Berger, E., Lv, Z.-P., & Komsa, H.-P. (2023). Raman spectra of 2D titanium carbide MXene from machine-learning force field molecular dynamics. In Journal of Materials Chemistry C (Vol. 11, Issue 4, pp. 1311–1319). Royal Society of Chemistry (RSC). https://doi.org/10.1039/d2tc04374b
Raman spectra of 2D titanium carbide MXene from machine-learning force field molecular dynamics
|Author:||Berger, Ethan1; Lv, Zhong-Peng2; Komsa, Hannu-Pekka1|
1Microelectronics Research Unit, Faculty of Information Technology and Electrical Engineering, University of Oulu, P. O. Box 4500, Oulu, Finland
2Department of Applied Physics, Aalto University, Aalto, Finland
|Online Access:||PDF Full Text (PDF, 2.6 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2023080994485
Royal Society of Chemistry,
|Publish Date:|| 2023-08-09
MXenes represent one of the largest classes of 2D materials with promising applications in many fields and their properties are tunable by altering the surface group composition. Raman spectroscopy is expected to yield rich information about the surface composition, but the interpretation of the recorded spectra has proven challenging. The interpretation is usually done via comparison to the simulated spectra, but there are large discrepancies between the experimental spectra and the earlier simulated spectra. In this work, we develop a computational approach to simulate the Raman spectra of complex materials which combines machine-learning force-field molecular dynamics and reconstruction of Raman tensors via projection to pristine system modes. This approach can account for the effects of finite temperature, mixed surfaces, and disorder. We apply our approach to simulate the Raman spectra of titanium carbide MXene and show that all these effects must be included in order to appropriately reproduce the experimental spectra, in particular the broad features. We discuss the origin of the peaks and how they evolve with the surface composition, which can then be used to interpret the experimental results.
Journal of materials chemistry. C, Materials with applications in optical, magnetic & electronic devices
|Pages:||1311 - 1319|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
216 Materials engineering
We are grateful to the Academy of Finland for support under the Academy Research Fellow funding No. 311058 and Academy Postdoc funding No. 330214.
Data for this paper, including input files, atomic structures, energies and forces of the training set, and MD trajectories are available at Materials Cloud Archive at https://doi.org/10.24435/materialscloud:w2-g5.
© 2022 The Author(s). This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.