Journal of Chemical Theory and Computation最新文献

{"title":"Fine-Tuning Graph Neural Networks via Active Learning: Unlocking the Potential of Graph Neural Networks Trained on Nonaqueous Systems for Aqueous CO2 Reduction","authors":"Zihao Jiao,&nbsp;Yu Mao,&nbsp;Ruihu Lu,&nbsp;Ya Liu,&nbsp;Liejin Guo* and Ziyun Wang*,&nbsp;","doi":"10.1021/acs.jctc.5c0008910.1021/acs.jctc.5c00089","DOIUrl":"https://doi.org/10.1021/acs.jctc.5c00089https://doi.org/10.1021/acs.jctc.5c00089","url":null,"abstract":"<p >Graph neural networks (GNNs) have revolutionized catalysis research with their efficiency and accuracy in modeling complex chemical interactions. However, adapting GNNs trained on nonaqueous data sets to aqueous systems poses notable challenges due to intricate water interactions. In this study, we proposed an active learning-based fine-tuning approach to extend the applicability of GNNs to aqueous environments. The geometry optimization and transition state search workflows are designed to reduce computational costs while maintaining DFT-level accuracy. Applied to the CO₂ reduction reaction, the workflow delivers a 2–3-fold acceleration in geometry optimization through a relaxed force threshold combined with DFT refinement. The versatility of the transition state search algorithm was demonstrated on key C–C coupling pathways, pinpointing *CO–*COH as the most energetically favorable pathway in aqueous systems of Cu and Cu-based Ag, Au, and Zn alloys. The Brønsted–Evans–Polanyi relationship remains robust under water-induced fluctuations, with alloyed metals such as Al, Ga, and Pd, along with Ag, Au, and Zn, exhibiting coupling efficiency comparable to that of Cu. Additionally, perturbation-based training on forces and energies extends the application of GNNs to aqueous ab initio molecular dynamics simulations, enabling efficient modeling of dynamical trajectories. This work presents novel approaches to adapting nonaqueous models for application in aqueous systems, highlighting GNNs’ potential in solvated environments and laying a foundation for accelerating predictions of catalytic mechanisms under realistic conditions.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":"21 6","pages":"3176–3186 3176–3186"},"PeriodicalIF":5.7,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143678824","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":"Shadow Molecular Dynamics with a Machine Learned Flexible Charge Potential.","authors":"Cheng-Han Li, Mehmet Cagri Kaymak, Maksim Kulichenko, Nicholas Lubbers, Benjamin T Nebgen, Sergei Tretiak, Joshua Finkelstein, Daniel P Tabor, Anders M N Niklasson","doi":"10.1021/acs.jctc.5c00062","DOIUrl":"10.1021/acs.jctc.5c00062","url":null,"abstract":"<p><p>We present an extended Lagrangian shadow molecular dynamics scheme with an interatomic Born-Oppenheimer potential determined by the relaxed atomic charges of a second-order charge equilibration model. To parametrize the charge equilibration model, we use machine learning with neural networks to determine the environment-dependent electronegativities and chemical hardness parameters for each atom, in addition to the charge-independent energy and force terms. The approximate shadow molecular dynamics potential in combination with the extended Lagrangian formulation improves the numerical stability and reduces the number of Coulomb potential calculations required to evaluate accurate conservative forces. We demonstrate efficient and accurate simulations with excellent long-term stability of the molecular dynamics trajectories. The significance of choosing fixed or environment-dependent electronegativities and chemical hardness parameters is evaluated. Finally, we compute the infrared spectrum of molecules via the dipole autocorrelation function and compare to experiments to highlight the accuracy of the shadow molecular dynamics scheme with a machine learned flexible charge potential.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143629981","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":"Thermal Adaptation of Cytosolic Malate Dehydrogenase Revealed by Deep Learning and Coevolutionary Analysis","authors":"Divyanshu Shukla,&nbsp;Jonathan Martin,&nbsp;Faruck Morcos and Davit A. Potoyan*,&nbsp;","doi":"10.1021/acs.jctc.4c0177410.1021/acs.jctc.4c01774","DOIUrl":"https://doi.org/10.1021/acs.jctc.4c01774https://doi.org/10.1021/acs.jctc.4c01774","url":null,"abstract":"<p >Protein evolution has shaped enzymes that maintain stability and function across diverse thermal environments. While sequence variation, thermal stability and conformational dynamics are known to influence an enzyme’s thermal adaptation, how these factors collectively govern stability and function across diverse temperatures remains unresolved. Cytosolic malate dehydrogenase (cMDH), a citric acid cycle enzyme, is an ideal model for studying these mechanisms due to its temperature-sensitive flexibility and broad presence in species from diverse thermal environments. In this study, we employ techniques inspired by deep learning and statistical mechanics to uncover how sequence variation and conformational dynamics shape patterns of cMDH’s thermal adaptation. By integrating coevolutionary models with variational autoencoders (VAE), we generate a latent generative landscape (LGL) of the cMDH sequence space, enabling us to explore mutational pathways and predict fitness using direct coupling analysis (DCA). Structure predictions via AlphaFold and molecular dynamics simulations further illuminate how variations in hydrophobic interactions and conformational flexibility contribute to the thermal stability of warm- and cold-adapted cMDH orthologs. Notably, we identify the ratio of hydrophobic contacts between two regions as a predictive order parameter for thermal stability features, providing a quantitative metric for understanding cMDH dynamics across temperatures. The integrative computational framework employed in this study provides mechanistic insights into protein adaptation at both sequence and structural levels, offering unique perspectives on the evolution of thermal stability and creating avenues for the rational design of proteins with optimized thermal properties.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":"21 6","pages":"3277–3287 3277–3287"},"PeriodicalIF":5.7,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acs.jctc.4c01774","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143678729","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":"Investigating Data Hierarchies in Multifidelity Machine Learning for Excitation Energies","authors":"Vivin Vinod*,&nbsp; and ,&nbsp;Peter Zaspel,&nbsp;","doi":"10.1021/acs.jctc.4c0149110.1021/acs.jctc.4c01491","DOIUrl":"https://doi.org/10.1021/acs.jctc.4c01491https://doi.org/10.1021/acs.jctc.4c01491","url":null,"abstract":"<p >Recent progress in machine learning (ML) has made high-accuracy quantum chemistry (QC) calculations more accessible. Of particular interest are multifidelity machine learning (MFML) methods, where training data from differing accuracies or fidelities are used. These methods usually employ a fixed scaling factor, γ, to relate the number of training samples across different fidelities, which reflects the cost and assumed sparsity of the data. This study investigates the impact of modifying γ on model efficiency and accuracy for the prediction of vertical excitation energies using the QeMFi benchmark data set. Further, this work introduces QC compute time-informed scaling factors, denoted as θ, that vary based on QC compute times at different fidelities. A novel error metric, error contours of MFML, is proposed to provide a comprehensive view of model error contributions from each fidelity. The results indicate that high model accuracy can be achieved with just 2 training samples at the target fidelity when a larger number of samples from lower fidelities are used. This is further illustrated through a novel concept, the Γ-curve, which compares model error against the time-cost of generating training samples, demonstrating that multifidelity models can achieve high accuracy while minimizing training data costs.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":"21 6","pages":"3077–3091 3077–3091"},"PeriodicalIF":5.7,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143678728","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":"Role of Electron Correlation beyond the Active Space in Achieving Quantitative Predictions of Spin-Phonon Relaxation.","authors":"Soumi Haldar, Lorenzo A Mariano, Alessandro Lunghi, Laura Gagliardi","doi":"10.1021/acs.jctc.4c01696","DOIUrl":"10.1021/acs.jctc.4c01696","url":null,"abstract":"<p><p>Single-molecule magnets (SMMs) are promising candidates for molecular-scale data storage and processing due to their strong magnetic anisotropy and long spin relaxation times. However, as the temperature rises, interactions between electronic states and lattice vibrations accelerate spin relaxation, significantly limiting their practical applications. Recently, ab initio simulations have made it possible to advance our understanding of phonon-induced magnetic relaxation, but significant deviations from the experiments have often been observed. The description of molecules' electronic structure has been mostly based on complete active space self-consistent field (CASSCF) calculations, and the impact of electron correlation beyond the active space remains largely unexplored. In this study, we provide the first systematic investigation of spin-phonon relaxation in SMMs with post-CASSCF multiconfigurational methods, specifically CAS, followed by second-order perturbation theory and multiconfiguration pair-density functional theory. Taking Co(II)- and Dy(III)-based SMMs as case studies, we analyze how electron correlation influences spin-phonon relaxation rates across a range of temperatures by comparing theoretical predictions with experimental observations. Our findings demonstrate that post-CASSCF treatments make it possible to achieve quantitative predictions for Co(II)-based SMMs. For Dy(III)-based systems, however, accurate predictions require the consideration of additional effects, underscoring the urgent necessity of further advancing the study of the effects of electronic correlation in these complex systems.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11948317/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143612823","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":"A Phase-Space View of Vibrational Energies without the Born–Oppenheimer Framework","authors":"Xuezhi Bian,&nbsp;Cameron Khan,&nbsp;Titouan Duston,&nbsp;Jonathan Rawlinson,&nbsp;Robert G. Littlejohn and Joseph E. Subotnik*,&nbsp;","doi":"10.1021/acs.jctc.4c0129410.1021/acs.jctc.4c01294","DOIUrl":"https://doi.org/10.1021/acs.jctc.4c01294https://doi.org/10.1021/acs.jctc.4c01294","url":null,"abstract":"<p >We show that following the standard mantra of quantum chemistry and diagonalizing the Born–Oppenheimer (BO) Hamiltonian <i>Ĥ</i>_BO(<b><i>R</i></b>) is not the optimal means to construct potential energy surfaces. A better approach is to diagonalize a phase-space electronic Hamiltonian, <i>Ĥ</i>_PS(<b><i>R</i></b>, <b><i>P</i></b>), which is parameterized by both nuclear position <b><i>R</i></b> and nuclear momentum <b><i>P</i></b>. Such a nonperturbative phase-space electronic Hamiltonian can be constructed using a partial Wigner transform and the method has exactly the same cost as BO for a semiclassical calculation (and only a slight increase in cost for a quantum nuclear calculation). For a three-particle system, with two heavy particles and one light particle, numerical results show that a phase-space electronic Hamiltonian produces not only meaningful electronic momenta (which are completely ignored by BO theory) but also far better vibrational energies. As such, for high level results and/or systems with degeneracies and spin degrees of freedom, we anticipate that future electronic structure and quantum chemistry packages will need to take as input not just the positions of the nuclei but also their momenta.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":"21 6","pages":"2880–2893 2880–2893"},"PeriodicalIF":5.7,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143678627","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":"Improved Free-Energy Estimates for the Permeation of Bulky Antibiotic Molecules through Porin Channels Using Temperature-Accelerated Sliced Sampling","authors":"Abhishek Acharya,&nbsp; and ,&nbsp;Ulrich Kleinekathöfer*,&nbsp;","doi":"10.1021/acs.jctc.4c0167910.1021/acs.jctc.4c01679","DOIUrl":"https://doi.org/10.1021/acs.jctc.4c01679https://doi.org/10.1021/acs.jctc.4c01679","url":null,"abstract":"<p >The estimation of accurate free energies for antibiotic permeation via the bacterial outer-membrane porins has proven to be challenging. Atomistic simulations of the process suffer from sampling issues that are typical of systems with complex and slow dynamics, even with the application of advanced sampling methods. Ultimately, the objective is to obtain accurate potential of mean force (PMF) for a large set of antibiotics and to predict permeation rates. Therefore, the computational expense becomes an important criterion as well. Simulation studies on the permeation process and similar complex processes have shown that both the sampling scheme employed and the procedure used for the generation of the initial states can critically affect the quality of the estimates obtained and the respective computational overhead. The temperature-accelerated sliced sampling method (TASS) has been shown to partly address the issues with efficient sampling of the important and slow degrees of freedom by enabling simultaneous biasing of a large number of collective variables. In this work, we investigate the effect of the procedure used for the generation of input conformations on the convergence of free-energy estimates obtained from TASS simulations. In particular, we compare the steered molecular dynamics (MD)-based procedure that has been used in previous TASS studies with the Monte Carlo pathway search method, which is used to obtain approximate permeation trajectories with minimum perturbation of the protein channel. We tested different input setups for enrofloxacin permeation through the porins OmpK35 and OmpE35. The best setup shows an improved agreement between independent PMFs in both cases at a much lower computational cost.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":"21 6","pages":"3246–3259 3246–3259"},"PeriodicalIF":5.7,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acs.jctc.4c01679","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143678629","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":"Role of Electron Correlation beyond the Active Space in Achieving Quantitative Predictions of Spin-Phonon Relaxation","authors":"Soumi Haldar,&nbsp;Lorenzo A. Mariano,&nbsp;Alessandro Lunghi* and Laura Gagliardi*,&nbsp;","doi":"10.1021/acs.jctc.4c0169610.1021/acs.jctc.4c01696","DOIUrl":"https://doi.org/10.1021/acs.jctc.4c01696https://doi.org/10.1021/acs.jctc.4c01696","url":null,"abstract":"<p >Single-molecule magnets (SMMs) are promising candidates for molecular-scale data storage and processing due to their strong magnetic anisotropy and long spin relaxation times. However, as the temperature rises, interactions between electronic states and lattice vibrations accelerate spin relaxation, significantly limiting their practical applications. Recently, ab initio simulations have made it possible to advance our understanding of phonon-induced magnetic relaxation, but significant deviations from the experiments have often been observed. The description of molecules’ electronic structure has been mostly based on complete active space self-consistent field (CASSCF) calculations, and the impact of electron correlation beyond the active space remains largely unexplored. In this study, we provide the first systematic investigation of spin-phonon relaxation in SMMs with post-CASSCF multiconfigurational methods, specifically CAS, followed by second-order perturbation theory and multiconfiguration pair-density functional theory. Taking Co(II)- and Dy(III)-based SMMs as case studies, we analyze how electron correlation influences spin-phonon relaxation rates across a range of temperatures by comparing theoretical predictions with experimental observations. Our findings demonstrate that post-CASSCF treatments make it possible to achieve quantitative predictions for Co(II)-based SMMs. For Dy(III)-based systems, however, accurate predictions require the consideration of additional effects, underscoring the urgent necessity of further advancing the study of the effects of electronic correlation in these complex systems.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":"21 6","pages":"2829–2838 2829–2838"},"PeriodicalIF":5.7,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acs.jctc.4c01696","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143678721","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":"Medium-Range Order in Iron Phosphate Glass Models Obtained Using Various Randomization Techniques: A Molecular Dynamics Study.","authors":"Shakti Singh, Manan Dholakia, Sharat Chandra","doi":"10.1021/acs.jctc.4c01372","DOIUrl":"10.1021/acs.jctc.4c01372","url":null,"abstract":"<p><p>Glasses are known to have medium-range order (MRO), but their link to any experimentally measurable quantity is still ambiguous. The first sharp diffraction peak (FSDP) in structure factor <i>S</i>(<i>q</i>) obtained from diffraction experiments on glasses has been associated with this MRO (∼7-15 Å), but understanding the fundamental origin of this universal peak is still an open problem. We have addressed this issue for a complex glass, i.e., iron phosphate glass (IPG), through atomistic models generated from a hybrid approach (our in-house-developed MC code + molecular dynamics simulation). IPG is a technologically important glass with applications in waste vitrification, bioactive glass, laser glass material, anode material for batteries, etc., and is seen as a strengthened substitute for borosilicate glasses. We performed a comparative study by generating glass models from different initial configurations and randomization techniques. The developed IPG models were first validated with existing data on short-range order (SRO) and MRO through the study of pair correlation functions, bond angle distributions, and coordination number for SRO and rings distribution, FSDP in structure factor, and void size distribution for MRO. The study of coordination environment of oxygen is specifically shown to aid in understanding glass formation through topological constraint theory. Thereafter, to understand the fundamental origin of FSDP in <i>S</i>(<i>q</i>), structure factors were calculated corresponding to the individual ring sizes present in the model. The relative contribution of these individual <i>S</i>(<i>q</i>)'s in the total experimental <i>S</i>(<i>q</i>) is estimated using an inverse fitting approach. The contributions thus obtained directly correlated with ring size percentages in the models for the considered q-range. In particular, the melt-quenched model obtained from the MC model as an initial structure is found to reproduce most experimental features seen in IPG. Through this exercise, we can connect the rings distribution of an atomistic glass model with an experimentally measurable quantity like FSDP in <i>S</i>(<i>q</i>) for a complex glass-like IPG. This gives physical meaning to the rings distribution while also proving that this structural descriptor is a useful tool for validation of MRO in simulation-produced models of glass.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"2582-2597"},"PeriodicalIF":5.7,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143466520","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":"Efficient Energy Measurement of Chemical Systems via One-Particle Reduced Density Matrix: A NOF-VQE Approach for Optimized Sampling.","authors":"Juan Felipe Huan Lew-Yee, Mario Piris","doi":"10.1021/acs.jctc.4c01734","DOIUrl":"10.1021/acs.jctc.4c01734","url":null,"abstract":"<p><p>In this work, we explore the use of the one-particle reduced density matrix (1RDM) to streamline energy measurements of chemical systems on quantum computers, particularly within the variational quantum eigensolver (VQE) framework. This approach leverages the existence of an exact energy functional of the 1RDM, enabling a reduction in both the number of expectation values to measure and the number of circuits to execute, thereby optimizing quantum resource usage. Specifically, sampling the 1RDM involves measuring only [Formula: see text] elements, which is significantly fewer than the [Formula: see text] required for the Hamiltonian's expectation value ⟨<i>Ĥ</i>⟩. We demonstrate our approach by harnessing the well-established natural orbital functional (NOF) theory, using the natural orbitals and occupation numbers derived from the diagonalization of the 1RDM measured from the quantum computer. Starting with the H₂ system, we validate the accuracy of our method by comparing the energy derived from NOF approximations applied to the exact wave function with the value obtained from ⟨<i>Ĥ</i>⟩. This is followed by an optimization of the gate parameters by minimizing the energy using the NOF approximations as the objective function. The analysis is extended to larger systems, such as LiH, Li₂, OH^-, FH, NeH⁺, and F₂ using a wave function ansatz with single and double excitation gates. This NOF-based method reduces the scaling cost of circuit executions compared to standard VQE implementations, achieving around 90% savings in the systems used in this work. Overall, by using a well-performing NOF as the objective function, the proposed NOF-VQE demonstrates the viability of NOF approximations for obtaining accurate energies in the noisy intermediate-scale quantum era and underscores the potential for developing new functionals tailored to quantum computing applications.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"2402-2413"},"PeriodicalIF":5.7,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143471992","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}