The data contains the Gaussian Approximation Potential (GAP) interatomic potential for carbon. Also contains the DFT training data that the potential was fit to. The folder "Carbon_GAP_20.tgz" contains the following folders and files. Carbon_GAP_20 -> Folder containing the XML files for the GAP-20 machine learning Carbon model Carbon_Training_Set_Total.xyz -> All of the training data generated in the construction of GAP-20 (approximately 17,000 configurations) Carbon_GAP_20_Training_Set.xyz -> The selection of training configurations used to fit GAP-20 r6_innercut.xml -> XML file containing the semianalytical 2b potential Example_Job -> Example job files for running a GAP-20 simulation in LAMMPS
A Spectral Neighbor Analysis (SNAP) machine learning interatomic potential (MLIP) has been developed...
We introduce a Gaussian approximation potential (GAP) for atomistic simulations of liquid and amorph...
Gaussian approximation potential (GAP) for amorphous carbon [1]. It has been fitted with QUIP/GAP [1...
This dataset contains a vertical slice of the data used to generate the results found in the publica...
Raw data relevant to the GAP interatomic potential model described in the publication, including out...
This is a machine learning interatomic potential for carbon, using the GAP framework
This data set contains the GAP model file and the original DFT training data for the general-purpose...
© 2020 Author(s). We present an accurate machine learning (ML) model for atomistic simulations of ca...
We present an accurate machine learning (ML) model for atomistic simulations of carbon, constructed ...
This dataset contains 60133 configurations of Carbon as generated in the paper "A systematic approac...
Original data regarding structures and properties of the carbon allotropes discussed in the associat...
© 2021 Author(s).Carbon materials and their unique properties have been extensively studied by molec...
Machine learned interatomic potentials for Carbon as presented in the paper "PANNA 2.0: Efficient ne...
This is a Gaussian approximation potential (GAP [1]) for carbon. The potential can be used to model ...
Data for manuscript, entitled: "Small-data-based Machine Learning Interatomic Potentials for Gr...
A Spectral Neighbor Analysis (SNAP) machine learning interatomic potential (MLIP) has been developed...
We introduce a Gaussian approximation potential (GAP) for atomistic simulations of liquid and amorph...
Gaussian approximation potential (GAP) for amorphous carbon [1]. It has been fitted with QUIP/GAP [1...
This dataset contains a vertical slice of the data used to generate the results found in the publica...
Raw data relevant to the GAP interatomic potential model described in the publication, including out...
This is a machine learning interatomic potential for carbon, using the GAP framework
This data set contains the GAP model file and the original DFT training data for the general-purpose...
© 2020 Author(s). We present an accurate machine learning (ML) model for atomistic simulations of ca...
We present an accurate machine learning (ML) model for atomistic simulations of carbon, constructed ...
This dataset contains 60133 configurations of Carbon as generated in the paper "A systematic approac...
Original data regarding structures and properties of the carbon allotropes discussed in the associat...
© 2021 Author(s).Carbon materials and their unique properties have been extensively studied by molec...
Machine learned interatomic potentials for Carbon as presented in the paper "PANNA 2.0: Efficient ne...
This is a Gaussian approximation potential (GAP [1]) for carbon. The potential can be used to model ...
Data for manuscript, entitled: "Small-data-based Machine Learning Interatomic Potentials for Gr...
A Spectral Neighbor Analysis (SNAP) machine learning interatomic potential (MLIP) has been developed...
We introduce a Gaussian approximation potential (GAP) for atomistic simulations of liquid and amorph...
Gaussian approximation potential (GAP) for amorphous carbon [1]. It has been fitted with QUIP/GAP [1...