ArticleNature communications2023
Deducing subnanometer cluster size and shape distributions of heterogeneous supported catalysts.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- Concurrent chemical reaction and cluster restructuring in a frustrated fluxional catalytic system identified via simple kMC model.Scientific reports · 2026Article
- Defect-engineered nonstoichiometric perovskite hosting high-activity PdO sites for enhanced hydrocarbon oxidation.Nature communications · 2026Article
- Collectivity effect in cluster catalysis under operational conditions.Nature communications · 2025Article
- Fourier Spectral Deconvolution to Describe Behaviors of pH-Dependent Monomeric and Self-Associated Anthocyanin Species.Journal of chemical information and modeling · 2025Article
- Single Atom Catalysts Based on Earth-Abundant Metals for Energy-Related Applications.Chemical reviews · 2024Review
- Ångstrom-scale gold particles loaded with alendronate via alpha-lipoic acid alleviate bone loss in osteoporotic mice.Journal of nanobiotechnology · 2024Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Infrared (IR) spectra of adsorbate vibrational modes are sensitive to adsorbate/metal interactions, accurate, and easily obtainable in-situ or operando. While they are the gold standards for characterizing single-crystals and large nanoparticles, analogous spectra for highly dispersed heterogeneous catalysts consisting of single-atoms and ultra-small clusters are lacking. Here, we combine data-based approaches with physics-driven surrogate models to generate synthetic IR spectra from first-principles. We bypass the vast combinatorial space of clusters by determining viable, low-energy structures using machine-learned Hamiltonians, genetic algorithm optimization, and grand canonical Monte Carlo calculations. We obtain first-principles vibrations on this tractable ensemble and generate single-cluster primary spectra analogous to pure component gas-phase IR spectra. With such spectra as standards, we predict cluster size distributions from computational and experimental data, demonstrated in the case of CO adsorption on Pd/CeO
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Registered trials
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