Molecular tailoring approach: a route for ab initio treatment of large clusters

Conspectus Chemistry on the scale of molecular clusters may be dramatically different from that in the macroscopic bulk. Greater understanding of chemistry in this size regime could greatly influence fields such as materials science and atmospheric and environmental chemistry. Recent advances in experimental techniques and computational resources have led to accurate investigations of the energies and spectral properties of weakly bonded molecular clusters. These have enabled researchers to learn how the physicochemical properties evolve from individual molecules to bulk materials and to understand the growth patterns of clusters. Experimental techniques such as infrared, microwave, and photoelectron spectroscopy are the most popular and powerful tools for probing molecular clusters. In general, these experimental techniques do not directly reveal the atomistic details of the clusters but provide data from which the structural details need to be unearthed. Furthermore, the resolution of the spectral properties of energetically close cluster conformers can be prohibitively difficult. Thus, these investigations of molecular aggregates require a combination of experiments and theory. On the theoretical front, researchers have been actively engaged in quantum chemical ab initio calculations as well as simulation-based studies for the last few decades. To obtain reliable results, there is a need to use correlated methods such as Møller-Plesset second order method, coupled cluster theory, or dispersion corrected density functional theory. However, due to nonlinear scaling of these methods, optimizing the geometry of large clusters still remains a formidable quantum chemistry challenge. Fragment-based methods, such as divide-and-conquer, molecular tailoring approach (MTA), fragment molecular orbitals, and generalized energy-based fragmentation approach, provide alternatives for overcoming the scaling problem for spatially extended molecular systems. Within MTA, a large system is broken down into two or more subsystems that can be readily treated computationally. Finally, the properties of the large system are obtained by patching the corresponding properties of all the subsystems. Due to these approximations, the resulting MTA-based energies carry some error in comparison with calculations based on the full system. An approach for correcting these errors has been attempted by grafting the error at a lower basis set onto a higher basis set. Furthermore, investigating the growth patterns and nucleation processes in clusters is necessary for understanding the structural transitions and the phenomena of magic numbers in cluster chemistry. Therefore, systematic building-up or the introduction of stochastics for generating molecular assemblies is the most crucial step for studying large clusters. In this Account, we discuss the working principle of MTA for probing molecular clusters at ab initio level followed by a brief summary of an automated and electrostatics-guided algorithm for building molecular assemblies. The molecular aggregates presented here as test cases are generated based on either an electrostatic criterion or the basin hopping method. At MP2 level computation, the errors in MTA-based grafted energies are typically reduced to a submillihartree level, reflecting the potential of finding accurate energies of molecular clusters much more quickly. In summary, MTA provides a platform for effectively studying large molecular clusters at ab initio level of theory using minimal computer hardware.