检索结果-内蒙古大学图书馆

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

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

来源：评论

学校读者我要写书评

暂无评论

Identifying the minimal sets of distance restraints for FRET-assisted protein structural modeling

arXiv

引用

arXiv 2024年

作者： Liu, Zhuoyi Grigas, Alex T. Sumner, Jacob Knab, Edward Davis, Caitlin M. O’Hern, Corey S. Department of Mechanical Engineering and Materials Science Yale University New HavenCT06520 United States Integrated Graduate Program in Physical and Engineering Biology Yale University New HavenCT06520 United States Graduate Program in Computational Biology and Bioinformatics Yale University New HavenCT06520 United States Department of Chemistry Yale University New HavenCT06520 United States Department of Physics Yale University New HavenCT06520 United States Department of Applied Physics Yale University New HavenCT06520 United States

Proteins naturally occur in crowded cellular environments and interact with other proteins, nucleic acids, and organelles. Since most previous experimental protein structure determination techniques require that proteins occur in idealized, non-physiological environments, the effects of realistic cellular environments on protein structure are largely unexplored. Recently, Förster resonance energy transfer (FRET) has been shown to be an effective experimental method for investigating protein structure in vivo. Inter-residue distances measured in vivo can be incorporated as restraints in molecular dynamics (MD) simulations to model protein structural dynamics in vivo. Since most FRET studies only obtain inter-residue separations for a small number of amino acid pairs, it is important to determine the minimum number of restraints in the MD simulations that are required to achieve a given root-mean-square deviation (RMSD) from the experimental structural ensemble. Further, what is the optimal method for selecting these inter-residue restraints? Here, we implement several methods for selecting the most important FRET pairs and determine the number of pairs Nr that are needed to induce conformational changes in proteins between two experimentally determined structures. We find that enforcing only a small fraction of restraints, Nr/N 0.08, where N is the number of amino acids, can induce the conformational changes. These results establish the efficacy of FRET-assisted MD simulations for atomic scale structural modeling of proteins in vivo. © 2024, CC BY.

关键词： Conformations

来源：评论

学校读者我要写书评

暂无评论

Robust Feature engineering Techniques for Designing Efficient Motor Imagery-Based BCI-Systems

arXiv

引用

arXiv 2024年

作者： Gardezi, Syed Saim Jawed, Soyiba Khan, Mahnoor Bukhari, Muneeba Khan, Rizwan Ahmed Department of Biomedical Engineering Faculty of Engineering Salim Habib University Karachi Pakistan Department of Computer Software Engineering College of Electrical and Mechanical Engineering NUST Islamabad Pakistan Department of Physics Faculty of Applied Sciences Riphah International University Islamabad Pakistan Department of Biomedical Engineering Faculty of Engineering NED University Karachi Pakistan Department of Computer Science School of Mathematics and Computer Science Institute of Business Administration Karachi Pakistan

A multitude of individuals across the globe grapple with motor disabilities. Neural prosthetics utilizing Brain-Computer Interface (BCI) technology exhibit promise for improving motor rehabilitation outcomes. The intricate nature of EEG data poses a significant hurdle for current BCI systems. Recently, a qualitative repository of EEG signals tied to both upper and lower limb execution of motor and motor imagery tasks has been unveiled. Despite this, the productivity of the Machine Learning (ML) Models that were trained on this dataset was alarmingly deficient, and the evaluation framework seemed insufficient. To enhance outcomes, robust feature engineering (signal processing) methodologies are implemented. A collection of time domain, frequency domain, and wavelet-derived features was obtained from 16-channel EEG signals, and the Maximum Relevance Minimum Redundancy (MRMR) approach was employed to identify the four most significant features. For classification K Nearest Neighbors, Support Vector Machine, Decision Tree, and Naïve Bayes models were implemented with these selected features, evaluating their effectiveness through metrics such as testing accuracy, precision, recall, and F1 Score. By leveraging SVM with a Gaussian Kernel, a remarkable maximum testing accuracy of 92.50% for motor activities and 95.48% for imagery activities is achieved. These results are notably more dependable and gratifying compared to the previous study, where the peak accuracy was recorded at 74.36%. This research work provides an in-depth analysis of the MI Limb EEG dataset and it will help in designing and developing simple, cost-effective and reliable BCI systems for neuro-rehabilitation. © 2024, CC BY-NC-ND.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Slenderness Ratio and Material Optimization of an Impact-Resistant 2d Auxetic Lattice

SSRN

引用

SSRN 2024年

作者： Zhai, Xuedong Heye-Smith, Karina Mao, Xiaoming Arruda, Ellen M. Department of Mechanical Engineering University of Michigan Ann ArborMI United States Department of Physics University of Michigan Ann ArborMI United States Department of Biomedical Engineering University of Michigan Ann ArborMI United States Program in Macromolecular Science and Engineering University of Michigan Ann ArborMI United States

It is well known that armor prevents failures of behind-armor targets by reducing the force in an impact event and thereby providing protection under certain impact events. However, the kinetic energy associated with an impact, often underappreciated in impact events, can be as fatal as the force by causing relative motion in the target and destructive damage as a consequence. Therefore, efficient protection gear and packaging should be lightweight and good at force reduction as well as energy mitigation. Although auxetic lattices have been studied as lightweight alternatives for force reduction, simultaneous optimization of force reduction and energy dissipation in impact mitigation via geometric and material choices for auxetic lattices has not been addressed. In the present study, we show that a 2D auxetic lattice with an optimized slenderness ratio of the struts that comprise the lattice and optimized elastic and visco-elastic material properties can not only reduce the transmitted peak force but also mitigate the energy significantly. A multi-step optimization method using Finite Element (FE) analysis and a verification procedure via impact experiments are described by which an optimal design of the auxetic lattice can be achieved by simultaneously considering both peak force and energy mitigation. © 2024, The Authors. All rights reserved.

关键词： Armor

来源：评论

学校读者我要写书评

暂无评论

Local stability guarantees for data-driven quadratically nonlinear models

arXiv

引用

arXiv 2024年

作者： Peng, Mai Kaptanoglu, Alan Hansen, Chris Stevens-Haas, Jacob Manohar, Krithika Brunton, Steve Department of Mechanical Engineering University of Washington SeattleWA98195 United States Courant Institute of Mathematical Sciences New York University New YorkNY10012 United States Department of Applied Physics and Applied Mathematics Columbia University New YorkNY10027 United States Department of Applied Mathematics University of Washington SeattleWA98195 United States

The Navier Stokes equations (NSEs) are partial differential equations (PDEs) to describe the nonlinear convective motion of fluids and they are computationally expensive to simulate because of their high nonlinearity and variables being fully coupled. Reduced-order models (ROMs) are simpler models for evolving the flows by capturing only the dominant behaviors of a system and can be used to design controllers for high-dimensional systems. However it is challenging to guarantee the stability of these models either globally or locally. Ensuring the stability of ROMs can improve the interpretability of the behavior of the dynamics and help develop effective system control strategies. For quadratically nonlinear systems that represent many fluid flows, the Schlegel and Noack trapping theorem [1] can be used to check if ROMs are globally stable (long-term bounded). This theorem was subsequently incorporated into system identification techniques that determine models directly from data [2]. In this work, we relax the quadratically energy-preserving constraints in this theorem, and then promote local stability in data-driven models of quadratically nonlinear dynamics. First, we prove a theorem outlining sufficient conditions to ensure local stability in linear-quadratic systems and provide an estimate of the stability radius. Second, we incorporate this theorem into system identification methods and produce a-priori locally stable data-driven models. Several examples are presented to demonstrate the effectiveness and accuracy of the proposed algorithm. Copyright © 2024, The Authors. All rights reserved.

关键词： Navier Stokes equations

来源：评论

学校读者我要写书评

暂无评论

Sensing with shallow recurrent decoder networks

arXiv

引用

arXiv 2023年

作者： Williams, Jan P. Zahn, Olivia Nathan Kutz, J. Department of Mechanical Engineering University of Washington SeattleWA United States Department of Physics University of Washington SeattleWA United States Departments of Applied Mathematics and Electrical and Computer Engineering University of Washington SeattleWA United States

Sensing is a universal task in science and engineering. Downstream tasks from sensing include inferring full state estimates of a system (system identification), control decisions, and forecasting. We propose a SHallow REcurrent Decoder (SHRED) neural network structure for sensing which incorporates (i) a recurrent neural network to learn a latent representation of the temporal dynamics of the sensors, and (ii) a shallow decoder that learns a mapping between this latent representation and the high-dimensional state space. SHRED enables accurate reconstructions with far fewer sensors, outperforms existing techniques when more measurements are available, and is more robust to random sensor placements. In the example cases explored, complex spatio-temporal dynamics are characterized with exceedingly limited sensors that can be randomly placed with minimal loss of performance. © 2023, CC BY.

关键词： Recurrent neural networks

来源：评论

学校读者我要写书评

暂无评论

Modeling Atomistically Assembled Diffractive Optics in Solids

arXiv

引用

arXiv 2024年

作者： Kling, Trevor Na, Dong-Yeop Hosseini, Mahdi Department of Electrical and Computer Engineering Applied Physics Program Northwestern University EvanstonIL60208 United States Department of Electrical Engineering Pohang University of Science and Technology Pohang37673 Korea Republic of Elmore Family School of Electrical and Computer Engineering Purdue University West LafayetteIN47907 United States

We develop a model describing long-range atom-atom interactions in a two-dimensional periodic or a-periodic lattice of optical centers inside a solid-state host material. We consider realistic environmental and technical conditions such as frequency and position broadening. Even when considering a significant frequency broadening in the ensemble (∼300 GHz), we observe up to a three-fold increase in directional scattering from the resonant lattice in a system. The model can be used to scalably design quantum optical elements, e.g. a quantum lens, harnessing atomistic engineering (e.g. via ion implantation) of collective interactions in materials to enhance quantum properties. © 2024, CC BY.

关键词： Nanocrystals

来源：评论

学校读者我要写书评

暂无评论

Electric-field-induced metal-insulator transition and quantum transport in large-area polycrystalline MoS2 monolayers

引用

Physical Review Materials 2022年第6期6卷 064005-064005页

作者： Hao Ou Tomoyuki Yamada Masaya Mitamura Yusuke Edagawa Tatsuma D. Matsuda Kazuhiro Yanagi Chang-Hsiao Chen Lain-Jong Li Taishi Takenobu Jiang Pu Department of Applied Physics Nagoya University Nagoya 464-8603 Japan Department of Physics Tokyo Metropolitan University Tokyo 192-0397 Japan Department of Electrical Engineering National Sun Yat-sen University Kaohsiung 80424 Taiwan Department of Mechanical Engineering The University of Hong Kong Pokfulam Road Hong Kong

Monolayer MoS2 is an attractive candidate for developing future electronics and exploring fundamental physics because of its unique quantum properties. High-performance MoS2 transistors with superior transport originating from spin-valley coupling have been reported. However, these transistors have used single-crystalline flakes. In most large-area polycrystalline MoS2, these excellent transport properties have not been realized because of the effects of grain boundaries, and their fundamental low-temperature transport has not been studied in detail. Here, we apply electrolyte-gating methods using chemically grown centimeter-scale polycrystalline monolayers. Owing to the high carrier density, the resistance is systematically tuned from insulating to metallic conduction. Importantly, we observed metallic transport at temperatures down to 1.9 K and a high mobility of >100cm2nV−1s−1. Moreover, the magnetotransport exhibits an electric-field-induced crossover from weak localization to weak antilocalization, indicating that high carrier density dramatically suppresses the grain boundary effects to enable intrinsic quantum transport. The results reveal that polycrystalline MoS2 monolayers have significant potential for use in large-area nanoelectronics.

关键词： Electrical conductivity Hall effect Localization Magnetotransport Phase diagrams Phase transitions

来源：评论

学校读者我要写书评

暂无评论

INTERPOLATING NEURAL NETWORK: A NOVEL UNIFICATION OF MACHINE LEARNING AND INTERPOLATION THEORY

arXiv

引用

arXiv 2024年

作者： Park, Chanwook Guo, Jiachen Xie, Xiaoyu Qian, Dong Wagner, Gregory J. Saha, Sourav Zhang, Hantao Bessa, Miguel A. Chen, Wei Cao, Jian Liu, Wing Kam Department of Mechanical Engineering Northwestern University EvanstonIL60208 United States Theoretical and Applied Mechanics Program Northwestern University EvanstonIL60208 United States Department of Mechanical Engineering University of Texas at Dallas RichardsonTX75080 United States Department of Aerospace and Ocean Engineering Virginia Polytechnic Institute State University BlacksburgVA24060 United States School of Engineering Brown University ProvidenceRI United States

Artificial intelligence (AI) has revolutionized software development, shifting from task-specific codes (Software 1.0) to neural network-based approaches (Software 2.0). However, applying this transition in engineering software presents challenges, including low surrogate model accuracy, the curse of dimensionality in inverse design, and rising complexity in physical simulations. We introduce an interpolating neural network (INN), grounded in numerical methods, to realize engineering Software 2.0 by advancing data training, partial differential equation solving, and parameter calibration. INN offers orders of magnitude fewer trainable/solvable parameters for comparable model accuracy than traditional multi-layer perceptron (MLP) or physics-informed neural networks (PINN). Demonstrated in metal additive manufacturing, INN rapidly constructs an accurate surrogate model of Laser Powder Bed Fusion (L-PBF) heat transfer simulation, achieving sub-10-micrometer resolution for a 10 mm path in under 15 minutes on a single GPU. This makes a transformative step forward across all domains essential to engineering software. Copyright © 2024, The Authors. All rights reserved.

关键词： Multilayer neural networks

来源：评论

学校读者我要写书评

暂无评论

Fracture propagation and induced strain response during supercritical CO_(2)jet fracturing

引用

Petroleum Science 2022年第4期19卷 1682-1699页

作者： Can Cai Bang-Run Li Yi-Yao Zhang Wen He Ying-Xin Yang Yong Kang Ji-Wei Wu School of Mechanical Engineering Southwest Petroleum UniversityChengdu610500SichuanP.R.China The State Key Laboratory of Oil&Gas Reservoir Geology and Exploitation Southwest Petroleum UniversityChengdu610500SichuanP.R.China Shu'nan Gas-Mine of Southwest Oil and Gas Field Company Luzhou646000SichuanP.R.China Hubei Key Laboratory of Waterjet Theory and New Technology Wuhan UniversityWuhan430072HubeiP.R.China School of Engineering and Applied Sciences and Department of Physics Harvard UniversityCambridge02138United States School of Mechanical Engineering Yangtze UniversityJingzhou434023HubeiP.R.China

To investigate fracture generation and strain variation during SC-CO_(2)(supercritical carbon dioxide)jet fracturing,the model of induced strain is established and the experiments are comprehensively *** influence factors are comprehensively explored,such as jet pressure,ambient pressure,*** the increasing jet pressure,the fracture morphology changes from parallel cracks to oblique *** the mass loss of specimen and CO_(2) absorption increase significantly,and the growth rate and minimum value of strain also rise *** a high ambient pressure of 8.0 MPa,the main fractures mostly propagated from the surface to the bottom surface of the *** maximum strain and the stable duration under higher ambient pressure are 1.5 times and 10 times,respectively,of the case under the ambient pressure of 5.0 *** comparison shows that the optimal jet distance is 5-7 times the nozzle diameter,resulting in massive mass loss,large CO_(2)absorption,and peak ***,the nonlinear variation of strain curve during jet pressurization is related to the type of rock and ambient *** studies clearly show the relationship between the fracture morphology and induced strain,which are crucial for SC-CO_(2)fracturing in shale gas reservoirs.

关键词： Supercritical carbon dioxide fracturing Jet fracturing Fracture morphology Strain variation

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：