Extensive ab initio calculations have been performed using the 6-31G(d,p) and 6-311++G(2d,2p) basis sets for several possible structures of water clusters (H 2 O) n , n ) 8-20. It is found that the most stable geometries arise from a fusion of tetrameric or pentameric rings. As a result, (H 2 O) n , n ) 8, 12, 16, and 20, are found to be cuboids, while (H 2 O) 10 and (H 2 O) 15 are fused pentameric structures. For the other water clusters (n ) 9, 11, 13, 14, and 17-19) under investigation, the most stable geometries can be thought of as arising from either the cuboid or the fused pentamers or a combination thereof. The stability of some of the clusters, namely, n ) 8-16, has also been studied using density functional theory. An attempt has been made to estimate the basis set superposition error and zero-point energy correction for such clusters at the HartreeFock (HF) level using the 6-311++G(2d,2p) basis set. To ensure that a minimum on the potential-energy surface has been located, frequency calculations have been carried out at the HF level using the 6-31G(d,p) and 6-311++G(2d,2p) basis sets for some of the clusters. Molecular electrostatic potential topography mapping has been employed for understanding the reactivity as well as the binding patterns of some of the structurally interesting clusters.

A linear-scaling scheme for estimating the electronic energy, gradients, and Hessian of a large molecule at ab initio level of theory based on fragment set cardinality is presented. With this proposition, a general, cardinality-guided molecular tailoring approach (CG-MTA) for ab initio geometry optimization of large molecules is implemented. The method employs energy gradients extracted from fragment wave functions, enabling computations otherwise impractical on PC hardware. Further, the method is readily amenable to large scale coarse-grain parallelization with minimal communication among nodes, resulting in a near-linear speedup. CG-MTA is applied for density-functional-theory-based geometry optimization of a variety of molecules including alpha-tocopherol, taxol, gamma-cyclodextrin, and two conformations of polyglycine. In the tests performed, energy and gradient estimates obtained from CG-MTA during optimization runs show an excellent agreement with those obtained from actual computation. Accuracy of the Hessian obtained employing CG-MTA provides good hope for the application of Hessian-based geometry optimization to large molecules.

We report on the organization and outcome of the fourth blind test of crystal structure prediction, an international collaborative project organized to evaluate the present state in computational methods of predicting the crystal structures of small organic molecules. There were 14 research groups which took part, using a variety of methods to generate and rank the most likely crystal structures for four target systems: three single-component crystal structures and a 1:1 cocrystal. Participants were challenged to predict the crystal structures of the four systems, given only their molecular diagrams, while the recently determined but as-yet unpublished crystal structures were withheld by an independent referee. Three predictions were allowed for each system. The results demonstrate a dramatic improvement in rates of success over previous blind tests; in total, there were 13 successful predictions and, for each of the four targets, at least two groups correctly predicted the observed crystal structure. The successes include one participating group who correctly predicted all four crystal structures as their first ranked choice, albeit at a considerable computational expense. The results reflect important improvements in modelling methods and suggest that, at least for the small and fairly rigid types of molecules included in this blind test, such calculations can be constructively applied to help understand crystallization and polymorphism of organic molecules.

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Evaluation of two-electron integrals forms a substantial part of the CPU time for any ab initio molecular orbital program. This part of the package, "MICROMOL", is parallelized. However, this parallelization leads to only sublinear speedups (typically 3 on a 4-node machine). In view of these results, the task of development of an efficient program for two-electron integrals suitable for the parallel environment has been taken up. The program is written in FORTRAN considering specific symmetry features and application of rigorous bounds. This program is further parallelized with a good load balancing strategy. The molecules used as the test cases are: trans-butadiene, benzene, nitrobenzene, naphtalene and cytosine, with 3 G and 4-31 G basis sets. The results indicate that the parallel version of this program gives a typical speedup of 3.6 for a 3 G basis set and approximately 3.4 for a 4-31 G basis set for all the molecules tested. The sequential version of this program is ~1.2 times faster than the sequential version of MICROMOL, whereas the parallel version is ~ 1.4 times faster than the parallelized MICROMOL. PACS: 31.15. + q; 31.20.Ej.

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 molecul...