A scheme for simulating multi-level phase change photonics materials

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 pr...

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Autores principales:	Yunzheng Wang, Jing Ning, Li Lu, Michel Bosman, Robert E. Simpson
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Materials of engineering and construction. Mechanics of materials TA401-492 Computer software QA76.75-76.765
Acceso en línea:	https://doaj.org/article/b5f228dc00b54e6c8c80143080f06015
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spelling	oai:doaj.org-article:b5f228dc00b54e6c8c80143080f060152021-11-14T12:15:31ZA scheme for simulating multi-level phase change photonics materials10.1038/s41524-021-00655-w2057-3960https://doaj.org/article/b5f228dc00b54e6c8c80143080f060152021-11-01T00:00:00Zhttps://doi.org/10.1038/s41524-021-00655-whttps://doaj.org/toc/2057-3960Abstract 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.Yunzheng WangJing NingLi LuMichel BosmanRobert E. SimpsonNature PortfolioarticleMaterials of engineering and construction. Mechanics of materialsTA401-492Computer softwareQA76.75-76.765ENnpj Computational Materials, Vol 7, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Materials of engineering and construction. Mechanics of materials TA401-492 Computer software QA76.75-76.765
spellingShingle	Materials of engineering and construction. Mechanics of materials TA401-492 Computer software QA76.75-76.765 Yunzheng Wang Jing Ning Li Lu Michel Bosman Robert E. Simpson A scheme for simulating multi-level phase change photonics materials
description	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.
format	article
author	Yunzheng Wang Jing Ning Li Lu Michel Bosman Robert E. Simpson
author_facet	Yunzheng Wang Jing Ning Li Lu Michel Bosman Robert E. Simpson
author_sort	Yunzheng Wang
title	A scheme for simulating multi-level phase change photonics materials
title_short	A scheme for simulating multi-level phase change photonics materials
title_full	A scheme for simulating multi-level phase change photonics materials
title_fullStr	A scheme for simulating multi-level phase change photonics materials
title_full_unstemmed	A scheme for simulating multi-level phase change photonics materials
title_sort	scheme for simulating multi-level phase change photonics materials
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/b5f228dc00b54e6c8c80143080f06015
work_keys_str_mv	AT yunzhengwang aschemeforsimulatingmultilevelphasechangephotonicsmaterials AT jingning aschemeforsimulatingmultilevelphasechangephotonicsmaterials AT lilu aschemeforsimulatingmultilevelphasechangephotonicsmaterials AT michelbosman aschemeforsimulatingmultilevelphasechangephotonicsmaterials AT robertesimpson aschemeforsimulatingmultilevelphasechangephotonicsmaterials AT yunzhengwang schemeforsimulatingmultilevelphasechangephotonicsmaterials AT jingning schemeforsimulatingmultilevelphasechangephotonicsmaterials AT lilu schemeforsimulatingmultilevelphasechangephotonicsmaterials AT michelbosman schemeforsimulatingmultilevelphasechangephotonicsmaterials AT robertesimpson schemeforsimulatingmultilevelphasechangephotonicsmaterials
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A scheme for simulating multi-level phase change photonics materials

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