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ZENODO
Dataset . 2026
License: CC BY SA
Data sources: Datacite
ZENODO
Dataset . 2026
License: CC BY SA
Data sources: Datacite
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Vapor-solid-solid growth of single-walled carbon nanotubes: model, dataset, inputs and trajectory

Authors: Hedman, Daniel;

Vapor-solid-solid growth of single-walled carbon nanotubes: model, dataset, inputs and trajectory

Abstract

This repository supports the publication Vapor-solid-solid growth of single-walled carbon nanotubes. It includes the NEP$_{\text{ReC}}$ models, an ensemble of neuroevolution potentials (NEPs) developed to simulate CNT growth on rhenium catalysts, along with data and files used in the training and simulation processes. NEP$_{\text{ReC}}$ models (neps.zip): The fully trained NEP models used for production simulations. Here 1_nep.txt is used to drive the simulations and the remaining NEPs are used for error estimation (force model deviation). NEP$_{\text{ReC}}$ dataset (dataset.zip): Contains the train and test datasets for NEP$_{\text{ReC}}$ in the xyz format used by GPUMD for training. Each image is labeled with total energy in eV, force in eV/Å, and virials in eV. GPUMD files (training.zip): Input files used for training the NEP$_{\text{ReC}}$ models using GPUMD. GPUMD files (growth.zip): Input files for simulating CNT growth using GPUMD. VASP files (vasp.zip): Input files used for labeling data with VASP. CNT growth trajectory (dump_a.tar.xz): The full trajectory of the 12 μs CNT growth simulation discussed in the manuscript.

Related Organizations
Keywords

machine-learning interatomic potential, NEP, NEP_ReC, single-walled carbon nanotubes, vapor-solid-solid growth, molecular dynamics

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average