TY - JOUR
T1 - Accelerating Battery Characterization Using Neutron and Synchrotron Techniques
T2 - Toward a Multi-Modal and Multi-Scale Standardized Experimental Workflow
AU - Atkins, Duncan
AU - Capria, Ennio
AU - Edström, Kristina
AU - Famprikis, Theodosios
AU - Grimaud, Alexis
AU - Jacquet, Quentin
AU - Johnson, Mark
AU - Matic, Aleksandar
AU - Wagemaker, Marnix
AU - More Authors, null
PY - 2021
Y1 - 2021
N2 - Li-ion batteries are the essential energy-storage building blocks of modern society. However, producing ultra-high electrochemical performance in safe and sustainable batteries for example, e-mobility, and portable and stationary applications, demands overcoming major technological challenges. Materials engineering and new chemistries are key aspects to achieving this objective, intimately linked to the use of advanced characterization techniques. In particular, operando investigations are currently attracting enormous interest. Synchrotron- and neutron-based bulk techniques are increasingly employed as they provide unique insights into the chemical, morphological, and structural changes inside electrodes and electrolytes across multiple length scales with high time/spatial resolutions. However, data acquisition, data analysis, and scientific outcomes must be accelerated to increase the overall benefits to the academic and industrial communities, requiring a paradigm shift beyond traditional single-shot, sophisticated experiments. Here a multi-scale and multi-technique integrated workflow is presented to enhance bulk characterization, based on standardized and automated data acquisition and analysis for high-throughput and high-fidelity experiments, the optimization of versatile and tunable cells, as well as multi-modal correlative characterization. Furthermore, new mechanisms, methods and organizations such as artificial intelligence-aided modeling-driven strategies, coordinated beamtime allocations, and community-unified infrastructures are discussed in order to highlight perspectives in battery research at large scale facilities.
AB - Li-ion batteries are the essential energy-storage building blocks of modern society. However, producing ultra-high electrochemical performance in safe and sustainable batteries for example, e-mobility, and portable and stationary applications, demands overcoming major technological challenges. Materials engineering and new chemistries are key aspects to achieving this objective, intimately linked to the use of advanced characterization techniques. In particular, operando investigations are currently attracting enormous interest. Synchrotron- and neutron-based bulk techniques are increasingly employed as they provide unique insights into the chemical, morphological, and structural changes inside electrodes and electrolytes across multiple length scales with high time/spatial resolutions. However, data acquisition, data analysis, and scientific outcomes must be accelerated to increase the overall benefits to the academic and industrial communities, requiring a paradigm shift beyond traditional single-shot, sophisticated experiments. Here a multi-scale and multi-technique integrated workflow is presented to enhance bulk characterization, based on standardized and automated data acquisition and analysis for high-throughput and high-fidelity experiments, the optimization of versatile and tunable cells, as well as multi-modal correlative characterization. Furthermore, new mechanisms, methods and organizations such as artificial intelligence-aided modeling-driven strategies, coordinated beamtime allocations, and community-unified infrastructures are discussed in order to highlight perspectives in battery research at large scale facilities.
KW - batteries
KW - experimental workflows
KW - neutron techniques
KW - operando characterization
KW - synchrotron techniques
UR - http://www.scopus.com/inward/record.url?scp=85121377396&partnerID=8YFLogxK
U2 - 10.1002/aenm.202102694
DO - 10.1002/aenm.202102694
M3 - Article
AN - SCOPUS:85121377396
SN - 1614-6832
VL - 12
JO - Advanced Energy Materials
JF - Advanced Energy Materials
IS - 17
M1 - 2102694
ER -