Published April 8, 2023 | Version v1

Data and code for "Tuning the lattice thermal conductivity in van-der-Waals structures through rotational (dis)ordering"

  • 1. Department of Physics, Chalmers University of Technology, SE-41296, Gothenburg, Sweden
  • 2. College of Physical Science and Technology, Bohai University, Jinzhou 121013, P. R. China

Description

This record contains neuroevolution potential (NEP) models for C, BN, and MoS2 that have been constructed to model the potential energy surfaces of these materials in the presence of interlayer rotations. It also contains databases with the results from density functional theory calculations that were used for constructing the NEP models.

Databases
The *.db files are databases with the results from density functional theory (DFT) calculations. These are sqlite databases in ase format, see here for more information. The demo-database-access.py script illustrates the most basic access.

Models
The neuroevolution potential (NEP) models described in the publication can be found in the nep-*.txt files. They can be used in conjunction with the GPUMD package. The calorine package provides a Python interface to GPUMD.

Primitive structures
Several primitive structures in extended xyz format can be found in the *.xyz files. These structures have been relaxed using the NEP models included here. The demo-for-using-structures-and-models.py script illustrates how to access the structures and models.

Files

nep-BN-CX.txt

Files (1.1 GB)

Name Size
md5:b9c93cf030415d886688d48c8153b250
1.0 kB Download
md5:b944376a5acf2774c80a83f7839e6081
1.0 kB Download
md5:d07c1ae7aa3e1e3f28d11400bd9031e4
1.0 kB Download
md5:73f49990b860e880afb961abca3a13a2
1.0 kB Download
md5:dbf1d85f45f2f8b98891fe0e8521be19
1.0 kB Download
md5:c9badfb7a31d7a0c0b74c46cf9c2caa4
718.1 MB Download
md5:33b84b0db93be1912ff7d3c7d74ea7c9
992 Bytes Download
md5:8cfe51a855119612a8a95df52ad5bc4c
998 Bytes Download
md5:f18dcb7824c0ccc31e06bf60bf15ec39
77.6 MB Download
md5:4968fe56516b21df53fa44a81f5e678c
1.0 kB Download
md5:2a99d2d0a0150bd20d7cc7ad87d92bce
997 Bytes Download
md5:c6acf3457e2d56ec17088b039a3e4698
75.7 MB Download
md5:57235cdbabb7f3e59575f2dd5e34d2ef
991 Bytes Download
md5:9685e57b0872652fbc9b804a19af651b
995 Bytes Download
md5:f9ce5ad40d4f439762116646d0c39f58
70.9 MB Download
md5:57c99ae7c6c34c48755d1a67786e4f22
152 Bytes Download
md5:2f3e00061333b3d57763cadd050726bf
723 Bytes Download
md5:e60510cde81da51252c41fe3715d4c64
1.1 kB Download
md5:97e521b37eabfb80eb2ade1897f6adeb
1.1 kB Download
md5:4cb56aface97c3e1395c838feaf02925
1.1 kB Download
md5:cecbedcb004d0d672ee18bfdae442d3b
1.1 kB Download
md5:14789a1c016225361bf9cd53da7c07c6
1.1 kB Download
md5:e0ee1c2dc7e468f00d9b2f1a44ed479f
112.6 MB Download
md5:7678a4e9f4a29573e3c25bbba1fa0094
41.1 kB Preview Download
md5:fff758a996956f7331f2cc1be396d4ae
44.1 kB Preview Download
md5:adf60b762bd26c55c61528f74ef65561
44.1 kB Preview Download
md5:5720e5000d7f2803f42fc097255e8f61
44.1 kB Preview Download
md5:f918ddf894af6a080fb19fbf91d233c1
41.1 kB Preview Download

Additional details

Related works

Cites
Preprint: 10.48550/arXiv.2304.06978 (DOI)
Is cited by
Preprint: 10.48550/arXiv.2304.06978 (DOI)
Is supplement to
Journal article: 10.1021/acsnano.3c09717 (DOI)