Journal of Computational Chemistry最新文献

The accuracy of pseudopotentials (PPs) in density functional theory (DFT) and time-dependent DFT (TDDFT) calculations has been studied previously. However, the performance of PPs including spin-orbit coupling (SOC) for superheavy element compounds where SOC is very strong was rarely investigated. In this work, we report the performance of the small-core energy-consistent PPs developed by Stuttgart groups on the ground state bond lengths, force constants, dissociation energies in DFT calculations and on vertical excitation energies in TDDFT calculations for a series of closed-shell superheavy element halides, compared with results obtained using all-electron Dirac-Coulomb(-Gaunt) Hamiltonian. In most cases, results with the PPs are in good agreement with all-electron results in scalar relativistic and SOC calculations. PP deviations are insensitive to the employed exchange-correlation functionals in most cases. Effects of the basis set on these properties in PP calculations are very small. Our results indicate that reasonable DFT and TDDFT results can be given by such PPs for these superheavy elements halides.

In this work, we newly optimized the parameters of the extended tight-binding method Ln-xTB for the entire lanthanide (Ln) series (La to Lu) by using a genetic algorithm (GA) and incorporating a relativistic Hamiltonian, enabling accurate exploration of lanthanide molecular chemistry in complex environments. To validate the accuracy and reliability of Ln-xTB, we conducted comprehensive benchmarks on different classes of lanthanide-containing molecules (including halides, aqua complexes, and ligand-coordinated complexes) and compared results with the reported all-electron DFT calculations, effective core potential (ECP) methods, GFN0-xTB, GFN1-xTB, GFN2-xTB, RM1, Sparkle/RM1, Sparkle/AM1, Sparkle/PMn (n = 3, 6, 7), HF, MP2, CCSD(T) methods and experimental data. The results show that Ln-xTB successfully optimizes lanthanide compound structures with an average mean absolute deviation (MAD) of 0.037 Å for bond lengths relative to all-electron DFT, outperforming GFN2-xTB (MAD = 0.134 Å) and approaching the accuracy of ECP methods (MAD = 0.024 Å). Relative errors in bond lengths of Ln-xTB are predominantly within 3% (vs. all-electron DFT) and 5% (vs. experimental data). The results of benchmarks indicate the newly developed Ln-xTB method is more accurate than the previously reported GFNn-xTB (n = 0, 1, 2) methods. The structure optimization of lanthanide complexes with hundreds of atoms by using the Ln-xTB was completed in several seconds on a single CPU core. This work provides a set of accurate, efficient Ln-xTB parameters, addressing the long-standing trade-off between precision and computational cost in lanthanide molecular chemistry.

The biodegradation of polylactic acid (PLA) is essentially controlled by its interaction with water although little is known about the molecular-level mechanisms that trigger hydrolysis. This limitation hinders the rational design of polymers with desired degradation kinetics. In this work, we unveil the hydration-induced degradation of PLA using a multilevel computational approach, combining DFT with M06-2X functional and cc-pVDZ basis set along with the estimation of solvent effect using solvation model density (SMD), natural bond orbital (NBO) analysis, noncovalent interaction (NCI) index and Quantum Theory of Atoms in Molecules (QTAIM). Our findings demonstrate that the aqueous stability of PLA is determined by a delicate interplay between opposing forces: strong, directional hydrogen bonds to water carbonyls complemented by widespread van der Waals interactions, which in turn are partly countered by intrinsic steric repulsion within the polymer. The AIM analysis finds that all hydrogen bonds are quantitatively classified as weak, closed-shell interactions and thus exhibit an electrostatic character of the hydration network. In addition, AIMD simulations provide insights into the early-stage process of hydrolytic chain scission, revealing a proton transfer facilitated by water and an ester bond cleavage. Supported by molecular docking, key microbial enzymes are identified and binding affinities (up to −5.8 kcal mol⁻¹) transpire through comprehensive hydrogen bonding networks. The work offers a first-ever electronic-level blueprint of PLA, providing a mechanistic basis for predictions of degradation kinetics and aiding in the design of the next generation of environmentally benign degradable polymers. By unmasking the molecular inception of water-induced PLA degradation, this study demonstrates coherent tuning of polymer stability as well as lifetime. The insights provide the design and development of next-generation biodegradable polymers with regulated breakdown behavior for industrial and environmental interests.

The kinetic isotope effect (KIE) is essential in various chemical applications from reaction mechanism studies to tritium removal from water, however, its evaluation is associated with computational difficulties, mainly related to the correct determination of the geometry of the transition state. Traditional KIE evaluation relies on experimental measurements or computational approaches like density functional theory (DFT), which are often costly and whose accuracy strongly depends on the level of theory used. Here, we present a novel semi-empirical method for rapid and precise KIE estimation in proton-exchange reactions. By refining transition state identification through an iterative surface scan, our approach significantly improves accuracy while maintaining computational efficiency. Benchmarking against experimental data demonstrates superior performance compared to both DFT and conventional semi-empirical methods. Additionally, validation with tritium exchange reactions confirms its robustness. The computational implementation is freely available, facilitating its integration into future research.

In this work, the REG–CCSD(T) method, which is the extension of the coupled cluster (CC) with single (S), double (D), and perturbative triple (T) excitations accelerated by regularizing (REG) the Fock and intermediate excitation matrix, is newly developed for molecules based on the canonical CCSD(T) references. The new technique performs the outstanding efficiency of the CCSD(T) method by adding the regularization parameter to solve the positive definiteness and invertibility issues of the matrix during the calculations. The accuracy of the REG–CCSD(T) method is extensively tested on several open–shell and closed-shell molecules, with a mean absolute deviation (MAD) value of calculated energy as only 4.06 × 10⁻⁴ kcal/mol compared with the results of the canonical CCSD(T) method. The REG–CCSD(T) method with density-fitting REGDF–CCSD(T), with frozen-core approximations REGFC–CCSD(T), and the REGDF–FC–CCSD(T) method were also developed in this work as the extensions of the REG–CCSD(T) approach, respectively. The average time (in seconds) for the calculation of each benchmarked complex is ranked as REGFC–CCSD(T) (1.23) < REG–CCSD(T) (1.56) < REGDF–FC–CCSD(T) (2.70) < REGDF–CCSD(T) (2.76) < CCSD(T) (16.32), using the cc–pVDZ basis set and 28 parallel cores for calculations. Among these five CCSD(T) methods, the REG–CCSD(T) approach is recommended since it balances the accuracy and efficiency of calculations. This work provides a new efficient CCSD(T) approach named REG–CCSD(T) and its several variants, which could be used in the calculations of quantum chemistry requiring high accuracy and efficiency with affordable computational costs.