3D Integration of functionally diverse 2D materials for optoelectronic reservoir computing

Anirban Chowdhury, Anshul Rasyotra, Harikrishnan Ravichandran, Denesh Kumar Manoharan, Yongwen Sun, Chen Chen, Joan M. Redwing, Yang Yang and Saptarshi Das ()
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Anirban Chowdhury: University Park, Engineering Science and Mechanics, Penn State University
Anshul Rasyotra: University Park, Engineering Science and Mechanics, Penn State University
Harikrishnan Ravichandran: University Park, Engineering Science and Mechanics, Penn State University
Denesh Kumar Manoharan: University Park, Engineering Science and Mechanics, Penn State University
Yongwen Sun: University Park, Engineering Science and Mechanics, Penn State University
Chen Chen: Penn State University, 2D Crystal Consortium Materials Innovation Platform
Joan M. Redwing: Penn State University, 2D Crystal Consortium Materials Innovation Platform
Yang Yang: University Park, Engineering Science and Mechanics, Penn State University
Saptarshi Das: University Park, Engineering Science and Mechanics, Penn State University

Nature Communications, 2025, vol. 16, issue 1, 1-10

Abstract: Abstract Recent years have seen remarkable progress in three-dimensional (3D) integration of non-silicon materials, enabling the convergence of diverse functionalities such as sensing, storage, and computing beyond mere transistor scaling. This advancement accelerates edge intelligence by enabling more efficient information processing at the source with reduced latency and power consumption. In this work, we contribute to this rapidly evolving landscape by demonstrating reservoir computing through 3D integration of In2Se3-based photodetectors with MoS2-based memtransistors. Our top tier exploits the variation in photoresponse of an optical reservoir constructed using flakes of different thicknesses of In2Se3. The bottom tier deploys programmable MoS2 memtransistors to convert the photocurrent into photovoltages which are subsequently processed by a trained readout circuit that is also based on MoS2 memtransistors. Notably, the physical proximity between sensors and computing elements is less than 50 nm, surpassing current state-of-the-art packaging solutions. We also demonstrate the benefits of near-sensor information processing for better photoresponse calibration and to achieve higher photoresponse speed. Overall, our 3D stack, with its near-sensor and in-memory compute capability, marks a significant milestone in vertically stacked functional layers composed of heterogeneous materials beyond silicon for edge applications.

Date: 2025
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DOI: 10.1038/s41467-025-65109-z

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