Literature by the same author
plus at Google Scholar

Bibliografische Daten exportieren
 

High-Entropy Energy Materials in the Age of Big Data : A Critical Guide to Next-Generation Synthesis and Applications

Title data

Wang, Qingsong ; Velasco, Leonardo ; Breitung, Ben ; Presser, Volker:
High-Entropy Energy Materials in the Age of Big Data : A Critical Guide to Next-Generation Synthesis and Applications.
In: Advanced Energy Materials. Vol. 11 (2021) Issue 47 . - 2102355.
ISSN 1614-6840
DOI: https://doi.org/10.1002/aenm.202102355

Official URL: Volltext

Project information

Project title:
Project's official title
Project's id
Nachwuchsgruppe Lehrstuhl für Anorganische Aktivmaterialien electrochemischer Speicher Dr. Qingsong Wang
No information

Abstract in another language

Abstract High-entropy materials (HEMs) with promising energy storage and conversion properties have recently attracted worldwide increasing research interest. Nevertheless, most research on the synthesis of HEMs focuses on a “trial and error” method without any guidance, which is very laborious and time-consuming. This review aims to provide an instructive approach to searching and developing new high-entropy energy materials in a much more efficient way. Toward materials design for future technologies, a fundamental understanding of the process/structure/property/performance linkage on an atomistic level will promote prescreening and selection of material candidates. With the help of computational material science, in which the fast development of computational capabilities that have a rapidly growing impact on new materials design, this fundamental understanding can be approached. Furthermore, high-throughput experimental methods, enabled by the advances in instrumentation and electronics, will accelerate the production of large quantities of results and stimulate the identification of the target products, adding knowledge in computational design. This review shows that combining computational preselection and verification by high-throughput can be an efficient approach to unveil the complexities of HEMs and design novel HEMs with enhanced properties for energy-related applications.

Further data

Item Type: Article in a journal
Refereed: Yes
Keywords: computational design; high-entropy materials; high-throughput; trial and error
Institutions of the University: Faculties > Faculty of Biology, Chemistry and Earth Sciences
Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Chemistry
Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Chemistry > Lehrstuhl Anorganische Aktivmaterialien für elektrochemische Energiespeicher
Research Institutions > Central research institutes > Bayerisches Zentrum für Batterietechnik - BayBatt
Faculties
Research Institutions
Research Institutions > Central research institutes
Result of work at the UBT: No
DDC Subjects: 500 Science
500 Science > 540 Chemistry
600 Technology, medicine, applied sciences > 620 Engineering
Date Deposited: 02 Nov 2022 09:25
Last Modified: 24 Oct 2023 12:28
URI: https://eref.uni-bayreuth.de/id/eprint/72593