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OCV intercalation workflow implemented across DFT and workflow engines

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DataCite Commons2026-03-12 更新2026-05-04 收录
下载链接:
https://archive.materialscloud.org/doi/10.24435/materialscloud:hk-ac
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Dataset: Interoperable DFT OCV Workflows (Final Alignment) We present a dataset enabling cross‑engine alignment and reproducibility of open‑circuit voltage (OCV) calculations for battery cathode materials within standardized density functional theory (DFT) workflows. The dataset implements a common, JSON‑based input/output schema and a semantic JSON‑LD description to express the workflow’s scientific intent, inputs, methods, and outputs in a code‑agnostic manner, supporting FAIR reuse. Using shared OPTIMADE‑style input structures, we execute an identical OCV protocol across multiple workflow managers and DFT engines (VASP via PerQueue and SimStack, GPAW, Quantum ESPRESSO, and CASTEP). Engine‑specific archives provide standardized output JSON files for cross‑comparison, and, where available, native files to enable full reproduction. We focus on five representative cathode chemistries (Li2Mn3NiO8, LiCoO2, LiTiS2, LiFePO4, and MgMo3S4), chosen to probe diverse structural and electronic regimes. The dataset documents strong cross‑engine agreement for average OCVs derived from pristine charged/discharged cells, and highlights where alignment is challenging, notably for vacancy‑containing supercells at low/high states of charge due to sensitivity to smearing, symmetry breaking, and optimization procedures. By releasing harmonized inputs, standardized outputs, and semantic metadata, this work provides a practical resource for benchmarking interoperable DFT workflows, facilitates transparent comparison across codes, and supports reproducible studies and future extensions (e.g., spin polarization and Hubbard corrections) in high‑throughput materials discovery.
提供机构:
Materials Cloud
创建时间:
2026-01-20
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