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Data · dataset · 2026

SuperBand: Superconductor's energy band

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In comparison to simpler data such as chemical formulas and lattice structures, energy band structure data provide a more fundamental and intuitive insight into superconducting phenomena.

Description

In this work, we generate superconductor's lattice structure files optimized for density functional theory (DFT) calculations. Through DFT, we obtain key electronic properties for experimentally confirmed superconductors, including band structures, density of states (DOS), and Fermi surface data.

Additionally, we outline efficient methodologies for acquiring structural data, establish high-throughput DFT computational protocols, and introduce tools for extracting this data from large-scale DFT calculations. As an example, we have curated a dataset containing information on 2474 superconductors along with their experimentally determined superconducting transition temperatures (Tc), which is well-suited for machine learning applications.

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This work also provides guidelines for accessing and utilizing this dataset. Furthermore, we present a neural network model designed for training with this data. All the aforementioned data and code are publicly available at superband.work.

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Where it is published

Catalogue records · 1

Topics

Inferred from text
Density functional theory 75%
Provenance · 1 source records, 10 field assertions
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ScienceDB10.57760/sciencedb.1672811 d agoJSON v1
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