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Combining Optical Control and Geometrical Optimization for Efficient Control of Competing Molecular Photoinduced Processes Far from the Ground State. 结合光学控制和几何优化有效控制远离基态的竞争分子光诱导过程。
IF 5.5 1区 化学 Q2 CHEMISTRY, PHYSICAL Pub Date : 2025-06-20 DOI: 10.1021/acs.jctc.5c00609
David Veintemillas,Bo Y Chang,Ignacio R Sola
The yield of a photochemical process can be maximized by optimizing the driving fields, such as in optical control, or the initial wave function, as in geometrical optimization. We combine both algorithms in an iterative process, showing very fast convergence and great improvement in the yields, as applied to driving population to the second excited state of the molecular hydrogen cation through the first excited dissociative state by a pump-pump scheme. The results reveal the impact of the initial vibrational coherences in photoinduced processes that occur at nuclear configurations very far from the ground state, or that are even mediated by processes in the continuum. On the other hand, depending on whether we maximize the total electronic population (that mainly dissociates) or the bound population, the initial wave functions change considerably, involving nodal patterns in the position or in the momentum representations, respectively, that lead to different dynamics.
光化学过程的产率可以通过优化驱动场(如光学控制)或初始波函数(如几何优化)来最大化。我们将这两种算法结合在一个迭代过程中,显示出非常快的收敛性和产率的极大提高,并应用于通过泵-泵方案将分子氢阳离子的居群从第一激发态解离态驱动到第二激发态。结果揭示了光诱导过程中初始振动相干的影响,这些影响发生在离基态很远的核构型上,或者甚至是由连续介质中的过程介导的。另一方面,取决于我们是否最大化总电子居群(主要是解离)或束缚居群,初始波函数会发生相当大的变化,分别涉及位置或动量表示中的节点模式,从而导致不同的动力学。
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引用次数: 0
Ab Initio Valence Bond Theory for Strongly Correlated Systems. 强相关系统的从头算价键理论。
IF 5.5 1区 化学 Q2 CHEMISTRY, PHYSICAL Pub Date : 2025-06-20 DOI: 10.1021/acs.jctc.5c00596
Chen Zhou,Xun Wu,Fuming Ying,Wei Wu
Strongly correlated systems, characterized by significant multiconfigurational character, pose a persistent challenge in quantum chemistry. While molecular orbital (MO)-based multiconfigurational self-consistent field methods such as CASSCF and CASPT2 have become standard tools for treating such systems, valence bond (VB) theory offers a conceptually distinct and chemically intuitive alternative. Rooted in the classical Lewis structure framework, VB theory provides a compact and localized description of electron pairing, making it especially well-suited for strongly correlated systems. This review presents a comprehensive overview of the methodological development and practical applications of ab initio VB approaches, including VB self-consistent field (VBSCF), breathing orbital VB (BOVB), VB configuration interaction (VBCI), VB perturbation theory (VBPT2), and density functional VB (DFVB) methods. Particularly, the VBPT2 and DFVB methods enable accurate treatment of bond dissociation, excitation energies, and reaction barriers. Benchmark comparisons demonstrate that VB-based methods achieve performance comparable to established MO-based methods. The findings highlight the promise of VB theory as a powerful and interpretable framework for advancing the theoretical understanding of strongly correlated systems.
强相关体系具有显著的多构型特征,是量子化学研究的一个长期挑战。虽然基于分子轨道(MO)的多构型自洽场方法(如CASSCF和CASPT2)已成为处理此类体系的标准工具,但价键(VB)理论提供了一种概念上独特且化学上直观的替代方法。VB理论植根于经典的路易斯结构框架,提供了电子对的紧凑和局部描述,使其特别适合于强相关系统。本文综述了从头算VB方法的方法论发展和实际应用,包括VB自洽场(VBSCF)、呼吸轨道VB (BOVB)、VB组态相互作用(VBCI)、VB摄动理论(VBPT2)和密度泛函VB (DFVB)方法。特别是,VBPT2和DFVB方法能够精确地处理键解离、激发能和反应势垒。基准比较表明,基于vb的方法实现的性能可与已建立的基于mo的方法媲美。这些发现强调了VB理论作为一个强大的、可解释的框架的前景,可以促进对强相关系统的理论理解。
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引用次数: 0
Modulation of Electric Field and Interface on Competitive Reaction Mechanisms. 竞争反应机制中电场和界面的调制。
IF 5.5 1区 化学 Q2 CHEMISTRY, PHYSICAL Pub Date : 2025-06-20 DOI: 10.1021/acs.jctc.5c00705
Pengchao Zhang,Xuefei Xu
Recently, much evidence has accumulated, showing that electric fields and water interfaces influence the characteristics and alignment of biomolecules and greatly boost reaction rates. The prototropic tautomerism is a fundamental process in biological systems; however, a comprehensive understanding of the electric field effects and interfacial effects on it is still lacking. In this work, we performed a theoretical study of the modulation of the electric field and the interface on the tautomerism dynamics of solvated glycine by using deep potential molecular dynamics technology with enhanced sampling. The deep learning potentials used were trained to integrate long-range electrostatic interactions in order to better describe the electric field effect. We observed that an external electric field of 10 mV/Å barely changed the key structures involved in tautomerism reactions but significantly influenced their relative free energies and consequently made the transformation from zwitterionic ([Z]) to neutral ([N]) glycine more achievable both thermodynamically and dynamically and altered the optimal reaction mechanism from intramolecular proton transfer (Intra-PT) to intermolecular proton transfer (Inter-PT) involving a separate cationic-glycine-hydroxide ion pair. The detailed analysis revealed that the electric field increased the thermodynamical stability of [N] relative to [Z] by 7 kJ/mol due to the entropy effect and promoted the Inter-PT pathway by electrostatically facilitating the separation of ion pairs, causing the free-energy-barrier decrease of the rate-determined step by approximately 10 kJ/mol. Interestingly, in the air-water interface, due to the interfacial propensity of the glycine and water self-ions, the separation of ion pairs is restricted, slowing the Inter-PT pathways. Nevertheless, the interfacial interconversion between the [Z] and [N] forms of glycine is dynamically accelerated via the Intra-PT pathway due to partial solvation. These findings provide new insights into how the electric field and interfaces modulate thermodynamics, kinetics, and the mechanism of chemical reactions.
近年来,越来越多的证据表明,电场和水界面影响生物分子的特性和排列,极大地提高了反应速率。原生互变异构是生物系统的一个基本过程;然而,对其电场效应和界面效应的全面认识仍然缺乏。本文采用强化采样的深电位分子动力学技术,从理论上研究了电场调制和界面对溶剂化甘氨酸互变异构动力学的影响。为了更好地描述电场效应,所使用的深度学习电位被训练来整合远程静电相互作用。我们观察到,10 mV/Å的外电场几乎没有改变互变异构反应的关键结构,但显著影响了它们的相对自由能,从而使两性离子([Z])向中性([N])甘氨酸的转化在热力学和动力学上都更容易实现,并改变了分子内质子转移(Intra-PT)到分子间质子转移(Inter-PT)的最佳反应机制阳离子-甘氨酸-氢氧化物离子对。详细分析表明,电场由于熵效应使[N]相对于[Z]的热力学稳定性提高了7 kJ/mol,并通过静电促进离子对的分离促进了Inter-PT途径,使速率决定步骤的自由能垒降低了约10 kJ/mol。有趣的是,在空气-水界面中,由于甘氨酸和水自离子的界面倾向,离子对的分离受到限制,减缓了Inter-PT途径。然而,由于部分溶剂化,甘氨酸的[Z]和[N]形式之间的界面相互转化通过Intra-PT途径动态加速。这些发现为电场和界面如何调节热力学、动力学和化学反应机制提供了新的见解。
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引用次数: 0
Transfer Learning for Predictive Molecular Simulations: Data-Efficient Potential Energy Surfaces at CCSD(T) Accuracy. 预测分子模拟的迁移学习:CCSD(T)精度的数据高效势能面。
IF 5.5 1区 化学 Q2 CHEMISTRY, PHYSICAL Pub Date : 2025-06-20 DOI: 10.1021/acs.jctc.5c00523
Silvan Käser,Jeremy O Richardson,Markus Meuwly
Accurate potential energy surfaces (PESs) are critical for predictive molecular simulations. However, obtaining a PES at the highest levels of quantum chemical accuracy, such as CCSD(T), becomes computationally infeasible as molecular size increases. This work presents CCSD(T)-quality PESs using data-efficient techniques based on transfer learning to obtain state-of-the-art accuracy at a fraction of the computational cost for systems that would otherwise be intractable. Most importantly, the framework for accurate molecular simulations pursued here extends beyond specific observables and follows a rational strategy to obtain highest-accuracy PESs, which can be used for applications to spectroscopy and other experiments. As rigorous tests of the PESs, semiclassical tunnelling splittings for tropolone and the (propiolic acid)-(formic acid) dimer (PFD) as well as anharmonic frequencies for tropolone were determined. For tropolone, all observables are in excellent agreement with the experiment using the high-level PES, whereas for PFD, the agreement is less good but still orders of magnitude better than previous calculations.
准确的势能面(PESs)是预测分子模拟的关键。然而,随着分子大小的增加,获得最高水平量子化学精度的PES,如CCSD(T),在计算上变得不可行。这项工作提出了CCSD(T)质量的PESs,使用基于迁移学习的数据高效技术,以一小部分计算成本获得最先进的精度,否则将是难以处理的系统。最重要的是,本文所追求的精确分子模拟框架超越了特定的可观测值,并遵循合理的策略来获得最高精度的PESs,可用于光谱学和其他实验。作为PESs的严格测试,确定了tropolone和(丙酸)-(甲酸)二聚体(PFD)的半经典隧道分裂以及tropolone的非谐波频率。对于tropolone,所有观测值都与使用高水平PES的实验非常吻合,而对于PFD,一致性不太好,但仍然比以前的计算好几个数量级。
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引用次数: 0
General Quantum Alchemical Free Energy Simulations via Hamiltonian Interpolation. 基于哈密顿插值的通用量子炼金术自由能模拟。
IF 5.7 1区 化学 Q2 CHEMISTRY, PHYSICAL Pub Date : 2025-06-20 DOI: 10.1021/acs.jctc.5c00682
Chenghan Li, Xing Zhang, Garnet Kin-Lic Chan

We present an implementation of alchemical free energy simulations at the quantum mechanical level by directly interpolating the electronic Hamiltonian. The method is compatible with any level of electronic structure theory and requires only one quantum calculation for each molecular dynamics step in contrast to multiple energy evaluations that would be needed when interpolating the ground-state energies. We demonstrate the correctness and applicability of the technique by computing alchemical free energy changes of gas-phase molecules, with both nuclear and electron creation/annihilation. We also show an initial application to first-principles pKa calculation for solvated molecules where we quantum mechanically annihilate a bonded proton.

我们通过直接插入电子哈密顿量,在量子力学水平上实现了炼金术自由能的模拟。该方法与任何水平的电子结构理论兼容,并且每个分子动力学步骤只需要一个量子计算,而不是在插入基态能量时需要多次能量评估。我们通过计算具有核和电子产生/湮灭的气相分子的炼金术自由能变化来证明该技术的正确性和适用性。我们还展示了对溶剂化分子的第一性原理pKa计算的初步应用,其中我们量子力学地湮灭了键合质子。
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引用次数: 0
Exploring Chemical Space with Chemistry-Inspired Dynamic Quantum Circuits in the NISQ Era. 在NISQ时代用化学启发的动态量子电路探索化学空间。
IF 5.5 1区 化学 Q2 CHEMISTRY, PHYSICAL Pub Date : 2025-06-19 DOI: 10.1021/acs.jctc.5c00305
Lung-Yi Chen,Tai-Yue Li,Yi-Pei Li,Nan-Yow Chen,Fengqi You
The generation of chemical molecular structures is crucial for advancements in drug design, materials science, and related fields. With the rise of artificial intelligence, numerous generative models have been developed to propose promising molecular structures to specific challenges. However, exploring the vast chemical space using classical generative models demands extensive chemical structure data, considerable computational resources, and a large number of model parameters, which hinders their efficiency. Quantum computing presents a promising alternative by exploiting quantum parallelism and entanglement, potentially reducing the computational overhead required for such tasks. In this study, we designed a quantum-based molecular generator (QMG) specifically tailored to generate small molecules containing carbon, nitrogen, and oxygen atoms. This model imposes strict constraints on the quantum circuit's output quantum states, significantly eliminating mathematically invalid connection graphs and enabling more efficient sampling of valid molecular structures. Remarkably, our quantum circuit, utilizing only 134 parameters, is capable of enumerating all molecular structures comprising up to nine heavy atoms, showcasing the parameter efficiency achievable through quantum superposition and entanglement. Our experimental results show that the output generated by this circuit exhibits a high degree of validity and uniqueness after Bayesian optimization, showing comparable performance to classical deep generative models. Furthermore, by fixing specific parameters in the quantum circuits, the quantum generator can constrain the chemical space and exclusively generate chemical molecules containing specified functional groups. This feature underscores its potential value for targeted applications in specific domains, especially in drug discovery. Overall, this compact design not only reduces parameter demands but also enables efficient exploration of a nontrivial portion of chemical space, demonstrating a key advantage of quantum-based generative models over larger classical counterparts.
化学分子结构的生成对于药物设计、材料科学和相关领域的进步至关重要。随着人工智能的兴起,许多生成模型已经被开发出来,以提出有前途的分子结构来应对特定的挑战。然而,利用经典生成模型探索广阔的化学空间需要大量的化学结构数据、大量的计算资源和大量的模型参数,这阻碍了它们的效率。量子计算通过利用量子并行性和纠缠提供了一个有前途的替代方案,有可能减少此类任务所需的计算开销。在这项研究中,我们设计了一个基于量子的分子发生器(QMG),专门用于生成含有碳、氮和氧原子的小分子。该模型对量子电路的输出量子态施加了严格的约束,显著地消除了数学上无效的连接图,并使有效分子结构的采样更有效。值得注意的是,我们的量子电路仅使用134个参数,就能够枚举包含多达9个重原子的所有分子结构,展示了通过量子叠加和纠缠实现的参数效率。实验结果表明,经过贝叶斯优化后,该电路生成的输出具有高度的有效性和唯一性,性能与经典深度生成模型相当。此外,通过在量子电路中固定特定参数,量子发生器可以约束化学空间,并专门生成含有特定官能团的化学分子。这一特性强调了它在特定领域的靶向应用的潜在价值,特别是在药物发现方面。总的来说,这种紧凑的设计不仅减少了参数需求,而且能够有效地探索化学空间的重要部分,展示了基于量子的生成模型相对于大型经典模型的关键优势。
{"title":"Exploring Chemical Space with Chemistry-Inspired Dynamic Quantum Circuits in the NISQ Era.","authors":"Lung-Yi Chen,Tai-Yue Li,Yi-Pei Li,Nan-Yow Chen,Fengqi You","doi":"10.1021/acs.jctc.5c00305","DOIUrl":"https://doi.org/10.1021/acs.jctc.5c00305","url":null,"abstract":"The generation of chemical molecular structures is crucial for advancements in drug design, materials science, and related fields. With the rise of artificial intelligence, numerous generative models have been developed to propose promising molecular structures to specific challenges. However, exploring the vast chemical space using classical generative models demands extensive chemical structure data, considerable computational resources, and a large number of model parameters, which hinders their efficiency. Quantum computing presents a promising alternative by exploiting quantum parallelism and entanglement, potentially reducing the computational overhead required for such tasks. In this study, we designed a quantum-based molecular generator (QMG) specifically tailored to generate small molecules containing carbon, nitrogen, and oxygen atoms. This model imposes strict constraints on the quantum circuit's output quantum states, significantly eliminating mathematically invalid connection graphs and enabling more efficient sampling of valid molecular structures. Remarkably, our quantum circuit, utilizing only 134 parameters, is capable of enumerating all molecular structures comprising up to nine heavy atoms, showcasing the parameter efficiency achievable through quantum superposition and entanglement. Our experimental results show that the output generated by this circuit exhibits a high degree of validity and uniqueness after Bayesian optimization, showing comparable performance to classical deep generative models. Furthermore, by fixing specific parameters in the quantum circuits, the quantum generator can constrain the chemical space and exclusively generate chemical molecules containing specified functional groups. This feature underscores its potential value for targeted applications in specific domains, especially in drug discovery. Overall, this compact design not only reduces parameter demands but also enables efficient exploration of a nontrivial portion of chemical space, demonstrating a key advantage of quantum-based generative models over larger classical counterparts.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":"21 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144320357","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
A Computational Framework for Simulations of Dissipative Nonadiabatic Dynamics on Hybrid Oscillator-Qubit Quantum Devices. 振荡-量子位混合量子器件耗散非绝热动力学模拟的计算框架。
IF 5.7 1区 化学 Q2 CHEMISTRY, PHYSICAL Pub Date : 2025-06-18 DOI: 10.1021/acs.jctc.5c00315
Nam P Vu, Daniel Dong, Xiaohan Dan, Ningyi Lyu, Victor Batista, Yuan Liu

We introduce a computational framework for simulating nonadiabatic vibronic dynamics on circuit quantum electrodynamics (cQED) platforms. Our approach leverages hybrid oscillator-qubit quantum hardware with midcircuit measurements and resets, enabling the incorporation of environmental effects such as dissipation and dephasing. To demonstrate its capabilities, we simulate energy transfer dynamics in a triad model of photosynthetic chromophores inspired by natural antenna systems. We specifically investigate the role of dissipation during the relaxation dynamics following photoexcitation, where electronic transitions are coupled to the evolution of quantum vibrational modes. Our results indicate that hybrid oscillator-qubit devices, operating with noise levels below the intrinsic dissipation rates of typical molecular antenna systems, can achieve the simulation fidelity required for practical computations on near-term and early fault-tolerant quantum computing platforms.

我们介绍了一个在电路量子电动力学(cQED)平台上模拟非绝热振动动力学的计算框架。我们的方法利用混合振荡器-量子比特量子硬件与中路测量和复位,使环境影响,如耗散和去相结合。为了证明它的能力,我们在受自然天线系统启发的光合作用发色团的三元模型中模拟能量传递动力学。我们特别研究了耗散在光激发后弛豫动力学中的作用,其中电子跃迁与量子振动模式的演化相耦合。我们的研究结果表明,在噪声水平低于典型分子天线系统固有耗散率的情况下,混合振荡器-量子比特器件可以在近期和早期容错量子计算平台上实现实际计算所需的模拟保真度。
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引用次数: 0
Combining Fast Exploration with Accurate Reweighting in the OPES-eABF Hybrid Sampling Method. OPES-eABF混合采样方法中快速勘探与精确加权的结合。
IF 5.5 1区 化学 Q2 CHEMISTRY, PHYSICAL Pub Date : 2025-06-18 DOI: 10.1021/acs.jctc.5c00395
Andreas Hulm,Robert P Schiller,Christian Ochsenfeld
On-the-fly probability enhanced sampling (OPES) has recently been introduced [Invernizzi, M.; Parrinello, M. J. Chem. Theory Comput. 2022, 18, 3988-3996], with important improvements over the highly popular metadynamics methods. In our work, we introduce a new combination of OPES with the extended-system adaptive biasing force (eABF) method. We show that the resulting OPES-eABF hybrid is highly robust to the choice of input parameters, while ensuring faster exploration of configuration space than the original OPES. The only critical parameter of OPES-eABF is the coupling width to the extended-system, for which we introduce an automatic algorithm based on a short initial unbiased simulation, such that OPES-eABF requires minimal user intervention. Additionally, we show that due to the decoupling of the physical system from the time-dependent potential, unbiased probabilities of visited configurations are recovered highly accurately.
动态概率增强抽样(OPES)最近被引入[Invernizzi, M.;Parrinello, m.j. Chem。理论计算,2022,18,3988-3996],对非常流行的元动力学方法进行了重要改进。在我们的工作中,我们引入了一种新的OPES与扩展系统自适应偏置力(eABF)方法的组合。结果表明,所得到的OPES- eabf混合算法对输入参数的选择具有高度鲁棒性,同时确保比原始OPES更快地探索配置空间。OPES-eABF的唯一关键参数是与扩展系统的耦合宽度,为此我们引入了一种基于短初始无偏模拟的自动算法,使得OPES-eABF需要最少的用户干预。此外,我们表明,由于物理系统与时间相关势的解耦,访问组态的无偏概率被高度准确地恢复。
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引用次数: 0
State-Interaction Approach for g-Matrix Calculations in TDDFT: Ground-Excited State Couplings and beyond First-Order Spin-Orbit Effects. TDDFT中g矩阵计算的状态-相互作用方法:基态激发态耦合和超一阶自旋轨道效应。
IF 5.5 1区 化学 Q2 CHEMISTRY, PHYSICAL Pub Date : 2025-06-18 DOI: 10.1021/acs.jctc.5c00514
Antonio Cebreiro-Gallardo,David Casanova
We introduce a state-interaction approach for computing g-matrices within time-dependent density functional theory (TDDFT) and the Tamm-Dancoff approximation (TDA), applied here for the first time. This method provides a detailed understanding of g-shifts by explicitly accounting for spin-orbit couplings (SOC) and excitation energies, enabling the analysis of different SOC orders and their contributions. To evaluate its accuracy and reliability, we compare state-interaction TDDFT and TDA with the widely used one-component coupled-perturbed Kohn-Sham approach. Applications to a diverse set of systems, including light and heavy atom molecules as well as transition-metal complexes, demonstrate that both methods yield comparable results in the absence of heavy elements, while the state-interaction approach offers improved insights into SOC effects and their impact on g-shifts.
我们在时间相关密度泛函理论(TDDFT)和tam - dancoff近似(TDA)中引入了一种状态相互作用方法来计算g矩阵,这是第一次在这里应用。该方法通过明确地考虑自旋轨道耦合(SOC)和激发能,提供了对g位移的详细理解,从而可以分析不同的SOC阶数及其贡献。为了评估其准确性和可靠性,我们将状态交互TDDFT和TDA与广泛使用的单分量耦合摄动Kohn-Sham方法进行了比较。应用于各种系统,包括轻原子分子和重原子分子以及过渡金属配合物,表明两种方法在缺乏重元素的情况下产生相似的结果,而状态相互作用方法提供了对SOC效应及其对g位移影响的改进见解。
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引用次数: 0
Graphically Defined Model Reactions Are Extensible, Accurate, and Systematically Improvable. 图形定义的模型反应是可扩展的,准确的,系统的改进。
IF 5.7 1区 化学 Q2 CHEMISTRY, PHYSICAL Pub Date : 2025-06-17 DOI: 10.1021/acs.jctc.5c00279
Qiyuan Zhao, Veerupaksh Singla, Hsuan-Hao Hsu, Brett M Savoie

Achieving fast and accurate reaction prediction is central to a suite of chemical applications. Nevertheless, classic approaches based on templates or simple models are typically fast but with limited scope or accuracy, while the emerging machine learning-based models are limited in their transferability due to the lack of large reaction databases. Here, we address these limitations by formalizing the model reaction concept based on fixed-depth condensed reaction graphs that are shown to achieve a cost and accuracy balance that is applicable to many problems. The model reaction concept can be utilized to provide reliable predictions of activation energies and transition state geometries for a large range of organic reactions. In addition, using an alkane pyrolysis system as a benchmarking example, we show that the accuracy of the activation energy prediction can be further improved by adding correction terms based on the empirical Brønsted-Evans-Polanyi (BEP) relationship. These successful applications demonstrate that the model reaction can serve as a general tool to reduce the cost associated with ab initio transition state searches.

实现快速和准确的反应预测是核心的一套化学应用。然而,基于模板或简单模型的经典方法通常速度很快,但范围或准确性有限,而新兴的基于机器学习的模型由于缺乏大型反应数据库而在可移植性方面受到限制。在这里,我们通过形式化基于固定深度浓缩反应图的模型反应概念来解决这些限制,这些反应图显示出实现适用于许多问题的成本和准确性平衡。模型反应概念可用于为大范围的有机反应提供活化能和过渡态几何形状的可靠预测。此外,以烷烃热解体系为基准,我们发现在经验Brønsted-Evans-Polanyi (BEP)关系的基础上加入校正项可以进一步提高活化能预测的准确性。这些成功的应用表明,模型反应可以作为一种通用的工具,以减少从头算过渡态搜索相关的成本。
{"title":"Graphically Defined Model Reactions Are Extensible, Accurate, and Systematically Improvable.","authors":"Qiyuan Zhao, Veerupaksh Singla, Hsuan-Hao Hsu, Brett M Savoie","doi":"10.1021/acs.jctc.5c00279","DOIUrl":"https://doi.org/10.1021/acs.jctc.5c00279","url":null,"abstract":"<p><p>Achieving fast and accurate reaction prediction is central to a suite of chemical applications. Nevertheless, classic approaches based on templates or simple models are typically fast but with limited scope or accuracy, while the emerging machine learning-based models are limited in their transferability due to the lack of large reaction databases. Here, we address these limitations by formalizing the model reaction concept based on fixed-depth condensed reaction graphs that are shown to achieve a cost and accuracy balance that is applicable to many problems. The model reaction concept can be utilized to provide reliable predictions of activation energies and transition state geometries for a large range of organic reactions. In addition, using an alkane pyrolysis system as a benchmarking example, we show that the accuracy of the activation energy prediction can be further improved by adding correction terms based on the empirical Brønsted-Evans-Polanyi (BEP) relationship. These successful applications demonstrate that the model reaction can serve as a general tool to reduce the cost associated with ab initio transition state searches.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144315558","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
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Journal of Chemical Theory and Computation
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