Proteins Crystal structures Finite-size scaling Molecular dynamics Percolation theory

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