Journal of Chemical Theory and Computation最新文献_第6页

Hybrid Gauge Approach for Accurate Real-Time TDDFT Simulations with Numerical Atomic Orbitals. 基于原子轨道的精确实时TDDFT模拟的混合测量方法。

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2025-04-08 Epub Date: 2025-03-24 DOI: 10.1021/acs.jctc.5c00111

Haotian Zhao, Lixin He

{"title":"Hybrid Gauge Approach for Accurate Real-Time TDDFT Simulations with Numerical Atomic Orbitals.","authors":"Haotian Zhao, Lixin He","doi":"10.1021/acs.jctc.5c00111","DOIUrl":"10.1021/acs.jctc.5c00111","url":null,"abstract":"Ultrafast real-time dynamics are critical for understanding a broad range of physical processes. Real-time time-dependent density functional theory (rt-TDDFT) has emerged as a powerful computational tool for simulating these dynamics, offering insight into ultrafast processes and light-matter interactions. In periodic systems, the velocity gauge is essential because it preserves the system's periodicity under an external electric field. Numerical atomic orbitals (NAOs) are widely employed in rt-TDDFT codes due to their efficiency and localized nature. However, directly applying the velocity gauge within the NAO basis set neglects the position-dependent phase variations within atomic orbitals induced by the vector potential, leading to significant computational errors - particularly in current calculations. To resolve this issue, we develop a hybrid gauge that incorporates both the electric field and the vector potential, preserving the essential phase information in atomic orbitals and thereby eliminating these errors. Our benchmark results demonstrate that the hybrid gauge fully resolves the issues encountered with the velocity gauge in NAO-based calculations, providing accurate and reliable results. This algorithm offers a robust framework for future studies on ultrafast dynamics in periodic systems using NAO bases.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"3335-3341"},"PeriodicalIF":5.7,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143699102","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}

引用次数: 0

Revisiting Many-Body Interaction Heat Current and Thermal Conductivity Calculations Using the Moment Tensor Potential/LAMMPS Interface. 利用矩张量势/LAMMPS界面重述多体相互作用热流和导热系数计算。

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2025-04-08 Epub Date: 2025-03-29 DOI: 10.1021/acs.jctc.4c01659

Siu Ting Tai, Chen Wang, Ruihuan Cheng, Yue Chen

{"title":"Revisiting Many-Body Interaction Heat Current and Thermal Conductivity Calculations Using the Moment Tensor Potential/LAMMPS Interface.","authors":"Siu Ting Tai, Chen Wang, Ruihuan Cheng, Yue Chen","doi":"10.1021/acs.jctc.4c01659","DOIUrl":"10.1021/acs.jctc.4c01659","url":null,"abstract":"The definition of heat current operator for systems for nonpairwise additive interactions and its impact on related lattice thermal conductivity (κL) via molecular dynamics (MD) simulation are ambiguous and controversial when migrating from empirical potential models to machine learning potential (MLP) models. Herein, we study and compare the significance of many-body interaction with heat current computation in one of the most popular MLP models, the moment tensor potential (MTP). Nonequilibrium MD simulations and equilibrium MD simulations among four different materials were performed, and inconsistencies in energy conservation between the simulation thermostat and the pairwise calculator were found. A new virial stress tensor expression with a many-body heat current description was integrated inside the MTP, and we uncovered the influence of the modification that could alter the κL results by 29-64% using the equilibrium MD computational approach. Our work demonstrates the importance of a many-body description during thermal analysis in MD simulations when MLPs are of concern.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"3649-3657"},"PeriodicalIF":5.7,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143741743","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}

引用次数: 0

Targeted TPS Shooting Using Computer Vision to Generate Ensemble of Trajectories. 利用计算机视觉生成轨迹集合的目标TPS射击。

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2025-04-08 Epub Date: 2025-03-17 DOI: 10.1021/acs.jctc.4c01725

Kseniia Korchagina, Steven D Schwartz

引用次数: 0

Learning Multiple Potential Energy Surfaces by Automated Discovery of a Compatible Representation. 通过自动发现兼容表示学习多个势能面。

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2025-04-08 Epub Date: 2025-03-21 DOI: 10.1021/acs.jctc.5c00178

Yinan Shu, Zoltan Varga, Dayou Zhang, Qinghui Meng, Aiswarya M Parameswaran, Jian-Ge Zhou, Donald G Truhlar

{"title":"Learning Multiple Potential Energy Surfaces by Automated Discovery of a Compatible Representation.","authors":"Yinan Shu, Zoltan Varga, Dayou Zhang, Qinghui Meng, Aiswarya M Parameswaran, Jian-Ge Zhou, Donald G Truhlar","doi":"10.1021/acs.jctc.5c00178","DOIUrl":"10.1021/acs.jctc.5c00178","url":null,"abstract":"Creating analytic representations of multiple potential energy surfaces for modeling electronically nonadiabatic processes is a major challenge being addressed in various ways by the chemical dynamics community. In this work, we introduce a new method that can achieve convenient learning of multiple potential energy surfaces (PESs) and their gradients (negatives of the forces) for a polyatomic system. This new method, called compatibilization by deep neural network (CDNN), is demonstrated to be accurate and, even more importantly, to be automatic. The only required input is a database with geometries and potential energies. The method produces a matrix, called the compatible potential energy matrix (CPEM), that may be interpreted as the electronic Hamiltonian in an implicit nonadiabatic basis, and the analytic adiabatic potential energy surfaces and their gradients are obtained by diagonalization and automatic differentiation. We show that the CPEM, which is neither adiabatic nor necessarily diabatic, can be discovered automatically during the learning procedure by the special design of a CDNN architecture. We believe that the CDNN method will be very useful in practice for learning coupled PESs for polyatomic systems because it is accurate and fully automatic.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"3342-3352"},"PeriodicalIF":5.7,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143672919","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}

引用次数: 0

Multisite λ-Dynamics for Protein-DNA Binding Affinity Prediction. 蛋白质- dna结合亲和力预测的多位点λ动力学。

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2025-04-08 Epub Date: 2025-03-24 DOI: 10.1021/acs.jctc.4c01408

Carmen Al Masri, Jonah Z Vilseck, Jin Yu, Ryan L Hayes

引用次数: 0

Plateaus in the Potentials of Density-Functional Theory: Analytical Derivation and Useful Approximations. 密度泛函理论势中的平台：解析推导和有用的近似。

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2025-04-08 Epub Date: 2025-03-27 DOI: 10.1021/acs.jctc.4c01771

Nathan E Rahat, Eli Kraisler

{"title":"Plateaus in the Potentials of Density-Functional Theory: Analytical Derivation and Useful Approximations.","authors":"Nathan E Rahat, Eli Kraisler","doi":"10.1021/acs.jctc.4c01771","DOIUrl":"10.1021/acs.jctc.4c01771","url":null,"abstract":"Density functional theory (DFT) is an extremely efficient and widely used method for electronic structure calculations. However, the quality of such calculations crucially depends on the quality of the approximation used for the exchange-correlation functional, for which there is no exact form. One important feature of the exact exchange-correlation potential, which common approximations usually do not capture, is the spatial steps and plateaus that occur in various scenarios, including ionization, excitation, dissociation, and charge transfer. In this paper, we derive an analytical expression for the plateau in the Kohn-Sham potential that forms around the center of the system, when the number of electrons infinitesimally surpasses an integer. The resulting formula is the first analytical expression of its kind. The derivation is performed using the orbital-free DFT framework, analyzing both the Kohn-Sham-Pauli and the Pauli potentials. Analytical results are compared to exact calculations for small atomic systems, showing close correspondence and high accuracy. Furthermore, it is shown that plateaus can be produced also when relying on approximate electron densities, even those obtained with the simplest exchange-correlation form─the local density approximation.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"3476-3492"},"PeriodicalIF":5.7,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143727086","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}

引用次数: 0

Going beyond the Computational Tool: Fermi Potential from DFT as an Electron (De)Localization Descriptor for Correlated Wave Functions. 超越计算工具：DFT中的费米势作为相关波函数的电子（去）局域描述符。

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2025-04-08 Epub Date: 2025-03-26 DOI: 10.1021/acs.jctc.4c01745

Elena O Levina, Vladimir G Tsirelson

{"title":"Going beyond the Computational Tool: Fermi Potential from DFT as an Electron (De)Localization Descriptor for Correlated Wave Functions.","authors":"Elena O Levina, Vladimir G Tsirelson","doi":"10.1021/acs.jctc.4c01745","DOIUrl":"10.1021/acs.jctc.4c01745","url":null,"abstract":"The Fermi potential, appearing in the basic equations of density functional theory (DFT), has been found to be an indispensable tool for the measurement of electron localization intensity in molecules and crystals. The regions of the most intensive electron localization appear there as negative wells, while the positive barriers of the Fermi potential prevent the electron concentration there to some extent. The shape of the Fermi potential distribution in covalent bonds reflects the bond order, while the structure of its components is able to provide valuable information about the bonding nature, e.g., helping to draw the line between covalent and noncovalent bonds. The accuracy of the Fermi potential's estimates of electron (de)localization stems from the ability of its components to preserve all the main features of the exchange-correlation hole behavior within the one-electron functions, while other popular descriptors can easily fail in this task. Such analysis is not restricted to DFT calculations; when applied to post-Hartree-Fock wave functions, it unravels details of how instantaneous Coulomb correlation prevents the overestimation of electron localization intensity in strongly correlated and ordinary systems. Generally, the slight decrease in localization intensity is achieved by the intensified response of electron correlation to variations in electron density, while in systems where instantaneous Coulomb correlation is particularly important, it also comes from the growth in the exchange-correlation hole mobility; the average hole depth increases in all cases.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"3440-3459"},"PeriodicalIF":5.7,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143707743","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}

引用次数: 0

Comparative Analysis of Reinforcement Learning Algorithms for Finding Reaction Pathways: Insights from a Large Benchmark Data Set. 寻找反应路径的强化学习算法的比较分析：来自大型基准数据集的见解。

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2025-04-08 Epub Date: 2025-03-19 DOI: 10.1021/acs.jctc.4c01780

Yoshihiro Matsumura, Koji Tabata, Tamiki Komatsuzaki

{"title":"Comparative Analysis of Reinforcement Learning Algorithms for Finding Reaction Pathways: Insights from a Large Benchmark Data Set.","authors":"Yoshihiro Matsumura, Koji Tabata, Tamiki Komatsuzaki","doi":"10.1021/acs.jctc.4c01780","DOIUrl":"10.1021/acs.jctc.4c01780","url":null,"abstract":"The identification of kinetically feasible reaction pathways that connect a reactant to its product, including numerous intermediates and transition states, is crucial for predicting chemical reactions and elucidating reaction mechanisms. However, as molecular systems become increasingly complex or larger, the number of local minimum structures and transition states grows, which makes this task challenging, even with advanced computational approaches. We introduced a reinforcement learning algorithm to efficiently identify a kinetically feasible reaction pathway between a given local minimum structure for the reactant and a given one for the product, starting from the reactant. The performance of the algorithm was validated using a benchmark data set of large-scale chemical reaction path networks. Several search policies were proposed, using metrics based on energetic or structural similarity to the product's goal structure, for each local minimum structure candidate found during the search. The performances of baseline greedy, random, and uniform search policies varied substantially depending on the system. In contrast, exploration-exploitation balanced policies such as Thompson sampling, probability of improvement, and expected improvement consistently demonstrated stable and high performance. Furthermore, we characterized the search mechanisms that depend on different policies in detail. This study also addressed potential avenues for further research, such as hierarchical reinforcement learning and multiobjective optimization, which could deepen the problem setting explored in this study.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"3523-3535"},"PeriodicalIF":5.7,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143655486","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}

引用次数: 0

First-Principles Simulations of Molecular Optoelectronic Materials: Elementary Excitations and Spatiotemporal Dynamics. 分子光电材料的第一性原理模拟：基本激发和时空动力学。

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2025-04-08 Epub Date: 2025-03-19 DOI: 10.1021/acs.jctc.5c00312

Irene Burghardt

引用次数: 0

Unsupervised Learning of Progress Coordinates during Weighted Ensemble Simulations: Application to NTL9 Protein Folding. 加权集成模拟过程中进度坐标的无监督学习：在NTL9蛋白折叠中的应用。

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2025-04-08 Epub Date: 2025-03-19 DOI: 10.1021/acs.jctc.4c01136

Jeremy M G Leung, Nicolas C Frazee, Alexander Brace, Anthony T Bogetti, Arvind Ramanathan, Lillian T Chong

{"title":"Unsupervised Learning of Progress Coordinates during Weighted Ensemble Simulations: Application to NTL9 Protein Folding.","authors":"Jeremy M G Leung, Nicolas C Frazee, Alexander Brace, Anthony T Bogetti, Arvind Ramanathan, Lillian T Chong","doi":"10.1021/acs.jctc.4c01136","DOIUrl":"10.1021/acs.jctc.4c01136","url":null,"abstract":"A major challenge for many rare-event sampling strategies is the identification of progress coordinates that capture the slowest relevant motions. Machine-learning methods that can identify progress coordinates in an unsupervised manner have therefore been of great interest to the simulation community. Here, we developed a general method for identifying progress coordinates \"on-the-fly\" during weighted ensemble (WE) rare-event sampling via deep learning (DL) of outliers among sampled conformations. Our method identifies outliers in a latent space model of the system's sampled conformations that is periodically trained using a convolutional variational autoencoder. As a proof of principle, we applied our DL-enhanced WE method to simulate the NTL9 protein folding process. To enable rapid tests, our simulations propagated discrete-state synthetic molecular dynamics trajectories using a generative, fine-grained Markov state model. Results revealed that our on-the-fly DL of outliers enhanced the efficiency of WE by >3-fold in estimating the folding rate constant. Our efforts are a significant step forward in the unsupervised learning of slow coordinates during rare event sampling.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"3691-3699"},"PeriodicalIF":5.7,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143655502","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}

引用次数: 0