Multi-Level Electro-Thermal Switching of Optical PhaseChange Materials Using Graphene
Multi-Level Electro-Thermal Switching of Optical PhaseChange Materials Using Graphene
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DOI：
10.1002/adpr.202000034
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发表时间：
2021-01-01
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影响因子：
--
通讯作者：
Hu, Juejun
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文献类型：
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作者：
Rios, Carlos;Zhang, Yifei;Hu, Juejun
具有最小功耗的可重构光子系统对于现实世界技术中的集成光学器件至关重要。然而，目前在铸造厂可用的有源器件使用易失性方法来调制光，需要恒定的电源和显著的形状因子。克服这些问题的重要方面是非易失性光学重构技术的发展，这些技术与不同光子平台的片上集成兼容，并且不会破坏它们的光学性能。在本文中，使用用于非易失性可调谐光子学的光电框架来展示解决方案，该解决方案使用未掺杂的石墨烯微加热器来热可逆地切换光学相变材料Ge（2）Sb（2）S（e）4 Te（1）（GSST）。原位拉曼光谱法被用来证明，在实时，可逆的四个不同的结晶度之间的切换。此外，一个三维计算模型的开发，以精确地解释开关特性，并量化电流饱和对功耗，热扩散和开关速度的影响。该模型用于通知非易失性有源光子器件的设计;即，宽带Si 3 N4集成光子电路，具有小形状因子调制器和通过神经网络设计的GSST元原子显示2 p相位覆盖的可重构元表面。该框架将在各种光子学平台上实现可扩展的低损耗非易失性应用。
Reconfigurable photonic systems featuring minimal power consumption are crucial for integrated optical devices in real-world technology. Current active devices available in foundries, however, use volatile methods to modulate light, requiring a constant supply of power and significant form factors. Essential aspects to overcome these issues are the development of nonvolatile optical reconfiguration techniques which are compatible with on-chip integration with different photonic platforms and do not disrupt their optical performances. Herein, a solution is demonstrated using an optoelectronic framework for nonvolatile tunable photonics that uses undoped-graphene microheaters to thermally and reversibly switch the optical phase-change material Ge(2)Sb(2)S(e)4Te(1) (GSST). An in situ Raman spectroscopy method is utilized to demonstrate, in real-time, reversible switching between four different levels of crystallinity. Moreover, a 3D computational model is developed to precisely interpret the switching characteristics, and to quantify the impact of current saturation on power dissipation, thermal diffusion, and switching speed. This model is used to inform the design of nonvolatile active photonic devices; namely, broadband Si3N4 integrated photonic circuits with small form-factor modulators and reconfigurable metasurfaces displaying 2p phase coverage through neural-network-designed GSST meta-atoms. This framework will enable scalable, low-loss nonvolatile applications across a diverse range of photonics platforms.