Internal Benchmarking of Semi-Empirical Methods: Bromine-Containing Crystals as a Sensitive Test Case

Selecting appropriate computational methods for organic crystals becomes particularly challenging for systems containing heavy halogens like bromine, whose complex electronic structures and diverse non-covalent interactions challenge approximate methods. Here we benchmark periodic DFT (PBE-D3BJ), CrystalExplorer (CE17/CE21), DFTB3-D3BJ, and PM7 against experimental stability data for 14 chlorine- and bromine-containing polymorphs across six CSD families. Chlorine systems show method-consistent performance, but bromine introduces large lattice energy variations (>10 kJ/mol) and, in several cases, qualitatively wrong stability rankings. Crucially, low mean absolute errors do not ensure correct thermodynamic ordering, and no semi-empirical method proves universally reliable for bromine. Only PBE-D3BJ achieves perfect experimental agreement. These results position bromine-containing crystals as exceptionally sensitive benchmarks and emphasize internal validation against experiment or reference DFT as essential before large-scale studies-particularly timely as machine-learning potentials emerge.

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Publication Details

Journal
Molecules
Published
2026-04-15
DOI
https://doi.org/10.3390/molecules31081288
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
0.00

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article

Internal Benchmarking of Semi-Empirical Methods: Bromine-Containing Crystals as a Sensitive Test Case

Ilona A. Isupova, Denis A. Rychkov
Molecules
Machine Learning in Materials Science
article

Internal Benchmarking of Semi-Empirical Methods: Bromine-Containing Crystals as a Sensitive Test Case

Ilona A. Isupova, Denis A. Rychkov
article en

Abstract

Selecting appropriate computational methods for organic crystals becomes particularly challenging for systems containing heavy halogens like bromine, whose complex electronic structures and diverse non-covalent interactions challenge approximate methods. Here we benchmark periodic DFT (PBE-D3BJ), CrystalExplorer (CE17/CE21), DFTB3-D3BJ, and PM7 against experimental stability data for 14 chlorine- and bromine-containing polymorphs across six CSD families. Chlorine systems show method-consistent performance, but bromine introduces large lattice energy variations (>10 kJ/mol) and, in several cases, qualitatively wrong stability rankings. Crucially, low mean absolute errors do not ensure correct thermodynamic ordering, and no semi-empirical method proves universally reliable for bromine. Only PBE-D3BJ achieves perfect experimental agreement. These results position bromine-containing crystals as exceptionally sensitive benchmarks and emphasize internal validation against experiment or reference DFT as essential before large-scale studies-particularly timely as machine-learning potentials emerge.

MoleculesVol. 31(8)
Boreskov Institute of Catalysis (RU), Institute of Solid State Chemistry and Mechanochemistry (RU)
Siberian Branch, Russian Academy of Sciences, Russian Science Foundation, Russian Academy of Sciences
Affordable and clean energy
Openalex Percentile: Top 25%
Machine Learning in Materials Science
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