Active pixel sensor matrix based on monolayer MoS2 phototransistor array.

In-sensor processing, which can reduce the energy and hardware burden for many machine vision applications, is currently lacking in state-of-the-art active pixel sensor (APS) technology. Photosensitive and semiconducting two-dimensional (2D) materials can bridge this technology gap by integrating image capture (sense) and image processing (compute) capabilities in a single device. Here, we introduce a 2D APS technology based on a monolayer MoS2 phototransistor array, where each pixel uses a single programmable phototransistor, leading to a substantial reduction in footprint (900 pixels in ∼0.09 cm2) and energy consumption (100s of fJ per pixel). By exploiting gate-tunable persistent photoconductivity, we achieve a responsivity of ∼3.6 × 107 A W-1, specific detectivity of ∼5.6 × 1013 Jones, spectral uniformity, a high dynamic range of ∼80 dB and in-sensor de-noising capabilities. Further, we demonstrate near-ideal yield and uniformity in photoresponse across the 2D APS array.

All-in-one, bio-inspired, and low-power crypto engines for near-sensor security based on two-dimensional memtransistors.

In the emerging era of the internet of things (IoT), ubiquitous sensors continuously collect, consume, store, and communicate a huge volume of information which is becoming increasingly vulnerable to theft and misuse. Modern software cryptosystems require extensive computational infrastructure for implementing ciphering algorithms, making them difficult to be adopted by IoT edge sensors that operate with limited hardware resources and at low energy budgets. Here we propose and experimentally demonstrate an "all-in-one" 8 × 8 array of robust, low-power, and bio-inspired crypto engines monolithically integrated with IoT edge sensors based on two-dimensional (2D) memtransistors. Each engine comprises five 2D memtransistors to accomplish sensing and encoding functionalities. The ciphered information is shown to be secure from an eavesdropper with finite resources and access to deep neural networks. Our hardware platform consists of a total of 320 fully integrated monolayer MoS2-based memtransistors and consumes energy in the range of hundreds of picojoules and offers near-sensor security.

An All-in-One Bioinspired Neural Network.

In spite of recent advancements in artificial neural networks (ANNs), the energy efficiency, multifunctionality, adaptability, and integrated nature of biological neural networks remain largely unimitated by hardware neuromorphic computing systems. Here, we exploit optoelectronic, computing, and programmable memory devices based on emerging two-dimensional (2D) layered materials such as MoS2 to demonstrate a monolithically integrated, multipixel, and "all-in-one" bioinspired neural network (BNN) capable of sensing, encoding, learning, forgetting, and inferring at minuscule energy expenditure. We also demonstrate learning adaptability and simulate learning challenges under specific synaptic conditions to mimic biological learning. Our findings highlight the potential of in-memory computing and sensing based on emerging 2D materials, devices, and integrated circuits to not only overcome the bottleneck of von Neumann computing in conventional CMOS designs but also to aid in eliminating the peripheral components necessary for competing technologies such as memristors.

Bioinspired and Low-Power 2D Machine Vision with Adaptive Machine Learning and Forgetting.

Natural intelligence has many dimensions, with some of its most important manifestations being tied to learning about the environment and making behavioral changes. In primates, vision plays a critical role in learning. The underlying biological neural networks contain specialized neurons and synapses which not only sense and process visual stimuli but also learn and adapt with remarkable energy efficiency. Forgetting also plays an active role in learning. Mimicking the adaptive neurobiological mechanisms for seeing, learning, and forgetting can, therefore, accelerate the development of artificial intelligence (AI) and bridge the massive energy gap that exists between AI and biological intelligence. Here, we demonstrate a bioinspired machine vision system based on a 2D phototransistor array fabricated from large-area monolayer molybdenum disulfide (MoS2) and integrated with an analog, nonvolatile, and programmable memory gate-stack; this architecture not only enables dynamic learning and relearning from visual stimuli but also offers learning adaptability under noisy illumination conditions at miniscule energy expenditure. In short, our demonstrated "all-in-one" hardware vision platform combines "sensing", "computing", and "storage" to not only overcome the von Neumann bottleneck of conventional complementary metal-oxide-semiconductor (CMOS) technology but also to eliminate the need for peripheral circuits and sensors.

Graphene and Beyond: Recent Advances in Two-Dimensional Materials Synthesis, Properties, and Devices.

Since the isolation of graphene in 2004, two-dimensional (2D) materials research has rapidly evolved into an entire subdiscipline in the physical sciences with a wide range of emergent applications. The unique 2D structure offers an open canvas to tailor and functionalize 2D materials through layer number, defects, morphology, moiré pattern, strain, and other control knobs. Through this review, we aim to highlight the most recent discoveries in the following topics: theory-guided synthesis for enhanced control of 2D morphologies, quality, yield, as well as insights toward novel 2D materials; defect engineering to control and understand the role of various defects, including in situ and ex situ methods; and properties and applications that are related to moiré engineering, strain engineering, and artificial intelligence. Finally, we also provide our perspective on the challenges and opportunities in this fascinating field.

Demonstration of Stochastic Resonance, Population Coding, and Population Voting Using Artificial MoS2 Based Synapses.

Fast detection of weak signals at low energy expenditure is a challenging but inescapable task for the evolutionary success of animals that survive in resource constrained environments. This task is accomplished by the sensory nervous system by exploiting the synergy between three astounding neural phenomena, namely, stochastic resonance (SR), population coding (PC), and population voting (PV). In SR, the constructive role of synaptic noise is exploited for the detection of otherwise invisible signals. In PC, the redundancy in neural population is exploited to reduce the detection latency. Finally, PV ensures unambiguous signal detection even in the presence of excessive noise. Here we adopt a similar strategies and experimentally demonstrate how a population of stochastic artificial neurons based on monolayer MoS2 field effect transistors (FETs) can use an optimum amount of white Gaussian noise and population voting to detect invisible signals at a frugal energy expenditure (∼10s of nano-Joules). Our findings can aid remote sensing in the emerging era of the Internet of things (IoT) that thrive on energy efficiency.

Secure Electronics Enabled by Atomically Thin and Photosensitive Two-Dimensional Memtransistors.

The rapid proliferation of security compromised hardware in today's integrated circuit (IC) supply chain poses a global threat to the reliability of communication, computing, and control systems. While there have been significant advancements in detection and avoidance of security breaches, current top-down approaches are mostly inadequate, inefficient, often inconclusive, and resource extensive in time, energy, and cost, offering tremendous scope for innovation in this field. Here, we introduce an energy and area efficient non-von Neumann hardware platform providing comprehensive and bottom-up security solutions by exploiting inherent device-to-device variation, electrical programmability, and persistent photoconductivity demonstrated by atomically thin two-dimensional memtransistors. We realize diverse security primitives including physically unclonable function, anticounterfeit measures, intellectual property (IP) watermarking, and IC camouflaging to prevent false authentication, detect recycled and remarked ICs, protect IP theft, and stop reverse engineering of ICs.

Stochastic resonance in MoS2 photodetector.

In this article, we adopt a radical approach for next generation ultra-low-power sensor design by embracing the evolutionary success of animals with extraordinary sensory information processing capabilities that allow them to survive in extreme and resource constrained environments. Stochastic resonance (SR) is one of those astounding phenomena, where noise, which is considered detrimental for electronic circuits and communication systems, plays a constructive role in the detection of weak signals. Here, we show SR in a photodetector based on monolayer MoS2 for detecting ultra-low-intensity subthreshold optical signals from a distant light emitting diode (LED). We demonstrate that weak periodic LED signals, which are otherwise undetectable, can be detected by a MoS2 photodetector in the presence of a finite and optimum amount of white Gaussian noise at a frugal energy expenditure of few tens of nano-Joules. The concept of SR is generic in nature and can be extended beyond photodetector to any other sensors.

Spontaneous chemical functionalization via coordination of Au single atoms on monolayer MoS2.

Surface functionalization of metallic and semiconducting 2D transition metal dichalcogenides (TMDs) have mostly relied on physi- and chemi-sorption at defect sites, which can diminish the potential applications of the decorated 2D materials, as structural defects can have substantial drawbacks on the electronic and optoelectronic characteristics. Here, we demonstrate a spontaneous defect-free functionalization method consisting of attaching Au single atoms to monolayers of semiconducting MoS2(1H) via S-Au-Cl coordination complexes. This strategy offers an effective and controllable approach for tuning the Fermi level and excitation spectra of MoS2 via p-type doping and enhancing the thermal boundary conductance of monolayer MoS2, thus promoting heat dissipation. The coordination-based method offers an effective and damage-free route of functionalizing TMDs and can be applied to other metals and used in single-atom catalysis, quantum information devices, optoelectronics, and enhanced sensing.

A biomimetic 2D transistor for audiomorphic computing.

In this article, we introduce a biomimetic audiomorphic device that captures the neurobiological architecture and computational map inside the auditory cortex of barn owl known for its exceptional hunting ability in complete darkness using auditory cues. The device consists of multiple split-gates with nanogaps on a semiconducting MoS2 channel connected to the source/drain contacts for imitating the spatial map of coincidence detector neurons and tunable RC circuits for imitating the interaural time delay neurons following the Jeffress model of sound localization. Furthermore, we use global back-gating capability to demonstrate neuroplasticity to capture behavioral and/or adaptation related changes in the barn owl. Finally, the virtual source model for current transport is combined with finite element COMSOL multiphysics simulations to explain and project the performance of the biomimetic audiomorphic device. We find that the precision of the biomimetic device can supersede the barn owl by orders of magnitude.

Electrochemical Polishing of Two-Dimensional Materials.

Two-dimensional (2D) layered materials demonstrate their exquisite properties such as high temperature superconductivity, superlubricity, charge density wave, piezotronics, flextronics, straintronics, spintronics, valleytronics, and optoelectronics, mostly, at the monolayer limit. Following initial breakthroughs based on micromechanically exfoliated 2D monolayers, significant progress has been made in recent years toward the bottom-up synthesis of large-area monolayer 2D materials such as MoS2 and WS2 using physical vapor deposition and chemical vapor deposition techniques in order to facilitate their transition into commercial technologies. However, the nucleation and subsequent growth of the secondary, tertiary, and greater numbers of vertical layers poses a significant challenge not only toward the realization of uniform monolayers but also toward maintaining their consistent electronic and optoelectronic properties which change abruptly when transitioning from the monolayer to multilayer form. Chemical or physical techniques which can remove the unwanted top layers without compromising the material quality will have tremendous consequences toward the development of atomically flat, large-area, uniform monolayers of 2D materials. Here, we report a simple, elegant, and self-limiting electrochemical polishing technique that can thin down any arbitrary thickness of 2D material, irrespective of whether these are obtained using powder vapor transport or mechanical exfoliation, into their corresponding monolayer form at room temperature within a few seconds without compromising their atomistic integrity. The effectiveness of this electrochemical polishing technique is inherent to 2D transition-metal dichalcogenides owing to the stability of their basal planes, enhanced edge reactivity, and stronger than van der Waals interaction with the substrate. Our study also reveals that 2D monolayers are chemically more robust and corrosion resistant compared to their bulk counterparts in similar oxidative environments, which enables electrochemical polishing of such materials down to a monolayer.

Anomalous Corrosion of Bulk Transition Metal Diselenides Leading to Stable Monolayers.

In this paper we provide insight into an anomalous corrosion process, referred to as electroablation (EA), which converts multilayer flakes of transition metal diselenides like MoSe2 into their corresponding monolayers when micromechanically exfoliated on a conductive electrode and subsequently subjected to a high anodic potential inside a conventional electrochemical cell. Photoluminescence intensity maps and scanning transmission electron microscopy (STEM) images confirmed the single crystalline nature and 2H-hexagonal lattice structure of the remnant monolayer MoSe2 flakes, indicating the superior corrosion stability of the monolayers compared to that of the bulk counterpart. It is noted that the EA technique is a low-cost alternative for high-yield synthesis of single crystalline monolayer MoSe2 at room temperature. We also found that the dynamics of such an electro-oxidation-mediated and self-limiting corrosion process differs significantly for MoSe2 and WSe2. While we were able to engineer the corrosion conditions for the EA process to obtain monolayers of MoSe2, our attempts to obtain monolayers of WSe2 were largely unsuccessful. Finally, we constructed a phenomenological physical chemistry framework to explain such anomalous corrosion processes in transition metal diselenides.