Journal of Chemical Theory and Computation最新文献

{"title":"A Practical Framework for Simulating Time-Resolved Spectroscopy Based on a Real-Time Dyson Expansion.","authors":"Cian C Reeves, Michael Kurniawan, Yuanran Zhu, Nikil Jampana, Jacob Brown, Chao Yang, Khaled Z Ibrahim, Vojtech Vlcek","doi":"10.1021/acs.jctc.5c00696","DOIUrl":"https://doi.org/10.1021/acs.jctc.5c00696","url":null,"abstract":"<p><p>Time-resolved spectroscopy is a powerful tool for probing electron dynamics in molecules and solids, revealing transient phenomena on subfemtosecond time scales. The interpretation of experimental results is often enhanced by parallel numerical studies, which can provide insight and validation for experimental hypotheses. However, developing a theoretical framework for simulating time-resolved spectra remains a significant challenge. The most suitable approach involves the many-body nonequilibrium Green's function formalism, which accounts for crucial dynamical many-body correlations during time evolution. While these dynamical correlations are essential for observing emergent behavior in time-resolved spectra, they also render the formalism prohibitively expensive for large-scale simulations. Substantial effort has been devoted to reducing this computational cost─through approximations and numerical techniques─while preserving the key dynamical correlations. The ultimate goal is to enable first-principles simulations of time-dependent systems ranging from small molecules to large, periodic, multidimensional solids. In this perspective, we outline key challenges in developing practical simulations for time-resolved spectroscopy, with a particular focus on Green's function methodologies. We highlight a recent advancement toward a scalable framework: the real-time Dyson expansion (RT-DE) [<i>Phys. Rev. Lett.</i> <b>2024</b>, <i>133</i>, 226902]. We introduce the theoretical foundation of RT-DE and discuss strategies for improving scalability, which have already enabled simulations of system sizes beyond the reach of previous fully dynamical approaches. We conclude with an outlook on future directions for extending RT-DE to first-principles studies of dynamically correlated, nonequilibrium systems.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144511283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Confinement-Tuned Pore Chemistry via Molecular Engineering Enables High-Efficiency Water-Boron Selective Transport in Polyamide Membranes.","authors":"Jinlong He, Yaxuan Yang, Jishan Wu, Hong Zhang, Xiaobao Tian, Yongjie Liu, Qingyuan Wang","doi":"10.1021/acs.jctc.5c00440","DOIUrl":"https://doi.org/10.1021/acs.jctc.5c00440","url":null,"abstract":"<p><p>Through molecular simulations and density functional theory, we explored a novel approach leveraging molecular engineering-tuned pore chemistry to create active pores in polyamide membranes, enabling exceptionally high-efficiency selective removal of neutral molecules such as boric acid from water. This approach aims to achieve supremely high-efficiency selective water-boric acid separation without sacrificing water permeation efficiency, delivering up to a 20-fold enhancement in selectivity along with a significant improvement in water permeance. To elucidate the underlying mechanism behind such exceptional efficiency, we systematically analyzed the transport properties of water and boric acid across polyamide membranes with pore chemistry precisely tailored through molecular engineering. Our simulations highlighted the pivotal role of pore chemical characteristics in governing molecular selective separation behavior. Specifically, the pore walls in polyamide membranes, characterized by enhanced electronegative attributes, effectively regulate water-membrane-boric acid interactions, diffusion behavior, and migration barriers, enabling efficient selective transport while maintaining high water permeance. These investigations provide molecular-level insights that inform the design and fabrication of next-generation high-performance polymer membranes with pore-chemistry-modulated properties for the separation of small neutral molecules.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144504164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Efficient Integrator Scheme for Sampling the (Quantum) Isobaric-Isothermal Ensemble in (Path Integral) Molecular Dynamics Simulations.","authors":"Weihao Liang, Sihan Wang, Cong Wang, Weizhou Wang, Xinchen She, Chongbin Wang, Jiushu Shao, Jian Liu","doi":"10.1021/acs.jctc.5c00573","DOIUrl":"https://doi.org/10.1021/acs.jctc.5c00573","url":null,"abstract":"<p><p>Because most chemical or biological experiments are performed under conditions of controlled pressure and temperature, it is important to simulate the isobaric-isothermal ensemble at the atomic level to reveal the microscopic mechanism. By extending our efficient configuration sampling approach for the canonical ensemble, we propose a unified \"middle\" scheme to sample the coordinate (configuration) and volume distribution, which can accurately simulate either classical or quantum isobaric-isothermal processes. Various barostats and thermostats can be employed in the unified \"middle\" scheme for simulating real molecular systems with or without holonomic constraints. In particular, we demonstrate the recommended \"middle\" scheme by employing the Martyna-Tuckerman-Tobias-Klein barostat and stochastic cell-rescaling barostat, with the Langevin thermostat, in molecular simulation packages (DL_POLY, AMBER, GROMACS, and so forth). Benchmark numerical tests show that, without additional numerical effort, the \"middle\" scheme is competent in increasing the time interval by a factor of 5 ∼ 10 to achieve the same accuracy of converged results for most thermodynamic properties in (path integral) molecular dynamics simulations.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144504162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neural Mulliken Analysis: Molecular Graphs from Density Matrices for QSPR on Raw Quantum-Chemical Data.","authors":"Oleg I Gromov","doi":"10.1021/acs.jctc.5c00425","DOIUrl":"https://doi.org/10.1021/acs.jctc.5c00425","url":null,"abstract":"<p><p>Here, molecular graphs derived from the one-electron density matrix are introduced within a more general effort to explore whether incorporating electronic structure awareness allows a single model to both better generalize from small data and better learn molecular encodings. Diagonal density matrix blocks serve as atomic node embeddings, while off-diagonal blocks provide embeddings for <i>\"link\"</i> nodes related to atomic pairs. In a minimal basis, these embeddings have dimensions of only 45 and 81, yet no information is lost and the original density matrix can be fully reconstructed. Blocks from the basis set overlap matrix are used as edge embeddings to encode structural information and as weights for message aggregation operations. Additionally, element-wise multiplication performed during aggregation may provide access to electronic charges, analogous to Mulliken population analysis. The proposed concept was evaluated using data from the First and Second Solubility Challenges (Llinàs et al. <i>J.Chem. Inf. Model.</i> <b>2008</b>, <i>48</i>, 1289-1303; Llinàs and Avdeef <i>J. Chem. Inf. Model.</i> <b>2019</b>, <i>59</i>, 3036-3040). A graph neural network (GNN) trained on sets of 94 and 1000 drug-like molecules achieved improved solubility prediction accuracy (RMSE 0.63, <i>R</i>² 0.79 in SC-1 and RMSE of 0.83 and 0.92, <i>R</i>² of 0.57 and 0.79 on the \"tight\" and \"loose\" SC-2 test sets, respectively). If combined with existing techniques for predicting electron density from molecular structures, this approach is promising for addressing a range of chemical machine-learning problems.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144504165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Toward Using Matrix-free Tensor Decompositions to Systematically Improve Approximate Tensor-Networks.","authors":"Karl Pierce","doi":"10.1021/acs.jctc.5c00413","DOIUrl":"https://doi.org/10.1021/acs.jctc.5c00413","url":null,"abstract":"<p><p>We investigate a novel approach to approximate tensor-network contraction via the exact, matrix-free decomposition of full tensor-networks. We study this method as a means to eliminate the propagation of error in the approximation of tensor-networks. Importantly, this decomposition-based approach is generic, i.e., it does not depend on a specific tensor-network, the tensor index (physical) ordering, or the choice of tensor decomposition. Careful consideration should be made to determine the best decomposition strategy. Furthermore, this method does not rely on robust cancellation of errors (i.e., the Taylor expansion). As a means to study the effectiveness of the approach, we replace the exact contraction of the particle-particle ladder (PPL) tensor diagram in the popular coupled-cluster with single and double excitation (CCSD) method with a low-rank tensor decomposition, namely the canonical polyadic decomposition (CPD). With this approach, we replace an <math><mi>O</mi><mrow><mo>(</mo><msup><mi>N</mi><mn>6</mn></msup><mo>)</mo></mrow></math> tensor contractions with a potentially reduced-scaling <math><mi>O</mi><mrow><mo>(</mo><msup><mi>N</mi><mn>4</mn></msup><mi>R</mi><mo>)</mo></mrow></math> optimization problem, where <i>R</i> is the CP rank, and we reduce the computational storage of the PPL tensor from <math><mi>O</mi><mrow><mo>(</mo><msup><mi>N</mi><mn>4</mn></msup><mo>)</mo></mrow></math> to <math><mi>O</mi><mrow><mo>(</mo><mi>N</mi><mi>R</mi><mo>)</mo></mrow></math>, although we do not take advantage of this compression in this study. To minimize the cost of the CPD optimization, we utilize the iterative structure of CCSD to efficiently initialize the CPD optimization. We show that accurate chemically relevant energy values can be computed with an error of less than 1 kcal/mol using a relatively low CP rank.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144493166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Twin-Space Representation of Classical Mapping Model in the Constraint Phase Space Representation: Numerically Exact Approach to Open Quantum Systems.","authors":"Jiaji Zhang, Jian Liu, Lipeng Chen","doi":"10.1021/acs.jctc.5c00224","DOIUrl":"https://doi.org/10.1021/acs.jctc.5c00224","url":null,"abstract":"<p><p>The <i>constraint</i> coordinate-momentum <i>phase space</i> (CPS) has recently been developed to study nonadiabatic dynamics in gas-phase and condensed-phase molecular systems. Although the CPS formulation is exact for describing the discrete (electronic/vibrational/spin) state degrees of freedom (DOFs), when system-bath models in condensed phase are studied, previous works often employ the approximation by discretizing environmental bath DOFs. In this paper, we develop an exact trajectory-based phase space approach by adopting the twin-space (TS) formulation of quantum statistical mechanics, in which the density operator of the reduced system is transformed to the wave function of an expanded system with twice the DOFs. The classical mapping model (CMM) is then used to map the Hamiltonian of the expanded system to its equivalent classical counterpart on CPS. To demonstrate the applicability of the TS-CMM approach, we compare simulated population dynamics and nonlinear spectra for a few benchmark condensed phase system-bath models with those obtained from the hierarchical equations of motion method, which shows that our approach yields accurate dynamics of open quantum systems.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144493167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Basis-Discretized Surface Hopping for Auger Processes.","authors":"Xuhui Xu, Shriya Gumber, Oleg V Prezhdo, Run Long","doi":"10.1021/acs.jctc.5c00727","DOIUrl":"https://doi.org/10.1021/acs.jctc.5c00727","url":null,"abstract":"<p><p>We develop a basis-discretized nonadiabatic molecular dynamics approach that enables large-scale simulations involving millions of states. The approach introduces a density-of-states (DOS) weighted discretization scheme that maps electronic state quasi-continua onto a manageable discrete set, while preserving the original DOS profile, with enhanced resolution near band edges. Benchmarks using both time-dependent Schrödinger equation and fewest-switches surface hopping confirm that the dynamics remain consistent before and after the discretization. The method is applied to study Auger-type processes in a silicon quantum dot by reducing an otherwise intractable basis set to a manageable discretized model. The simulations show that biexciton and triexciton states significantly broaden energy dissipation pathways and accelerate electron-vibrational energy relaxation via Coulomb-mediated Auger processes, as compared to the single exciton dynamics. The work offers an efficient and robust framework for accurate simulations of excited-state dynamics in low-dimensional and nanoscale materials at the atomistic level.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144504163","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the Design Space of Machine Learning Models for Quantum Chemistry with a Fully Differentiable Framework.","authors":"Divya Suman, Jigyasa Nigam, Sandra Saade, Paolo Pegolo, Hanna Türk, Xing Zhang, Garnet Kin-Lic Chan, Michele Ceriotti","doi":"10.1021/acs.jctc.5c00522","DOIUrl":"https://doi.org/10.1021/acs.jctc.5c00522","url":null,"abstract":"<p><p>Traditional atomistic machine learning (ML) models serve as surrogates for quantum mechanical (QM) properties, predicting quantities such as dipole moments and polarizabilities directly from compositions and geometries of atomic configurations. With the emergence of ML approaches to predict the \"ingredients\" of a QM calculation, such as the ground-state charge density or the effective single-particle Hamiltonian, it has become possible to obtain multiple properties through analytical physics-based operations on these intermediate ML predictions. We present a framework that seamlessly integrates the prediction of an effective electronic Hamiltonian, for both molecular and condensed-phase systems, with PySCFAD, a differentiable QM workflow. This integration facilitates training models indirectly against functions of the Hamiltonian, such as electronic energy levels, dipole moments, polarizability, etc. We then use this framework to explore various possible choices within the design space of hybrid ML/QM models, examining the influence of incorporating multiple targets on model performance and learning a reduced-basis ML Hamiltonian that can reproduce targets computed on a much larger basis. Our benchmarks evaluate the accuracy and transferability of these hybrid models, compare them against predictions of atomic properties from their surrogate models, and provide indications to guide the design of the interface between the ML and QM components of the model.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144482562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"Jakub Kára*,&nbsp;Kyle Acheson and Adam Kirrander*,&nbsp;","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":"21 12","pages":"XXX-XXX XXX-XXX"},"PeriodicalIF":5.7,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.4c01750","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144429724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Communication Pathway Analysis within Protein-Nucleic Acid Complexes.","authors":"Sneha Bheemireddy, Roy González-Alemán, Emmanuelle Bignon, Yasaman Karami","doi":"10.1021/acs.jctc.5c00445","DOIUrl":"https://doi.org/10.1021/acs.jctc.5c00445","url":null,"abstract":"<p><p>Inter-residue communication forms a vast and intricate network that underpins essential biological processes such as catalysis, gene expression, and cell signaling. Allostery, a crucial phenomenon where distant regions of a macromolecule are energetically coupled to elicit functional responses, operates through these intricate communication networks within macromolecular complexes. Despite the pivotal role of nucleic acids in these networks, their contributions to allostery have largely been overlooked. To address this gap, we developed ComPASS, a large-scale computational method designed to study communication networks in protein-protein and protein-nucleic acid complexes. Recognizing the significance of dynamics in the communication of macromolecules, our approach leverages molecular dynamics (MD) simulation data to extract inter-residue key properties, including dynamical correlations, interactions, and distances. These properties are integrated to construct a weighted communication network that comprehensively represents the dependencies among amino acids and nucleotides. Using ComPASS, we uncovered distinct mechanisms of signal transmission in diverse macromolecular systems. In Cysteinyl-tRNA synthetase, the central domain was found to mediate coordination between substrate recognition and enzymatic activity, ensuring functional precision. In the LacI repressor, allosteric communication occurs through interface pathways within the dimer, effectively linking ligand sensing to DNA binding. For the Type IIF restriction endonuclease Bse634I, structural communication across the dimer and tetramer interfaces was crucial for specific DNA recognition. In the liver X receptor, a key helical region was identified as a bridge connecting ligand-binding events to DNA interactions. Finally, our analysis with ComPASS aligned with previous literature, confirming the role of H2A L1 loops in mediating communication across histone interfaces and coordinating interactions between structural domains in nucleosome complexes. ComPASS is available as an open-source tool, maintained at https://github.com/yasamankarami/compass. By offering an integrated framework for studying communication networks, ComPASS advances our understanding of conformational dynamics, particularly within protein-nucleic acid complexes.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144473416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}