Part II Molecules , Interfaces , and Solids

Future Generation Computer Systems, 1996

Over the last three decades the methods of quantum chemistry have shown an impressive development: a large number of reliable and efficient approximations to the solution of the non-relativistic Schrödinger and the relativistic Dirac equation, respectively, are available. This is complemented by the availability of a number of well-developed computer programs which allow of the treatment of chemical problems as a matter of routine. This progress has been acknowledged by the Nobel prize in chemistry 1998 to John Pople and Walter Kohn for the development of quantum chemical methods.

Computer Physics Communications, 2001

In this paper we would discuss the increasing role played by the past and upcoming silicon technology in solving real computational applications' cases in correlated scientific fields ranging from quantum chemistry, materials science, atomic and molecular physics and bio-chemistry. Although the wide range of computational applications of computer technology in this areas does not permit to have a full rationale of its present and future role, some basic features appear to be so clearly defined that an attempt to find common numerical behaviours become now feasible to be exploited.

2016

Computing in theoretical chemistry has been largely and traditionally based on purely numerical 'non-intelligent' computing techniques. The tools of 'Artificial Intelligence' (AI) or 'Computational Intelligence' have been little explored and exploited In the context of research in theoretical chemistry. Over the last decade and a half we had been experimenting with 'evolutionary computing techniques' like the Genetic Algorithms and Random Mutation Hill Climbing in the general context of computing electronic structure of atoms and molecules. These methods have the underpinning of certain microscopic low-level biological processes and are supposed to be endowed with' Artificial Intelligence'. We trace the evolution of the AI-based techniques developed by us and review some of the rather non-trivial applications. In particular, we focus on an Adaptive Random Mutation HilI Climbing (ARMHC) method Cor locating global minima on the complex potential energy landscapes of 3-D Coulomb clusters and assessing the possibilities of structural phase transitions in them. Possible directions of future developments are indicated.

2014

Israel Journal of Chemistry, 2015

Journal of Chemical Theory and Computation, 2009

Modern videogames place increasing demands on the computational and graphical hardware, leading to novel architectures that have great potential in the context of high performance computing and molecular simulation. We demonstrate that Graphical Processing Units (GPUs) can be used very efficiently to calculate two-electron repulsion integrals over Gaussian basis functionssthe first step in most quantum chemistry calculations. A benchmark test performed for the evaluation of approximately 10 6 (ss|ss) integrals over contracted s-orbitals showed that a naïve algorithm implemented on the GPU achieves up to 130-fold speedup over a traditional CPU implementation on an AMD Opteron. Subsequent calculations of the Coulomb operator for a 256-atom DNA strand show that the GPU advantage is maintained for basis sets including higher angular momentum functions.

Theoretical and Computational Chemistry, 1999

Computation, 2013

Environmental Health Perspectives, 1996

Molecular dynamics is a general technique for simulating the time-dependent properties of molecules and their environments. Quantum mechanics, as applied to molecules or clusters of molecules, provides a prescription for predicting properties exactly (in principle). It is reasonable to expect that both will have a profound effect on our understanding of environmental chemistry in the future. In this review, we consider several recent advances and applications in computational chemistry.