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| Format: | Recurso digital |
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Zenodo
2026
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| Online Access: | https://doi.org/10.5281/zenodo.18151591 |
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Table of Contents:
- <p>This dataset contains the electric-fields -specific machine-learned potentials described in the manuscript "Electric-Field Control of Interlayer Binding and Friction in h-BN Contacts" (to be submitted).</p> <p>MACE models for h-BN bilayers under varying electric fields (EFs) (trained using the MACE package, version 0.3.10):</p> <p>1. EF_-2: -2 V/nm<br>2. EF_-1: -1 V/nm<br>3. EF_0: 0 V/nm<br>4. EF_1: 1 V/nm<br>5. EF_2: 2 V/nm</p> <p>Each folder contains the trained MACE model file along with the corresponding reference datasets, as well as the input and output files. </p> <p>The introduction of an external EF requires breaking the inherent rotational symmetry encoded into the MLP algorithm. To that end, we artificially relabeled the B and N atoms in the bottom layer as C and O for MACE training and subsequent MD simulations. All five MACE models were trained using the same reference structures generated during the active learning process without an EF, while the total energy and atomic forces were subsequently evaluated under different EFs.</p>