Published December 7, 2022 | Version v1
Dataset Open

Raman spectra of 2D titanium carbide MXene from machine-learning force field molecular dynamics

  • 1. Microelectronics Research Unit, Faculty of Information Technology and Electrical Engineering, University of Oulu, P.O. Box 4500, Oulu, FIN-90014, Finland
  • 2. Department of Applied Physics, Aalto University, Aalto, FIN-00076, Finland

* Contact person

Description

MXenes represent one of the largest class of 2D materials with promising applications in many fields and their properties tunable by the surface group composition. Raman spectroscopy is expected to yield rich information about the surface composition, but the interpretation of measured spectra has proven challenging. The interpretation is usually done via comparison to simulated spectra, but there are large discrepancies between the experimental and earlier simulated spectra. In this work, we develop a computational approach to simulate Raman spectra of complex materials that combines machine-learning force-field molecular dynamics and reconstruction of Raman tensors via projection to pristine system modes. The approach can account for the effects of finite temperature, mixed surfaces, and disorder. We apply our approach to simulate Raman spectra of titanium carbide MXene and show that all these effects must be included in order to properly reproduce the experimental spectra, in particular the broad features. We discuss the origin of the peaks and how they evolve with surface composition, which can then be used to interpret experimental results. This record contains input files for MLFF training and production runs, information on the training set (atomic structures, energies and forces) and some of the molecular dynamics trajectories used to obtain Raman spectra.

Files

File preview

files_description.md

All files

Files (3.4 GiB)

Name Size
md5:23b7f2208d7c2022658ccfb9afbd5df6
690 Bytes Preview Download
md5:eed5ce561f014f9295a700f68de104f4
236 Bytes Download
md5:aa7c01dbec449b6bed81b3991def4203
279 Bytes Download
md5:2103c11c8f1f1b25642735cef9cc6bd7
254 Bytes Download
md5:cac2be4b7bfe97dc4e1d3e7ad14e8d45
26.1 MiB Download
md5:5ee434a99dbd71d6ef8ecb018f761e72
804 Bytes Preview Download
md5:cd7b739bb17430c3225a4694b7bf7f4a
741.6 MiB Download
md5:614bb43c19bf09c7ca632e5b72004ffe
697.4 MiB Download
md5:88a2af1bdb7a61550c11a9d6638f74f9
652.5 MiB Download
md5:6617e5301bbb07529711b7bf26c199f4
783.0 MiB Download
md5:79bc58a61fecd07e4a7451a322a34cb0
604.9 MiB Download

References

Preprint (Preprint where the data is discussed)
E. Berger, Z-P Lv, H-P Komsa, arXiv:2209.15294 [physics.comp-ph] (2022), doi: 10.48550/arXiv.2209.15294