Jaramillo-Botero Andres, Nielsen Robert, Abrol Ravi, Su Julius, Pascal Tod, Mueller Jonathan, Goddard William A
Chemistry and Chemical Engineering, California Institute of Technology, Mail code 139-74, 1200 E California Blvd, Pasadena, CA 91125, USA.
Top Curr Chem. 2012;307:1-42. doi: 10.1007/128_2010_114.
We expect that systematic and seamless computational upscaling and downscaling for modeling, predicting, or optimizing material and system properties and behavior with atomistic resolution will eventually be sufficiently accurate and practical that it will transform the mode of development in the materials, chemical, catalysis, and Pharma industries. However, despite truly dramatic progress in methods, software, and hardware, this goal remains elusive, particularly for systems that exhibit inherently complex chemistry under normal or extreme conditions of temperature, pressure, radiation, and others. We describe here some of the significant progress towards solving these problems via a general multiscale, multiparadigm strategy based on first-principles quantum mechanics (QM), and the development of breakthrough methods for treating reaction processes, excited electronic states, and weak bonding effects on the conformational dynamics of large-scale molecular systems. These methods have resulted directly from filling in the physical and chemical gaps in existing theoretical and computational models, within the multiscale, multiparadigm strategy. To illustrate the procedure we demonstrate the application and transferability of such methods on an ample set of challenging problems that span multiple fields, system length- and timescales, and that lay beyond the realm of existing computational or, in some case, experimental approaches, including understanding the solvation effects on the reactivity of organic and organometallic structures, predicting transmembrane protein structures, understanding carbon nanotube nucleation and growth, understanding the effects of electronic excitations in materials subjected to extreme conditions of temperature and pressure, following the dynamics and energetics of long-term conformational evolution of DNA macromolecules, and predicting the long-term mechanisms involved in enhancing the mechanical response of polymer-based hydrogels.
我们期望，通过原子尺度分辨率对材料和系统的性质及行为进行建模、预测或优化的系统且无缝的计算上采样和下采样，最终将足够准确和实用，从而改变材料、化学、催化和制药行业的发展模式。然而，尽管在方法、软件和硬件方面取得了巨大进展，但这一目标仍然难以实现，特别是对于在温度、压力、辐射等正常或极端条件下呈现固有复杂化学性质的系统。我们在此描述了通过基于第一性原理量子力学（QM）的通用多尺度、多范式策略解决这些问题所取得的一些重大进展，以及开发用于处理反应过程、激发电子态和弱键合对大规模分子系统构象动力学影响的突破性方法。这些方法直接源于在多尺度、多范式策略中填补现有理论和计算模型中的物理和化学空白。为了说明该过程，我们在一系列具有挑战性的问题上展示了此类方法的应用和可转移性，这些问题跨越多个领域、系统长度和时间尺度，超出了现有计算方法或在某些情况下超出了实验方法的范畴，包括理解溶剂化对有机和有机金属结构反应性的影响、预测跨膜蛋白结构、理解碳纳米管的成核和生长、理解在极端温度和压力条件下材料中电子激发的影响、跟踪DNA大分子长期构象演化的动力学和能量学，以及预测增强聚合物基水凝胶机械响应的长期机制。
