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Related Experiment Video

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Atomically Traceable Nanostructure Fabrication
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A database of low-energy atomically precise nanoclusters.

Sukriti Manna1, Yunzhe Wang1, Alberto Hernandez1

  • 1Department of Materials Science and Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA.

Scientific Data
|May 20, 2023
PubMed
Summary
This summary is machine-generated.

We created the largest database of atomically precise nanocluster structures and properties using ab-initio calculations. This resource aids in discovering new low-energy nanoclusters for advanced materials and technologies.

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Last Updated: Jul 29, 2025

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Area of Science:

  • * Materials Science
  • * Computational Chemistry
  • * Nanoscience

Background:

  • * Atomically precise nanoclusters exhibit unique chemical and structural properties crucial for diverse applications.
  • * Predicting nanocluster structures computationally is often resource-intensive.
  • * Existing databases lack comprehensive, ab-initio derived structural and property data.

Purpose of the Study:

  • * To establish the largest database of nanocluster structures and properties derived from ab-initio methods.
  • * To identify novel low-energy nanocluster configurations.
  • * To provide a resource for understanding nanoscale chemical and structural relationships.

Main Methods:

  • * Employed ab-initio computational methods for structure prediction and property calculation.
  • * Developed methodologies for efficient discovery of low-energy nanocluster configurations.
  • * Calculated energies, relaxed structures, relative stability, and HOMO-LUMO gaps for numerous clusters.

Main Results:

  • * Compiled a database of 63,015 clusters across 55 elements.
  • * Identified lower-energy structures for 593 previously studied cluster systems (element-size pairs).
  • * Discovered novel low-energy structures for 1320 systems lacking prior literature data.

Conclusions:

  • * The database provides unprecedented insights into nanoscale chemical and structural relationships.
  • * Facilitates future research in nanocluster science and the development of nanocluster-based technologies.
  • * Offers a valuable resource for computational materials discovery and design.