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High-Throughput Experimentation and Computational Freeway Lanes for Accelerated Battery Electrolyte and Interface Development Research

Benayad, A.; Diddens, D.; Heuer, A.; Krishnamoorthy, A. N.; Maiti, M.; Cras, F. L.; Legallais, M.; Rahmanian, F.; Shin, Y.; Stein, H. ORCID iD icon; Winter, M.; Wölke, C.; Yan, P.; Cekic-Laskovic, I.


The timely arrival of novel materials plays a key role in bringing advances to society, as the pace at which major technological breakthroughs take place is usually dictated by the discovery rate at which novel materials are identified within chemical space. High-throughput experimentation and computation strategy, now widely considered as a watershed in accelerating the discovery and optimization of novel materials in virtually every field, enables simultaneous screening, synthesis and characterization of large arrays of different material classes toward identification of the lead candidates for given system and targeted application. However, the ability to acquire data, through the continued advancement of automation platforms and workflows especially in the field of battery research and development, often outpaces the ability to optimally leverage obtained data for improved decision-making. Closing this gap inevitably calls for adapted algorithms, development of reliable predictive models and enhanced integration with machine learning, deep learning, and artificial intelligence. This Review aims to highlight state-of-the-art achievements along with an assessment of current and future challenges as well as resulting perspectives toward accelerated development of advanced battery electrolytes and their interfaces.

Verlagsausgabe §
DOI: 10.5445/IR/1000140462
Veröffentlicht am 02.12.2021
DOI: 10.1002/aenm.202102678
Zitationen: 50
Web of Science
Zitationen: 52
Zitationen: 57
Cover der Publikation
Zugehörige Institution(en) am KIT Helmholtz-Institut Ulm (HIU)
Institut für Physikalische Chemie (IPC)
Post Lithium Storage (POLiS)
Publikationstyp Zeitschriftenaufsatz
Publikationsdatum 05.05.2022
Sprache Englisch
Identifikator ISSN: 1614-6832, 1614-6840
KITopen-ID: 1000140462
HGF-Programm 38.02.01 (POF IV, LK 01) Fundamentals and Materials
Erschienen in Advanced Energy Materials
Verlag Wiley-VCH Verlag
Band 12
Heft 17
Seiten Art.Nr.: 2102678
Bemerkung zur Veröffentlichung Special Issue: Advanced Battery Materials ‐ Battery2030+
Vorab online veröffentlicht am 09.11.2021
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