Skip to content
DraconiticResearch
Search Sources API
201,683 studies31 sourcesUpdated 36 min ago
Peer-reviewedCC BY 4.0Inorganics

Reproducibility of Thermodynamic Stability and Band-Gap Screening of Inorganic Materials Across Materials Project Versions

  1. 1Intelligent Manufacturing School, Jilin Tiedao University, Jilin 132299, China
  2. 2School of Energy and Mechanical Engineering, Dezhou University, Dezhou 253023, China

Abstract

High-throughput computational databases have become central to the discovery and screening of inorganic materials, yet the reproducibility of candidate selection across database versions has rarely been quantified. Here, a frozen 2018 Materials Project snapshot was harmonized with database version 2026.04.13 to evaluate the cross-version stability of thermodynamic and electronic screening. Among 78,756 historical mp-* records in the primary longitudinal cohort, 76,931 remained traceable (97.68%). Despite high cross-version property rank agreement, screening reversal rates ranged from 1.2% to 8.1% across the 16 combined threshold pairs. Under the representative criterion Ehull ≤ 0.05 eV·atom−1 and Eg ≥ 2 eV, 15,754 materials were selected in 2018 and 14,191 in 2026; 1818 original candidates exited and 255 entered, corresponding to 88.46% candidate retention and a Jaccard similarity of 0.871. Instability was concentrated near decision boundaries and remained chemically structured after multivariable adjustment. Cl-, Br-, and N-containing materials were dominated by energy-above-hull threshold crossings, whereas the 3d-series metal group showed a larger contribution from band-gap changes. These results distinguish property reproducibility from decision reproducibility: strong cross-version property agreement does not guarantee stable candidate sets. The database version should therefore be treated as essential reproducibility metadata in high-throughput inorganic materials screening.

Related

  1. Machine Learning of Band Gaps and Thermodynamic Stability in A2BB′X6 (X = F, Cl, Br, I) Double Perovskites with Uncertainty-Aware Multi-Objective Screening
    Qilin Wei, Haiyan Zhang, Chengyu Peng +5
    Nanomaterials (Basel, Switzerland)Peer-reviewedCC BYFull textMaterials & polymersEurope PMC
  2. The Open Materials 2024 (OMat24) inorganic materials dataset and models
    Luis Barroso-Luque, Muhammed Shuaibi, Xiang Fu +7
    Nature Computational SciencePeer-reviewedLicence not statedFull text455 citedMaterials & polymersOpenAlex
  3. NEP89: universal neuroevolution potential for inorganic and organic materials across 89 elements
    Ting Bo Liang, Ke Xu, Eric Lindgren +16
    Nature Computational SciencePeer-reviewedLicence not statedFull text89 citedMaterials & polymersOpenAlex
  4. Mechanoluminescence in crystalline inorganic materials: local disorder and the elastic distortion hypothesis
    Tanguy Rouxel, Xavier Rocquefelte, S. Tanabe
    Optical Materials: XPeer-reviewedCC BY 4.0Full textMaterials & polymersGeneral physicsHAL
  5. Autonomous in-silico inorganic materials discovery via multi-agent physics-aware scientific reasoning
    Alireza Ghafarollahi, Markus J. Buehler
    npj Computational MaterialsPeer-reviewedCC BY-NC-ND 4.0Full text19 citedMaterials & polymersOpenAlexPMCEurope PMC
BibTeX
@article{lou2026reproducibility,
  title = {{Reproducibility of Thermodynamic Stability and Band-Gap Screening of Inorganic Materials Across Materials Project Versions}},
  author = {Yunfei Lou and Ningning Wei},
  journal = {Inorganics},
  year = {2026},
  month = oct,
  doi = {10.3390/inorganics14110269},
  url = {https://www.mdpi.com/2304-6740/14/11/269},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Reproducibility of Thermodynamic Stability and Band-Gap Screening of Inorganic Materials Across Materials Project Versions
AU  - Yunfei Lou
AU  - Ningning Wei
PY  - 2026
DA  - 2026/10/23
JO  - Inorganics
DO  - 10.3390/inorganics14110269
UR  - https://www.mdpi.com/2304-6740/14/11/269
AB  - High-throughput computational databases have become central to the discovery and screening of inorganic materials, yet the reproducibility of candidate selection across database versions has rarely been quantified. Here, a frozen 2018 Materials Project snapshot was harmonized with database version 2026.04.13 to evaluate the cross-version stability of thermodynamic and electronic screening. Among 78,756 historical mp-* records in the primary longitudinal cohort, 76,931 remained traceable (97.68%). Despite high cross-version property rank agreement, screening reversal rates ranged from 1.2% to 8.1% across the 16 combined threshold pairs. Under the representative criterion Ehull ≤ 0.05 eV·atom−1 and Eg ≥ 2 eV, 15,754 materials were selected in 2018 and 14,191 in 2026; 1818 original candidates exited and 255 entered, corresponding to 88.46% candidate retention and a Jaccard similarity of 0.871. Instability was concentrated near decision boundaries and remained chemically structured after multivariable adjustment. Cl-, Br-, and N-containing materials were dominated by energy-above-hull threshold crossings, whereas the 3d-series metal group showed a larger contribution from band-gap changes. These results distinguish property reproducibility from decision reproducibility: strong cross-version property agreement does not guarantee stable candidate sets. The database version should therefore be treated as essential reproducibility metadata in high-throughput inorganic materials screening.
SN  - 2304-6740
ER  -