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The ability to design and dynamically control chiroptical responses in solid-state matter at a wafer scale enables new opportunities in various areas. Here, we present a full stack of computer-aided designs and experimental implementations of a dynamically programmable, unified, scalable chiroptical heterostructure containing wafer-scale twisted aligned one-dimensional carbon nanotubes and non-volatile phase change materials. We develop a software infrastructure based on high-performance machine learning frameworks, including differentiable programming and derivative-free optimization, to efficiently optimize the tunability of both reciprocal and nonreciprocal circular dichroism responses, which are experimentally validated. Further, we demonstrate the heterostructure scalability regarding stacking layers and the dual roles of aligned carbon nanotubes - the layer to produce chiroptical responses and the Joule heating electrode to electrically program phase change materials. This heterostructure platform is versatile and expandable to a library of one-dimensional nanomaterials, phase change materials, and electro-optic materials for exploring novel chiral phenomena and photonic and optoelectronic devices.
Fan et al. (Wed,) studied this question.