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Slurry Design for a Low Cost, High Capacity Magnesium Semi-Solid Flow Battery

ECS Meeting Abstracts 2020年第2期MA2020-02卷

作者： Matt McPhail Rajan Kumar Vivek Subramanian Dept. of Electrical Engineering and Computer Sciences UC Berkeley Dept. of Materials Science and Engineering Stanford University Dept. of Microengineering École polytechnique fédérale de Lausanne

Semi solid flow batteries (SSFB) are developed by forming suspensions of electrochemically active and conductive particles for use as an anolyte or catholyte in a redox flow battery. By utilizing micron-scale powders from mature battery chemistries in a flowable suspension, the benefits of energy-dense intercalation chemistries with the scalability of flow battery architectures can be combined for low cost electrochemical storage. Presently, a narrow set of materials has been explored, focusing on chemistries with a lithium anode. In this work, a magnesium SSFB with an optimized MoS2 cathodic slurry is demonstrated as a low cost, high material abundance alternative to lithium-based chemistries. A mixed ionic-electronic conductive network is designed around a dual-ion (Mg, Li) electrolyte, by combining the all-phenyl complex (APC) + LiCl, MoS2, and ketjen black (KB) to form the cathodic slurry. The rheological, electrical, and electrochemical properties of MoS2-KB-APC slurries with varying compositions have been measured. Full cells, with a Mg foil anode and MoS2 slurry cathode, are shown to cycle reversibly for 20 cycles at C/5 in a non-flowing configuration, reaching 180 mAh/g discharge capacity. LiCl concentration and KB concentration are identified as critical to high capacity slurry cathodes. The relative impacts of Mg and Li ions are quantitatively analyzed, showing that both ions are reversibly intercalated during cycling. Finally, a custom flow cell is used to demonstrate 120 mAh/g discharge capacity at C/8, highlighting the flowable nature of the cathode suspension. This work provides experimental data and insight into how existing low cost material sets can be utilized in a semi solid flow battery architecture. Figure 1

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Single-Trial EEG Predicts Memory Retrieval Using Leave-One-Subject-Out Classification

Single-Trial EEG Predicts Memory Retrieval Using Leave-One-S...

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2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018

作者： Liao, Kueida Mollison, Matthew V. Curran, Tim Sa, Virginia R. De Dept. of Electrical and Computer Engineering UC San Diego San DiegoCA United States Dept. of Psychology and Neuroscience University of Colorado Boulder BoulderCO United States Dept. of Cognitive Science UC San Diego San DiegoCA United States

ISBN: (纸本)9781538654880

In this study, we perform single-trial EEG classification in memory retrieval predictions using classifiers trained on a leave-one-subject-out (LOSO) cross-validation basis. We also compare the performance to that of classification using leave-one-trial-out (LOTO) when trained on data for an individual subject. Unlike traditional single-trial EEG analysis performed within an individual subject, we show that it is possible to perform single-trial EEG classification using classifiers trained on different subjects leading the way to more general classifiers for brain-computer interface (BCI) applicable to first-time BCI users. © 2018 IEEE.

关键词： Brain computer interface

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Design, development and evaluation of an open source gateway for the SmartFarm decision support system

Design, development and evaluation of an open source gateway...

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ASABE 2018 Annual International Meeting

作者： Fink, Caleb Liu, Bo Easton, Fletcher Krintz, Chandra Wolski, Rich Sethuramasamyraja, Balaji BioResource and Agricultural Engineering Cal Poly San Luis Obispo United States Computer Science Dept. UC Santa Barbara United States Agronomy and Precision Ag CSU Fresno United States

The purpose of this research is to design, develop and evaluate an open source gateway for the SmartFarm open source decision support system in improving agricultural stewardship, environmental conservation, and providing a system that is solely owned by the farmer. There are very limited options for an open source gateway for collecting on farm data that the farmer owns and sending it to the cloud. The options available are: expensive, require professional maintenance, are not portable between systems, improvements are made only by the manufacturer, limited in customization options, difficult to operate, and data is owned by the company rather than the farmer. The gateway is designed to send data to the cloud from remote SmartFarm Data Acquisition (DAQ) nodes, collect measurement data from remote SmartFarm DAQ nodes, provide a means of wirelessly programming remote SmartFarm DAQ nodes, and a tool that provides data analysis and insight from remote SmartFarm DAQ nodes. It is evaluated to work with 900MHz radios, SmartFarm DAQ nodes, and costs $35. Its setup takes 4 steps and ~20 minutes installation time, does not require maintenance, can utilize Wi-Fi, Bluetooth, and other wireless protocols, and software can port to other systems. The method of evaluation is quantitative. The gateway measured for data rate of 93.4Mbit/s internet upload speed, passing a range of 252 to 1592 bytes of data from a remote node to the cloud, consumes 2.8 Watts, software efficiency is 25% CPU usage, measurement efficiency is 1 message every 15 seconds, data analysis can be accomplished with the cloud service tool, and it can wirelessly program remote DAQ nodes. © 2018 American Society of Agricultural and Biological Engineers. All rights reserved.

关键词： Precision agriculture

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Development and evaluation of using a mobile application as a demonstration tool for outreach to inform and educate farmers, academia, and the community of agricultural stewardship using the SmartFarm decision support system

Development and evaluation of using a mobile application as ...

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ASABE 2018 Annual International Meeting

Agricultural stewardship is the careful utilization of agricultural and natural resources to prevent depletion. Development and use of a smart device mobile application educates schools, farmers, and the community about farm stewardship and environmental conservation on the farm. The goal is educating farmers, academia, and community members, of farming sustainably today, and for the future. People are equipped with smartphones and tablets, whether in the classroom, on the farm, downtown in the office, or anywhere they go. With these devices available, a mobile app can be utilized to encourage and foster agricultural stewardship and sustainable farming. A fact of life is people need food to live, and to continue to produce the amount of food needed to feed all people, sustainable farming practices are needed. A mobile application is developed and is used to teach academia, farmers, and community members about sustainable farming and stewardship practices. The app is used as a tool to aid people in farming sustainably, teaching agricultural stewardship, and teaching environmental conservation. The app is evaluated with adaptation of 85.1%, frequency of use at 0.12 respondents/minute, and 22 respondents said they find the SmartFarm DSS as beneficial. © 2018 American Society of Agricultural and Biological Engineers. All rights reserved.

关键词： Decision support systems

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Sparsity preserving discretization with error bounds

arXiv

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arXiv 2019年

作者： Anderson, James Matni, Nikolai Chen, Yuxiao Department of Computing + Mathematical Sciences California Institute of Technology PasadenaCA91125 United States Department of Mechanical and Civil Engineering California Institute of Technology PasadenaCA91125 United States Department of Electrical Engineering and Computer Science UC Berkeley CA94709 United States

Typically when designing distributed controllers it is assumed that the state-space model of the plant consists of sparse matrices. However, in the discrete-time setting, if one begins with a continuous-time model, the discretization process annihilates any sparsity in the model. In this work we propose a discretization procedure that maintains the sparsity of the continuous-time model. We show that this discretization out-performs a simple truncation method in terms of its ability to approximate the "ground truth" model. Leveraging results from numerical analysis we are also able to upper-bound the error between the dense discretization and our method. Furthermore, we show that in a robust control setting we can design a distributed controller on the approximate (sparse) model that stabilizes the dense ground truth model. Copyright © 2019, The Authors. All rights reserved.

关键词： State space methods

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Accuracy-resource tradeoff for edge devices in Internet of Things

Accuracy-resource tradeoff for edge devices in Internet of T...

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2017 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2017

作者： Mousavi, Nima Aksanli, Baris Akyurek, Alper Sinan Rosing, Tajana Šimunic Electrical and Computer Engineering UC San Diego United States Computer Science and Engineering UC San Diego United States

ISBN: (纸本)9781509043385

Modern power grid has evolved from a passive network into an application of Internet of Things with numerous interconnected elements and users. In this environment, household users greatly benefit from a prediction algorithm that estimates their future power demand to help them control off-grid generation, battery storage, and power consumption. In particular, household power consumption prediction plays a pivotal role in optimal utilization of batteries used alongside photovoltaic generation, creating saving opportunities for users. Since edge devices in Internet of Things offer limited capabilities, the computational complexity and memory and energy consumption of the prediction algorithms are capped. In this paper we forecast 24-hour demand from power consumption, weather, and time data, using Support Vector Regression models, and compare it to state-of-the-art prediction methods such as Linear Regression and persistence. We use power consumption traces from real datasets and a Raspberry Pi 3 embedded computer as testbed to evaluate the resource-accuracy trade-off. Our study reveals that Support Vector Regression is able to achieve 21% less prediction error on average compared to Linear Regression, which translates into 16% more cost savings for users when using residential batteries with photovoltaic generation. © 2017 IEEE.

关键词： Electric power utilization

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CEPC Technical Design Report

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Radiation Detection Technology and Methods 2024年第1期8卷 I0003-I0016,1-1091页

作者： Waleed Abdallah Tiago Carlos Adorno de Freitas Konstantin Afanaciev Shakeel Ahmad Ijaz Ahmed Xiaocong Ai Abid Aleem Wolfgang Altmannshofer Fabio Alves Weiming An Rui An Daniele Paolo Anderle Stefan Antusch Yasuo Arai Andrej Arbuzov Abdesslam Arhrib Mustafa Ashry Sha Bai Yu Bai Yang Bai Vipul Bairathi Csaba Balazs Philip Bambade Yong Ban Tripamo Bandyopadhyay Shou-Shan Bao Desmond P.Barber Ayse Bat Varvara Batozskaya Subash Chandra Behera Alexander Belyaev Michele Bertucci Xiao-Jun Bi Yuanjie Bi Tianjian Bian Fabrizio Bianchi Thomas Biekotter Michela Biglietti Shalva Bilanishvili Deng Binglin Denis Bodrov Anton Bogomyagkov Serge Bondarenko Stewart Boogert Maarten Boonekamp Marcello Borri Angelo Bosotti Vincent Boudry Mohammed Boukidi Igor Boyko Ivanka Bozovic Giuseppe Bozzi Jean-Claude Brient Anastasiia Budzinskaya Masroor Bukhari Vladimir Bytev Giacomo Cacciapaglia Hua Cai Wenyong Cai Wujun Cai Yijian Cai Yizhou Cai Yuchen Cai Haiying Cai Huacheng Cai Lorenzo Calibbi Junsong Cang Guofu Cao Jianshe Cao Antoine Chance Xuejun Chang Yue Chang Zhe Chang Xinyuan Chang Wei Chao Auttakit Chatrabhuti Yimin Che Yuzhi Che Bin Chen Danping Chen Fuqing Chen Fusan Chen Gang Chen Guoming Chen Hua-Xing Chen Huirun Chen Jinhui Chen Ji-Yuan Chen Kai Chen Mali Chen Mingjun Chen Mingshui Chen Ning Chen Shanhong Chen Shanzhen Chen Shao-Long Chen Shaomin Chen Shiqiang Chen Tianlu Chen Wei Chen Xiang Chen Xiaoyu Chen Xin Chen Xun Chen Xurong Chen Ye Chen Ying Chen Yukai Chen Zelin Chen Zilin Chen Gang Chen Boping Chen Chunhui Chen Hok Chuen Cheng Huajie Cheng Shan Cheng Tongguang Cheng Yunlong Chi Pietro Chimenti Wen Han Chiu Guk Cho Ming-Chung Chu Xiaotong Chu Ziliang Chu Guglielmo Coloretti Andreas Crivellin Hanhua Cui Xiaohao Cui Zhaoyuan Cui Brunella D'Anzi Ling-Yun Dai Xinchen Dai Xuwen Dai Antonio De Maria Nicola De Filippis Christophe De La Taille Francesca De Mori Chiara De Sio Elisa Del Core Shuangxue Deng Wei-Tian Deng Zhi Deng Ziyan Deng Bhupal Dev Tang Dewen Biagio Di Micco Ran Ding Siqin Dingl Yadong Ding Haiyi Dong Jianin AGH University of Science and Technology Faculty of Physics and Applied Computer ScienceKrakow Anhui University HefeiAnhui Applied Physics Department Federal Urdu University of ArtsScience and TechnologyIslamabad Banaras Hindu University Institute of ScienceVaranasi Bandirma Onyedi Eylul University Bandirma Beihang University Beijing Beijing Computational Science Research Center Beijing Beijing Conveyi LTD Beijing Beijing Glass Research Institute Co. LtdBeijing Beijing Institute of Technology Beijing Beijing Normal University Beijing Brown University ProvidenceRI Budker Institute of Nuclear Physics Novosibirsk Cadi Ayyad University Laboratory of Fundamental and Applied PhysicsPolydisciplinary FacultyMarrakech Cairo University Giza Center for Theory and Computation National Tsing Hua UniversityHsinchu Central China Normal University WuhanHubei Central South University ChangshaHunan Centro de Fisica Teorica de Particulas Universidade Tecnica de LisboaLisboa Chengdu KaitengSifang Digital Radio&TV Equipment Co. LtdChengduSichuan China academy of engineering physics MianyangSichuan China building materials academy Beijing China Center of Advanced Science and Technology Beijing China Institute of Atomic Energy Beijing China Jiliang University HangzhouZhejiang China Nuclear Instrument CO. LTDBeijing China University of Geosciences Beijing China University of Geosciences WuhanHubei China University of Mining and Technology XuzhouJiangsu China West Normal University NanchongSichuan Chongqing University Department of PhysicsChongqing Chulalongkorn University Bangkok City University of Hong Kong Department of PhysicsHong Kong Cockcroft Institute Daresbury Cornell University IthacaNY CPPM(AMU/IPhU&CNRS/INP) Marseille Dalian Minzu University DalianLiaoning Dalian University of Technology Department of PhysicsDalian Deutsches Elektronen-Synchrotron DESY Hamburg Dzhelepov Laboratory of Nuclear Problems of Joint Institute for Nuclear Research(DLNP JINR) Dubna East China University Of Science And Technol

The Circular Electron Positron Collider(CEPC)is a large scientific project initiated and hosted by China,fostered through extensive collaboration with international *** complex comprises four accelerators:a 30 GeV Linac,a 1.1 GeV Damping Ring,a Booster capable of achieving energies up to 180 GeV,and a Collider operating at varying energy modes(Z,W,H,and tt).The Linac and Damping Ring are situated on the surface,while the subterranean Booster and Collider are housed in a 100 km circumference underground tunnel,strategically accommodating future expansion with provisions for a potential Super Proton Proton Collider(SPPC).The CEPC primarily serves as a Higgs *** its baseline design with synchrotron radiation(SR)power of 30 MW per beam,it can achieve a luminosity of 5×10^(34)cm^(-2)s^(-1)per interaction point(IP),resulting in an integrated luminosity of 13 ab^(-1)for two IPs over a decade,producing 2.6 million Higgs *** the SR power to 50 MW per beam expands the CEPC's capability to generate 4.3 million Higgs bosons,facilitating precise measurements of Higgs coupling at sub-percent levels,exceeding the precision expected from the HL-LHC by an order of *** Technical Design Report(TDR)follows the Preliminary Conceptual Design Report(Pre-CDR,2015)and the Conceptual Design Report(CDR,2018),comprehensively detailing the machine's layout,performance metrics,physical design and analysis,technical systems design,R&D and prototyping efforts,and associated civil engineering ***,it includes a cost estimate and a preliminary construction timeline,establishing a framework for forthcoming engineering design phase and site selection *** is anticipated to begin around 2027-2028,pending government approval,with an estimated duration of 8 *** commencement of experiments and data collection could potentially be initiated in the mid-2030s.

关键词： initiated exceeding precise

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Decomposed structured subsets for semidefinite and sum-of-squares optimization

arXiv

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arXiv 2019年

作者： Miller, Jared Zheng, Yang Sznaier, Mario Papachristodoulou, Antonis The ECE Department Northeastern University BostonMA02115 United States The Department of Electrical and Computer Engineering UC San Diego San DiegoCA92093 United States The Department of Engineering Science University of Oxford OxfordOX1 3PJ United Kingdom

Semidefinite programs (SDPs) are standard convex problems that are frequently found in control and optimization applications. Interior-point methods can solve SDPs in polynomial time up to arbitrary accuracy, but scale poorly as the size of matrix variables and the number of constraints increases. To improve scalability, SDPs can be approximated with lower and upper bounds through the use of structured subsets (e.g., diagonally-dominant and scaled-diagonally dominant matrices). Meanwhile, any underlying sparsity or symmetry structure may be leveraged to form an equivalent SDP with smaller positive semidefinite constraints. In this paper, we present a notion of decomposed structured subsets to approximate an SDP with structured subsets after an equivalent conversion. The lower/upper bounds found by approximation after conversion become tighter than the bounds obtained by approximating the original SDP directly. We apply decomposed structured subsets to semidefinite and sum-of-squares optimization problems with examples of H∞ norm estimation and constrained polynomial optimization. An existing basis pursuit method is adapted into this framework to iteratively refine bounds. Copyright © 2019, The Authors. All rights reserved.

关键词： Iterative methods

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Towards optimal estimation of bivariate isotonic matrices with unknown permutations

arXiv

引用

arXiv 2018年

作者： Mao, Cheng Pananjady, Ashwin Wainwright, Martin J. Department of Statistics and Data Science Yale University Department of Electrical Engineering and Computer Sciences UC Berkeley Department of Statistics UC Berkeley

Many applications, including rank aggregation, crowd-labeling, and graphon estimation, can be modeled in terms of a bivariate isotonic matrix with unknown permutations acting on its rows and columns. We consider the problem of estimating such a matrix based on noisy observations of a subset of its entries, and design and analyze polynomial-time algorithms that improve upon the state of the art. In particular, our results imply that any such n×n matrix can be estimated efficiently in the normalized, squared Frobenius norm at rate e O(n-3=4), thus narrowing the gap between e O(n-1) and e O(n-1=2), hitherto the rates of the most statistically and computationally efficient methods, respectively. Additionally, our algorithms are minimax optimal in another natural metric that measures how well an estimate captures each row of the matrix. Along the way, we prove matching upper and lower bounds on the minimax radii of certain cone testing problems, which may be of independent interest. Copyright © 2018, The Authors. All rights reserved.

关键词： Polynomial approximation

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Efficient and Safe Exploration in Deterministic Markov Decision Processes with Unknown Transition Models

Efficient and Safe Exploration in Deterministic Markov Decis...

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American Control Conference

作者： Erdem Biyik Jonathan Margoliash Shahrouz Ryan Alimo Dorsa Sadigh Electrical Engineering Stanford University CA 94305 United States UC San Diego Jacobs School of Engineering United States CA 92093 Jet Propulsion Laboratory California Institute of Technology CA 91109 United States Computer Science Stanford University CA 94305 United States

ISBN: (纸本)9781538679012;9781538679265

We propose a safe exploration algorithm for deterministic Markov Decision Processes with unknown transition models. Our algorithm guarantees safety by leveraging Lipschitz-continuity to ensure that no unsafe states are visited during exploration. Unlike many other existing techniques, the provided safety guarantee is deterministic. Our algorithm is optimized to reduce the number of actions needed for exploring the safe space. We demonstrate the performance of our algorithm in comparison with baseline methods in simulation on navigation tasks.

关键词： Markov chain algorithms Exploration deterministic Task navigation baseline method Unknown Safes space escape

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