今年的诺贝尔化学奖给了理论学者Martin Karplus, Michael Levitt and Arieh Warshel，相信不少做过催化反应计算的学者都会为之兴奋。

  在分子尺度（粗略100个原子）和微观尺度（粗略1万个原子）之间，存在有一个gap。分子尺度下，基于量子力（QM）学密度泛函理论的第一性原理计算可以描述小颗粒的电子结构特性。在微观尺度下，基于经典力学的分子动力学模拟（MM) 可以描述物质的热力学特性。然而，在两者之间，昂贵的第一原理计算无法计算如此大的体系，而基于经典的分子动力学无法计算物质的电子结构等量子力学特性。由此，产生了QM/MM的计算方法。其核心思想是分层计算，重要的位置用较贵的QM算法，周围的位置用MM算法。

  除QM/MM之外，TB算法，或DFTB算法也可以计算较大体系的物质。我们组提出的BOLS-TB算法，也是对处于此区间的物质的计算所做的尝试。

附1：

This year laureates have developed and applied every kind of theoretical technique, from strictly quantum mechanical calculations to highly parametrized classical and semiclassical ones based on empirical data, to simulating a vast number of diverse molecules. They have also developed software that brought these computations to the masses. The quantum mechanical methods are often called ‘ab initio’ – from first principles – and were already recognized with a prize in 1998, but this prize honors something much broader. Techniques developed by the trio include molecular dynamics (MD) which tries to simulate the real life movement of complex entities like proteins, along with electrostatic calculations which try to calculate the attraction and repulsion between charged atoms and molecules.

附2：

BOLS-TB算法在graphene上的应用：

 Nanoscale，2010，Volume: 2，Issue: 10，Pages: 2160-2163

Carbon，2011，Volume: 49，Issue: 11，Pages: 3615-3621