Literature DB >> 26263464

Accelerating Electrolyte Discovery for Energy Storage with High-Throughput Screening.

Lei Cheng1, Rajeev S Assary1, Xiaohui Qu2, Anubhav Jain2, Shyue Ping Ong3, Nav Nidhi Rajput2, Kristin Persson2, Larry A Curtiss1.   

Abstract

Computational screening techniques have been found to be an effective alternative to the trial and error of experimentation for discovery of new materials. With increased interest in development of advanced electrical energy storage systems, it is essential to find new electrolytes that function effectively. This Perspective reviews various methods for screening electrolytes and then describes a hierarchical computational scheme to screen multiple properties of advanced electrical energy storage electrolytes using high-throughput quantum chemical calculations. The approach effectively down-selects a large pool of candidates based on successive property evaluation. As an example, results of screening are presented for redox potentials, solvation energies, and structural changes of ∼1400 organic molecules for nonaqueous redox flow batteries. Importantly, on the basis of high-throughput screening, in silico design of suitable candidate molecules for synthesis and electrochemical testing can be achieved. We anticipate that the computational approach described in this Perspective coupled with experimentation will have a significant role to play in the discovery of materials for future energy needs.

Year:  2015        PMID: 26263464     DOI: 10.1021/jz502319n

Source DB:  PubMed          Journal:  J Phys Chem Lett        ISSN: 1948-7185            Impact factor:   6.475


  15 in total

Review 1.  Multidimensional materials and device architectures for future hybrid energy storage.

Authors:  Maria R Lukatskaya; Bruce Dunn; Yury Gogotsi
Journal:  Nat Commun       Date:  2016-09-07       Impact factor: 14.919

2.  Materials Genomics Screens for Adaptive Ion Transport Behavior by Redox-Switchable Microporous Polymer Membranes in Lithium-Sulfur Batteries.

Authors:  Ashleigh L Ward; Sean E Doris; Longjun Li; Mark A Hughes; Xiaohui Qu; Kristin A Persson; Brett A Helms
Journal:  ACS Cent Sci       Date:  2017-04-27       Impact factor: 14.553

3.  A general representation scheme for crystalline solids based on Voronoi-tessellation real feature values and atomic property data.

Authors:  Randy Jalem; Masanobu Nakayama; Yusuke Noda; Tam Le; Ichiro Takeuchi; Yoshitaka Tateyama; Hisatsugu Yamazaki
Journal:  Sci Technol Adv Mater       Date:  2018-03-19       Impact factor: 8.090

4.  Machine learning for the prediction of molecular dipole moments obtained by density functional theory.

Authors:  Florbela Pereira; João Aires-de-Sousa
Journal:  J Cheminform       Date:  2018-08-22       Impact factor: 5.514

5.  Comparison of computational chemistry methods for the discovery of quinone-based electroactive compounds for energy storage.

Authors:  Qi Zhang; Abhishek Khetan; Süleyman Er
Journal:  Sci Rep       Date:  2020-12-17       Impact factor: 4.379

6.  A quantitative evaluation of computational methods to accelerate the study of alloxazine-derived electroactive compounds for energy storage.

Authors:  Qi Zhang; Abhishek Khetan; Süleyman Er
Journal:  Sci Rep       Date:  2021-02-18       Impact factor: 4.379

7.  ChemSpaX: exploration of chemical space by automated functionalization of molecular scaffold.

Authors:  Adarsh V Kalikadien; Evgeny A Pidko; Vivek Sinha
Journal:  Digit Discov       Date:  2022-01-06

8.  SEI-forming electrolyte additives for lithium-ion batteries: development and benchmarking of computational approaches.

Authors:  Piotr Jankowski; Władysław Wieczorek; Patrik Johansson
Journal:  J Mol Model       Date:  2016-12-13       Impact factor: 1.810

9.  Substituent Pattern Effects on the Redox Potentials of Quinone-Based Active Materials for Aqueous Redox Flow Batteries.

Authors:  S Schwan; D Schröder; H A Wegner; J Janek; D Mollenhauer
Journal:  ChemSusChem       Date:  2020-09-23       Impact factor: 8.928

Review 10.  Self-Driving Laboratories for Development of New Functional Materials and Optimizing Known Reactions.

Authors:  Mikhail A Soldatov; Vera V Butova; Danil Pashkov; Maria A Butakova; Pavel V Medvedev; Andrey V Chernov; Alexander V Soldatov
Journal:  Nanomaterials (Basel)       Date:  2021-03-02       Impact factor: 5.076

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