4.7 Article

Semi-Automated Creation of Density Functional Tight Binding Models through Leveraging Chebyshev Polynomial-Based Force Fields

期刊

JOURNAL OF CHEMICAL THEORY AND COMPUTATION
卷 17, 期 7, 页码 4435-4448

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.jctc.1c00172

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资金

  1. U.S. Department of Energy by Lawrence Livermore National Laboratory [DE-AC52-07NA27344]
  2. Laboratory Directed Research and Development Program at LLNL [18-SI-001, 20-SI-004]
  3. DFG [RTG 2247]

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A rapid-screening approach has been developed for determining systematically improvable DFTB interaction potentials that can yield transferable models for a variety of conditions. The method leverages a recent reactive molecular dynamics force field and linear combinations of Chebyshev polynomials, allowing for efficient creation of multi-center representations with minimal initial DFT calculations. The workflow has been focused on TiH2 as a model system, demonstrating its ability to produce reliable DFTB models over a broad range of thermodynamic conditions.
Density functional tight binding (DFTB) is an attractive method for accelerated quantum simulations of condensed matter due to its enhanced computational efficiency over standard density functional theory (DFT) approaches. However, DFTB models can be challenging to determine for individual systems of interest, especially for metallic and interfacial systems where different bonding arrangements can lead to significant changes in electronic states. In this regard, we have created a rapid-screening approach for determining systematically improvable DFTB interaction potentials that can yield transferable models for a variety of conditions. Our method leverages a recent reactive molecular dynamics force field where many-body interactions are represented by linear combinations of Chebyshev polynomials. This allows for the efficient creation of multi-center representations with relative ease, requiring only a small investment in initial DFT calculations. We have focused our workflow on TiH2 as a model system and show that a relatively small training set based on unit-cell-sized calculations yields a model accurate for both bulk and surface properties. Our approach is easy to implement and can yield reliable DFTB models over a broad range of thermodynamic conditions, where physical and chemical properties can be difficult to interrogate directly and there is historically a significant reliance on theoretical approaches for interpretation and validation of experimental results.

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