Journal of Chemical Theory and Computation最新文献_第7页

Deciphering the Scattering of Mechanically Driven Polymers Using Deep Learning 利用深度学习破译机械驱动聚合物的散射

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2025-04-08 DOI: 10.1021/acs.jctc.5c0040910.1021/acs.jctc.5c00409

Lijie Ding, Chi-Huan Tung, Bobby G. Sumpter, Wei-Ren Chen and Changwoo Do*,

{"title":"Deciphering the Scattering of Mechanically Driven Polymers Using Deep Learning","authors":"Lijie Ding, Chi-Huan Tung, Bobby G. Sumpter, Wei-Ren Chen and Changwoo Do*, ","doi":"10.1021/acs.jctc.5c0040910.1021/acs.jctc.5c00409","DOIUrl":"https://doi.org/10.1021/acs.jctc.5c00409https://doi.org/10.1021/acs.jctc.5c00409","url":null,"abstract":"We present a deep learning approach for analyzing two-dimensional scattering data of semiflexible polymers under external forces. In our framework, scattering functions are compressed into a three-dimensional latent space using a Variational Autoencoder (VAE), and two converter networks establish a bidirectional mapping between the polymer parameters (bending modulus, stretching force, and steady shear) and the scattering functions. The training data are generated using off-lattice Monte Carlo simulations to avoid the orientational bias inherent in lattice models, ensuring robust sampling of polymer conformations. The feasibility of this bidirectional mapping is demonstrated by the organized distribution of polymer parameters in the latent space. By integrating the converter networks with the VAE, we obtain a generator that produces scattering functions from given polymer parameters and an inferrer that directly extracts polymer parameters from scattering data. While the generator can be utilized in a traditional least-squares fitting procedure, the inferrer produces comparable results in a single pass and operates 3 orders of magnitude faster. This approach offers a scalable automated tool for polymer scattering analysis and provides a promising foundation for extending the method to other scattering models, experimental validation, and the study of time-dependent scattering data.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":"21 8","pages":"4176–4182 4176–4182"},"PeriodicalIF":5.7,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143854362","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

Simulations of Two-Photon Absorption Spectra of Fluorescent Dyes: The Impact of Non-Condon Effects. 荧光染料双光子吸收光谱的模拟：非安全套效应的影响。

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.4c01545

Rudraditya Sarkar, Carmelo Naim, Karan Ahmadzadeh, Robert Zaleśny, Denis Jacquemin, Josep M Luis

{"title":"Simulations of Two-Photon Absorption Spectra of Fluorescent Dyes: The Impact of Non-Condon Effects.","authors":"Rudraditya Sarkar, Carmelo Naim, Karan Ahmadzadeh, Robert Zaleśny, Denis Jacquemin, Josep M Luis","doi":"10.1021/acs.jctc.4c01545","DOIUrl":"10.1021/acs.jctc.4c01545","url":null,"abstract":"Computer simulations play a pivotal role in interpreting experimental two-photon absorption (2PA) spectra. One of the key aspects of the simulation of these spectra is to take into account the vibrational fine structure of the bands in electronic spectra. This is typically done by employing Franck-Condon (FC) term and low-order terms in the Herzberg-Teller (HT) expansion. In this work, we present a systematic study of first-order HT effects on the vibronic structure of π → π* electronic bands in 2PA spectra of 13 common fluorophores. We begin by evaluating the performance of several density functional approximations (DFAs) against the second-order coupled cluster singles and doubles model (CC2) for reproducing two-photon transition moments and their first- and second-order derivatives with respect to normal modes of vibration on a set of six donor-acceptor molecules. Our findings reveal that most DFAs produce inaccurate values for these derivatives, with the exception of the LC-BLYP functionals with range-separation parameters of 0.33 and 0.47. Although these functionals underestimate the HT contribution to the 2PA total intensities of the π → π* electronic bands, they offer a reasonable qualitative reproduction of the HT vibrational fine structure of the reference spectra. We further explore HT effects on fluorescent chromophores, finding that HT contributions are secondary to FC effects, leading to small shifts of the wavelengths peaks, and minimal changes in the intensities. Additionally, the adiabatic Hessian, vertical Hessian, and vertical gradient vibronic models are assessed. The general agreement among these models confirms that the harmonic approximation is suitable for studying the selected fluorophores.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"3587-3599"},"PeriodicalIF":5.7,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143727088","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

Reconstruction of the On-Top Two-Electron Density from Natural Orbitals and Their Occupation Numbers. 用自然轨道重建上双电子密度及其占据数。

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2025-04-08 DOI: 10.1021/acs.jctc.5c00024

Jerzy Cioslowski, Krzysztof Strasburger

引用次数: 0

Deciphering the Scattering of Mechanically Driven Polymers Using Deep Learning. 利用深度学习破译机械驱动聚合物的散射。

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2025-04-08 DOI: 10.1021/acs.jctc.5c00409

Lijie Ding, Chi-Huan Tung, Bobby G Sumpter, Wei-Ren Chen, Changwoo Do

{"title":"Deciphering the Scattering of Mechanically Driven Polymers Using Deep Learning.","authors":"Lijie Ding, Chi-Huan Tung, Bobby G Sumpter, Wei-Ren Chen, Changwoo Do","doi":"10.1021/acs.jctc.5c00409","DOIUrl":"https://doi.org/10.1021/acs.jctc.5c00409","url":null,"abstract":"We present a deep learning approach for analyzing two-dimensional scattering data of semiflexible polymers under external forces. In our framework, scattering functions are compressed into a three-dimensional latent space using a Variational Autoencoder (VAE), and two converter networks establish a bidirectional mapping between the polymer parameters (bending modulus, stretching force, and steady shear) and the scattering functions. The training data are generated using off-lattice Monte Carlo simulations to avoid the orientational bias inherent in lattice models, ensuring robust sampling of polymer conformations. The feasibility of this bidirectional mapping is demonstrated by the organized distribution of polymer parameters in the latent space. By integrating the converter networks with the VAE, we obtain a generator that produces scattering functions from given polymer parameters and an inferrer that directly extracts polymer parameters from scattering data. While the generator can be utilized in a traditional least-squares fitting procedure, the inferrer produces comparable results in a single pass and operates 3 orders of magnitude faster. This approach offers a scalable automated tool for polymer scattering analysis and provides a promising foundation for extending the method to other scattering models, experimental validation, and the study of time-dependent scattering data.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143802017","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

Acceleration of the Relativistic Dirac-Kohn-Sham Method with GPU: A Pre-Exascale Implementation of BERTHA and PyBERTHA. 用GPU加速相对论Dirac-Kohn-Sham方法：BERTHA和PyBERTHA的前百亿亿次实现。

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.4c01759

Loriano Storchi, Laura Bellentani, Jeff Hammond, Sergio Orlandini, Leonardo Pacifici, Nicoló Antonini, Leonardo Belpassi

{"title":"Acceleration of the Relativistic Dirac-Kohn-Sham Method with GPU: A Pre-Exascale Implementation of BERTHA and PyBERTHA.","authors":"Loriano Storchi, Laura Bellentani, Jeff Hammond, Sergio Orlandini, Leonardo Pacifici, Nicoló Antonini, Leonardo Belpassi","doi":"10.1021/acs.jctc.4c01759","DOIUrl":"10.1021/acs.jctc.4c01759","url":null,"abstract":"In this paper, we present the recent advances in the computation of the Dirac-Kohn-Sham (DKS) method of the BERTHA code. We show here that the simple underlined structure of the FORTRAN code also favors efficient porting of the code to GPUs, leading to a particularly efficient hybrid CPU/GPU implementation (OpenMP/OpenACC), where the most computationally intensive part for DKS matrix evaluation (three-center two-electron integrals evaluated via the McMurchie-Davidson scheme) is efficiently offloaded to the GPU via compiler directives based on the OpenACC programming model. This scheme in combination with the use of a linear algebra library optimized for GPUs (cuBLAS, cuSOLVER) significantly accelerates the DKS calculations. In addition, the low-level integral kernel developed here at FORTRAN level was used to port our real-time DKS (RT-TDDKS) implementation based on Python (PyBERTHART) for the utilization of the GPU. The results obtained on the new Tier-0 EuroHPC supercomputer (LEONARDO) of the CINECA Supercomputing Centre with a single NVIDIA A100 card are very satisfactory. We achieve a speedup up to 30 for Au16 in a single-point DKS energy calculation and up to 10 for the Au8 systems in an RT-TDDKS calculation, compared to our OpenMP (i.e., CPU only) parallel implementation (with 32 cores). The approach presented here is very general and, to our knowledge, represents the first port of a Python API to GPUs based on a FORTRAN kernel for the evaluation of two-electron integrals. The implementation is currently limited to the use of a single GPU accelerator, but future paths to an actual exascale implementation are discussed.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"3460-3475"},"PeriodicalIF":5.7,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143672915","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

Structure Search with the Strategic Escape Algorithm. 基于策略逃逸算法的结构搜索。

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.4c01746

Jordan Burkhardt, Yinglu Jia, Wan-Lu Li

{"title":"Structure Search with the Strategic Escape Algorithm.","authors":"Jordan Burkhardt, Yinglu Jia, Wan-Lu Li","doi":"10.1021/acs.jctc.4c01746","DOIUrl":"10.1021/acs.jctc.4c01746","url":null,"abstract":"This work introduces the Strategic Escape (SE) algorithm, an approach that systematically ensures effective exploration of the potential energy surface during global minimum searches for atomic clusters. The SE algorithm prioritizes the escape from local minima prior to geometry optimization, leveraging a combination of randomized direction vectors, distance-based uniqueness criteria, and covalent bonding heuristics. These principles enhance structural diversity and computational efficiency by reducing redundant geometry optimizations. Additionally, a symmetry-guided seed generation method based on an adaptive polygon is proposed to provide diverse and physically realistic initial configurations. Together, these methods achieve a 2.3-fold improvement in computational efficiency compared to conventional Basin-Hopping approaches. The effectiveness of the SE algorithm is demonstrated through its application to boron, metal clusters, and binary-composition clusters, achieving rapid convergence to global minimum structures with high reliability. These advancements establish the SE algorithm as a robust and scalable tool for exploring complex chemical systems.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"3765-3773"},"PeriodicalIF":5.7,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143672925","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

Simple Linear Regression Models for Prediction of Ionization Energies, Electron Affinities, and Fundamental Gaps of Atoms and Molecules. 简单线性回归模型预测电离能，电子亲和力，原子和分子的基本间隙。

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.4c01591

Rebecca K Carlson

引用次数: 0

Targeted Transferable Machine-Learned Potential for Linear Alkanes Trained on C₁₄H₃₀ and Tested for C₄H₁₀ to C₃₀H₆₂. 在C14H30上训练线性烷烃的目标可转移机器学习潜力，并在C4H10至C30H62上进行测试。

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.4c01793

Chen Qu, Paul L Houston, Thomas Allison, Joel M Bowman

{"title":"Targeted Transferable Machine-Learned Potential for Linear Alkanes Trained on C14H30 and Tested for C4H10 to C30H62.","authors":"Chen Qu, Paul L Houston, Thomas Allison, Joel M Bowman","doi":"10.1021/acs.jctc.4c01793","DOIUrl":"10.1021/acs.jctc.4c01793","url":null,"abstract":"Given the great importance of linear alkanes in fundamental and applied research, an accurate machine-learned potential (MLP) would be a major advance in computational modeling of these hydrocarbons. Recently, we reported a novel, many-body permutationally invariant model that was trained specifically for the 44-atom hydrocarbon C14H30 on roughly 250,000 B3LYP energies (Qu, C.; Houston, P. L.; Allison, T.; Schneider, B. I.; Bowman, J. M. J. Chem. Theory Comput. 2024, 20, 9339-9353). Here, we demonstrate the accuracy of the transferability of this potential for linear alkanes ranging from butane C4H10 up to C30H62. Unlike other approaches for transferability that aim for universal applicability, the present approach is targeted for linear alkanes. The mean absolute error (MAE) for energy ranges from 0.26 kcal/mol for butane and rises to 0.73 kcal/mol for C30H62 over the energy range up to 80 kcal/mol for butane and 600 kcal/mol for C30H62. These values are unprecedented for transferable potentials and indicate the high performance of a targeted transferable potential. The conformational barriers are shown to be in excellent agreement with high-level ab initio calculations for pentane, the largest alkane for which such calculations have been reported. Vibrational power spectra of C30H62 from molecular dynamics calculations are presented and briefly discussed. Finally, the evaluation time for the potential is shown to vary linearly with the number of atoms.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"3552-3562"},"PeriodicalIF":5.7,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143717639","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

Calculating the Energy Profile of an Enzymatic Reaction on a Quantum Computer. 在量子计算机上计算酶促反应的能量分布。

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2025-04-08 Epub Date: 2025-03-31 DOI: 10.1021/acs.jctc.5c00022

Patrick Ettenhuber, Mads Bøttger Hansen, Pier Paolo Poier, Irfansha Shaik, Stig Elkjaer Rasmussen, Niels Kristian Madsen, Marco Majland, Frank Jensen, Lars Olsen, Nikolaj Thomas Zinner

{"title":"Calculating the Energy Profile of an Enzymatic Reaction on a Quantum Computer.","authors":"Patrick Ettenhuber, Mads Bøttger Hansen, Pier Paolo Poier, Irfansha Shaik, Stig Elkjaer Rasmussen, Niels Kristian Madsen, Marco Majland, Frank Jensen, Lars Olsen, Nikolaj Thomas Zinner","doi":"10.1021/acs.jctc.5c00022","DOIUrl":"10.1021/acs.jctc.5c00022","url":null,"abstract":"Quantum computing (QC) provides a promising avenue for enabling quantum chemistry calculations, which are classically impossible due to computational complexity that increases exponentially with system size. As fully fault-tolerant algorithms and hardware, for which an exponential speedup is predicted, are currently out of reach, recent research efforts have been dedicated to developing and scaling algorithms for Noisy Intermediate-Scale Quantum (NISQ) devices to showcase the practical usefulness of such machines. To demonstrate the usefulness of NISQ devices in the field of chemistry, we apply our recently developed FAST-VQE algorithm and a state-of-the-art quantum gate reduction strategy based on propositional satisfiability together with standard optimization tools for the simulation of the rate-determining proton transfer step for CO2 hydration catalyzed by carbonic anhydrase resulting in the first application of a quantum computing device for the simulation of an enzymatic reaction. To this end, we have combined classical force field simulations with quantum mechanical methods on classical and quantum computers in a hybrid calculation approach. The presented technique significantly enhances the accuracy and capabilities of QC-based molecular modeling and finally pushes it into compelling and realistic applications. The framework is general and can be applied beyond the case of computational enzymology.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"3493-3503"},"PeriodicalIF":5.7,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143750259","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

Dynamic Programming for Chain Propagator Computation of Branched Block Copolymers in Polymer Field Theory Simulations. 聚合物场理论模拟中支链嵌段共聚物链传播子计算的动态规划。

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2025-04-08 Epub Date: 2025-03-30 DOI: 10.1021/acs.jctc.5c00103

Daeseong Yong, Jaeup U Kim

{"title":"Dynamic Programming for Chain Propagator Computation of Branched Block Copolymers in Polymer Field Theory Simulations.","authors":"Daeseong Yong, Jaeup U Kim","doi":"10.1021/acs.jctc.5c00103","DOIUrl":"10.1021/acs.jctc.5c00103","url":null,"abstract":"We present an algorithmic approach to optimize chain propagator computations in polymer field theory simulations, including self-consistent field theory (SCFT) calculations and field-theoretic simulations (FTSs). Propagator calculations for branched block copolymers often involve recursive structures and overlapping subproblems, resulting in redundant computations. By employing dynamic programming (DP) and encoding computational dependencies as strings, our method systematically eliminates these redundancies in mixtures of branched polymers. The algorithm achieves optimal time complexity for various polymeric systems, including star-shaped, comb, dendrimer polymers, and homopolymer mixtures, by reusing and aggregating propagators for symmetric and repetitive structures. This enhances computational efficiency and reduces memory usage, addressing a key limitation in developing versatile polymer field theory simulation software. Our approach streamlines the simulation of complex branched polymers without requiring manual software adjustments, facilitating more efficient workflows for polymer researchers. Furthermore, the method enables automated searches for inverse design by optimizing computations across diverse branched polymer architectures, contributing to the discovery and design of novel polymeric materials. The algorithm is implemented in open-source software, ensuring accessibility for further development and broader application in computational polymer science.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"3676-3690"},"PeriodicalIF":5.7,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143750260","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