International Journal of Quantum Chemistry

Cover image for Vol. 115 Issue 13

Online ISSN: 1097-461X

Associated Title(s): Journal of Computational Chemistry

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  • Current Issue:July 5, 2015

    Volume 115, Issue 13

  • June 15, 2015

    Volume 115, Issue 12

  • June 5, 2015

    Volume 115, Issue 11

    Special Issue: Theoretical Chemistry in China

  • May 15, 2015

    Volume 115, Issue 10

    Special Issue: Theoretical Chemistry in China

  • May 5, 2015

    Volume 115, Issue 9

    Special Issue: Theoretical Chemistry in China

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Recently Published Articles

  1. Understanding kernel ridge regression: Common behaviors from simple functions to density functionals

    Kevin Vu, John C. Snyder, Li Li, Matthias Rupp, Brandon F. Chen, Tarek Khelif, Klaus-Robert Müller and Kieron Burke

    Article first published online: 26 MAY 2015 | DOI: 10.1002/qua.24939

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    Machine learning with kernel ridge regression has recently been used to obtain approximations to density functionals. These approximations have been highly accurate for one-dimensional systems including the spinless fermion in a box and orbital-free bond breaking between diatomics. This article explores the behavior of machine learning models with respect to the properties of the kernel. Machine learning methods are tested on a simple function in order to elucidate this dependence.

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    Tensor product methods and entanglement optimization for ab initio quantum chemistry

    Szilárd Szalay, Max Pfeffer, Valentin Murg, Gergely Barcza, Frank Verstraete, Reinhold Schneider and Örs Legeza

    Article first published online: 25 MAY 2015 | DOI: 10.1002/qua.24898

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    Building on research performed in the past decade, entanglement-based methods,—developed for different purposes in distinct communities—have matured into tools that can be employed to attack highly challenging problems in quantum chemistry. For example, controlled manipulation of quantum entanglement in tensor product approximations yields a novel approach to treat high-dimensional optimization problems and time-dependent equations, such as the Schrödinger equation.

  3. Nonlinear gradient denoising: Finding accurate extrema from inaccurate functional derivatives

    John C. Snyder, Matthias Rupp, Klaus-Robert Müller and Kieron Burke

    Article first published online: 24 MAY 2015 | DOI: 10.1002/qua.24937

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    When applying machine learning to model high-dimensional data, the gradient of the model can exhibit high levels of noise. In applications of machine learning to density functional theory to learn the kinetic energy as a functional of the density, the gradient is necessary to minimize the total energy and find a self-consistent ground-state density. A novel technique, called nonlinear gradient denoising, is developed to remove such noise.

  4. Application of Si-doped graphene as a metal-free catalyst for decomposition of formic acid: A theoretical study

    Mehdi D. Esrafili, Roghaye Nurazar and Esmail Vessally

    Article first published online: 24 MAY 2015 | DOI: 10.1002/qua.24942

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    The catalytic decomposition reaction of formic acid (HCOOH) is considered an important step for the generation of pure hydrogen in electric fuel cells. Si-doped graphene provides an alternative to more traditional catalysts for the decomposition of HCOOH, based on noble metals. Density functional theory calculations explore both the dehydration and dehydrogenation pathways of HCOOH on this efficient nonmetal catalyst.

  5. Tuning anion-π interaction via halogen substituent effects in cyanuric acids and its derivatives

    Shuangli Du, Bingqiang Wang, Jian Zhang and Caiyun Zhang

    Article first published online: 24 MAY 2015 | DOI: 10.1002/qua.24938

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    The interactions between π-electron-deficient aromatic rings and anions have been recognized possessing pivotal role in many key chemical and biological processes, especially with respect to molecular recognition. Therefore, the design of highly selective anion receptor has attracted considerable attention in recent years. The anion-π interaction can be tuned via halogen substituent effects in cyanuric acids and its derivatives. This principle may be applicable to the design of new neutral anion receptors.

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