2D Atomic‐Molecular Heterojunctions toward Brainoid Applications

Author:

Shu Fan1,Chen Weilin1,Chen Yu2,Liu Gang1ORCID

Affiliation:

1. Department of Micro/Nano Electronics, School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai 200240 China

2. School of Chemistry and Molecular Engineering East China University of Science and Technology Shanghai 200237 China

Abstract

AbstractBrainoid computing using 2D atomic crystals and their heterostructures, by emulating the human brain's remarkable efficiency and minimal energy consumption in information processing, poses a formidable solution to the energy‐efficiency and processing speed constraints inherent in the von Neumann architecture. However, conventional 2D material based heterostructures employed in brainoid devices are beset with limitations, performance uniformity, fabrication intricacies, and weak interfacial adhesion, which restrain their broader application. The introduction of novel 2D atomic‐molecular heterojunctions (2DAMH), achieved through covalent functionalization of 2D materials with functional molecules, ushers in a new era for brain‐like devices by providing both stability and tunability of functionalities. This review chiefly delves into the electronic attributes of 2DAMH derived from the synergy of polymer materials with 2D materials, emphasizing the most recent advancements in their utilization within memristive devices, particularly their potential in replicating the functionality of biological synapses. Despite ongoing challenges pertaining to precision in modification, scalability in production, and the refinement of underlying theories, the proliferation of innovative research is actively pursuing solutions. These endeavors illuminate the vast potential for incorporating 2DAMH within brain‐inspired intelligent systems, highlighting the prospect of achieving a more efficient and energy‐conserving computing paradigm.

Funder

National Key Research and Development Program of China

Publisher

Wiley

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