From 80ae12ddf745966a91f070acc5e89745a515a410 Mon Sep 17 00:00:00 2001 From: YB_HU <138468445+RussellHu41@users.noreply.github.com> Date: Mon, 23 Dec 2024 19:04:08 +0800 Subject: [PATCH] Update GPUMD&NEP_06_12_2024.md --- source/_posts/GPUMD&NEP_06_12_2024.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/source/_posts/GPUMD&NEP_06_12_2024.md b/source/_posts/GPUMD&NEP_06_12_2024.md index 440b757..48f4b9c 100644 --- a/source/_posts/GPUMD&NEP_06_12_2024.md +++ b/source/_posts/GPUMD&NEP_06_12_2024.md @@ -9,6 +9,8 @@ GPUMD is an efficient domestic molecular dynamics simulation software developed In June 2024, GPUMD&NEP joined the DeepModeling community. As an innovative and highly efficient MD simulation and machine learning potential function tool, it further provides support for the Materials Genome Project and the AI4S community. + + ## Introduction In recent years, all-solid-state lithium-ion batteries have attracted much attention due to their high safety and high energy density. As a solid-state electrolyte material with high ionic conductivity and stability, Li7La3Zr2O12 (LLZO) is particularly remarkable. However, there is a significant difference between the theoretically predicted activation energy (about 1.2 eV) and the experimentally measured value (about 0.45 eV) for lithium-ion migration in the tetragonal phase LLZO. This contradiction limits the in-depth understanding and optimization of the material's performance.