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

Dependence of Thermally Activated Relaxation of Crystalline Stems on the Molecular Topology at Crystalline/Amorphous Interfaces in Polyethylene 结晶茎的热激活松弛与聚乙烯结晶/非晶界面分子拓扑的关系

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2024-10-28 DOI: 10.1021/acs.jctc.4c0040010.1021/acs.jctc.4c00400

Yiyang Li, Jianlan Ye, Vipin Agrawal and Jay Oswald*,

{"title":"Dependence of Thermally Activated Relaxation of Crystalline Stems on the Molecular Topology at Crystalline/Amorphous Interfaces in Polyethylene","authors":"Yiyang Li, Jianlan Ye, Vipin Agrawal and Jay Oswald*, ","doi":"10.1021/acs.jctc.4c0040010.1021/acs.jctc.4c00400","DOIUrl":"https://doi.org/10.1021/acs.jctc.4c00400https://doi.org/10.1021/acs.jctc.4c00400","url":null,"abstract":"We investigate the relaxation dynamics of crystalline stems in relation to the molecular topology of the crystalline/amorphous interface, employing coarse–grained molecular dynamics. To efficiently generate model semicrystalline systems of linear polyethylene with a realistic interphase morphology, we simplified the Monte Carlo method by introducing molecular dynamics for faster relaxation. The structural properties of the generated systems are validated against experimental measurements, theoretical predictions, and existing simulation data. The models suggest that the probability distribution of loop-entry sites on the lamellar surface can be described by a power law in terms of the distance between the entry sites. By considering realistic interphase morphology, we are able to improve the prediction of the overall activation energy for the relaxation of crystalline stems, aligning it closely with experimental measurements. The largest model predicts that crystalline stems connected via large loops, i.e., those that exceed the entanglement length, and long tails are associated with increased activation energy; whereas stems connected to shorter tails show the lowest activation energy. These predictions can guide the future development of tougher semicrystalline polymers by providing insights into how amorphous chain morphology contributes to the activation energy and the relaxation dynamics of crystalline chains.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":null,"pages":null},"PeriodicalIF":5.7,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142608871","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

Comparison of Methodologies for Absolute Binding Free Energy Calculations of Ligands to Intrinsically Disordered Proteins 配体与本质无序蛋白绝对结合自由能计算方法的比较

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2024-10-28 DOI: 10.1021/acs.jctc.4c0094210.1021/acs.jctc.4c00942

Michail Papadourakis, Zoe Cournia, Antonia S. J. S. Mey* and Julien Michel*,

{"title":"Comparison of Methodologies for Absolute Binding Free Energy Calculations of Ligands to Intrinsically Disordered Proteins","authors":"Michail Papadourakis, Zoe Cournia, Antonia S. J. S. Mey* and Julien Michel*, ","doi":"10.1021/acs.jctc.4c0094210.1021/acs.jctc.4c00942","DOIUrl":"https://doi.org/10.1021/acs.jctc.4c00942https://doi.org/10.1021/acs.jctc.4c00942","url":null,"abstract":"Modulating the function of Intrinsically Disordered Proteins (IDPs) with small molecules is of considerable importance given the crucial roles of IDPs in the pathophysiology of numerous diseases. Reported binding affinities for ligands to diverse IDPs vary broadly, and little is known about the detailed molecular mechanisms that underpin ligand efficacy. Molecular simulations of IDP ligand binding mechanisms can help us understand the mode of action of small molecule inhibitors of IDP function, but it is still unclear how binding energies can be modeled rigorously for such a flexible class of proteins. Here, we compare alchemical absolute binding free energy calculations (ABFE) and Markov-State Modeling (MSM) protocols to model the binding of the small molecule 10058-F4 to a disordered peptide extracted from a segment of the oncoprotein c-Myc. The ABFE results produce binding energy estimates that are sensitive to the choice of reference structure. In contrast, the MSM results produce more reproducible binding energy estimates consistent with weak mM binding affinities and transient intermolecular contacts reported in the literature.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":null,"pages":null},"PeriodicalIF":5.7,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acs.jctc.4c00942","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142609030","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

Crystal Structure Prediction Using Generative Adversarial Network with Data-Driven Latent Space Fusion Strategy 利用数据驱动的潜空间融合策略生成对抗网络进行晶体结构预测

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2024-10-25 DOI: 10.1021/acs.jctc.4c0109610.1021/acs.jctc.4c01096

Zian Chen, Haichao Li, Chen Zhang, Hongbin Zhang, Yongxiao Zhao, Jian Cao, Tao He, Lina Xu*, Hongping Xiao, Yi Li, Hezhu Shao, Xiaoyu Yang, Xiao He* and Guoyong Fang*,

{"title":"Crystal Structure Prediction Using Generative Adversarial Network with Data-Driven Latent Space Fusion Strategy","authors":"Zian Chen, Haichao Li, Chen Zhang, Hongbin Zhang, Yongxiao Zhao, Jian Cao, Tao He, Lina Xu*, Hongping Xiao, Yi Li, Hezhu Shao, Xiaoyu Yang, Xiao He* and Guoyong Fang*, ","doi":"10.1021/acs.jctc.4c0109610.1021/acs.jctc.4c01096","DOIUrl":"https://doi.org/10.1021/acs.jctc.4c01096https://doi.org/10.1021/acs.jctc.4c01096","url":null,"abstract":"Crystal structure prediction (CSP) is an important field of material design. Herein, we propose a novel generative adversarial network model, guided by a data-driven approach and incorporating the real physical structure of crystals, to address the complexity of high-dimensional data and improve prediction accuracy in materials science. The model, termed GAN-DDLSF, introduces a novel sampling method called data-driven latent space fusion (DDLSF), which aims to optimize the latent space of generative adversarial networks (GANs) by combining the statistical properties of real data with a standard Gaussian distribution, effectively mitigating the “mode collapse” problem prevalent in GANs. Our approach introduces a more refined generation mechanism specifically for binary crystal structures such as gallium nitride (GaN). By optimizing for the specific crystallographic features of GaN while maintaining structural rationality, we achieve higher precision and efficiency in predicting and designing structures for this particular material system. The model generates 9321 GaN binary crystal structures, with 16.59% reaching a stable state and 24.21% found to be metastable. These results can significantly enhance the accuracy of crystal structure predictions and provide valuable insights into the potential of the GAN-DDLSF approach for the discovery and design of binary, ternary, and multinary materials, offering new perspectives and methods for materials science research and applications.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":null,"pages":null},"PeriodicalIF":5.7,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142609244","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

Chemical Reaction Simulator on Quantum Computers by First Quantization (II)─Basic Treatment: Implementation 量子计算机上的化学反应模拟器（II）--基本处理：实现

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2024-10-25 DOI: 10.1021/acs.jctc.4c0070810.1021/acs.jctc.4c00708

Hideo Takahashi*, Tatsuya Tomaru, Toshiyuki Hirano, Saisei Tahara and Fumitoshi Sato*,

{"title":"Chemical Reaction Simulator on Quantum Computers by First Quantization (II)─Basic Treatment: Implementation","authors":"Hideo Takahashi*, Tatsuya Tomaru, Toshiyuki Hirano, Saisei Tahara and Fumitoshi Sato*, ","doi":"10.1021/acs.jctc.4c0070810.1021/acs.jctc.4c00708","DOIUrl":"https://doi.org/10.1021/acs.jctc.4c00708https://doi.org/10.1021/acs.jctc.4c00708","url":null,"abstract":"Chemical simulation is a key application area that can leverage the power of quantum computers. A chemical simulator that implements a grid-based first quantization method has promising characteristics, but an implementation fully in quantum circuits seems to have not been published. Here, we present “crsQ” (chemical reaction simulator Q), which is a quantum circuit generator that generates such a chemical simulator. The generated simulator is capable of antisymmetrization of the initial wave function and time-evolution of the wave function based on the Suzuki–Trotter decomposition. The potential energy term of the Hamiltonian is implemented using arithmetic gates, such as adders, subtractors, multipliers, dividers, and square roots. Circuit diagrams and output samples are shown. The number of qubits in the circuits scales on the order of O(η log η), where η is the number of electrons. Each component of the generated circuit was verified in unit tests. Along with this development, we designed frameworks to ease the development of large-scale circuits, namely, a temporary qubit allocation framework and an abstract syntax tree framework for arithmetic formulas. These frameworks are expected to be useful in large-scale quantum circuit generators.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":null,"pages":null},"PeriodicalIF":5.7,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acs.jctc.4c00708","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142608752","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

Crystal Structure Prediction Using Generative Adversarial Network with Data-Driven Latent Space Fusion Strategy 利用数据驱动的潜空间融合策略生成对抗网络进行晶体结构预测

IF 5.5 1区化学

Journal of Chemical Theory and Computation Pub Date : 2024-10-25 DOI: 10.1021/acs.jctc.4c01096

Zian Chen, Haichao Li, Chen Zhang, Hongbin Zhang, Yongxiao Zhao, Jian Cao, Tao He, Lina Xu, Hongping Xiao, Yi Li, Hezhu Shao, Xiaoyu Yang, Xiao He, Guoyong Fang

{"title":"Crystal Structure Prediction Using Generative Adversarial Network with Data-Driven Latent Space Fusion Strategy","authors":"Zian Chen, Haichao Li, Chen Zhang, Hongbin Zhang, Yongxiao Zhao, Jian Cao, Tao He, Lina Xu, Hongping Xiao, Yi Li, Hezhu Shao, Xiaoyu Yang, Xiao He, Guoyong Fang","doi":"10.1021/acs.jctc.4c01096","DOIUrl":"https://doi.org/10.1021/acs.jctc.4c01096","url":null,"abstract":"Crystal structure prediction (CSP) is an important field of material design. Herein, we propose a novel generative adversarial network model, guided by a data-driven approach and incorporating the real physical structure of crystals, to address the complexity of high-dimensional data and improve prediction accuracy in materials science. The model, termed GAN-DDLSF, introduces a novel sampling method called data-driven latent space fusion (DDLSF), which aims to optimize the latent space of generative adversarial networks (GANs) by combining the statistical properties of real data with a standard Gaussian distribution, effectively mitigating the “mode collapse” problem prevalent in GANs. Our approach introduces a more refined generation mechanism specifically for binary crystal structures such as gallium nitride (GaN). By optimizing for the specific crystallographic features of GaN while maintaining structural rationality, we achieve higher precision and efficiency in predicting and designing structures for this particular material system. The model generates 9321 GaN binary crystal structures, with 16.59% reaching a stable state and 24.21% found to be metastable. These results can significantly enhance the accuracy of crystal structure predictions and provide valuable insights into the potential of the GAN-DDLSF approach for the discovery and design of binary, ternary, and multinary materials, offering new perspectives and methods for materials science research and applications.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":null,"pages":null},"PeriodicalIF":5.5,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142490035","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

Uncertainty of DFT Calculated Mechanical and Structural Properties of Solids due to Incompatibility of Pseudopotentials and Exchange–Correlation Functionals 伪势和交换相关函数的不兼容性导致 DFT 计算的固体力学和结构特性的不确定性

IF 5.5 1区化学

Journal of Chemical Theory and Computation Pub Date : 2024-10-24 DOI: 10.1021/acs.jctc.4c01036

Marcin Maździarz

引用次数: 0

Uncertainty of DFT Calculated Mechanical and Structural Properties of Solids due to Incompatibility of Pseudopotentials and Exchange–Correlation Functionals 伪势和交换相关函数的不兼容性导致 DFT 计算的固体力学和结构特性的不确定性

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2024-10-24 DOI: 10.1021/acs.jctc.4c0103610.1021/acs.jctc.4c01036

Marcin Maździarz*,

引用次数: 0

Accurate Calculation of Interatomic Forces with Neural Networks Based on a Generative Transformer Architecture 利用基于生成变压器架构的神经网络精确计算原子间作用力

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2024-10-23 DOI: 10.1021/acs.jctc.4c0120510.1021/acs.jctc.4c01205

Juntao Lai, Bowen Kan, Yangjun Wu, Qiang Fu*, Honghui Shang*, Zhenyu Li and Jinlong Yang*,

{"title":"Accurate Calculation of Interatomic Forces with Neural Networks Based on a Generative Transformer Architecture","authors":"Juntao Lai, Bowen Kan, Yangjun Wu, Qiang Fu*, Honghui Shang*, Zhenyu Li and Jinlong Yang*, ","doi":"10.1021/acs.jctc.4c0120510.1021/acs.jctc.4c01205","DOIUrl":"https://doi.org/10.1021/acs.jctc.4c01205https://doi.org/10.1021/acs.jctc.4c01205","url":null,"abstract":"Using neural networks to express electronic wave functions represents a new paradigm for solving the Schrödinger equation in quantum chemistry. For practical quantum chemistry simulations, one needs to know not only energies of molecules, but also accurate forces acting on constituent atoms. In this work, we achieve the accurate calculation of interatomic forces on QiankunNet, a platform that combines transformer-based deep neural networks with efficient batched autoregressive sampling. Our approach permits the application of the Hellmann–Feynman theorem to force calculations without introducing corrective Pulay terms. The results show that the calculated interatomic forces are in close agreement with those derived from the full configuration interaction method, irrespective of whether the system is a simple molecule or a strongly correlated electron system like a linear hydrogen chain. Furthermore, the calculated interatomic forces are employed for atomic relaxation in the torsional rotation process of ethylene, and the energy barrier obtained from the scanned potential energy surface is in excellent agreement with the experiment. Our work contributes to the application of artificial intelligence to broader quantum chemistry simulations, such as modeling challenging chemical transformations where electron correlations are difficult to describe.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":null,"pages":null},"PeriodicalIF":5.7,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142608735","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

Accurate Calculation of Interatomic Forces with Neural Networks Based on a Generative Transformer Architecture 利用基于生成变压器架构的神经网络精确计算原子间作用力

IF 5.5 1区化学

Journal of Chemical Theory and Computation Pub Date : 2024-10-23 DOI: 10.1021/acs.jctc.4c01205

Juntao Lai, Bowen Kan, Yangjun Wu, Qiang Fu, Honghui Shang, Zhenyu Li, Jinlong Yang

{"title":"Accurate Calculation of Interatomic Forces with Neural Networks Based on a Generative Transformer Architecture","authors":"Juntao Lai, Bowen Kan, Yangjun Wu, Qiang Fu, Honghui Shang, Zhenyu Li, Jinlong Yang","doi":"10.1021/acs.jctc.4c01205","DOIUrl":"https://doi.org/10.1021/acs.jctc.4c01205","url":null,"abstract":"Using neural networks to express electronic wave functions represents a new paradigm for solving the Schrödinger equation in quantum chemistry. For practical quantum chemistry simulations, one needs to know not only energies of molecules, but also accurate forces acting on constituent atoms. In this work, we achieve the accurate calculation of interatomic forces on QiankunNet, a platform that combines transformer-based deep neural networks with efficient batched autoregressive sampling. Our approach permits the application of the Hellmann–Feynman theorem to force calculations without introducing corrective Pulay terms. The results show that the calculated interatomic forces are in close agreement with those derived from the full configuration interaction method, irrespective of whether the system is a simple molecule or a strongly correlated electron system like a linear hydrogen chain. Furthermore, the calculated interatomic forces are employed for atomic relaxation in the torsional rotation process of ethylene, and the energy barrier obtained from the scanned potential energy surface is in excellent agreement with the experiment. Our work contributes to the application of artificial intelligence to broader quantum chemistry simulations, such as modeling challenging chemical transformations where electron correlations are difficult to describe.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":null,"pages":null},"PeriodicalIF":5.5,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142487984","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

Polaritonic Chemistry Using the Density Matrix Renormalization Group Method 使用密度矩阵重正化群法的极性化学

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2024-10-23 DOI: 10.1021/acs.jctc.4c0098610.1021/acs.jctc.4c00986

Mikuláš Matoušek*, Nam Vu, Niranjan Govind, Jonathan J. Foley IV* and Libor Veis*,

{"title":"Polaritonic Chemistry Using the Density Matrix Renormalization Group Method","authors":"Mikuláš Matoušek*, Nam Vu, Niranjan Govind, Jonathan J. Foley IV* and Libor Veis*, ","doi":"10.1021/acs.jctc.4c0098610.1021/acs.jctc.4c00986","DOIUrl":"https://doi.org/10.1021/acs.jctc.4c00986https://doi.org/10.1021/acs.jctc.4c00986","url":null,"abstract":"The emerging field of polaritonic chemistry explores the behavior of molecules under strong coupling with cavity modes. Despite recent developments in ab initio polaritonic methods for simulating polaritonic chemistry under electronic strong coupling, their capabilities are limited, especially in cases where the molecule also features strong electronic correlation. To bridge this gap, we have developed a novel method for cavity QED calculations utilizing the Density Matrix Renormalization Group (DMRG) algorithm in conjunction with the Pauli–Fierz Hamiltonian. Our approach is applied to investigate the effect of the cavity on the S0–S1 transition of n-oligoacenes, with n ranging from 2 to 5, encompassing 22 fully correlated π orbitals in the largest pentacene molecule. Our findings indicate that the influence of the cavity intensifies with larger acenes. Additionally, we demonstrate that, unlike the full determinantal representation, DMRG efficiently optimizes and eliminates excess photonic degrees of freedom, resulting in an asymptotically constant computational cost as the photonic basis increases.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":null,"pages":null},"PeriodicalIF":5.7,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acs.jctc.4c00986","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142608601","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