Soliman Mohamed, Marchand Cédric, Mahmoudi Aymen, Kumar Rajak Neeraj, Taniguchi Takashi, Watanabe Kenji, Gloppe Arnaud, Doudin Bernard, Deleruyelle Damien, O'Connor Ian, Ouerghi Abdelkarim, Dayen Jean-Francois
Université de Strasbourg, IPCMS-CNRS UMR 7504, 23 Rue du Loess, Strasbourg 67034, France.
Centrale Lyon, INSA Lyon, CNRS, Université Claude Bernard Lyon 1, CPE Lyon, INL, UMR5270, Ecully 69134, France.
ACS Nano. 2025 May 20;19(19):18757-18768. doi: 10.1021/acsnano.5c03875. Epub 2025 May 12.
An inverted floating gate device architecture is introduced, demonstrated with all-van-der-Waals technology, targeting both logic and neuromorphic circuits. Integrating a top polymorphic multilayer graphene floating gate improves the electrostatic coupling to the ReS semiconductor channel by facilitating efficient dynamic conductance tuning and enabling dual-mode reconfigurable logic and memory operations. The non-volatile capability is used to implement compact logic gates for in-memory computing. The device is also shown to emulate synaptic plasticity, with an accuracy of 92% demonstrated in simple artificial neural network simulations. Moreover, spiking neuron circuits for neural networks through a five-transistor design makes it a versatile building block for artificial intelligence electronics. These findings demonstrate the potential of hybrid integration of van der Waals materials to address the limitations of traditional semiconductor technologies and become key to developments of next-generation electronics.
本文介绍了一种倒置浮栅器件架构,并通过全范德华技术进行了演示,该架构适用于逻辑电路和神经形态电路。集成顶部多晶多层石墨烯浮栅可通过促进有效的动态电导调谐并实现双模可重构逻辑和存储操作,从而改善与ReS半导体通道的静电耦合。非易失性功能用于实现用于内存计算的紧凑型逻辑门。该器件还被证明可以模拟突触可塑性,在简单的人工神经网络模拟中准确率达到92%。此外,通过五晶体管设计实现的用于神经网络的脉冲神经元电路使其成为人工智能电子学的通用构建模块。这些发现证明了范德华材料混合集成在解决传统半导体技术局限性方面的潜力,并成为下一代电子学发展的关键。