Please use this identifier to cite or link to this item: https://doi.org/10.1038/s41524-021-00655-w
Title: A scheme for simulating multi-level phase change photonics materials
Authors: Wang, Yunzheng
Ning, Jing
Lu, Li
Bosman, Michel 
Simpson, Robert E.
Issue Date: 11-Nov-2021
Publisher: Nature Research
Citation: Wang, Yunzheng, Ning, Jing, Lu, Li, Bosman, Michel, Simpson, Robert E. (2021-11-11). A scheme for simulating multi-level phase change photonics materials. npj Computational Materials 7 (1) : 183. ScholarBank@NUS Repository. https://doi.org/10.1038/s41524-021-00655-w
Rights: Attribution 4.0 International
Abstract: Chalcogenide phase change materials (PCMs) have been extensively applied in data storage, and they are now being proposed for high resolution displays, holographic displays, reprogrammable photonics, and all-optical neural networks. These wide-ranging applications all exploit the radical property contrast between the PCMs’ different structural phases, extremely fast switching speed, long-term stability, and low energy consumption. Designing PCM photonic devices requires an accurate model to predict the response of the device during phase transitions. Here, we describe an approach that accurately predicts the microstructure and optical response of phase change materials during laser induced heating. The framework couples the Gillespie Cellular Automata approach for modelling phase transitions with effective medium theory and Fresnel equations. The accuracy of the approach is verified by comparing the PCM’s optical response and microstructure evolution with the results of nanosecond laser switching experiments. We anticipate that this approach to simulating the switching response of PCMs will become an important component for designing and simulating programmable photonics devices. The method is particularly important for predicting the multi-level optical response of PCMs, which is important for all-optical neural networks and PCM-programmable perceptrons. © 2021, The Author(s).
Source Title: npj Computational Materials
URI: https://scholarbank.nus.edu.sg/handle/10635/232696
ISSN: 2057-3960
DOI: 10.1038/s41524-021-00655-w
Rights: Attribution 4.0 International
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