Journal of Chemical Theory and Computation最新文献_第8页

Deep Learning Potential Assisted Prediction of Local Structure and Thermophysical Properties of the SrCl₂-KCl-MgCl₂ Melt. 深度学习势能辅助预测 SrCl2-KCl-MgCl2 熔体的局部结构和热物理性质。

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2024-09-10 Epub Date: 2024-08-28 DOI: 10.1021/acs.jctc.4c00824

Jia Zhao, Taixi Feng, Guimin Lu

引用次数: 0

Five-Site Water Models for Ice and Liquid Water Generated by a Series-Parallel Machine Learning Strategy. 通过串并联机器学习策略生成冰水和液态水的五点水模型。

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2024-09-10 Epub Date: 2024-08-12 DOI: 10.1021/acs.jctc.4c00440

Jian Wang, Haitao Hei, Yonggang Zheng, Hongwu Zhang, Hongfei Ye

{"title":"Five-Site Water Models for Ice and Liquid Water Generated by a Series-Parallel Machine Learning Strategy.","authors":"Jian Wang, Haitao Hei, Yonggang Zheng, Hongwu Zhang, Hongfei Ye","doi":"10.1021/acs.jctc.4c00440","DOIUrl":"10.1021/acs.jctc.4c00440","url":null,"abstract":"Icing, a common natural phenomenon, always originates from a molecule. Molecular simulation is crucial for understanding the relevant process but still faces a great challenge in obtaining a uniform and accurate description of ice and liquid water with limited model parameters. Here, we propose a series-parallel machine learning (ML) approach consisting of a classification back-propagation neural network (BPNN), parallel regression BPNNs, and a genetic algorithm to establish conventional TIP5P-BG and temperature-dependent TIP5P-BGT models. The established water models exhibit a comprehensive balance among the crucial physical properties (melting point, density, vaporization enthalpy, self-diffusion coefficient, and viscosity) with mean absolute percentage errors of 2.65 and 2.40%, respectively, and excellent predictive performance on the related properties of liquid water. For ice, the simulation results on the critical nucleus size and growth rate are in good accordance with experiments. This work offers a powerful molecular model for phase transition and icing in nanoconfinement and a construction strategy for a complex molecular model in the extreme case.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":null,"pages":null},"PeriodicalIF":5.7,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141915466","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

Interconnection between Polarization-Detected and Population-Detected Signals: Theoretical Results and Ab Initio Simulations. 极化探测信号与种群探测信号之间的相互联系：理论结果和 Ab Initio 仿真。

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2024-09-10 Epub Date: 2024-08-26 DOI: 10.1021/acs.jctc.4c00592

Kewei Sun, Luis Vasquez, Raffaele Borrelli, Lipeng Chen, Yang Zhao, Maxim F Gelin

{"title":"Interconnection between Polarization-Detected and Population-Detected Signals: Theoretical Results and Ab Initio Simulations.","authors":"Kewei Sun, Luis Vasquez, Raffaele Borrelli, Lipeng Chen, Yang Zhao, Maxim F Gelin","doi":"10.1021/acs.jctc.4c00592","DOIUrl":"10.1021/acs.jctc.4c00592","url":null,"abstract":"Most of spectroscopic signals are specified by the nonlinear laser-induced polarization. In recent years, population-detection of signals becomes a trend in femtosecond spectroscopy. Polarization-detected (PD) and population-detected signals are fundamentally different, because they are determined by photoinduced processes acting on disparate time scales. In this work, we consider the fluorescence-detected (FD) N-wave-mixing (NWM) signal as a representative example of population-detected signals, derive a rigorous expression for this signal, and discuss its approximate variants suitable for numerical simulations. This leads us to the definition of the phenomenological FD (PFD) signal, which contains as a special case all definitions of FD signals available in the literature. Then we formulate and prove the population-polarization equivalence (PPE) theorem, which states that PFD NWM signals produced by (possibly strong) laser pulses can be evaluated as conventional PD signals in which the effective polarization is determined by the PFD transition dipole moment operator. We use the PPE theorem for the construction of the ab initio protocol for the simulation of PFD 4WM signals. As an example, we calculate electronic two-dimensional (2D) PFD spectra of the gas-phase pyrazine and compare them with the corresponding PD 2D spectra.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":null,"pages":null},"PeriodicalIF":5.7,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142054166","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

Martini 3 OliGo̅mers: A Scalable Approach for Multimers and Fibrils in GROMACS. Martini 3 OliGo̅mers：在 GROMACS 中实现多聚物和纤维的可扩展方法。

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2024-09-10 Epub Date: 2024-08-27 DOI: 10.1021/acs.jctc.4c00677

Ksenia Korshunova, Julius Kiuru, Juho Liekkinen, Giray Enkavi, Ilpo Vattulainen, Bart M H Bruininks

{"title":"Martini 3 OliGo̅mers: A Scalable Approach for Multimers and Fibrils in GROMACS.","authors":"Ksenia Korshunova, Julius Kiuru, Juho Liekkinen, Giray Enkavi, Ilpo Vattulainen, Bart M H Bruininks","doi":"10.1021/acs.jctc.4c00677","DOIUrl":"10.1021/acs.jctc.4c00677","url":null,"abstract":"Martini 3 is a widely used coarse-grained simulation method for large-scale biomolecular simulations. It can be combined with a Go̅ model to realistically describe higher-order protein structures while allowing the folding and unfolding events. However, as of today, this method has largely been used only for individual monomers. In this article, we describe how the Go̅ model can be implemented within the framework of Martini 3 for a multimer system, taking into account both intramolecular and intermolecular interactions in an oligomeric protein system. We demonstrate the method by showing how it can be applied to both structural stability maintenance and assembly/disassembly of protein oligomers, using aquaporin tetramer, insulin dimer, and amyloid-β fibril as examples. We find that addition of intermolecular Go̅ potentials stabilizes the quaternary structure of proteins. The strength of the Go̅ potentials can be tuned so that the internal fluctuations of proteins match the behavior of atomistic simulation models, however, the results also show that the use of too strong intermolecular Go̅ potentials weakens the chemical specificity of oligomerization. The Martini-Go̅ model presented here enables the use of Go̅ potentials in oligomeric molecular systems in a computationally efficient and parallelizable manner, especially in the case of homopolymers, where the number of identical protein monomers is high. This paves the way for coarse-grained simulations of large protein complexes, such as viral protein capsids and prion fibrils, in complex biological environments.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":null,"pages":null},"PeriodicalIF":5.7,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11391574/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142071399","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}

引用次数: 0

The Localized Active Space Method with Unitary Selective Coupled Cluster 具有单元选择性耦合簇的局部主动空间法

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2024-09-10 DOI: 10.1021/acs.jctc.4c0052810.1021/acs.jctc.4c00528

Abhishek Mitra, Ruhee D’Cunha, Qiaohong Wang, Matthew R. Hermes, Yuri Alexeev, Stephen K. Gray*, Matthew Otten* and Laura Gagliardi*,

{"title":"The Localized Active Space Method with Unitary Selective Coupled Cluster","authors":"Abhishek Mitra, Ruhee D’Cunha, Qiaohong Wang, Matthew R. Hermes, Yuri Alexeev, Stephen K. Gray*, Matthew Otten* and Laura Gagliardi*, ","doi":"10.1021/acs.jctc.4c0052810.1021/acs.jctc.4c00528","DOIUrl":"https://doi.org/10.1021/acs.jctc.4c00528https://doi.org/10.1021/acs.jctc.4c00528","url":null,"abstract":"We introduce a hybrid quantum-classical algorithm, the localized active space unitary selective coupled cluster singles and doubles (LAS-USCCSD) method. Derived from the localized active space unitary coupled cluster (LAS-UCCSD) method, LAS-USCCSD first performs a classical LASSCF calculation, then selectively identifies the most important parameters (cluster amplitudes used to build the multireference UCC ansatz) for restoring interfragment interaction energy using this reduced set of parameters with the variational quantum eigensolver method. We benchmark LAS-USCCSD against LAS-UCCSD by calculating the total energies of (H2)2, (H2)4, and trans-butadiene, and the magnetic coupling constant for a bimetallic compound [Cr2(OH)3(NH3)6]3+. For these systems, we find that LAS-USCCSD reduces the number of required parameters and thus the circuit depth by at least 1 order of magnitude, an aspect which is important for the practical implementation of multireference hybrid quantum-classical algorithms like LAS-UCCSD on near-term quantum computers.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":null,"pages":null},"PeriodicalIF":5.7,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142309782","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

Training Machine-Learned Density Functionals on Band Gaps. 在带隙上训练机器学习密度函数。

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2024-09-10 Epub Date: 2024-08-23 DOI: 10.1021/acs.jctc.4c00999

Kyle Bystrom, Stefano Falletta, Boris Kozinsky

{"title":"Training Machine-Learned Density Functionals on Band Gaps.","authors":"Kyle Bystrom, Stefano Falletta, Boris Kozinsky","doi":"10.1021/acs.jctc.4c00999","DOIUrl":"10.1021/acs.jctc.4c00999","url":null,"abstract":"The systematic underestimation of band gaps is one of the most fundamental challenges in semilocal density functional theory (DFT). In addition to hindering the application of DFT to predicting electronic properties, the band gap problem is intimately related to self-interaction and delocalization errors, which make the study of charge transfer mechanisms with DFT difficult. To expand the range of available tools for addressing the band gap problem, we design an approach for machine learning density functionals based on Gaussian processes to explicitly fit single-particle energy levels. We also introduce nonlocal features of the density matrix that are expressive enough to fit these single-particle levels. Combining these developments, we train a machine-learned functional for the exact exchange energy that predicts molecular energy gaps and reaction energies of a wide range of molecules in excellent agreement with reference hybrid DFT calculations. In addition, while being trained solely on molecular data, our model predicts reasonable formation energies of polarons in solids, showcasing its transferability and robustness. We discuss how this approach can be generalized to full exchange-correlation functionals, thus paving the way to the design of state-of-the-art functionals for the prediction of electronic properties of molecules and materials.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":null,"pages":null},"PeriodicalIF":5.7,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142043785","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

Efficient Shift-and-Invert Preconditioning for Multi-GPU Accelerated Density Functional Calculations. 多 GPU 加速密度函数计算的高效移位和反转预处理。

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2024-09-10 Epub Date: 2024-08-27 DOI: 10.1021/acs.jctc.4c00721

Jeheon Woo, Woo Youn Kim, Sunghwan Choi

{"title":"Efficient Shift-and-Invert Preconditioning for Multi-GPU Accelerated Density Functional Calculations.","authors":"Jeheon Woo, Woo Youn Kim, Sunghwan Choi","doi":"10.1021/acs.jctc.4c00721","DOIUrl":"10.1021/acs.jctc.4c00721","url":null,"abstract":"To accelerate the iterative diagonalization of electronic structure calculations, we propose a new inexact shift-and-invert (ISI) preconditioning method. The key idea is to improve shift values in the ISI preconditioning to be closer to the exact eigenvalues, leading to a significant boost in the convergence speed of the iterative diagonalization. Furthermore, we adopted a preconditioned conjugate gradient solver to rapidly evaluate an inversion process. Finally, we accelerated overall processes, including the proposed modification, with state-of-the-art graphical processing units (GPUs) and assessed its parallel efficiency with real-space density functional calculations of 1D, 2D, and 3D periodic systems. Our method attains both fast diagonalization convergence and high multi-GPU parallel efficiency. This is evident from the fact that single-point density functional calculations for hundreds of atom systems can be done in approximately 10 s using 8 GPUs. The proposed method can be generally applied to any electronic structure calculation methods involving large-scale diagonalizations.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":null,"pages":null},"PeriodicalIF":5.7,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11391578/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142071398","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}

引用次数: 0

Driven Self-Assembly of Patchy Particles Overcoming Equilibrium Limitations 克服平衡限制的斑状颗粒驱动型自组装

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2024-09-10 DOI: 10.1021/acs.jctc.4c0111810.1021/acs.jctc.4c01118

Shubhadeep Nag, and , Gili Bisker*,

引用次数: 0

Efficient Generation of Torsional Energy Profiles by Multifidelity Gaussian Processes for Hindered Rotor Corrections. 通过多保真度高斯过程高效生成扭转能量曲线，用于受阻转子修正。

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2024-09-10 Epub Date: 2024-08-20 DOI: 10.1021/acs.jctc.4c00475

Maximilian Fleck, Wassja A Kopp, Narasimhan Viswanathan, Niels Hansen, Joachim Gross, Kai Leonhard

{"title":"Efficient Generation of Torsional Energy Profiles by Multifidelity Gaussian Processes for Hindered Rotor Corrections.","authors":"Maximilian Fleck, Wassja A Kopp, Narasimhan Viswanathan, Niels Hansen, Joachim Gross, Kai Leonhard","doi":"10.1021/acs.jctc.4c00475","DOIUrl":"10.1021/acs.jctc.4c00475","url":null,"abstract":"Accurate thermochemistry computations often require proper treatment of torsional modes. The one-dimensional hindered rotor model has proven to be a computationally efficient solution, given a sufficiently accurate potential energy surface. Methods that provide potential energies at various compromises of uncertainty and computational time demand can be optimally combined within a multifidelity treatment. In this study, we demonstrate how multifidelity modeling leads to (1) smooth interpolation along low-fidelity scan points with uncertainty estimates, (2) inclusion of high-fidelity data that change the energetic order of conformations, and (3) predicting best next-point calculations to extend an initial coarse grid. Our diverse application set comprises molecules, clusters, and transition states of alcohols, ethers, and rings. We discuss limitations for cases in which the low-fidelity computation is highly unreliable. Different features of the potential energy curve affect different quantities. To obtain \"optimal\" fits, we apply strategies ranging from simple minimization of deviations to developing an acquisition function tailored for statistical thermodynamics. Bayesian prediction of best next calculations can save a substantial amount of computation time for one- and multidimensional hindered rotors.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":null,"pages":null},"PeriodicalIF":5.7,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142007792","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

Exploring the Polymorphism of Dicalcium Silicates Using Transfer Learning Enhanced Machine Learning Atomic Potentials. 利用迁移学习增强型机器学习原子势探索硅酸二钙的多态性。

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2024-09-10 Epub Date: 2024-08-22 DOI: 10.1021/acs.jctc.4c00479

Jon López-Zorrilla, Xabier M Aretxabaleta, Hegoi Manzano

{"title":"Exploring the Polymorphism of Dicalcium Silicates Using Transfer Learning Enhanced Machine Learning Atomic Potentials.","authors":"Jon López-Zorrilla, Xabier M Aretxabaleta, Hegoi Manzano","doi":"10.1021/acs.jctc.4c00479","DOIUrl":"10.1021/acs.jctc.4c00479","url":null,"abstract":"Belitic cements are a greener alternative to Ordinary Portland Cement due to the lower CO2 associated with their production. However, their low reactivity with water is currently a drawback, resulting in longer setting times. In this study, we utilize a combination of evolutionary algorithms and machine learning atomic potentials (MLPs) to identify previously unreported belite polymorphs that may exhibit higher hydraulic reactivity than the known phases. To address the high computational demand of this methodology, we propose a novel transfer learning approach for generating MLPs. First, the models are pretrained on a large set of classical data (ReaxFF) and then retrained with density functional theory (DFT) data. We demonstrate that the transfer learning enhanced potentials exhibit higher accuracy, require less training data, and are more transferable than those trained exclusively on DFT data. The generated machine learning potential enables a fast, exhaustive, and reliable exploration of the dicalcium silicate polymorphs. This includes studying their stability through phonon analysis and calculating their structural and elastic properties. Overall, we identify ten new belite polymorphs within the energy range of the existing ones, including a layered phase with potentially high reactivity.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":null,"pages":null},"PeriodicalIF":5.7,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142015506","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