arrow
Return

Principles of the Battery Data Genome

delete2022-10-01
delete40
delete
OA
AI
L
Logan Ward
S
Susan Babinec *
E
Eric J. Dufek *
D
David A. Howey *
V
Venkatasubramanian Viswanathan *
M
Muratahan Aykol
D
David Beck
B
Blaiszik, Benjamin
B
Bor‐Rong Chen
G
G. W. Crabtree
S
Simon Clark
V
Valerio De Angelis
P
Philipp Dechent
M
Matthieu Dubarry
E
Erica Eggleton
D
Donal P. Finegan
I
Ian Foster
C
Chirranjeevi Balaji Gopal
P
Patrick K. Herring
V
Victor Waiman Hu
N
Noah H. Paulson
Y
Yuliya Preger
D
Dirk Uwe Sauer
K
Kandler Smith
S
Seth W. Snyder
S
Shashank Sripad
T
Tanvir R. Tanim
L
Linnette Teo
DOI:10.1016/j.joule.2022.08.008delete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
Batteries are central to modern society. They are no longer just a convenience but a critical enabler of the transition to a resilient, low-carbon economy. Battery development capabilities are provided by communities spanning materials discovery, battery chemistry and electrochemistry, cell and pack design, scale-up, manufacturing, and deployments. Despite their relative maturity, data-science practices among these diverse groups are far behind the state of the art in other fields, which have demonstrated an ability to significantly improve innovation and economic impact. The negative consequences of the present paradigm include incremental improvements but few breakthroughs, significant manufacturing uncertainties, and cascading investment risks that collectively slow deployments. The primary roadblock to a battery-data-science renaissance is the requirement for large amounts of high-quality data, which are not available in the current fragmented ecosystem. Here, we identify gaps and propose principles that enable the solution by building a robust community of data hubs with standardized practices and flexible sharing options that will seed advanced tools spanning innovation to deployment. Precedents are offered that demonstrate that both public good and immense economic gains will arise from sharing valuable battery data. The proposed Battery Data Genome looks to broadly transform innovations and revolutionize their translation from research to societal impact.
Keywords:
LITHIUM-ION BATTERIES
ENERGY-STORAGE
LIFETIME PREDICTION
COIN-CELL
RANGE
MODEL
SCIENCE
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Joule cover
Joule
IF:
35.4
Papers:
2.3K
Citations:
4.5W

Organization

T
toyota motor corporation
Scholars:
1.3K
Papers: 1.3K
Citations: 2
A
Argonne National Laboratory
Scholars:
1.1W
Papers: 9.2K
Citations: 3.8W
C
Carnegie Mellon University
Scholars:
1.4W
Papers: 1.4W
Citations: 2.7W
U
University of Illinois Chicago
Scholars:
1.7W
Papers: 1.4W
Citations: 3.0W
U
university of chicago
Scholars:
4.4W
Papers: 3.7W
Citations: 80
U
united states department of energy (doe)
Scholars:
11.2W
Papers: 9.6W
Citations: 246
University of Illinois System cover
University of Illinois System
Scholars:
6.8W
Papers: 6.1W
Citations: 644
U
university of oxford
Scholars:
9.6W
Papers: 8.5W
Citations: 137
S
SINTEF
Scholars:
3.5K
Papers: 4.0K
Citations: 1
researcher View more organizations