Neuromorphic vision sensors: Principle, progress and perspectives

Conventional frame-based image sensors suffer greatly from high energy consumption and latency.Mimicking neurobiological structures and functionalities of the retina provides a promising way to build a neuromorphic vision sensor with highly efficient image processing.In this review article,we will start with a brief introduction to explain the working mechanism and the challenges of conventional frame-based image sensors,and introduce the structure and functions of biological retina.In the main section,we will overview recent developments in neuromorphic vision sensors,including the silicon retina based on conventional Si CMOS digital technologies,and the neuromorphic vision sensors with the implementation of emerging devices.Finally,we will provide a brief outline of the prospects and outlook for the development of this field.

A multi-terminal ion-controlled transistor with multifunctionality and wide temporal dynamics for reservoir computing

Reservoir computing(RC)is an energy-efficient computational framework with low training cost and high efficiency in processing spatiotemporal information.The state-of-the-art fully memristor-based hardware RC system suffers from bottlenecks in the computation efficiencies and accuracy due to the limited temporal tunability in the volatile memristor for the reservoir layer and the nonlinearity in the nonvolatile memristor for the readout layer.Additionally,integrating different types of memristors brings fabrication and integration complexities.To overcome the challenges,a multifunctional multi-terminal electrolyte-gated transistor(MTEGT)that combines both electrostatic and electrochemical doping mechanisms is proposed in this work,integrating both widely tunable volatile dynamics with high temporal tunable range of 10^(2) and nonvolatile memory properties with high long-term potentiation/long-term depression(LTP/LTD)linearity into a single device.An ion-controlled physical RC system fully implemented with only one type of MTEGT is constructed for image recognition using the volatile dynamics for the reservoir and nonvolatility for the readout layer.Moreover,an ultralow normalized mean square error of 0.002 is achieved in a time series prediction task.It is believed that the MTEGT would underlie next-generation neuromorphic computing systems with low hardware costs and high computational performance.

2D Materials Based Optoelectronic Memory: Convergence of Electronic Memory and Optical Sensor

Te continuous development of electron devices towards the trend of“More than Moore”requires functional diversifcation that can collect data(sensors)and store(memories)and process(computing units)information.Considering the large occupation proportion of image data in both data center and edge devices,a device integration with optical sensing and data storage and processing is highly demanded for future energy-efcient and miniaturized electronic system.Two-dimensional(2D)materials and their heterostructures have exhibited broadband photoresponse and high photoresponsivity in the confguration of optical sensors and showed fast switching speed,multi-bit data storage,and large ON/OFF ratio in memory devices.In addition,its ultrathin body thickness and transfer process at low temperature allow 2D materials to be heterogeneously integrated with other existing materials system.In this paper,we overview the state-of-the-art optoelectronic random-access memories(ORAMs)based on 2D materials,as well as ORAM synaptic devices and their applications in neural network and image processing.Te ORAM devices potentially enable direct storage/processing of sensory data from external environment.We also provide perspectives on possible directions of other neuromorphic sensor design(e.g.,auditory and olfactory)based on 2D materials towards the future smart electronic systems for artifcial intelligence.

Crypto primitive of MOCVD MoS_(2) transistors for highly secured physical unclonable functions

Physically unclonable crypto primitives have potential applications for anti-counterfeiting,identification,and authentication,which are clone proof and resistant to variously physical attack.Conventional physical unclonable function(PUF)based on Si complementary metal-oxide-semiconductor(CMOS)technologies greatly suffers from entropy loss and bit instability due to noise sensitivity.Here we grow atomically thick MoS2 thin film and fabricate field-effect transistors(FETs).The inherently physical randomness of MoS2 transistors from materials growth and device fabrication process makes it appropriate for the application of PUF device.We perform electrical characterizations of MoS2 FETs,collect the data from 448 devices,and generate PUF keys by splitting drain current at specific levels to evaluate the response performance.Proper selection of splitting threshold enables to generate binary,ternary,and double binary keys.The generated PUF keys exhibit good randomness and uniqueness,providing a possibility for harvesting highly secured PUF devices with two-dimensional materials.