Dataset of molecular dual-atom site complexes for catalysis.

Ba Long Nguyen, Thor Kongstad Madsen, Vladislav Ivanistsev, Nadezda Kongi

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Article in Data in brief, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 authors.

Ba Long NguyenInstitute of Chemistry, University of Tartu, Ravila 14a, 50411 Tartu, Estonia.

Thor Kongstad MadsenInstitute of Chemistry, University of Tartu, Ravila 14a, 50411 Tartu, Estonia.

Vladislav IvanistsevDepartment of Chemistry, University of Latvia, Jelgavas iela 1, 1004 Riga, Latvia.

Nadezda KongiInstitute of Chemistry, University of Tartu, Ravila 14a, 50411 Tartu, Estonia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dual-atom site catalysts (DACs) are characterized by two adjacent metal centers embedded within a well-defined coordination environment. The close proximity of the metal sites enables cooperative interactions, allowing more flexible tuning of adsorption energetics and reaction pathways. To accelerate rational design, screening, and comparative analysis of DACs, standardized, reusable computational datasets are essential. In this work, we present a dataset of molecular DACs (i.e., complexes) in a human- and machine-readable Atomic Simulation Environment (ASE)-native JSON format. The data were generated using an automated computational workflow, which has been made available on Zenodo. Geometry optimizations and single-point calculations were performed using density functional theory. For each catalyst, the optimized structure is provided together with single-point geometric, energetic, and electronic properties.

Indexed as

Computational catalysisDensity functionalDual-atom site molecular catalystsHigh-throughput screeningLarge-scale catalyst database

Identifiers

PMID42181299

DOI10.1016/j.dib.2026.112806

PMCPMC13191655

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