Complementary memtransistors for neuromorphic computing: How, what and why

Memtransistors in which the source-drain channel conductance can be nonvolatilely manipulated through the gate signals have emerged as promising components for implementing neuromorphic computing.On the other side,it is known that the complementary metal-oxide-semiconductor(CMOS)field effect transistors have played the fundamental role in the modern integrated circuit technology.Therefore,will complementary memtransistors(CMT)also play such a role in the future neuromorphic circuits and chips?In this review,various types of materials and physical mechanisms for constructing CMT(how)are inspected with their merits and need-to-address challenges discussed.Then the unique properties(what)and poten-tial applications of CMT in different learning algorithms/scenarios of spiking neural networks(why)are reviewed,including super-vised rule,reinforcement one,dynamic vision with in-sensor computing,etc.Through exploiting the complementary structure-related novel functions,significant reduction of hardware consuming,enhancement of energy/efficiency ratio and other advan-tages have been gained,illustrating the alluring prospect of design technology co-optimization(DTCO)of CMT towards neuro-morphic computing.

Low operating voltage memtransistors based on ion bombarded p-type GeSe nanosheets for artificial synapse applications

Two-dimensional(2D)layered materials have many potential applications in memristors owing to their unique atomic structures and electronic properties.Memristors can overcome the in-memory bottleneck for use in brain-like neuromorphic computing.However,exploiting additional lateral memtransistors based on 2D layered materials remains challenging.There are few studies on p-type semiconductors that have not been theoretically analyzed.In this study,a lateral memtransistor based on p-type GeSe nanosheets is investigated.A threeterminal GeSe memtransistor that modulated the interfacial barrier height was fabricated using low-energy ion irradiation;the memtransistor exhibited a low operating voltage.The memtransistor successfully mimics biological synapse,including neuroplasticity functions,such as short-term plasticity,long-term plasticity,paired-pulse facilitation,and spike-timing-dependent plasticity.The mechanism of interfacial modulation was verified by experimental results and theoretical calculations.The results show that it is feasible to modulate the interface of 2D GeSe nanosheets using low-energy ion irradiation to realize a lateral memtransistor.This may provide promising opportunities for artificial neuromorphic system applications based on 2D layered materials.

Recent Advances in In-Memory Computing:Exploring Memristor and Memtransistor Arrays with 2D Materials

The conventional computing architecture faces substantial chal-lenges,including high latency and energy consumption between memory and processing units.In response,in-memory computing has emerged as a promising alternative architecture,enabling computing operations within memory arrays to overcome these limitations.Memristive devices have gained significant attention as key components for in-memory computing due to their high-density arrays,rapid response times,and ability to emulate biological synapses.Among these devices,two-dimensional(2D)material-based memristor and memtransistor arrays have emerged as particularly promising candidates for next-generation in-memory computing,thanks to their exceptional performance driven by the unique properties of 2D materials,such as layered structures,mechanical flexibility,and the capability to form heterojunctions.This review delves into the state-of-the-art research on 2D material-based memristive arrays,encompassing critical aspects such as material selection,device perfor-mance metrics,array structures,and potential applications.Furthermore,it provides a comprehensive overview of the current challenges and limitations associated with these arrays,along with potential solutions.The primary objective of this review is to serve as a significant milestone in realizing next-generation in-memory computing utilizing 2D materials and bridge the gap from single-device characterization to array-level and system-level implementations of neuromorphic computing,leveraging the potential of 2D material-based memristive devices.

Optically-controlled resistive switching effects of CdS nanowire memtransistor

Since it was proposed,memtransistors have been a leading candidate with powerful capabilities in the field of neural morphological networks.A memtransistor is an emerging structure combining the concepts of a memristor and a field-effect transistor with low-dimensional materials,so that both optical excitation and electrical stimuli can be used to modulate the memristive characteristics,which make it a promising multi-terminal hybrid device for synaptic structures.In this paper,a single CdS nanowire memtransistor has been constructed by the micromechanical exfoliation and alignment lithography methods.It is found that the CdS memtransistor has good non-volatile bipolar memristive characteristics,and the corresponding switching ratio is as high as 10^(6) in the dark.While under illumination,the behavior of the CdS memtransistor is similar to that of a transistor or a memristor depending on the incident wavelengths,and the memristive switching ratio varies in the range of 10 to 10^(5) with the increase of the incident wavelength in the visible light range.In addition,the optical power is also found to affect the memristive characteristics of the device.All of these can be attributed to the modulation of the potential barrier by abundant surface states of nanowires and the illumination influences on the carrier concentrations in nanowires.