Journal of Computational Chemistry最新文献

{"title":"Precursor Design Principles for Area-Selective Atomic Layer Deposition of Alumina: Quantifying the Role of Lewis Acidity, Steric Repulsion, and Dimerization in Surface Adsorption.","authors":"Patrick Maue, Douglas L Miller, Fabian Pieck, Ralf Tonner-Zech","doi":"10.1002/jcc.70493","DOIUrl":"10.1002/jcc.70493","url":null,"abstract":"<p><p>In atomic layer deposition (ALD), precursor adsorption plays a critical role in determining growth characteristics. This is particularly important in area-selective ALD (AS-ALD), where adsorption on the non-growth surface (NGS) leads to selectivity loss. In this context, both the ability of a precursor to access reactive surface groups on the NGS and the strength of its binding are key parameters governing the selectivity in experiment. Adsorption on the NGS is strongly influenced by the precursor's substituents, which control Lewis acidity, steric demand, and propensity for dimerization. We applied energy decomposition analysis for extended systems (pEDA) to a set of commonly used aluminum precursors to quantitatively assess how these factors affect adsorption energetics on SiO₂ as the NGS, with trimethoxypropylsilane (TMPS) as a small-molecule inhibitor (SMI). Using fluoride ion affinity (FIA) as a metric for Lewis acidity, we find that this largely governs the trends in precursor bonding to both the surface and the SMIs. Notable exceptions are precursors bearing branched alkyl substituents for which steric repulsion dominates over Lewis acidity. Lewis acidity furthermore determines whether adsorption between the SMI layer remains energetically favorable. In this regime, steric effects-Pauli repulsion and deformation of the SMI layer-substantially weaken the adsorption. Dimerization generally reduces adsorption energies. This weakening effect is less pronounced, however, when adsorption takes place within the inhibitor layer. Based on these insights on bonding energetics, we recommend targeted modifications of existing aluminum precursors and propose systematic strategies for precursor design aimed at minimizing interactions with the NGS.</p>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"47 23","pages":"e70493"},"PeriodicalIF":2.9,"publicationDate":"2026-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13539961/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148885935","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":"A Fast and Parallelized Procedure for Checking Molecular Dynamics 3D Structure.","authors":"Daniel R Roe, Bernard R Brooks","doi":"10.1002/jcc.70494","DOIUrl":"10.1002/jcc.70494","url":null,"abstract":"<p><p>Structures built for or generated from Molecular Dynamics simulations can often have problems such as wrong chiralities, bad parameter assignment, steric clashes, and/or distorted geometries. It is important to be able to detect such problems in a rapid and automated way since such issues can prevent subsequent simulations from running successfully. Here we detail a structure check procedure which focuses on checking for some of the more common structural issues, including atomic overlaps, distorted bonds, and ring intersections, as well as the strategies for parallelizing the check procedure so it can rapidly detect issues in structures with millions of atoms.</p>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"47 23","pages":"e70494"},"PeriodicalIF":2.9,"publicationDate":"2026-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13539980/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148885976","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":"Computational Design and Theoretical Evaluation of Novel Heterocyclic Energetic Materials Based on 5-H-Imidazo-[4,5-c]-Pyridazine and 1,2,4-Triazolo-[4,3-a]-Pyrazine Scaffolds.","authors":"Luciana Amorim da Silva, Nathália Magalhães Paixão Rosa, Danillo Fernando Vianna Cantini, Aline Cardoso Anastácio","doi":"10.1002/jcc.70490","DOIUrl":"10.1002/jcc.70490","url":null,"abstract":"<p><p>Novel energetic materials based on 5-H-imidazo-[4,5-c]-pyridazine and 1,2,4-triazolo-[4,3-a]-pyrazine scaffolds, modified with explosophore groups (NO₂, NHNO₂, N₃, and ONO₂), were theoretically designed and evaluated by DFT at the B3LYP/def2-TZVPP // B3LYP/6-311G(d,p) level. Nitramino derivatives exhibited the highest chemical stability based on HOMO-LUMO gap analysis. Heat of formation followed the trend N₃ > NO₂ > NHNO₂ > ONO₂. Most imidazopyridazine derivatives exceeded RDX density, while all surpassed TNT. All derivatives showed superior detonation parameters over TNT, with 18 exceeding RDX performance. Impact sensitivity analysis revealed favorable safety profiles, with all di- and tri-substituted nitramines less sensitive than RDX. Mayer bond order analysis of all 88 compounds identified the trigger bonds for each compound and class, revealing distinct lability ranges for each explosophore:ONO₂ (0.490-0.728), CNO₂ (0.737-0.789), HNNO₂ (0.784-0.892), CNHNO₂ (0.917-0.944), and CN₃ (1.018-1.102). Aromaticity analysis ( <math><mrow><mtext>NICS</mtext> <msub><mfenced><mn>1</mn></mfenced> <mi>zz</mi></msub> </mrow> </math> ) showed that explosophore substitution systematically reduces aromatic character relative to the unsubstituted scaffolds, a trend correlated with molecular electrostatic potential (MEP) redistribution and associated with higher density, heat of detonation, detonation velocity, and detonation pressure. After a combined analysis of detonation performance, impact sensitivity profiles, trigger bond lability, and bond dissociation enthalpies, three compounds (IA345, IA356, and TA356) emerged as the most promising candidates, exhibiting heat of formation > 303.7 kJ mol^-1, oxygen balance > -28.2%, density > 1.85 g cm^-3, detonation velocity > 8.76 km s^-1, and detonation pressure > 33.17 GPa.</p>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"47 23","pages":"e70490"},"PeriodicalIF":2.9,"publicationDate":"2026-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13542628/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148885937","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":"Theoretical Investigation on Pyrene-Based Self-Assembled Molecules Toward Efficient Interface Performance of Perovskite/Transparent Electrode","authors":"Yucheng Li,&nbsp;Jianbing Zhu,&nbsp;Zhiheng Li,&nbsp;Yu Pei,&nbsp;Lei Yang,&nbsp;Kui Xu,&nbsp;Xueqin Ran,&nbsp;Yonghua Chen","doi":"10.1002/jcc.70489","DOIUrl":"10.1002/jcc.70489","url":null,"abstract":"<div>\u0000 \u0000 <p>Self-assembled monolayers (SAMs) provide a molecular platform for tuning electrode interfaces in perovskite solar cells (PSCs). To examine substituent effects in pyrene-derived phosphonic acids, we designed six derivatives of (2-(pyren-1-yl)ethyl)phosphonic acid (py3) and evaluated their gas-phase electronic structures, reorganization energies, predicted packing motifs, Marcus-Hush hopping descriptors, and adsorption on indium tin oxide (ITO) using density functional theory. Methyl and phenyl substitution increased the calculated intermolecular transfer integrals in the predicted packing models, whereas hydroxy substitution increased molecular polarity and reorganization energy. Adsorption calculations revealed substituent-dependent binding and charge redistribution on pristine and oxygen-deficient ITO. SAM/ITO DOS/PDOS analysis further showed that the near-Fermi electronic structure remains predominantly ITO-derived, while oxygen vacancies redistribute spectral weight on neighboring In atoms in a substituent- and energy-window-dependent manner. DOS/PDOS calculations for molecule/FAPbI₃(001) adsorption models also revealed distinct changes in near-Fermi spectral weight. Together, these calculations establish a multiscale structure–property picture linking molecular substitution to packing-mediated coupling, ITO adsorption, vacancy-sensitive electronic redistribution, and perovskite interfacial electronic structure. The resulting trends provide theoretical guidance for the design and experimental evaluation of pyrene-derived SAM molecules, while collective monolayer organization remains an additional factor in device operation.</p>\u0000 </div>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"47 23","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148809951","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":"Data Compression of the D1200 Suite: Achieving the Optimal Balance Between Size and Accuracy with the Diet-D200 Subset","authors":"Luis Soriano-Agueda","doi":"10.1002/jcc.70488","DOIUrl":"10.1002/jcc.70488","url":null,"abstract":"<div>\u0000 \u0000 <p>The evaluation of non-covalent interactions remains a cornerstone of density functional theory benchmarking, yet the increasing size of reference datasets like the D1200 presents a significant computational bottleneck. This work introduces an optimized “Diet-D1200” protocol, utilizing a genetic algorithm to identify highly representative subsets of interaction energies across an expansive chemical space, including p-block elements such as Boron, Sulfur, Phosphorus, halogens, and noble gases. By employing a WTMAD-4 (Weighted Total Mean Absolute Deviation) scheme—normalized specifically to the D1200 intrinsic energy scale—we demonstrate that subsets as small as 100 to 250 systems can faithfully reproduce the statistical performance of the full dataset. To evaluate the generalization performance of the optimized subsets and mitigate the risk of overfitting to the training manifold, a rigorous external validation protocol was performed. This assessment utilized twenty density functionals approximations, from GGAs and meta-GGAs to range-separated hybrids and double-hybrids. Our results demonstrate that the Diet-D200 protocol effectively preserves the topological features of the error surface, reducing the computational overhead by 83.3% while maintaining an exceptional Pearson correlation (<span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>r</mi>\u0000 <mo>&gt;</mo>\u0000 <mn>0.995</mn>\u0000 </mrow>\u0000 <annotation>$$ r&gt;0.995 $$</annotation>\u0000 </semantics></math>) with the parent D1200.</p>\u0000 </div>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"47 23","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148808033","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":"PARSEC.py: A Python-Based Real-Space Kohn–Sham Density Functional Theory Code Accelerated by Machine Learned Charge Density","authors":"Zeyi Zhang,&nbsp;Carlos Mora Perez,&nbsp;Patrick Kwon,&nbsp;Martin Head-Gordon,&nbsp;Jin Qian","doi":"10.1002/jcc.70482","DOIUrl":"10.1002/jcc.70482","url":null,"abstract":"<p>PARSEC.py is a Python-based real-space Kohn–Sham density functional theory (real-space KS-DFT) framework designed to provide a user- and developer-friendly platform for first-principles electronic-structure simulations. Discretization on real-space grids eliminates basis-set approximations, while enabling systematic control of numerical accuracy and large-scale parallelization. Building upon the theoretical foundations of the original PARSEC code, the framework leverages the Python scientific ecosystem to support modular development and integration with modern machine learning (ML) tools. PARSEC.py incorporates ML-predicted density as an alternative initial guess for the superposition of atomic density (SAD) in self-consistent field (SCF) iterations. This capability provides a framework for integrating ML models into electronic-structure calculations and offers a pathway for accelerating SCF convergence. We present the theoretical framework, key algorithms, and performance characteristics of PARSEC.py using both SAD and ML initializations.</p>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"47 23","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcc.70482","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148768762","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":"SolvateIt: A Tool for Solvating Molecules. A Case Study of Phloroglucinol in Solution","authors":"Yamil Hernández-Urquieta,&nbsp;Andrea Moreno-Ceballos,&nbsp;María Eugenia Castro,&nbsp;Francisco J. Melendez","doi":"10.1002/jcc.70486","DOIUrl":"10.1002/jcc.70486","url":null,"abstract":"<div>\u0000 \u0000 <p>The explicit first solvation shell remains a pivotal challenge in quantum chemical studies of solution-phase systems. A surface coverage-based protocol to construct explicit solvation environment is presented, in which the number and arrangement of solvent molecules emerge from the percentage of Solvent Accessible Surface (SAS) surrounding the solute rather than being user-defined. This strategy is implemented in a computational tool to ensure reproducibility. Phloroglucinol (PG) in ethanol is analyzed to validate this approach, comparing in vacuum, implicit solvent, and explicit ethanol systems corresponding to 10%, 25%, 50%, and 90% SAS coverage. Density Functional Theory calculations within a QM/QM methodology reveal that full first-shell improves the prediction of solvent-perturbed properties. In particular, the dipole moment obtained with 90% SAS coverage deviates by only 0.7% from the experimental value. Explicit solvation is shown to strongly influence geometry, electrostatic potential and intermolecular interactions, highlighting the importance of physically motivated solvation shell construction.</p>\u0000 </div>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"47 23","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148768852","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":"Accurate Solution-Phase Thermodynamics via Composite Quantum Chemistry and Machine Learning: Application to Biomass Decomposition","authors":"Mikito Fujinami,&nbsp;Akihiko Okubo,&nbsp;Shuhei Ogo,&nbsp;Ayumu Onda,&nbsp;Hiromi Nakai","doi":"10.1002/jcc.70483","DOIUrl":"10.1002/jcc.70483","url":null,"abstract":"<p>Thermodynamic quantities in the hydrated state provide essential reference information for understanding hydrothermal biomass decomposition. However, accurately estimating thermodynamic quantities in the hydrated state using computational methods remains challenging. In this study, we develop a general computational framework to evaluate accurate solution-phase thermodynamics in the standard state for compounds involved in the decomposition of xylose and glucose in water by combining gas-phase free-energy calculations with machine-learning prediction of hydration free energies. Gas-phase thermodynamic quantities are evaluated by a composite method designed to reproduce coupled-cluster theory with singles, doubles, and perturbative triples in the complete basis set limit (CCSD(T)/CBS) accuracy. Hydration free energies are predicted using molecular descriptors and machine learning. The resulting approach enables efficient evaluation of large reaction networks and is demonstrated for a dataset comprising 84 molecules and 73 reactions. Comparison with experimentally-derived free-energy differences for sugar isomerization indicates that the method achieves an accuracy within 3.7 kcal/mol in aqueous solution. The computed thermodynamic data further identify furfural and 5-hydroxymethylfurfural as thermodynamically favorable products in the xylose and glucose systems, respectively. This framework provides a practical route to accurate standard-state solution-phase thermodynamics by combining high-accuracy gas-phase thermochemistry with machine-learning prediction of hydration free energies.</p>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"47 23","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcc.70483","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148768753","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":"Efficient Calculation of Absorption Spectra of Platinum Complexes Used as Luminescent Probes for Cancer Detection","authors":"Lena T. T. Nguyen,&nbsp;Ernst D. Larsson,&nbsp;Kajsa M. F. Niklasson,&nbsp;Erna K. Wieduwilt,&nbsp;Erik D. Hedegård","doi":"10.1002/jcc.70481","DOIUrl":"https://doi.org/10.1002/jcc.70481","url":null,"abstract":"<p>Despite major advances in oncology, many chemotherapeutic agents still cause severe side effects that reduce quality of life, motivating new approaches for early detection and targeted elimination of cancer cells. Luminescent transition metal complexes are promising biomolecular probes as their photo-physical properties are dependent on the surrounding environment. This makes it possible to differentiate between different environments and as a result, allows for identification of abnormalities in DNA. However, reliable computational protocols to predict optical properties of transition metal intercalators are limited, making accurate absorption spectra calculations essential for screening candidates. Here, we benchmark methods for computing UV-Vis spectra of a Pt(II) pincer complex. The complex is studied both in isolation and intercalated in a small DNA model, representing probes designed to target DNA-associated molecular abnormalities. We find that the Tamm–Dancoff approximation (TDA) and the resolution of identity (RI) approximations provide a significant increase in speed for time-dependent density functional theory (TD-DFT) with only a modest loss of accuracy. Since geometry optimization is often the dominant cost, PBEh-3c emerges as an efficient alternative to conventional density functional theory (DFT), introducing errors comparable to those from TDA. Tight-binding methods (GFN-xTB) offer further acceleration, but yield larger deviations in structures and UV-Vis spectra; thus, unless extensive optimization is required, PBEh-3c provides the best balance between accuracy and efficiency. The largest source of uncertainty stems from the exchange-correlation functional used in the TD-DFT calculation, where we obtain good results with PBE0 based on PBEh-3c structures.</p>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"47 23","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcc.70481","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148754065","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":"Physically Informed Population Initialization Improves Bonobo Optimizer Searches for Atomic Cluster Global Minima","authors":"Bhrigu Chakraborty,&nbsp;Anakuthil Anoop","doi":"10.1002/jcc.70484","DOIUrl":"https://doi.org/10.1002/jcc.70484","url":null,"abstract":"<div>\u0000 \u0000 <p>Reliable global optimization of atomic clusters is limited not only by the ruggedness of the potential energy surface but also by the quality of the starting population supplied to the search algorithm. We examine this issue for the Bonobo Optimizer (BO) using a workflow that combines external PyAR-style population initialization, local Lennard-Jones relaxation, geometry repair, and structural similarity filtering. The initializer generates physically reasonable and structurally diverse trial clusters before the BO loop begins, while the relaxation and filtering steps map candidates to local minima and reduce redundant population updates. On Lennard-Jones clusters, the unmodified BO framework becomes unreliable beyond LJ₁₃, and local relaxation with similarity filtering alone remains insufficient for the double-funnel LJ₃₈ benchmark, reaching the global minimum only six times in 25 runs. Adding the Tabu-style initializer changes this outcome: LJ₃₈ is solved in all 20 independent runs, and the full LJ₂–LJ₁₀₀ benchmark reaches 943 successes in 1030 runs, corresponding to an overall success rate of 91.5%. The main remaining failures occur for LJ₇₅–LJ₇₇, consistent with the known difficulty of the Marks-decahedral exceptions. These results identify physically informed population construction as a practical route for improving BO-based cluster global optimization.</p>\u0000 </div>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"47 23","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148753997","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}