Nagy Péter R
Department of Physical Chemistry and Materials Science, Faculty of Chemical Technology and Biotechnology, Budapest University of Technology and Economics Műegyetem rkp. 3. H-1111 Budapest Hungary.
HUN-REN-BME Quantum Chemistry Research Group Műegyetem rkp. 3. H-1111 Budapest Hungary.
Chem Sci. 2024 Aug 28;15(36):14556-84. doi: 10.1039/d4sc04755a.
In this feature, we review the current capabilities of local electron correlation methods up to the coupled cluster model with single, double, and perturbative triple excitations [CCSD(T)], which is a gold standard in quantum chemistry. The main computational aspects of the local method types are assessed from the perspective of applications, but the focus is kept on how to achieve chemical accuracy (, <1 kcal mol uncertainty), as well as on the broad scope of chemical problems made accessible. The performance of state-of-the-art methods is also compared, including the most employed DLPNO and, in particular, our local natural orbital (LNO) CCSD(T) approach. The high accuracy and efficiency of the LNO method makes chemically accurate CCSD(T) computations accessible for molecules of hundreds of atoms with resources affordable to a broad computational community (days on a single CPU and 10-100 GB of memory). Recent developments in LNO-CCSD(T) enable systematic convergence and robust error estimates even for systems of complicated electronic structure or larger size (up to 1000 atoms). The predictive power of current local CCSD(T) methods, usually at about 12 order of magnitude higher cost than hybrid density functional theory (DFT), has become outstanding on the palette of computational chemistry applicable for molecules of practical interest. We also review more than 50 LNO-based and other advanced local-CCSD(T) applications for realistic, large systems across molecular interactions as well as main group, transition metal, bio-, and surface chemistry. The examples show that properly executed local-CCSD(T) can contribute to binding, reaction equilibrium, rate constants, which are able to match measurements within the error estimates. These applications demonstrate that modern, open-access, and broadly affordable local methods, such as LNO-CCSD(T), already enable predictive computations and atomistic insight for complicated, real-life molecular processes in realistic environments.
在本专题中，我们回顾了直至包含单、双激发以及微扰三激发的耦合簇模型[CCSD(T)]的局域电子相关方法的当前能力，CCSD(T)是量子化学中的金标准。从应用的角度评估了局域方法类型的主要计算方面，但重点是如何实现化学精度（不确定性<1 kcal/mol），以及可解决的化学问题的广泛范围。还比较了最先进方法的性能，包括最常用的DLPNO方法，特别是我们的局域自然轨道（LNO）CCSD(T)方法。LNO方法的高精度和高效率使得对于拥有数百个原子的分子，能够以广大计算群体可承受的资源（单个CPU上运行数天以及10 - 100 GB内存）进行化学精度的CCSD(T)计算。LNO - CCSD(T)的最新进展使得即使对于具有复杂电子结构或更大尺寸（多达1000个原子）的系统也能实现系统收敛和稳健的误差估计。当前局域CCSD(T)方法的预测能力，通常比杂化密度泛函理论（DFT）高约12个数量级的成本，在适用于实际感兴趣分子的计算化学方法中已表现出色。我们还回顾了50多个基于LNO以及其他先进的局域CCSD(T)在涉及分子相互作用以及主族、过渡金属、生物和表面化学的实际大型系统中的应用。这些例子表明，正确执行的局域CCSD(T)可用于结合、反应平衡、速率常数的计算，其结果能够在误差估计范围内与测量值相匹配。这些应用表明，诸如LNO - CCSD(T)之类的现代、开放获取且广泛适用的局域方法，已经能够对现实环境中复杂的实际分子过程进行预测性计算并提供原子层面的见解。
