Journal of Computational Chemistry

Gregory, Kasimir P.; Karton, Amir

doi: 10.1002/jcc.70198pmid: 40747742

Accurate, efficient stability predictors are essential for understanding isomer formation in polycyclic aromatic hydrocarbons (PAHs), with implications for pollution toxicity and carbon‐material design, holding broad environmental and technological significance. Recently, a benchmark study demonstrated that PBE0‐D4 reproduces CCSD(T)‐level isomerization energies for 335 PAHs with a mean absolute deviation (MAD) of 0.67 kcal mol−1. Here, we apply the PBE0‐D4/6‐31G(2df,p) level of theory to 38,264 PAH isomers from the COMPAS‐3x database and identify fast, geometry‐based parameters that predict isomer stability. The total dihedral deviation (ΣDihedral) provides a cost‐free nonplanarity metric yielding a mean absolute deviation (MAD) of 3.6 kcal mol−1, outperforming maximal z‐displacement (MAD = 4.8 kcal mol−1) and the Harmonic Oscillator Model of Aromaticity (HOMA; MAD = 5.3 kcal mol−1). A combined ΣDihedral–HOMA model reduces the MAD to 2.5 kcal mol−1, and adding a fitted semiempirical xTB correction further lowers the MAD to 0.8 kcal mol−1. We implement these descriptors in the PAH Automated Property Scanner (PAHAPS) web tool, enabling rapid estimation of PAH isomer energies from molecular coordinates without intensive quantum calculations. This integrated approach facilitates large‐scale screening and efficient design of stable PAH isomers for environmental and materials applications.

doi: 10.1002/jcc.27415pmid: N/A

Lek Chaton, Kham; Meuwly, Markus

doi: 10.1002/jcc.70162pmid: 40751928

The effects of replacing individual contributions to an empirical energy function are assessed for halogenated benzenes (X‐Bz, X = H, F, Cl, Br) and chlorinated phenols (Cl‐PhOH). Introducing electrostatic models based on minimal distributed charges (MDCM) instead of usual atom‐centered point charges (PCs) to realistically describe features such as σ−holes yields overestimated hydration free energies unless the van der Waals parameters are reparametrized. Scaling van der Waals ranges by 10% to 20% for three Cl‐PhOH and most X‐Bz yield results within experimental error bars, which is encouraging, whereas for benzene (H‐Bz) PC‐based models are sufficient. Replacing the bonded terms by a neural network‐trained energy function featuring fluctuating atom‐centered PCs also yields qualitatively correct hydration free energies, which can be brought into agreement with experiments within error bars after adaptation of the van der Waals parameters. The infrared spectroscopy of Cl‐PhOH is rather well captured by all models, although the ML‐based energy function performs somewhat better in the region of the framework modes. The present work finds that refinements of empirical energy functions for targeted applications are a meaningful way toward more quantitative and physics‐based simulations. At the same time, empirical energy functions have matured to a remarkable degree, at least for the species considered in the present work.

Murtaza, Hudabia; Ain, Quratul; Kumar, Abhinav; Ali, Atif Mossad; Oza, Ankit Dilipkumar; Munir, Junaid

doi: 10.1002/jcc.70199pmid: 40751393

Bandgap engineering is the process of modifying a material's electronic structure to optimize its bandgap for specific applications. Applying pressure is an effective technique to alter a material's physical properties to meet device requirements. In this manuscript, we have investigated the impact of bandgap engineering through pressure application on the physical characteristics of AcGaO3. Using the Wien2K code and the FP‐LAPW method, we evaluated the material's properties under pressures ranging from 0 to 30 GPa, with additions of 5 GPa in each calculation. The Modified Becke‐Johnson approximation was employed to accurately account for exchange‐correlation effects. The elastic constants show a significant decrease with increasing pressure, indicating a reduction in the material's resistance to external strain. Lower speed values of the elastic waves suggest that the atomic bonding becomes weaker as the pressure is enhanced. Similarly, the Debye and melting temperatures decline as pressure increases. Electronic properties reveal a reduction in the indirect bandgap, while optical properties exhibit a shift from the higher energy region to the lower energy region under elevated pressures. The optical properties report a significant reduction in the polarization ability, absorption, and conductivity as the pressure is increased. This approach opens new possibilities for technological applications, as AcGaO3's reduced bandgap and optical characteristics in the visible area make it an attractive contender for next‐generation optoelectronic and energy storage devices.

Pollard, Nia; Choudhary, Kamal

doi: 10.1002/jcc.70202pmid: 40755323

The Variational Quantum Eigensolver (VQE) is a widely studied hybrid classical‐quantum algorithm for approximating ground‐state energies in molecular and materials systems. This study benchmarks the performance of the VQE for calculating ground‐state energies of small aluminum clusters (Al−$$ {\mathrm{Al}}^{-} $$, Al2$$ {\mathrm{Al}}_2 $$, and Al3−$$ {\mathrm{Al}}_3^{-} $$) within a quantum‐density functional theory (DFT) embedding framework, systematically varying key parameters: (I) classical optimizers, (II) circuit types, (III) number of repetitions, (IV) simulator types, (V) basis sets, and (VI) noise models. All calculations were performed using quantum simulators to evaluate VQE performance under both idealized and noise‐augmented conditions. Our findings demonstrate that certain optimizers converge efficiently, while circuit choice and basis set selection have a marked impact on energy estimates, with higher‐level basis sets closely matching classical computation data from Numerical Python Solver (NumPy) and Computational Chemistry Comparison and Benchmark DataBase (CCCBDB). To approximate realistic conditions, we employed IBM noise models to simulate the effects of hardware noise. The results showed close agreement with CCCBDB benchmarks, with percent errors consistently below 0.2%. The results demonstrate that VQE can approximate energy estimates under simulated conditions for small aluminum clusters and highlight the importance of optimizing quantum‐DFT parameters to balance computational cost and precision. This work contributes to ongoing efforts to benchmark VQE in practical settings and lays the groundwork for future benchmarking tools for quantum chemistry and materials applications.