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Gaussian 76 is a general-purpose computer program for ab initio Hartree-Fock molecular orbital calculations. It can handle basis sets involving s, p and d-type Gaussian functions. Certain standard sets (STO-3G, 4-31G, 6-31G*, etc.) are stored internally for easy use. Closed shell (RHF) or unrestricted open shell (UHF) wave functions can be obtained. Facilities are provided for geometry optimization to potential minima and for limited potential surface scans.
Carbon monoxide chemisorption on transition metal surfaces has been one of the most extensively studied in surface science in past years due to its importance in a variety of catalytic processes, especially, automotive catalytic converters using Pt or Pd. The authors have performed ab initio studies to understand the electronic and geometric aspects of the Pd-CO bond in small carbonyl clusters and the CO covered (2 x 1)p2mg superstructure of the Pd(110) surface. They have used the standard quantum chemistry package Gaussian to study the former system and a LDA (local density approximation) formalism using ab initio pseudopotentials and amore plane wave basis to study the latter. The latter results are preliminary; the authors intended to study thicker slabs in the future. The organization of the paper is as follows. The authors describe the methods used in their calculation in Sec. 2. In Sec. 3, they present results and discussion; here, they first look at the smallest possible clusters, viz, Pdsub 2 and PdCO, take a brief look at the orbital chemistry involved and then move on to the study of the CO covered Pd(110) surface and examine the geometry of the near equilibrium structure. less
A neural network/trajectory approach is presented for the development of accurate potential-energy hypersurfaces that can be utilized to conduct ab initio molecular dynamics (AIMD) and Monte Carlo studies of gas-phase chemical reactions, nanometric cutting, and nanotribology, and of a variety of mechanical properties of importance in potential microelectromechanical systems applications. The method is sufficiently robust that it can be applied to a wide range of polyatomic systems. The overall method integrates ab initio electronic structure calculations with importance sampling techniques that permit the critical regions of configuration space to be determined. The computed ab initio energies and gradients are then accurately interpolated using neural networks (NN) rather than arbitrary parametrized analytical functional forms, moving interpolation or least-squares methods. The sampling method involves a tight integration of molecular dynamics calculations with neural networks that employ early stopping and regularization procedures to improve network performance and test for convergence. The procedure can be initiated using an empirical potential surface or direct dynamics. The accuracy and interpolation power of the method has been tested for two cases, the global potential surface for vinyl bromide undergoing unimolecular decomposition via four different reaction channels and nanometric cutting of silicon. The results show that the sampling methods permit the important regions of configuration space to be easily and rapidly identified, that convergence of the NN fit to the ab initio electronic structure database can be easily monitored, and that the interpolation accuracy of the NN fits is excellent, even for systems involving five atoms or more. The method permits a substantial computational speed and accuracy advantage over existing methods, is robust, and relatively easy to implement.
Extreme deformation and homogeneous fracture can be readily studied via ab initio methods by subjecting crystals to numerical "tensile tests", where the energy of locally stable crystal configurations corresponding to elongated and fractured states are evaluated by means of density functional method calculations. The information obtained can then be used to construct traction curves of cohesive zone models in order to address fracture at the macroscopic scale. In this work, we perform an in depth analysis of traction curves and how ab initio calculations must be interpreted to rigorously parameterize an atomic scale cohesive zone model, using crystalline Ag as an example. Our analysis of traction curves reveal the existence of two qualitatively distinct decohesion criteria: (i) an energy criterion whereby the released elastic energy equals the energy cost of creating two new surfaces and (ii) an instability criterion that occurs at a higher and size independent stress than that of the energy criterion. We find that increasing the size of the simulation cell renders parts of the traction curve inaccessible to ab initio calculations involving the uniform decohesion of the crystal. We also find that the separation distance below which a crack heals is not a material parameter as has been proposed in the past. Finally, we show that a large energy barrier separates the uniformly stressed crystal from the decohered crystal, resolving a paradox predicted by a scaling law based on the energy criterion that implies that large crystals will decohere under vanishingly small stresses. This work clarifies confusion in the literature as to how a cohesive zone model is to be parameterized with ab initio "tensile tests" in the presence of internal relaxations.
Recent quantum mechanical calculations of the interaction energy of pairs of helium atoms are accurate and some include reliable estimates of their uncertainty. We combined these ab initio results with earlier published results to obtain a helium-helium interatomic potential that includes relativistic retardation effects over all ranges of interaction. From this potential, we calculated the thermophysical properties of helium, i.e., the second virial coefficients, the dilute-gas viscosities, and the dilute-gas thermal conductivities of 3He, 4He, and their equimolar mixture from 1 K to 104 K. We also calculated the diffusion and thermal diffusion coefficients of mixtures of 3He and 4He. For the pure fluids, the uncertainties of the calculated values are dominated by the uncertainties of the potential; for the mixtures, the uncertainties of the transport properties also include contributions from approximations in the transport theory. In all cases, the uncertainties are smaller than the corresponding experimental uncertainties; therefore, we recommend the ab initio results be used as standards for calibrating instruments relying on these thermophysical properties. We present the calculated thermophysical properties in easy-to-use tabular form. PMID:27551630