Scalable computational chemistry: new developments and applications

The computational part of the thesis is the investigation of titanium chloride (II) as a potential catalyst for the bis-silylation reaction of ethylene with hexaclorodisilane at different levels of theory. Bis-silylation is an important reaction for producing bis(silyl) compounds and new C-Si bonds, which can serve as monomers for silicon containing polymers and silicon carbides. Ab initio calculations on the steps involved in a proposed mechanism are presented. This choice of reactants allows us to study this reaction at reliable levels of theory without compromising accuracy. Our calculations indicate that this is a highly exothermic barrierless reaction. The TiCl 2 catalyst removes a 50 kcal/mol activation energy barrier required for the reaction without the catalyst. The first step is interaction of TiCl 2 with ethylene to form an intermediate that is 60 kcal/mol below the energy of the reactants. This is the driving force for the entire reaction. Dynamic correlation plays a significant role because RHF calculations indicate that the net barrier for the catalyzed reaction is 50 kcal/mol. We conclude that divalent Ti has the potential to become an important industrial catalyst for silylation reactions.;In the programming part of the thesis, parallelization of different quantum chemistry methods is presented. The parallelization of code is becoming important aspect of quantum chemistry code development. Two trends contribute to it: the overall desire to study large chemical systems and the desire to employ highly correlated methods which are usually computationally and memory expensive. In the presented distributed data algorithms computation is parallelized and the largest arrays are evenly distributed among CPUs. First, the parallelization of the Hartree-Fock self-consistent field (SCF) method is considered. SCF method is the most common starting point for more accurate calculations. The Fock build (sub step of SCF) from AO integrals is also often used to avoid MO integral computation. The presented distributed data SCF increases the size of chemical systems that can be calculated by using RHF and DFT. The important ab initio method to study bond formation and breaking as well as excited molecules is CASSCF. The presented distributed data CASSCF algorithm can significantly decrease computational time and memory requirements per node. Therefore, large CASSCF computations can be performed. The most time consuming operation to study potential energy surfaces of reactions and chemical systems is Hessian calculations. The distributed data parallelization of CPHF will allow scientists carry out large analytic Hessian calculations

An efficient MPI/OpenMP parallelization of the Hartree-Fock method for the second generation of Intel Xeon Phi processor

Modern OpenMP threading techniques are used to convert the MPI-only Hartree-Fock code in the GAMESS program to a hybrid MPI/OpenMP algorithm. Two separate implementations that differ by the sharing or replication of key data structures among threads are considered, density and Fock matrices. All implementations are benchmarked on a super-computer of 3,000 Intel Xeon Phi processors. With 64 cores per processor, scaling numbers are reported on up to 192,000 cores. The hybrid MPI/OpenMP implementation reduces the memory footprint by approximately 200 times compared to the legacy code. The MPI/OpenMP code was shown to run up to six times faster than the original for a range of molecular system sizes.Comment: SC17 conference paper, 12 pages, 7 figure

CRYSTAL14: A program for the ab initio investigation of crystalline solids

The capabilities of the CRYSTAL14 program are presented, and the improvements made with respect to the previous CRYSTAL09 version discussed. CRYSTAL14 is an ab initio code that uses a Gaussian-type basis set: both pseudopotential and all-electron strategies are permitted; the latter is not much more expensive than the former up to the first-second transition metal rows of the periodic table. A variety of density functionals is available, including as an extreme case Hartree–Fock; hybrids of various nature (global, range-separated, double) can be used. In particular, a very efficient implementation of global hybrids, such as popular B3LYP and PBE0 prescriptions, allows for such calculations to be performed at relatively low computational cost. The program can treat on the same grounds zero-dimensional (molecules), one-dimensional (polymers), two-dimensional (slabs), as well as three-dimensional (3D; crystals) systems. No spurious 3D periodicity is required for low-dimensional systems as happens when plane-waves are used as a basis set. Symmetry is fully exploited at all steps of the calculation; this permits, for example, to investigate nanotubes of increasing radius at a nearly constant cost (better than linear scaling!) or to perform self-consistent-field (SCF) calculations on fullerenes as large as (10,10), with 6000 atoms, 84,000 atomic orbitals, and 20 SCF cycles, on a single core in one day. Three versions of the code exist, serial, parallel, and massive-parallel. In the second one, the most relevant matrices are duplicated, whereas in the third one the matrices in reciprocal space are distributed for diagonalization. All the relevant vectors are now dynamically allocated and deallocated after use, making CRYSTAL14 much more agile than the previous version, in which they were statically allocated.The program now fits more easily in low-memory machines (as many supercomputers nowadays are). CRYSTAL14 can be used on parallel machines up to a high number of cores (benchmarks up to 10,240 cores are documented) with good scalability, the main limitation remaining the diagonalization step. Many tensorial properties can be evaluated in a fully automated way by using a single input keyword: elastic, piezoelectric, photoelastic, dielectric, as well as first and second hyperpolarizabilies, electric field gradients, Born tensors and so forth. Many tools permit a complete analysis of the vibrational properties of crystalline compounds. The infrared and Raman intensities are now computed analytically and related spectra can be generated. Isotopic shifts are easily evaluated, frequencies of only a fragment of a large system computed and nuclear contribution to the dielectric tensor determined. New algorithms have been devised for the investigation of solid solutions and disordered systems. The topological analysis of the electron charge density, according to the Quantum Theory of Atoms in Molecules, is now incorporated in the code via the integrated merge of the TOPOND package. Electron correlation can be evaluated at the Möller–Plesset second-order level (namely MP2) and a set of double-hybrids are presently available via the integrated merge with the CRYSCOR program

A needed response: Fragment molecular orbital analytic gradients

Ab initio quantum chemistry seeks to describe and elucidate chemical species and processes using quantum mechanics. For dynamical chemical processes, molecular dynamics (MD), where the atoms of a chemical system move according to Newton\u27s laws of motion, is frequently used. MD calculations have historically used classical mechanics rather than quantum mechanics to describe the evolution of a chemical system. The use of classical mechanics with MD has proven to be a great success, but classical MD has deficiencies, since quantum mechanics must be used to describe important chemical phenomena such as bond breaking or excited states accurately. With the increase of computer power over the past half-century, ab initio MD (AIMD) methods that describe a chemical system using quantum mechanics have been developed to eliminate the deficiencies of classical MD. Unfortunately, the application of AIMD is limited to small systems and short time scales since standard quantum chemical methods exhibit non-linear scaling with system size. More recently, new approaches have circumvented the non-linear scaling of quantum chemical methods by exploiting the fact that most chemical interactions are local and therefore distant interactions can be approximated or even ignored. Other methods obtain quantum mechanical accuracy at a cost associated with classical mechanics by deriving a classical force field directly from ab initio calculations. Individually and in combination, methods that eliminate the non-linear scaling of standard ab initio methods have the potential to extend the reach of AIMD to larger systems such as surfaces, molecular clusters, bulk liquids, and proteins