Journal of Computational Chemistry最新文献

{"title":"A Theoretical Investigation of Substituent Effects on the Electronic Spectra of Antimony(III) Corrolates","authors":"Feng Li,&nbsp;Yun-Rui Lv,&nbsp;Mian-Ying Huang,&nbsp;Qing-Hua Yu,&nbsp;Yan-Fang Yao,&nbsp;Yi-Feng Qiu,&nbsp;Hai-Yang Liu","doi":"10.1002/jcc.70367","DOIUrl":"10.1002/jcc.70367","url":null,"abstract":"<div>\u0000 \u0000 <p>Sb(III) corrolates show single/double Soret bands depending on peripheral substituents. To clarify the mechanism, all-electron realistic TDDFT calculations and wave function analyses are performed on a series of Sb(III) corrolates bearing different <i>meso</i>-substituents. The results indicate that the split mainly stems from the large transition energy gap (Δ<i>E</i>) between S₀ → S₃ (HOMO → LUMO + 1) and S₀ → S₄ (HOMO-1 → LUMO + 1) excitations, enlarged with the macrocyclic electron density increasing. The large oscillator strength difference (Δ<i>f</i>) plays a secondary role in the detectable split at a close Δ<i>E</i>. Sb atom contributes significantly to the inner orbitals (HOMO-2/HOMO-7/HOMO-8). Decomposition of the total transition dipole moment (<i>μ</i>^T) demonstrates that transitions related to these orbitals induce non-negligible negative contributions to the <i>μ</i>^T of S₀ → S₄ excitation, thereby reducing the oscillator strength. The less electropositive Sb atoms trigger the more obvious offsetting effects. In conclusion, electron-donating groups (EDGs) lower the Δ<i>E</i> and Δ<i>f</i> of Sb(III) corrolates, leading to splitting Soret bands.</p>\u0000 </div>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"47 9","pages":""},"PeriodicalIF":4.8,"publicationDate":"2026-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147611945","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":"Modulating Carbon Dioxide Hydrate With Ammonium and Phosphonium-Based Deep Eutectic Solvent: A Molecular Dynamics Study of Cage-Specific Dissociation Mechanism","authors":"Abhilasha P. Shastri,&nbsp;Mazharuddin A. Quazi,&nbsp;Shrikant S. Mete,&nbsp;Debashis Kundu","doi":"10.1002/jcc.70358","DOIUrl":"10.1002/jcc.70358","url":null,"abstract":"<div>\u0000 \u0000 <p>The controlled release of CO₂ from structure I (sI) hydrates is essential for advancing carbon capture and storage (CCS) technologies. This study utilizes molecular dynamics (MD) simulations to investigate the pressure-dependent (1–80 bar) dissociation of CO₂ hydrates in two aqueous deep eutectic solvents (DESs) medium: tetrabutylammonium bromide/ethylene glycol (TBAB/EG, DES1) and methyl triphenyl phosphonium bromide/ethylene glycol (MTPB/EG, DES2), each in a 1:4 M ratio. The results demonstrate that both pressure and DES composition critically influence hydrate stability. DES1 promotes greater CO₂ release by reducing the CO₂ density from 640 kg/m³ within the sI hydrate to 206 kg/m³ at the sI hydrate–aqueous DES1 interface at 80 bar. DES1 shows more hydrogen bonding between CO₂ and aqueous water, while enhancing CO₂ mobility, outperforming DES2. The radial distribution function (RDF) analysis shows that CO₂ interacts more strongly with aqueous water in the presence of DES1, with a coordination number (<i>CN</i>) of approximately 27.02 at 1 bar, compared to DES2, which shows a maximum <i>CN</i> of about 26.37 at 1 bar. Higher CO₂ mobility in the aqueous DES1 phase from CO₂ hydrate is further supported by mean square displacement (MSD) compared to DES2. These findings establish a molecular-level framework for understanding how DES composition modulates hydrate dissociation, offering valuable insights for the rational design of DES-based media for targeted CO₂ sequestration.</p>\u0000 </div>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"47 9","pages":""},"PeriodicalIF":4.8,"publicationDate":"2026-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147599139","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":"New High-Pressure Polymorphs of Rb2CO3 and Cs2CO3: Crystal Structure Prediction and P–T Phase Diagrams","authors":"Anastassiya V. Mezentseva,&nbsp;Nursultan E. Sagatov,&nbsp;Dinara N. Sagatova,&nbsp;Maksim V. Banaev,&nbsp;Pavel N. Gavryushkin","doi":"10.1002/jcc.70363","DOIUrl":"10.1002/jcc.70363","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 &lt;p&gt;In this work, we performed crystal structure searches for rubidium and cesium carbonates (Rb&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mrow&gt;&lt;/mrow&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ {}_2 $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;CO&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mrow&gt;&lt;/mrow&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;3&lt;/mn&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ {}_3 $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; and Cs&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mrow&gt;&lt;/mrow&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ {}_2 $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;CO&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mrow&gt;&lt;/mrow&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;3&lt;/mn&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ {}_3 $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;) in the pressure range of 0–100 GPa using evolutionary algorithms based on the density functional theory. As a result, two new stable high-pressure polymorphs, &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;C&lt;/mi&gt;\u0000 &lt;mi&gt;c&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ Cc $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; and &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;C&lt;/mi&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;mo&gt;/&lt;/mo&gt;\u0000 &lt;mi&gt;c&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ C2/c $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;, were predicted for both carbonates. The M&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mrow&gt;&lt;/mrow&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ {}_2 $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;CO&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mrow&gt;&lt;/mrow&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;3&lt;/mn&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ {}_3 $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;-&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 ","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"47 9","pages":""},"PeriodicalIF":4.8,"publicationDate":"2026-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147585595","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":"Tackling Orientational Isomerism in Metal–Organic Frameworks Comprising Low-Symmetry Linker Molecules via Simulated Annealing Featuring a Neural Network Potential","authors":"Benedikt E. Hörfarter,&nbsp;Stefan Seiwald,&nbsp;Clemens Hofstötter,&nbsp;Armin Penz,&nbsp;Josef M. Gallmetzer,&nbsp;Thomas S. Hofer","doi":"10.1002/jcc.70349","DOIUrl":"10.1002/jcc.70349","url":null,"abstract":"<p>The perplexing structural diversity of metal–organic frameworks (MOFs) leads to astonishing unique properties and versatile potential technological applications of this porous materials class. However, whenever the organic linker molecules in a specific MOF compound may adopt multiple spatial orientations in-between the inorganic nodes they coordinate to, a near infinite number of possible MOF configurations arises through orientational isomerism. The latter is particularly challenging to account for in computational studies. In this work, we present a novel simulated annealing (SA) approach via Monte Carlo (MC) runs to gain insights into linker molecule orientations within such compounds, at the example of the three increasingly complex MOF systems MOF-5-OH, SNU-70 and UiO-66(Zr)-NH₂. We thereby successfully identify reasonable approximations to the global minimum structures for all MOFs with regard to collective linker molecule orientations by performing random re-orientation attempts of a randomly chosen organic linker in each MC step. The efficiency of the simulated annealing procedure is improved and guaranteed by exploiting the accuracy and speed of the state-of-the-art neural network potential (NNP) MACE-MP-0a in all energy and force calculations. Critically, a substantial potential energy gain is observed during annealing, accompanied by systematic structural changes within the MOF compounds. The combined results of these energetic and structural characteristics highlight how it is indeed cooperative effects arising from the organic linker molecules that play a decisive role in determining the most favorable MOF configuration. Intriguingly, root-mean-square-deviation (RMSD) calculations based exclusively on atoms of the inorganic nodes are found to be sensitive structural descriptors for tracking linker molecule re-orientations, while powder X-ray diffraction (PXRD) patterns and radial distribution functions (RDFs) derived from molecular dynamics (MD) simulations at standard conditions show less distinctive trends. In summary, the utility of the presented simulated annealing strategy is justifiable by its broad applicability for investigating linker-related orientational isomerism in any relevant MOF as well as the possibility for studying even more complex host–guest systems in a similar manner.</p>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"47 9","pages":""},"PeriodicalIF":4.8,"publicationDate":"2026-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcc.70349","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147585650","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":"Simulon: An AI-Assisted, PyTorch-Native Framework of Molecular Dynamics and Modeling","authors":"Zongxiao Jin,&nbsp;Xiaobo Sun,&nbsp;Xiaoli Xi,&nbsp;Zuoren Nie","doi":"10.1002/jcc.70364","DOIUrl":"10.1002/jcc.70364","url":null,"abstract":"<div>\u0000 \u0000 <p>The growing complexity of modern molecular simulations calls for new frameworks that unify physical modeling, machine learning, and human–AI interaction in the era of artificial intelligence. Simulon is an open-source, PyTorch-native molecular dynamics (MD) platform designed to bridge MD and artificial intelligence through a tensor-based architecture. By representing atomic systems, forces, and trajectories as differentiable tensors, Simulon enables end-to-end learning over molecular data while leveraging GPU hardware and PyTorch software to accelerate simulations. Compared with other similar frameworks, Simulon employs a highly optimized tensor-based computational kernel, achieving substantial speedup. A retrieval-augmented large language model (LLM) agent serves as an intelligent interface, translating natural-language instructions into executable simulation workflows and analytical routines, which allow scientists to configure, execute, and interpret MD simulations conversationally, forming an autonomous loop between physical computation and semantic intent. This integration can relieve scientists of tedious data processing jobs and enable them to focus on more creative work. Simulon supports both classical and machine-learning potentials under GPU acceleration and achieves quantitative agreement with established engines such as LAMMPS while maintaining ML compatibility. By combining differentiable simulation, scalable computation, and natural-language control, Simulon establishes a new paradigm for AI-assisted molecular modeling—where chemical information, data-driven potentials, and autonomous agents converge to accelerate scientific discovery.</p>\u0000 </div>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"47 8","pages":""},"PeriodicalIF":4.8,"publicationDate":"2026-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147536205","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":"ASH: A Multi-Scale, Multi-Theory Modeling Program","authors":"Ragnar Bjornsson","doi":"10.1002/jcc.70359","DOIUrl":"10.1002/jcc.70359","url":null,"abstract":"<p>We introduce ASH, a multi-scale, multi-theory modeling program for quantum mechanics (QM), molecular mechanics (MM), and hybrid calculations, written in the Python programming language. ASH is written in response to the increasingly diverse computational chemistry software landscape that features more QM and MM programs than ever before, and with machine learning interatomic potentials (MLIP) further changing the way modern computational chemistry is being performed. ASH is a Python library that intentionally separates computational chemistry jobs (geometry optimizations, frequency calculations, molecular dynamics, surface scans, reaction paths, etc.) from the QM, MM, or ML method (calculated by the specialized QM or MM programs or ML libraries). By keeping the jobs separate from the Hamiltonian, a highly flexible computational chemistry environment emerges that can be used in workflows involving QM methods (using interfaces to many different QM programs), classical MM methods with multiple force fields (via an interface to the OpenMM library), machine-learning potentials, or hybrid methods. ASH is especially powerful as a program for performing hybrid simulations: including QM/MM, QM/ML, ML/MM, QM + ML, or ONIOM calculations for proteins, solvated molecules, or molecular crystals. Molecular dynamics and enhanced sampling can be performed using any level of theory allowing for highly flexible free-energy simulations (such as metadynamics) enabled by interfaces to algorithms in OpenMM and Plumed. There are flexible interfaces to many QM programs such as ORCA, xTB, pySCF, CP2K, MRCC, Turbomole, CFour, and many others.</p>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"47 8","pages":""},"PeriodicalIF":4.8,"publicationDate":"2026-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13033825/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147571406","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 Comparative DFT Study of Pd- and Ni-Based Catalysts in the Narasaka–Heck/C(sp3)–H Activation Reaction","authors":"Renjith Thomas,&nbsp;Maha I. Al-Zaben,&nbsp;Abdullah Yahya Abdullah Alzahrani,&nbsp;Ralph Puchta,&nbsp;Ali A. Khairbek","doi":"10.1002/jcc.70361","DOIUrl":"10.1002/jcc.70361","url":null,"abstract":"<div>\u0000 \u0000 <p>Density functional theory (DFT) calculations were performed to investigate the mechanistic features of metal-catalyzed C(sp³)–H activation in the Narasaka–Heck cascade reaction, with a particular focus on comparative trends between palladium- and nickel-based catalyst systems. Using the experimentally reported Pd–PCy₃ complex as a benchmark, two nickel catalysts supported by distinct ligand frameworks (NHC_F and ADAP) were examined to assess how metal identity and ligand environment jointly influence the catalytic pathway. The computational results confirm that the concerted metalation–deprotonation (CMD) step constitutes the rate-determining process for all systems considered. Compared with palladium, nickel catalysts exhibit systematically lower CMD activation barriers across a range of solvent environments. This behavior is traced to enhanced electronic softness, more delocalized charge redistribution, and reduced structural rigidity in the nickel systems, which collectively facilitate geometric reorganization along the reaction coordinate. In contrast, the Pd–PCy₃ catalyst relies on strongly polarized metal–substrate interactions that correlate with higher energetic penalties upon distortion. Further analysis reveals that key elementary steps, including CMD and reductive elimination, proceed through weakly coordinated and transient intermediates rather than idealized closed-shell geometries. Under these conditions, ligand flexibility and metal–ligand bonding lability emerge as decisive factors governing the relative accessibility of the catalytic steps. Overall, this study highlights relative mechanistic trends and electronic structure effects that rationalize the observed differences between palladium and nickel catalysts, providing design-oriented insights for the development of experimentally relevant nickel-based alternatives.</p>\u0000 </div>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"47 8","pages":""},"PeriodicalIF":4.8,"publicationDate":"2026-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147536201","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":"FastMDAnalysis: Software for Automated Analysis of Molecular Dynamics Trajectories","authors":"Adekunle Aina,&nbsp;Derrick Kwan","doi":"10.1002/jcc.70350","DOIUrl":"10.1002/jcc.70350","url":null,"abstract":"<p>The analysis of molecular dynamics (MD) trajectories remains fragmented, requiring researchers to integrate multiple computational methods in bespoke scripts. This creates a significant barrier to reproducibility and limits analytical scope. We present <span>FastMDAnalysis</span>, a unified framework that establishes a reproducible, automated workflow for end-to-end trajectory analysis. The system orchestrates a comprehensive and extensible suite of core analysis modules, including root-mean-square deviation and fluctuation, radius of gyration, hydrogen bonding, solvent-accessible surface area, secondary structure assignment, dimensionality reduction, clustering, fraction of native contacts for protein folding studies, and dihedral angle analysis, within a single, consistent environment built on <span>MDTraj</span>, <span>scikit-learn</span>, and <span>SciPy</span>. The software natively supports all major trajectory formats, including <span>GROMACS</span>, <span>AMBER</span>, and <span>CHARMM</span>. We demonstrate a <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mo>&gt;</mo>\u0000 <mn>90</mn>\u0000 <mo>%</mo>\u0000 </mrow>\u0000 <annotation>$$ &gt;90% $$</annotation>\u0000 </semantics></math> reduction in code volume for standard workflows and validate its numerical equivalence to reference implementations. <span>FastMDAnalysis</span> provides a methodological advance that makes rigorous, multi-analysis MD studies accessible and reproducible for the computational chemistry, biology, and biophysics communities. The software is freely available under the MIT license at https://github.com/aai-research-lab/fastmdanalysis.</p>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"47 8","pages":""},"PeriodicalIF":4.8,"publicationDate":"2026-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13033318/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147571392","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":"σ-Resonance Stabilization of Aminomethylene by N-Halogenation","authors":"Serhii Medvedko,&nbsp;Virinder Bhagat,&nbsp;J. Philipp Wagner","doi":"10.1002/jcc.70360","DOIUrl":"10.1002/jcc.70360","url":null,"abstract":"<p>Amino substitution effectively stabilizes carbenes via π-resonance, enabling their isolation as <i>N</i>-heterocyclic carbenes (NHCs). Our group has recently demonstrated that <i>N</i>-halogenation of pyridinylidenes (Hammick intermediates) provides an additional stabilization mode through a rarely utilized σ-resonance. However, this σ-resonance interaction might not yet have reached its full potential due to the constriction of the carbene motif within a cyclic structure. Thus, we have studied the impact of <i>N</i>-halogenation (X = Br, I) on the structure, energetics, and spectroscopic properties of the parent open-chain aminocarbene, aminomethylene, utilizing fully unconstrained CCSD(T) and NEVPT2 geometry optimizations together with a def2-TZVPP basis set. We find that the halogenated carbenes prefer a <i>Z</i> configuration of the C–N bond, which is impossible in a cyclic arrangement. Halogenated aminomethylenes are kinetically protected against unimolecular rearrangement by barriers exceeding 35 kcal mol⁻¹. Short C–N bond lengths (1.23 Å) and wide carbene angles (~125°) indicate cooperative π- and σ-resonance stabilization, resulting in carbene stabilization energies (CSEs) increased by ~12–13 kcal mol⁻¹ relative to the parent aminomethylene. The electronic structure is characterized by the σ* orbital of the N–X bond as the lowest unoccupied molecular orbital.</p>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"47 8","pages":""},"PeriodicalIF":4.8,"publicationDate":"2026-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcc.70360","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147536203","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":"Thermal Decomposition Simulations of Hydroxylamine Pentazolate With Deep Neural Network Potential","authors":"Guozhen Sheng,&nbsp;Caimu Wang,&nbsp;Jiao Zhang,&nbsp;Wei Guo,&nbsp;Ruibin Liu","doi":"10.1002/jcc.70362","DOIUrl":"10.1002/jcc.70362","url":null,"abstract":"<div>\u0000 \u0000 <p>Against the backdrop of insufficient research into the microscopic reaction mechanisms of pentazole anion (<span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msubsup>\u0000 <mi>N</mi>\u0000 <mn>5</mn>\u0000 <mo>−</mo>\u0000 </msubsup>\u0000 </mrow>\u0000 <annotation>$$ {mathrm{N}}_5^{-} $$</annotation>\u0000 </semantics></math>) salts, the present study developed a deep neural network potential (DNNP) model calibrated with first principles data. On this basis, large-scale molecular dynamics (MD) simulations were performed to conduct an in-depth investigation into the thermal decomposition mechanism and kinetic processes of hydroxylamine pentazole (NH₃OHN₅) at the atomic scale. A highly precision DNNP model was constructed using an active learning strategy, whose predictions for energy and atomic forces showed excellent agreement with Density Functional Theory (DFT) results. MD simulations revealed that the thermal decomposition of NH₃OHN₅ initiates with a hydrogen transfer reaction. The protonation of the <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msubsup>\u0000 <mi>N</mi>\u0000 <mn>5</mn>\u0000 <mo>−</mo>\u0000 </msubsup>\u0000 </mrow>\u0000 <annotation>$$ {mathrm{N}}_5^{-} $$</annotation>\u0000 </semantics></math> reduces its ring-opening energy barrier from 125.45 to 112.13 kJ/mol, significantly promoting the ring-opening decomposition process. The final decomposition products were predominantly N₂, H₂O, and NH₃. This research elucidates the decomposition pathways and reaction mechanism of NH₃OHN₅ at the atomic scale, demonstrating the exceptional capability of the DNNP in simulating the reaction dynamics of energetic materials and providing a theoretical foundation for the subsequent molecular design of high-performance, green energetic materials.</p>\u0000 </div>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"47 8","pages":""},"PeriodicalIF":4.8,"publicationDate":"2026-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147518917","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}