  The ability to design and dynamically control chiroptical responses in
solid-state matter at 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 twisted aligned one-dimensional (1D) carbon
nanotubes (CNTs) and non-volatile phase change materials (PCMs). 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 excitonic reciprocal and
linear-anisotropy-induced nonreciprocal circular dichroism (CD) responses. We
experimentally implement designed heterostructures with wafer-scale
self-assembled aligned CNTs and deposited PCMs. We dynamically program
reciprocal and nonreciprocal CD responses by inducing phase transitions of
PCMs, and nonreciprocal responses display polarity reversal of CD upon sample
flipping in broadband spectral ranges. All experimental results agree with
simulations. Further, we demonstrate that the vertical dimension of
heterostructure is scalable with the number of stacking layers and aligned CNTs
play dual roles - the layer to produce CD responses and the Joule heating
electrode to electrically program PCMs. This heterostructure platform is
versatile and expandable to a library of 1D nanomaterials and electro-optic
materials for exploring novel chiral phenomena and photonic and optoelectronic
devices.
