Mistry, A., Verma, A., Sripad, S., Ciez, R., Sulzer, V., Brosa Planella, F., … Viswanathan, V. (2021). A Minimal Information Set To Enable Verifiable Theoretical Battery Research. ACS Energy Letters, 3831–3835. doi:10.1021/acsenergylett.1c01710
Abstract:
Batteries are an enabling technology for addressing sustainability through the electrification of various forms of transportation and grid storage. Batteries are truly multi-scale, multi-physics devices, and accordingly various theoretical descriptions exist to understand their behavior ranging from atomistic details to techno-economic trends. As we explore advanced battery chemistries or previously inaccessible aspects of existing ones, new theories are required to drive decisions. 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. This checklist covers all flavors of theoretical battery research, ranging from atomic/molecular calculations to mesoscale and continuum-scale interactions, and techno-economic analysis. Also, as more and more experimental studies analyze raw data, we feel this checklist would be broadly relevant.
License type:
Publisher Copyright
Funding Info:
This research / project is supported by the Agency for Science, Technology and Research (A*STAR) - Career Development Fund (CDF)
Grant Reference no. : C210112037