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Computer simulations aid scientists in gauging battery performance

Computer simulations help scientists measure battery performance

Schematic of ionic migration in a sample intercalation host framework. The yellow spheres are the active ions (eg, Li, Na, Mg), while the other species that make up the structure are shown in blue and orange spheres. The inset shows the nominal change in potential energy as the ion migrates within the structure, with Em denoting the migration barrier. Credit: Reshma Devi

An important but poorly studied parameter that dictates battery performance is the migration barrier. It determines the speed of movement of ions in an electrode inside the battery, and finally the speed of charging or discharging it. Because it is difficult to measure the migration barrier in the lab, researchers usually use various computer simulations or approximations to quickly predict migration barrier values. However, few of these simulations have been experimentally verified so far.

In a new study, researchers at the Indian Institute of Science (IISc) and their colleagues comprehensively analyzed widely used computational techniques, and confirmed their predictions of migrations. barrier values ​​against actual data observed in lab measurements. Based on their analysis, the team proposed a set of robust guidelines to help researchers choose the most appropriate computational framework for testing materials that can be used to develop highly efficient batteries. in the future.

Lithium-ion batteries, which power mobile phones and laptops, consist of three major components: a solid negative electrode (anode), a solid positive electrode (cathode) and even a liquid or solid electrolyte that separates them. While charging or discharging, lithium ions migrate through the electrolyte, creating a potential difference. “The electrodes of lithium-ion batteries are not 100% solid. Think of them like a sponge. They have ‘pores’ through which a lithium ion must pass,” explained Sai Gautam Gopalakrishnan, Assistant Professor in the Department of Materials Engineering, IISc, and corresponding author of the paper published in npj Computational Materials.

An important parameter that determines the rate at which lithium ions penetrate these pores is the migration barrier-the energy threshold that the ions need to overcome crossing through the electrode. “The lower the migration barrier, the faster you can charge or discharge the battery,” says Reshma Devi, Ph.D. student in the Department of Materials Engineering and first author of the study.

“The same migration barrier value was calculated by one group using one computational technique and another group by using another technique. The values ​​may be equivalent, but we cannot know for sure,” explained Gopalakrishnan.

Two specific approximations, called Strongly Constrained and Approximately Normed (SCAN) and Generalized Gradient Approximation (GGA), are the most widely used methods to calculate the migration barrier, but each has its own limitations. disadvantage. “We took nine different materials,” explains Reshma Devi. “We check which of the estimates are closest to the experimental values ​​for each.”

The team found that the SCAN functional had better numerical accuracy overall, but the GGA calculation was faster. GGA has been found to have a reasonable degree of accuracy in calculating the migration barrier of some materials (such as lithium phosphate), and may be a better option when a quick estimate is needed, it is suggested of researchers.

Such insights could be valuable for scientists looking to test new materials for their performance before adapting them for battery-related applications, Gopalakrishnan said. “Suppose you have an unknown material and if you want to quickly see if this material is useful in your application, then you can use calculations to do that, if you know which calculation calculation gives you to the nearest values. It is useful when it comes. to the discovery of materials.”

The team is also working on developing machine learning tools that can help speed up predictions of migration barriers for different materials.

New strategy to perform fast charging of solid-state batteries

More information:
Reshma Devi et al, Effect of exchange-correlation functionals on the estimation of migration barriers in battery materials, npj Computational Materials (2022). DOI: 10.1038/s41524-022-00837-0

Given by the Indian Institute of Science

Citation: Computer simulations help scientists measure battery performance (2022, July 25) retrieved on July 25, 2022 from -gauging-battery.html

This document is subject to copyright. Except for any fair dealing for the purpose of private study or research, no part may be reproduced without written permission. Content is provided for informational purposes only.

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