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A Minimal Information Set To Enable Verifiable Theoretical Battery Research

  • Aashutosh Mistry
  • , Ankit Verma
  • , Shashank Sripad
  • , Rebecca Ciez
  • , Valentin Sulzer
  • , Ferran Brosa Planella
  • , Robert Timms
  • , Yumin Zhang
  • , Rachel Kurchin
  • , Philipp Dechent
  • , Weihan Li
  • , Samuel Greenbank
  • , Zeeshan Ahmad
  • , Dilip Krishnamurthy
  • , Alexis Fenton Jr.
  • , Kevin Tenny
  • , Prehit Patel
  • , Daniel Juarez Robles
  • , Paul Gasper
  • , Andrew Colclasure
  • Artem Baskin, Corinne Scown, Venkat Subramanian, Edwin Khoo, Srikanth Allu, David Howey, Steven Decaluwe, Scott Roberts, Venkatasubramanian Viswanathan
  • Argonne National Laboratory
  • Carnegie Mellon University
  • Purdue University
  • University of Warwick
  • University of Oxford
  • RWTH Aachen University
  • Massachusetts Institute of Technology
  • University of Alabama in Huntsville
  • NASA Ames Research Center
  • Lawrence Berkeley National Laboratory
  • University of Texas at Austin
  • Agency for Science, Technology and Research, Singapore
  • Oak Ridge National Laboratory
  • Colorado School of Mines
  • Sandia National Laboratories

Research output: Contribution to journal › Article › peer-review

25 Scopus Citations

Abstract

Batteries are an enabling technology for addressing sustainability through the electrification of various forms of transportation (1) and grid storage. (2) Batteries are truly multi-scale, multi-physics devices, and accordingly various theoretical descriptions exist to understand their behavior (3-5) ranging from atomistic details to techno-economic trends. As we explore advanced battery chemistries (6,7) or previously inaccessible aspects of existing ones, (8-10) new theories are required to drive decisions. (11-13) The decisions are influenced by the limitations of the underlying theory. Advanced theories used to understand battery phenomena are complicated and require substantial effort to reproduce. However, such constraints should not limit the insights from these theories. We can strive to make the theoretical research verifiable such that any battery stakeholder can assess the veracity of new theories, sophisticated simulations or elaborate analyses. We distinguish verifiability, which amounts to "Can I trust the results, conclusions and insights and identify the context where they are relevant?", from reproducibility, which ensures "Would I get the same results if I followed the same steps?" With this motivation, we propose a checklist to guide future reports of theoretical battery research in Table 1. We hereafter discuss our thoughts leading to this and how it helps to consistently document necessary details while allowing complete freedom for creativity of individual researchers. Given the differences between experimental and theoretical studies, the proposed checklist differs from its experimental counterparts. (14,15) This checklist covers all flavors of theoretical battery research, ranging from atomic/molecular calculations (16-19) to mesoscale (20,21) and continuum-scale interactions, (9,22) and techno-economic analysis. (23,24) Also, as more and more experimental studies analyze raw data, (25) we feel this checklist would be broadly relevant.
Original languageAmerican English
Pages (from-to)3831-3835
Number of pages5
JournalACS Energy Letters
Volume6
Issue number11
DOIs
StatePublished - 12 Nov 2021

NLR Publication Number

  • NREL/JA-5700-80730

Keywords

  • equations
  • Li-ion battery
  • modeling
  • parameters
  • sensitivity
  • theory

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