The emulation of biological synapses with learning and memory functions and versatile plasticity is sig-nificantly promising for neuromorphic computing systems.Here,a robust and continuously adjustable mechanoplastic semifloating-gate transistor is demonstrated based on an integrated graphene/hexagonal boron nitride/tungsten diselenide van der Waals heterostructure and a triboelectric nanogenerator(TENG).The working states(p-n junction or n+-n junction)can be manipulated and switched under the sophisticated modulation of triboelectric potential derived from mechanical actions,which is attrib-uted to carriers trapping and detrapping in the graphene layer.Furthermore,a reconfigurable artificial synapse is constructed based on such mechanoplastic transistor that can simulate typical synaptic plas-ticity and implement dynamic control correlations in each response mode by further designing the amplitude and duration.The artificial synapse can work with ultra-low energy consumption at 74.2 fJ per synaptic event and the extended synaptic weights.Under the synergetic effect of the semifloating gate,the synaptic device can enable successive mechanical facilitation/depression,short-/long-term plas-ticity and learning-experience behavior,exhibiting the mechanical behavior derived synaptic plasticity.Such reconfigurable and mechanoplastic features provide an insight into the applications of energy-efficient and real-time interactive neuromodulation in the future artificial intelligent system beyond von Neumann architecture.

Mengmeng Jia;Pengwen Guo;Wei Wang;Aifang Yu;Yufei Zhang;Zhong Lin Wang;Junyi Zhai

CAS Center for Excellence in Nanoscience,Beijing Key Laboratory of Micro-nano Energy and Sensor,Beijing Institute of Nanoenergy and Nanosystems,Chinese Academy of Sciences,Beijing 100083,China;School of Nanoscience and Technology,University of Chinese Academy of Sciences,Beijing 100049,China;Center on Nanoenergy Research,School of Physical Science and Technology,Guangxi University,Nanning 530004,China;School of Materials Science and Engineering,Georgia Institute of Technology,Atlanta,GA 30332,USA

科学通报（英文版）

[1]Mengmeng Jia;Pengwen Guo;Wei Wang;Aifang Yu;Yufei Zhang;Zhong Lin Wang;Junyi Zhai-.Tactile tribotronic reconfigurable p-n junctions for artificial synapses)[J].科学通报（英文版）,2022(08):803-812

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