Potential energy surfaces governing chemical reactions involving carbon, oxygen and hydrogen

The lowest singlet states of O[subscript]3 in C[subscript] 2v are studied in the Full Optimized Reaction Space (FORS) MCSCF level of theory with an extended atomic basis set plus polarization functions. The [superscript]1A\u27 ground state potential energy surface contains two minima. The upper minimum lies 29.8 kcal/mole above the ground state minimum and most importantly above the O[subscript]2([superscript]3[sigma][subscript]g[superscript]-) + O([superscript]3P) dissociation limit. It resembles a ring structure having D[subscript] 3h symmetry. The potential energy surface governing the C[subscript] 2v restricted ring opening of the cyclic O[subscript]3 to the ground state is also computed. A conical intersection is found between the 1-[superscript]1A[subscript]1 and 2-[superscript]1A[subscript]1 potential energy surfaces. This first case of an intersection of two states of the same symmetry in a real system is definitively proved by monitoring the sign of the wavefunction on a closed loop around it;Ab-initio calculations elucidating the structure, the ring opening and the dissociation process of the cyclic CO[subscript]2 isomer are reported. The optimal isosceles-triangle (C[subscript] 2v) geometries corresponding to the C[subscript] 2v constraint dissociation OCO → C + O[subscript]2 are determined. The entire C[subscript] 2v surface is computed, revealing the existence of a metastable cyclic carbene-type species corresponding to a local minimum 137.6 kcal/mole above the linear total minimum. Finally, energies are determined for various relevant cross sections with lower symmetry (C[subscript] s), i.e. for asymmetric bond lengths;Extended basis set calculations for the key regions of the ground state [superscript]1A[subscript]1 cyclopropylidene (C[subscript] 2v) to allene (D[subscript] 2d) ring opening reaction surface are performed within the FORS MCSCF framework. Optimized geometries of the reactant, product, transition state and allene isomerization transition state as well as the barrier for the ring opening and the allene isomerization together with the overall exothermicity are reported in the various levels of MCSCF approximation incorporating FORS spaces ranging from 20 to 1764 configurations. The reaction path from the transition state passes from a point where the two surfaces corresponding to the [superscript]1A\u27 and [superscript]1A\u27\u27 states intersect each other. Explanations for the various features of the potential energy surface governing the ring opening of cyclopropylidene to allene are obtained through localized quasi-atomic FORS MO\u27s. ftn*Performed under Contract No. W-7405-Eng-82 for the U.S. Dept. of Energ

Helical Organic and Inorganic Polymers

Despite being a staple of synthetic plastics and biomolecules, helical polymers are scarcely studied with Gaussian-basis-set {\it ab initio} electron-correlated methods on an equal footing with molecules. This article introduces an {\it ab initio} second-order many-body Green's-function [MBGF(2)] method with nondiagonal, frequency-dependent Dyson self-energy for infinite helical polymers using screw-axis-symmetry-adapted Gaussian-spherical-harmonics basis functions. Together with the Gaussian-basis-set density-functional theory for energies, analytical atomic forces, translational-period force, and helical-angle force, it can compute correlated energy, quasiparticle energy bands, structures, and vibrational frequencies of an infinite helical polymer, which smoothly converge at the corresponding oligomer results. These methods can handle incommensurable structures, which have an infinite translational period and are hard to characterize by any other method, just as efficiently as commensurable structures. We apply these methods to polyethylene ($2/1$ helix), polyacetylene (Peierls' system), and polytetrafluoroethylene ($13/6$ helix) to establish the quantitative accuracy of MBGF(2)/cc-pVDZ in simulating their (angle-resolved) ultraviolet photoelectron spectra, and of B3LYP/cc-pVDZ or 6-31G** in reproducing their structures, infrared and Raman band positions, phonon dispersions, and (coherent and incoherent) inelastic neutron scattering spectra. We then predict the same properties for infinitely catenated chains of nitrogen or oxygen and discuss their possible metastable existence under ambient conditions. They include planar zigzag polyazene (N$_2$)$_x$ (Peierls' system), $11/3$-helical isotactic polyazane (NH)$_x$, $9/4$-helical isotactic polyfluoroazane (NF)$_x$, and $7/2$-helical polyoxane (O)$_x$ as potential high-energy-density materials

The Melting Temperature of Liquid Water with the Effective Fragment Potential

The direct simulation of the solid–liquid water interface with the effective fragment potential (EFP) via the constant enthalpy and pressure (NPH) ensemble was used to estimate the melting temperature (Tm) of ice-Ih. Initial configurations and velocities, taken from equilibrated constant pressure and temperature (NPT) simulations at P = 1 atm and T = 305 K, 325 K and 399 K, respectively, yielded corresponding Tm values of 378 ± 16 K, 382 ± 14 K and 384 ± 15 K. These estimates are consistently higher than experiment, albeit to the same degree as previously reported estimates using density functional theory (DFT)-based Born–Oppenheimer simulations with the Becke-Lee–Yang–Parr functional plus dispersion corrections (BLYP-D)

Extreme Acceleration of Graph Neural Network-based Prediction Models for Quantum Chemistry

Molecular property calculations are the bedrock of chemical physics. High-fidelity \textit{ab initio} modeling techniques for computing the molecular properties can be prohibitively expensive, and motivate the development of machine-learning models that make the same predictions more efficiently. Training graph neural networks over large molecular databases introduces unique computational challenges such as the need to process millions of small graphs with variable size and support communication patterns that are distinct from learning over large graphs such as social networks. This paper demonstrates a novel hardware-software co-design approach to scale up the training of graph neural networks for molecular property prediction. We introduce an algorithm to coalesce the batches of molecular graphs into fixed size packs to eliminate redundant computation and memory associated with alternative padding techniques and improve throughput via minimizing communication. We demonstrate the effectiveness of our co-design approach by providing an implementation of a well-established molecular property prediction model on the Graphcore Intelligence Processing Units (IPU). We evaluate the training performance on multiple molecular graph databases with varying degrees of graph counts, sizes and sparsity. We demonstrate that such a co-design approach can reduce the training time of such molecular property prediction models from days to less than two hours, opening new possibilities for AI-driven scientific discovery

Anomalously Strong Effect of the Ion Sign on the Thermochemistry of Hydrogen Bonded Aqueous Clusters of Identical Chemical Composition

The sign preference of hydrogen bonded aqueous ionic clusters X±(H2O)i (n =1–5, X = F; Cl; Br) has been investigated using the Density Functional Theory and ab initio MP2 method. The present study indicates the anomalously large difference in formation free energies between cations and anions of identical chemical composition. The effect of vibrational anharmonicity on stepwise Gibbs free energy changes has been investigated, and possible uncertainties associated with the harmonic treatment of vibrational spectra have been discussed