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Vilhjálmur Ásgeirsson

Researcher at University of Iceland

Publications -  12
Citations -  483

Vilhjálmur Ásgeirsson is an academic researcher from University of Iceland. The author has contributed to research in topics: Saddle point & Delocalized electron. The author has an hindex of 8, co-authored 12 publications receiving 290 citations. Previous affiliations of Vilhjálmur Ásgeirsson include University of Bonn.

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Nudged elastic band calculations accelerated with Gaussian process regression.

TL;DR: In this paper, the Hessian matrix at the initial and final state minima can be used as input in the minimum energy path calculation, thereby improving stability and reducing the number of iterations needed for convergence.
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Nudged elastic band calculations accelerated with Gaussian process regression

TL;DR: The number of evaluations of the Hessian matrix at the initial and final state minima can be carried out beforehand and used as input in the minimum energy path calculation, thereby improving stability and reducing the number of iterations needed for convergence.
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Nudged Elastic Band Method for Molecular Reactions Using Energy-Weighted Springs Combined with Eigenvector Following.

TL;DR: In this paper, the climbing image nudged elastic band method (CI-NEB) is used to identify reaction coordinates and to find saddle points representing transition states of reactions, which can make efficient use of parallel computing as the calculations of the discretization points, the so-called images can be carried out simultaneously.
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Quantum chemical calculation of electron ionization mass spectra for general organic and inorganic molecules

TL;DR: Grimme et al. as mentioned in this paper introduced a fully stand-alone version of the Quantum Chemistry Electron Ionization Mass Spectra (QCEIMS) program allowing efficient simulations for molecules composed of elements with atomic numbers up to Z = 86.
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Nudged Elastic Band Calculations Accelerated with Gaussian Process Regression Based on Inverse Interatomic Distances.

TL;DR: A significant improvement to the Gaussian process regression approach is obtained by basing the difference measure between two atomic configurations in the covariance function on the inverted inter-atomic distances and by adding a new early stopping criterion for the path relaxation phase.