Journal of Computational Chemistry最新文献

{"title":"Machine‐Learning Surrogate Modeling of DFT ‐Calculated Binding Energies for Ionic Liquid Ion‐Pairs","authors":"Abu Taqui Md Tahsin, Paul Trusov, Rafid Bendimerad, Elaine Petro","doi":"10.1002/jcc.70528","DOIUrl":"https://doi.org/10.1002/jcc.70528","url":null,"abstract":"Ion–pair binding energy is a fundamental property that governs the physicochemical behavior of ionic liquids (ILs), influencing ion dissociation, transport, interfacial behavior, and field‐driven extraction processes across a wide range of applications. Accurate prediction of this quantity is therefore essential for rational IL design. While density functional theory (DFT) delivers precise energetic characterization of ion pairs, its computational demands render it impractical for high‐throughput evaluation of ionic liquid (IL) candidates. Here, we present a machine learning (ML) approach for direct prediction of DFT‐derived ion‐pair binding energies from SMILES strings of component ions. To resolve the mapping from molecular structure to binding energy, we considered seven machine learning surrogates: (1) kernel ridge regression (KRR), (2) Gaussian process regression (GPR), (3) random forest (RF), (4) XGBoost, (5) LightGBM, (6) CatBoost, and (7) graph neural network (GNN), trained on a set of 100 ion pairs and tested on a held‐out set of 20 ion pairs. The gradient‐boosted trees (XGBoost, LightGBM, and CatBoost) achieved the best predictive performance, yielding an average coefficient of determination () of about 0.844 and an average Spearman's rank correlation coefficient () of about 0.879. The results from this study highlight the strong potential of descriptor‐driven ML approaches to estimate ion‐pair binding energies, establishing their utility as computationally efficient alternatives to DFT for preliminary screening of ionic liquids across varied application domains.","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"11 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149221346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improved GAFF Force Field for Fused Ring Non‐Fullerene Acceptors With 1,1‐Dicyanomethylene‐3‐Indanone Based End Groups","authors":"Konstantinos Kordos, Dimitrios G. Papageorgiou","doi":"10.1002/jcc.70527","DOIUrl":"https://doi.org/10.1002/jcc.70527","url":null,"abstract":"The introduction of non‐fullerene acceptors (NFAs) in bulk heterojunction organic solar cells has advanced their power conversion efficiencies beyond 20%. NFAs consisting of a fused ring electron‐donating core, capped with electron‐withdrawing end groups, are being intensely investigated both experimentally and computationally, since they demonstrate superior performance. 1,1‐dicyanomethylene‐3‐indanone (IC) is a widely used end group due to its strong electron‐withdrawing ability and ease of chemical modification. The functionality of this end group can be further enhanced by employing two common strategies. Halogenation, that adjusts energy levels, and addition of π‐extensions that red‐shifts optical absorption. In the present work we improve the General Amber Force Field to model fused ring NFAs with a thiophene unit at the edge of the core. To this end, 10 different NFA structures that incorporate the IC end group along with its halogenated and π‐extended variants are employed. They are classified into three popular families according to their structural characteristics. Using ab initio computations, the dihedral angles between the fused ring core and the end group are reparametrized, while partial atomic charges are derived using the standard RESP procedure, thus creating complete force field models. Using experimentally resolved crystal structures available in the literature we validate the new parameterization and demonstrate its suitability for modeling a variety of fused ring NFAs.","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"30 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149221347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Representation, Transferability, and Trustworthy Uncertainty in Machine‐Learning Prediction of the HOMO – LUMO Gap of Transition‐Metal Complexes","authors":"Ali A. Khairbek, Abdullah Yahya Abdullah Alzahrani, Sana Ben Moussa, Pooventhiran Thangaiyan, Renjith Thomas","doi":"10.1002/jcc.70524","DOIUrl":"https://doi.org/10.1002/jcc.70524","url":null,"abstract":"The frontier–orbital (HOMO–LUMO) gap is a compact descriptor of the electronic structure of transition–metal complexes (TMCs) and a recurrent screening target for catalysis, photophysics, and functional material design; however, its evaluation by density functional theory (DFT) is costly at the library scale. Working entirely from the public tmQM database, with no additional DFT calculations and no experiments, we examine three questions that are seldom treated together: how much structural detail a model requires, whether it generalizes across the periodic table, and how far its uncertainty estimates can be trusted. For 108,541 mononuclear TMCs, we construct a hierarchy of representations of increasing cost: composition‐and‐coordination descriptors; the same descriptors augmented with inexpensive cheminformatics (RDKit) features; and a SchNet graph neural network that operates directly on the three‐dimensional geometry. The predictive accuracy increases monotonically across the hierarchy (test <jats:italic>R</jats:italic> <jats:sup>2</jats:sup> ≈ 0.57 → 0.63 → 0.77; mean absolute error 0.44 → 0.30 eV), and Shapley value analysis attributes the predictions to chemically reasonable factors. We then show that this in‐domain accuracy is a poor proxy for reliability. Leave‐one‐series‐out and leave‐one‐metal‐out evaluations reveal a sharp loss of accuracy on unseen chemistry (median leave‐one‐metal‐out <jats:italic>R</jats:italic> <jats:sup>2</jats:sup> ≈ 0.34; worst case d <jats:sup>10</jats:sup> zinc, <jats:italic>R</jats:italic> <jats:sup>2</jats:sup> &lt; 0), and, contrary to a natural expectation, neither of two geometry networks (SchNet, DimeNet++) extrapolates better than the simpler tabular model across metal series—both are often worse—although the directional architecture alone extrapolates with positive skill to a single withheld metal. Finally, although standard split‐conformal intervals are well calibrated in the domain (≈90% coverage), they undercover (81%) for an unseen series; we demonstrate that series‐conditional (Mondrian) calibration restores per‐series coverage and that a distance‐based applicability‐domain filter flags essentially all out‐of‐domain complexes, recovering calibrated coverage on the retained subset. The study offers a transparent, reproducible recipe for deciding when and how confidently such models may be applied.","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"73 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149221348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Low-Attosecond Resolution Electronic and Nuclear Dynamics: How Helical Electron Motion Drives Chiral Asymmetry","authors":"Tianlv Xu,&nbsp;Jiawen Kong,&nbsp;Jingqin Tu,&nbsp;Martin J. Paterson,&nbsp;Herbert Früchtl,&nbsp;Tanja van Mourik,&nbsp;Yasuteru Shigeta,&nbsp;Steven R. Kirk,&nbsp;Samantha Jenkins","doi":"10.1002/jcc.70529","DOIUrl":"10.1002/jcc.70529","url":null,"abstract":"<div>\u0000 \u0000 <p>Controlling and observing electron motion in chiral molecules is a fundamental challenge spanning chemical synthesis, materials science, and spintronics. The electronic origin of chiral asymmetry is revealed by combining real-space analysis of the total electronic charge density with time-dependent density functional theory (DFT) electron-nuclear dynamics simulations. Using simulated ultrafast circularly polarized laser pulses, the correct enantiomeric assignment for (<i>S</i>)-1-chloro-1-fluoroethane is demonstrated. Modulating the carrier envelope phase (CEP) angle altered the so-called extrinsic electronic chirality in both chiral (<i>S</i>)-1-chloro-1-fluoroethane and achiral chloroethane. Helical bound electron motion, quantified as intrinsic electronic chirality, however, was uniquely observed in the structurally chiral molecule and tuned to induce a significant degree of electronic achiral character via CEP variation. Furthermore, eigenvector-space trajectories exhibited distinct 3-D and 1-D morphologies for chiral (<i>S</i>)-1-chloro-1-fluoroethane and achiral chloroethane, respectively. This framework provides the molecular-level design principles needed to transition from static structural descriptors to dynamic electronic properties that can directly impact future practical applications, particularly in asymmetric synthesis and the design of next-generation chiral materials, such as those that exploit the chirality-induced spin selectivity (CISS) effect.</p>\u0000 </div>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"47 28","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149198901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Molecular Entropies of Conformationally Flexible, Gas-Phase Forms of Clinical Drugs: A Black-Box Approach Versus Systematic Sampling","authors":"Andrey D. Moshchenkov,&nbsp;Alexander S. Ryzhako,&nbsp;Timofey P. Rozov,&nbsp;Arseniy A. Otlyotov,&nbsp;Yury Minenkov","doi":"10.1002/jcc.70520","DOIUrl":"10.1002/jcc.70520","url":null,"abstract":"<div>\u0000 \u0000 <p>The results of the exhaustive conformational sampling are contrasted with metadynamics-based CREST simulations for a set of 13 gas-phase forms of clinical drug molecules retrieved from the CD25 dataset. [<i>Chem. Sci</i>. <b>2021</b>, <i>12</i> (19), 6551] The GFN1- and GFN2-xTB methods complement each other in the identification of the most stable conformer. The GFN-FF performs worse due to fundamental differences between the force field and the density functional theory (DFT) potential energy surfaces. Conformational entropies (S_conf) from the systematic search as well as from the standard CREST entropy mode calculations with the single-point Hessian (SPH) deactivated are in reasonable agreement with their molecular dynamics counterparts that account for torsional correlation [<i>J. Chem. Theory Comput</i>. <b>2022</b>, <i>18</i>, 7166–7178]. The CREST entropy mode evaluations on the DFT-refined geometries using the activated SPH routine yield too large S_conf values for some species due to the overestimation of the Boltzmann entropy averaging (<span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msup>\u0000 <mover>\u0000 <mi>S</mi>\u0000 <mo>¯</mo>\u0000 </mover>\u0000 <mo>°</mo>\u0000 </msup>\u0000 <mo>−</mo>\u0000 <msubsup>\u0000 <mi>S</mi>\u0000 <mn>1</mn>\u0000 <mo>°</mo>\u0000 </msubsup>\u0000 </mrow>\u0000 <annotation>$$ {overline{S}}^{{}^{circ}}-{S}_1^{{}^{circ}} $$</annotation>\u0000 </semantics></math>) contribution.</p>\u0000 </div>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"47 27","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149172994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"EASIQ-Marcus: An Automated Workflow for Applying Marcus Theory to Computational Chemistry Output Files","authors":"Albert Solé-Daura,&nbsp;Lucía Morán-González,&nbsp;Edmond Apaloo-Messan,&nbsp;Feliu Maseras","doi":"10.1002/jcc.70513","DOIUrl":"10.1002/jcc.70513","url":null,"abstract":"<div>\u0000 \u0000 <p>Single-electron transfer (SET) and energy-transfer (EnT) events play a central role in contemporary mechanistic proposals across photochemistry, electrochemistry, and catalysis. However, in routine computational practice, these steps are often treated less systematically than conventional bond-forming or bond-breaking events because their barrier evaluation usually requires a Marcus-theory workflow built from multiple quantum-chemical calculations, solvent-state manipulations, and careful post-processing of energies. Here, we present <i>EASIQ-Marcus</i> (https://github.com/maserasgroup-repo/easiq_marcus/), a Python package that automates this practical workflow for Gaussian users. The code implements several literature approaches for estimating reorganization energies and barriers, including hard-sphere, simplified hard-sphere, and four-point Marcus strategies in both symmetric and asymmetric forms. By turning the required file preparation and data extraction into explicit command-line steps, <i>EASIQ-Marcus</i> is designed to make the practical evaluation of SET and EnT events transparent, reproducible, and suitable for routine mechanistic studies.</p>\u0000 </div>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"47 27","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149163408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Simulating Infrared Spectra of Matrix Isolation Experiments: What Works Best?","authors":"Matthew H. V. Graneri,&nbsp;Dino Spagnoli,&nbsp;Duncan A. Wild,&nbsp;Allan J. McKinley","doi":"10.1002/jcc.70518","DOIUrl":"10.1002/jcc.70518","url":null,"abstract":"<p>Matrix isolation is an experimental technique which allows spectroscopists to observe highly reactive or weakly bound systems by trapping them in frozen noble gas matrices. In this work, we studied the viability of using ab initio molecular dynamics (AIMD) to simulate several H₂S·amine complexes isolated in solid argon crystals, comparing the results with conventional density functional theory (DFT) harmonic and anharmonic calculations to assess the most practical and accurate method to calculate the vibrational spectrum of such systems. While AIMD accurately predicted the intensity ratios of certain peaks, the frequencies themselves were no more accurate than conventional harmonic DFT calculations. Modeling an explicit argon matrix did not improve the results. Based on the computational cost of each method, a gas phase anharmonic or scaled harmonic frequency calculation at an appropriate level of theory was determined to be the most accurate and efficient way to simulate matrix isolation spectra.</p>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"47 26","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcc.70518","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149086304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Molecular-Environment Feedback Improves Superposition-of-Atomic-Potential SCF Guesses","authors":"Yukun Han,&nbsp;Yuhang Deng,&nbsp;Qinyu Zhang,&nbsp;Ruike Yang","doi":"10.1002/jcc.70514","DOIUrl":"10.1002/jcc.70514","url":null,"abstract":"<div>\u0000 \u0000 <p>Self-consistent-field calculations require an inexpensive initial electronic structure that nevertheless reflects the molecular environment. Standard superposition of atomic potentials (SAP) is efficient, but its component potentials describe isolated atoms. We show that the missing environmental information is already encoded in the first molecular SAP density and can be returned through one damped atom-resolved update of the fitted screening potentials. With the feedback strength frozen at 0.25, the intrinsic-atomic-orbital (IAO) realization reduces median density distance by 25.10%, 25.89%, and 25.96% for RHF, PBE, and PBE0 on an independent 80-structure hold-out. IAO charge correlations remain at least 0.99989 from def2-SVP through augmented triple- and quadruple-zeta bases. The original symmetric-Löwdin realization gives the same response direction in compact bases but exposes the expected diffuse-basis pathology. No target-functional information, converged target density, or auxiliary fragment calculation enters either guess.</p>\u0000 </div>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"47 26","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149086308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Thermodynamic Mapping of C5-Substituent Autoxidation Pathways in 1,5-Dimethylcytosine: A Quantum Chemical Study","authors":"Vasilii Korotenko,&nbsp;Hendrik Zipse","doi":"10.1002/jcc.70478","DOIUrl":"https://doi.org/10.1002/jcc.70478","url":null,"abstract":"<p>The autoxidation pathways of the methyl substituent at position 5 in 1,5-dimethylcytosine (1,5dmC) were investigated using DFT and DLPNO-CCSD(T) calculations with implicit SMD(H₂O) solvation. A radical reaction network was constructed to assess nonenzymatic pathways leading to hydroxymethyl, formyl, and carboxyl oxidation products. The results show that the reactivity of methylated cytosine derivatives is governed not by isolated C<span></span>H bond strengths alone, but by the coupled thermodynamics of radical formation, oxygen addition, hydroperoxide formation, and hydroperoxide decomposition. Hydrogen abstraction from the 5-methyl substituent is the most accessible radical-forming step in 1,5dmC, whereas protonation increases BDE(C<span></span>H) values and suppresses radical formation. Hydroperoxide intermediates play an important role within the considered propagation network, with O<span></span>O cleavage being more accessible than O<span></span>H cleavage. The calculated reaction free energies rationalize the possible accumulation of the formyl derivative 1m5fC: this formyl derivative is formed through strongly exergonic pathways, whereas its further conversion to the carboxyl derivative 1m5caC is more thermodynamically constrained. Representative transition-state calculations provide a kinetic consistency check, showing only moderate substrate-dependent variations in H-abstraction barriers within each model-radical class. Overall, the results identify thermodynamically relevant radical intermediates, limiting steps, and product-forming routes within the considered reaction network for the nonenzymatic autoxidation of methylated cytosine derivatives.</p>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"47 26","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcc.70478","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149083926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PyOrbb—Automated Analyses of Orbital-Interaction Mechanisms","authors":"Yuman Hordijk,&nbsp;Steven E. Beutick,&nbsp;Xiaobo Sun,&nbsp;Laurens Groot,&nbsp;Tori Gijzen,&nbsp;Jordi Poater,&nbsp;Trevor A. Hamlin,&nbsp;F. Matthias Bickelhaupt,&nbsp;Célia Fonseca Guerra","doi":"10.1002/jcc.70512","DOIUrl":"https://doi.org/10.1002/jcc.70512","url":null,"abstract":"<p>We present PyOrbb, an open-source, user-friendly Python-based program that automates the analysis and visualization of orbital interaction mechanisms between molecular fragments or reactants, based on quantum-chemical computations with the Amsterdam Density Functional (ADF) program. PyOrbb extracts the essential mixing patterns, presents them in an interactively adjustable orbital interaction diagram, and summarizes all relevant quantitative data in a convenient Excel spreadsheet for further analysis. The tool enables efficient interpretation of chemical bonding across a broad range of systems, including examples from organic, inorganic, and supramolecular chemistry. The application runs on macOS and Windows operating systems. PyOrbb is shown to accurately and rapidly visualize relevant bonding mechanisms from the often-overwhelming output of density functional computations.</p>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"47 26","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcc.70512","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149084206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}