# Gaussian Approximation Potential: an interatomic potential derived from first principles Quantum Mechanics

@article{Bartk2010GaussianAP, title={Gaussian Approximation Potential: an interatomic potential derived from first principles Quantum Mechanics}, author={Albert P. Bart{\'o}k}, journal={arXiv: Materials Science}, year={2010} }

Simulation of materials at the atomistic level is an important tool in studying microscopic structure and processes. The atomic interactions necessary for the simulation are correctly described by Quantum Mechanics. However, the computational resources required to solve the quantum mechanical equations limits the use of Quantum Mechanics at most to a few hundreds of atoms and only to a small fraction of the available configurational space. This thesis presents the results of my research on the…

## 26 Citations

### First principles interatomic potential for tungsten based on Gaussian process regression

- Materials Science
- 2014

An accurate description of atomic interactions, such as that provided by first principles quantum mechanics, is fundamental to realistic prediction of the properties that govern plasticity, fracture…

### Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials

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### Automated Algorithms for Quantum-Level Accuracy in Atomistic Simulations: LDRD Final Report.

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A SNAP potential for tantalum that accurately reproduces a variety of solid and liquid properties and correctly predicts the Peierls barrier for screw dislocation motion is described.

### Peridynamic Multiscale Finite Element Methods

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The problem of computing quantum-accurate design-scale solutions to mechanics problems is rich with applications and serves as the background to modern multiscale science research. The prob- lem can…

### Machine-Learning Based Interatomic Potential for Studying the Properties of Crystal Structures

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In the process of modeling multilayer semiconductor nanostructures, an important role is played by the rapid acquisition of accurate values of the characteristics of the structure under…

### Permutation-invariant distance between atomic configurations.

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We present a permutation-invariant distance between atomic configurations, defined through a functional representation of atomic positions. This distance enables us to directly compare different…

### TeaNet: universal neural network interatomic potential inspired by iterative electronic relaxations

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### Temperature effect on the phonon dispersion stability of zirconium by machine learning driven atomistic simulations

- Materials Science, PhysicsPhysical Review B
- 2018

It is well known that conventional harmonic lattice dynamics cannot be applied to energetically unstable crystals at 0 K, such as high temperature body centered cubic (BCC) phase of crystalline Zr.…

### Quantum-Accurate Molecular Dynamics Potential for Tungsten

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The purpose of this short contribution is to report on the development of a Spectral Neighbor Analysis Potential (SNAP) for tungsten. We have focused on the characterization of elastic and defect…

### Energetics and thermodynamics of α-iron from first-principles and machine-learning potentials

- Materials Science
- 2016

Iron is a material of fundamental importance in the industrial and economic processes of our society as it is the major constituent of steels. With advances in computational science, much progress…

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