Chiroptical Ternary Entropy Harvesting from Self-Assembled Block Copolymer Nanopatterns

TL;DR

This paper introduces a chiroptical platform that converts stochastic nanopattern microstates into ternary optical responses, enabling higher entropy harvesting for secure key generation beyond binary limits.

Contribution

It demonstrates a scalable, self-assembled nanostructure-based method for ternary entropy harvesting with high information density and security features.

Findings

Achieves ternary digitization with 1.585 bits per trit, surpassing binary limits.

Outputs exhibit near-balanced symbol populations and minimal correlations.

Resistant to statistical and machine-learning-based prediction.

Abstract

Nanoscale fabrication inevitably produces local stochasticity that is commonly treated as a defect, but can instead be harnessed as a material resource for information security. Here we report a chiroptical platform for ternary entropy harvesting based on stochastic Au nanopatterns formed by block copolymer self-assembly. By transducing fabrication-induced stochastic microstates into handedness-dependent optical responses through chiroptical mapping, our platform enables native ternary digitization rather than conventional binary encoding, allowing physically harvested ternary random sequences to be used for key generation. This raises the information density to log2(3) = 1.585 bits per trit, approximately 58.5% higher than the binary limit, enabling more entropy to be harvested from a limited physical footprint. The harvested outputs exhibit near-balanced symbol populations, negligible spatial and inter-sample correlations, Shannon entropy approaching the ternary ideal, and resistance to statistical and machine-learning-based prediction. These results establish self-assembled chiroptical nanostructures as a scalable platform for cryptographic key generation, secure edge devices, and distributed Internet-of-Things platforms.