Monika Vogler, Simon Krarup Steensen, Francisco Fernando Ramírez, Leon Merker, Jonas Busk, Johan Martin Carlsson, Laura Hannemose Rieger, Bojing Zhang, François Liot, Giovanni Pizzi, Felix Hanke, Eibar Flores, Hamidreza Hajiyani, Stefan Fuchs, Alexey Sanin, Miran Gaberšček, Ivano Eligio Castelli, Simon Clark, Tejs Vegge, Arghya Bhowmik, Helge Sören Stein
{"title":"Autonomous Battery Optimization by Deploying Distributed Experiments and Simulations","authors":"Monika Vogler, Simon Krarup Steensen, Francisco Fernando Ramírez, Leon Merker, Jonas Busk, Johan Martin Carlsson, Laura Hannemose Rieger, Bojing Zhang, François Liot, Giovanni Pizzi, Felix Hanke, Eibar Flores, Hamidreza Hajiyani, Stefan Fuchs, Alexey Sanin, Miran Gaberšček, Ivano Eligio Castelli, Simon Clark, Tejs Vegge, Arghya Bhowmik, Helge Sören Stein","doi":"10.1002/aenm.202403263","DOIUrl":null,"url":null,"abstract":"Non-trivial relationships link individual materials properties to device-level performance. Device optimization therefore calls for new automation approaches beyond the laboratory bench with tight integration of different research methods. This study demonstrates a Materials Acceleration Platform (MAP) in the field of battery research based on the problem-agnostic Fast INtention-Agnostic LEarning Server (FINALES) framework, which integrates simulations and physical experiments while leaving the active control of the hardware and software resources executing experiments or simulations with the partners running the respective units. This decentralization of control is a distinctive feature of MAPs using the FINALES framework. The connected capabilities entail the formulation and characterization of electrolytes, cell assembly and testing, early lifetime prediction, and ontology-mapped data storage provided by institutions distributed across Europe. The infrastructure is used to optimize the ionic conductivity of electrolytes and the End Of Life (EOL) of lithium-ion coin cells by varying the electrolyte formulation. Trends in ionic conductivity are rediscovered and the effect of the electrolyte formulation on the EOL is investigated. Further, the capability of this MAP to bridge diverse research modalities, scales, and institutions enabling system-level investigations under asynchronous conditions while handling concurrent workflows on the material- and system-level is shown, demonstrating true intention-agnosticism.","PeriodicalId":111,"journal":{"name":"Advanced Energy Materials","volume":null,"pages":null},"PeriodicalIF":24.4000,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Energy Materials","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1002/aenm.202403263","RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Non-trivial relationships link individual materials properties to device-level performance. Device optimization therefore calls for new automation approaches beyond the laboratory bench with tight integration of different research methods. This study demonstrates a Materials Acceleration Platform (MAP) in the field of battery research based on the problem-agnostic Fast INtention-Agnostic LEarning Server (FINALES) framework, which integrates simulations and physical experiments while leaving the active control of the hardware and software resources executing experiments or simulations with the partners running the respective units. This decentralization of control is a distinctive feature of MAPs using the FINALES framework. The connected capabilities entail the formulation and characterization of electrolytes, cell assembly and testing, early lifetime prediction, and ontology-mapped data storage provided by institutions distributed across Europe. The infrastructure is used to optimize the ionic conductivity of electrolytes and the End Of Life (EOL) of lithium-ion coin cells by varying the electrolyte formulation. Trends in ionic conductivity are rediscovered and the effect of the electrolyte formulation on the EOL is investigated. Further, the capability of this MAP to bridge diverse research modalities, scales, and institutions enabling system-level investigations under asynchronous conditions while handling concurrent workflows on the material- and system-level is shown, demonstrating true intention-agnosticism.
期刊介绍:
Established in 2011, Advanced Energy Materials is an international, interdisciplinary, English-language journal that focuses on materials used in energy harvesting, conversion, and storage. It is regarded as a top-quality journal alongside Advanced Materials, Advanced Functional Materials, and Small.
With a 2022 Impact Factor of 27.8, Advanced Energy Materials is considered a prime source for the best energy-related research. The journal covers a wide range of topics in energy-related research, including organic and inorganic photovoltaics, batteries and supercapacitors, fuel cells, hydrogen generation and storage, thermoelectrics, water splitting and photocatalysis, solar fuels and thermosolar power, magnetocalorics, and piezoelectronics.
The readership of Advanced Energy Materials includes materials scientists, chemists, physicists, and engineers in both academia and industry. The journal is indexed in various databases and collections, such as Advanced Technologies & Aerospace Database, FIZ Karlsruhe, INSPEC (IET), Science Citation Index Expanded, Technology Collection, and Web of Science, among others.