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Showing 1 to 20 of 50 for “"Interatomic potentials"”.

  1. Data-driven linear interatomic potentials

    … due to the rapid development of data-driven interatomic potential frameworks over the last decade. This thesis presents two novel frameworks, namely 'atomic permutation invariant polynomials' and 'atomic cluster expansion'. Both frameworks are linear models that can be used to create …

    cambridge Repository record for Data-driven linear interatomic potentials (opens in a new tab)

  2. Fitting Interatomic Potentials to Reproduce Phase Transitions

    … a large number of atoms. These so called “interatomic potentials” take a variety of forms ranging from the simple Lennard-Jones potential to machine learning potentials. They are usually fitted for specific structures as well as pressure and temperature realms and do not necessarily …

    cambridge Repository record for Fitting Interatomic Potentials to Reproduce Phase Transitions (opens in a new tab)

  3. Predicting Material Properties with Machine Learned Interatomic Potentials

    Machine learning interatomic potentials (ML-IPs) have emerged as a promising approach for bridging the gap between quantum electronic structure calculations (QM) and large scale classical molecular modeling simulations and have shifted the development of these many-body force fields to become …

    mit Repository record for Predicting Material Properties with Machine Learned Interatomic Potentials (opens in a new tab)

  4. Designing efficient, interpretable, and generalizable machine learning interatomic potentials

    Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-03-01 without embargo terms

    uiuc Repository record for Designing efficient, interpretable, and generalizable machine learning interatomic potentials (opens in a new tab)

  5. Machine Learning Interatomic Potentials to Predict Bond Dissociation Energies

    … structures. Recently, Machine Learning Interatomic Potentials (MLIPs) have emerged as versatile surrogate models capable of accurately reproducing ab initio potential energy surfaces. However, most of their applications have been targeted at near-equilibrium closed-shell structures. This …

    cambridge Repository record for Machine Learning Interatomic Potentials to Predict Bond Dissociation Energies (opens in a new tab)

  6. Mechanics of Carbon Nanotubes: A Continuum Theory Incorporating Interatomic Potentials

    The elastic modulus predicted by the proposed continuum theory is in good agreement with experimental and atomistic findings. It is also found that the critical strain at which instability occurs when a carbon nanotube is subject to tension is agreeable to that predicted by atomistic models.

    uiuc Repository record for Mechanics of Carbon Nanotubes: A Continuum Theory Incorporating Interatomic Potentials (opens in a new tab)

  7. Simulations of silicon-graphene anodes using machine-learning-based interatomic potentials

    … the aim by developing a Machine Learning Interatomic Potential (MLIP) using the Gaussian Approximation Potential (GAP) framework. The study represents the first comprehensive effort to model the full electrochemical cycle of a silicon-graphene anode system, aiming to provide atomic-scale …

    cambridge Repository record for Simulations of silicon-graphene anodes using machine-learning-based interatomic potentials (opens in a new tab)

  8. Exploration of the Application of Machine Learning to the Improvement of Interatomic Potentials

    … molecular dynamics (CMD) simulations use interatomic potentials (IPs) to describe larger systems at a reduced computational cost, but with a reduced accuracy. Creating more robust IPs enables more precise CMD simulations. In this thesis, the application of a specific machine learning …

    umkc Repository record for Exploration of the Application of Machine Learning to the Improvement of Interatomic Potentials (opens in a new tab)

  9. Enhancing Robustness of Neural Network Interatomic Potentials through Sampling Methods and Uncertainty Quantification

    Neural network interatomic potentials (NNIPs) are a significant advancement in computational materials science and chemistry for their ability to accurately approximate the potential energy surface (PES) of atomic systems with significantly reduced computational costs compared to quantum mechanical …

    mit Repository record for Enhancing Robustness of Neural Network Interatomic Potentials through Sampling Methods and Uncertainty Quantification (opens in a new tab)

  10. First Principles-Based Interatomic Potentials for Modeling the Body-Centered Cubic Metals V, Nb, Ta, Mo, and W

    … depend crucially on high-quality classical interatomic potentials. This study constructs embedded-atom method (EAM) and modified embedded-atom method (MEAM) interatomic potentials for the body-centered cubic (bcc) metals V, Nb, Ta, Mo, and W from data generated by first-principles …

    ohiolink Repository record for First Principles-Based Interatomic Potentials for Modeling the Body-Centered Cubic Metals V, Nb, Ta, Mo, and W (opens in a new tab)

  11. Development of Kinetic Monte Carlo Code to Study Oxygen Mobility in Lanthanum-doped Ceria

    … Statics simulations were performed using interatomic potentials for cerium oxide provided by Gotte et al., Minervini et al. and Sayle et al. to calculate local configuration-dependent oxygen vacancy migration energies. Kinetic Monte Carlo simulations of oxygen vacancy diffusion were …

    uiuc Repository record for Development of Kinetic Monte Carlo Code to Study Oxygen Mobility in Lanthanum-doped Ceria (opens in a new tab)

  12. Nanoscale solidification of metals by atomistic simulations: From nucleation to nanostructural evolution

    … modified embedded atom method (2NN-MEAM) potentials. Spontaneous homogenous nucleation from the melt was produced without any influence of pressure, free surface effects and impurities. We also study the effect on the simulation size on homogenous nucleation and the heterogeneity in …

    must-thes Repository record for Nanoscale solidification of metals by atomistic simulations: From nucleation to nanostructural evolution (opens in a new tab)

  13. A scalable machine learning approach to thermal and non-thermal order-disorder phase transitions with ab initio accuracy

    … based on high-fidelity machine learning interatomic potentials. These tools are utilized to investigate three distinct out-of- equilibrium regimes: • Ultrafast non-thermal melting in silicon: a novel framework based on constrained density functional perturbation theory and machine …

    trento Repository record for A scalable machine learning approach to thermal and non-thermal order-disorder phase transitions with ab initio accuracy (opens in a new tab)

  14. Modeling nonlinear material behavior at the nano and macro scales

    … simulations with embedded atom method (EAM) interatomic potentials. The study included both single crystal films and films containing low angle grain boundaries perpendicular to the film surface. The simulation results for single crystal films show that as film thickness decreases, larger …

    vt Repository record for Modeling nonlinear material behavior at the nano and macro scales (opens in a new tab)

  15. A computational study of germanium dioxide

    … on germanium dioxide. These have been done with interatomic pair potentials developed with the aid of a fitting procedure. Results for the crystalline modifications and the glassy state are presented. This includes static and dynamic properties of the GeO$_{2}$ modifications. Germanium dioxide is …

    cambridge Repository record for A computational study of germanium dioxide (opens in a new tab)

  16. Numerical Constitutive Modelling for Continuum Mechanics Simulation

    … simulations of shock waves using empirical interatomic potentials and compare with our indirect method. We also present a direct ab initio molecular dynamics simulation of an elastic shock-wave in silicon, the first performed, to our knowledge. The third and final investigation is into the …

    cambridge Repository record for Numerical Constitutive Modelling for Continuum Mechanics Simulation (opens in a new tab)

  17. Investigation of Alignment Dynamics in Mg-Ne and Mg-Ar Two-Photon Fractional Collisions

    … and laser detunings. This accesses a range of interatomic separations and produces a spectrum which represents a frequency domain analog of the time evolution of the alignment in the intermediate state. Spectra for Mg-Ne and Mg-Ar show features which depend strongly on the rare gas and the …

    odu Repository record for Investigation of Alignment Dynamics in Mg-Ne and Mg-Ar Two-Photon Fractional Collisions (opens in a new tab)

  18. Spin-Aware Neural Network Interatomic Potential for Atomistic Simulation

    … but at high cost and limited scale. Empirical potentials are faster and scale better, but cannot compare to ab initio in numerical and physical accuracy. Machine learning (ML) interatomic potentials (IPs) of recent years offer a balance: excellent phenomenology and accuracy, while scaling well …

    mit Repository record for Spin-Aware Neural Network Interatomic Potential for Atomistic Simulation (opens in a new tab)

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