About

Log in?

DTU users get better search results including licensed content and discounts on order fees.

Anyone can log in and get personalized features such as favorites, tags and feeds.

Log in as DTU user Log in as non-DTU user No thanks

DTU Findit

Journal article

Accelerating Battery Characterization Using Neutron and Synchrotron Techniques: Toward a Multi‐Modal and Multi‐Scale Standardized Experimental Workflow

From

Institut Laue-Langevin1

Synchrotron Soleil2

European Synchrotron Radiation Facility3

Uppsala University4

Delft University of Technology5

Collège de France6

Université Grenoble Alpes7

Chalmers University of Technology8

Imaging and Structural Analysis, Department of Energy Conversion and Storage, Technical University of Denmark9

Department of Energy Conversion and Storage, Technical University of Denmark10

...and 0 more

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.

Language: English
Year: 2022
Pages: 2102694
ISSN: 16146840 and 16146832
Types: Journal article
DOI: 10.1002/aenm.202102694
ORCIDs: 0000-0003-2580-8439 and Norby, Poul

DTU users get better search results including licensed content and discounts on order fees.

Log in as DTU user

Access

Analysis