From Energies to Geometries: Development and Validation of a Robust yet Accurate Tool for Explicitly Correlated Structural Optimizations at an Affordable Cost

We present a new computational tool that integrates a robust geometry optimization module with external electronic-structure engines, enabling accurate and efficient optimizations at high levels of theory. Electronic energies and, when available, analytical gradients are directly imported, while numerical gradients are internally computed through an optimized parallel implementation with automatic symmetry reduction and granular resource control. This design ensures flexibility, stability, and full compatibility with composite post-Hartree-Fock frameworks. A key innovation is the extension of frozen natural orbital (FNO) techniques, previously employed to reduce the cost of correlated energy evaluations, to equilibrium geometry optimizations. The resulting FNO-based schemes markedly expand the size of systems that can be treated with near-spectroscopic accuracy. Extensive benchmarks demonstrate that both additive ("geometry") and composite-gradient formulations deliver stable and reliable convergence across a wide range of molecular systems. Overall, this development bridges energetic and structural focal-point analyses, paving the way for next-generation composite simulations integrating structural, thermochemical, and spectroscopic predictions.

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Publication Details

Journal
The Journal of Physical Chemistry Letters
Published
2025-12-08
DOI
https://doi.org/10.1021/acs.jpclett.5c03312
Citations
1
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
0.52
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article

From Energies to Geometries: Development and Validation of a Robust yet Accurate Tool for Explicitly Correlated Structural Optimizations at an Affordable Cost

Luigi Crisci, Mihály Kállay, Vincenzo Barone
1 citations
The Journal of Physical Chemistry Letters
Machine Learning in Materials Science
0.52
article

From Energies to Geometries: Development and Validation of a Robust yet Accurate Tool for Explicitly Correlated Structural Optimizations at an Affordable Cost

Luigi Crisci, Mihály Kállay, Vincenzo Barone
article en
1 citations

Abstract

We present a new computational tool that integrates a robust geometry optimization module with external electronic-structure engines, enabling accurate and efficient optimizations at high levels of theory. Electronic energies and, when available, analytical gradients are directly imported, while numerical gradients are internally computed through an optimized parallel implementation with automatic symmetry reduction and granular resource control. This design ensures flexibility, stability, and full compatibility with composite post-Hartree-Fock frameworks. A key innovation is the extension of frozen natural orbital (FNO) techniques, previously employed to reduce the cost of correlated energy evaluations, to equilibrium geometry optimizations. The resulting FNO-based schemes markedly expand the size of systems that can be treated with near-spectroscopic accuracy. Extensive benchmarks demonstrate that both additive ("geometry") and composite-gradient formulations deliver stable and reliable convergence across a wide range of molecular systems. Overall, this development bridges energetic and structural focal-point analyses, paving the way for next-generation composite simulations integrating structural, thermochemical, and spectroscopic predictions.

The Journal of Physical Chemistry LettersVol. 16(50)
Budapest University of Technology and Economics (HU), Montavid Thermodynamic Research Group (HU), Ospedale San Giuseppe (IT), Scuola Superiore Meridionale (IT)
Openalex Percentile: Top 30%
Machine Learning in Materials Science
0.52
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From Energies to Geometries: Development and Validation of a Robust yet Accurate Tool for Explicitly Correlated Structural Optimizations at an Affordable Cost — Luigi Crisci, Mihály Kállay, et al. · The Journal of Physical Chemistry Letters (2025) | TGRS Research Map | TGRS