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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 (MoS

Detecting a potential collision at night is a challenging task owing to the lack of discernible features that can be extracted from the available visual stimuli. To alert the driver or, alternatively, the maneuvering system of an autonomous vehicle, current technologies utilize resource draining and expensive solutions such as light detection and ranging (LiDAR) or image sensors coupled with extensive software running sophisticated algorithms. In contrast, insects perform the same task of collision detection with frugal neural resources. Even though the general architecture of separate sensing and processing modules is the same in insects and in image-sensor-based collision detectors, task-specific obstacle avoidance algorithms allow insects to reap substantial benefits in terms of size and energy. Here, we show that insect-inspired collision detection algorithms, when implemented in conjunction with in-sensor processing and enabled by innovative optoelectronic integrated circuits based on atomically thin and photosensitive memtransistor technology, can greatly simplify collision detection at night. The proposed collision detector eliminates the need for image capture and image processing yet demonstrates timely escape responses for cars on collision courses under various real-life scenarios at night. The collision detector also has a small footprint of ∼40 μm

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 MoS

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.

Reverse engineering (RE) is one of the major security threats to the semiconductor industry due to the involvement of untrustworthy parties in an increasingly globalized chip manufacturing supply chain. RE efforts have already been successful in extracting device level functionalities from an integrated circuit (IC) with very limited resources. Camouflaging is an obfuscation method that can thwart such RE. Existing work on IC camouflaging primarily involves transformable interconnects and/or covert gates where variation in doping and dummy contacts hide the circuit structure or build cells that look alike but have different functionalities. Emerging solutions, such as polymorphic gates based on a giant spin Hall effect and Si nanowire field effect transistors (FETs), are also promising but add significant area overhead and are successfully decamouflaged by the satisfiability solver (SAT)-based RE techniques. Here, we harness the properties of two-dimensional (2D) transition-metal dichalcogenides (TMDs) including MoS

Realization of wafer-scale single-crystal films of transition metal dichalcogenides (TMDs) such as WS2 requires epitaxial growth and coalescence of oriented domains to form a continuous monolayer. The domains must be oriented in the same crystallographic direction on the substrate to inhibit the formation of inversion domain boundaries (IDBs), which are a common feature of layered chalcogenides. Here we demonstrate fully coalesced unidirectional WS2 monolayers on 2 in. diameter c-plane sapphire by metalorganic chemical vapor deposition using a multistep growth process to achieve epitaxial WS2 monolayers with low in-plane rotational twist (0.09°). Transmission electron microscopy analysis reveals that the WS2 monolayers are largely free of IDBs but instead have translational boundaries that arise when WS2 domains with slightly offset lattices merge together. By regulating the monolayer growth rate, the density of translational boundaries and bilayer coverage were significantly reduced. The unidirectional orientation of domains is attributed to the presence of steps on the sapphire surface coupled with growth conditions that promote surface diffusion, lateral domain growth, and coalescence while preserving the aligned domain structure. The transferred WS2 monolayers show neutral and charged exciton emission at 80 K with negligible defect-related luminescence. Back-gated WS2 field effect transistors exhibited an ION/OFF of ∼107 and mobility of 16 cm2/(V s). The results demonstrate the potential of achieving wafer-scale TMD monolayers free of inversion domains with properties approaching those of exfoliated flakes.

Integration of low-power consumer electronics on glass can revolutionize the automotive and transport sectors, packaging industry, smart building and interior design, healthcare, life science engineering, display technologies, and many other applications. However, direct growth of high-performance, scalable, and reliable electronic materials on glass is difficult owing to low thermal budget. Similarly, development of energy-efficient electronic and optoelectronic devices on glass requires manufacturing innovations. Here, we accomplish both by relatively low-temperature (

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.

A true random number generator (TRNG) is a critical hardware component that has become increasingly important in the era of Internet of Things (IoT) and mobile computing for ensuring secure communication and authentication schemes. While recent years have seen an upsurge in TRNGs based on nanoscale materials and devices, their resilience against machine learning (ML) attacks remains unexamined. In this article, we demonstrate a ML attack resilient, low-power, and low-cost TRNG by exploiting stochastic programmability of floating gate (FG) field effect transistors (FETs) with atomically thin channel materials. The origin of stochasticity is attributed to the probabilistic nature of charge trapping and detrapping phenomena in the FG. Our TRNG also satisfies other requirements, which include high entropy, uniformity, uniqueness, and unclonability. Furthermore, the generated bit-streams pass NIST randomness tests without any postprocessing. Our findings are important in the context of hardware security for resource constrained IoT edge devices, which are becoming increasingly vulnerable to ML attacks.

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 MoS

A defect-controlled approach for the nucleation and epitaxial growth of WSe2 on hBN is demonstrated. The WSe2 domains exhibit a preferred orientation of over 95%, leading to a reduced density of inversion domain boundaries (IDBs) upon coalescence. First-principles calculations and experimental studies as a function of growth conditions and substrate pretreatment confirm that WSe2 nucleation density and orientation are controlled by the hBN surface defect density rather than thermodynamic factors. Detailed transmission electron microscopy analysis provides support for the role of single-atom vacancies on the hBN surface that trap W atoms and break surface symmetry leading to a reduced formation energy for one orientation of WSe2 domains. Through careful control of nucleation and extended lateral growth time, fully coalesced WSe2 monolayer films on hBN were achieved. Low-temperature photoluminescence (PL) measurements and transport measurements of back-gated field-effect transistor devices fabricated on WSe...

Realization of wafer-scale single-crystal films of transition metal dichalcogenides (TMDs) such as WS

Integration of low-power consumer electronics on glass can revolutionize the automotive and transport sectors, packaging industry, smart building and interior design, healthcare, life science engineering, display technologies, and many other applications. However, direct growth of high-performance, scalable, and reliable electronic materials on glass is difficult owing to low thermal budget. Similarly, development of energy-efficient electronic and optoelectronic devices on glass requires manufacturing innovations. Here, we accomplish both by relatively low-temperature (600 °C) metal-organic chemical vapor deposition growth of atomically thin MoS

Structural defects govern various physical, chemical, and optoelectronic properties of two-dimensional transition-metal dichalcogenides (TMDs). A fundamental understanding of the spatial distribution and dynamics of defects in these low-dimensional systems is critical for advances in nanotechnology. However, such understanding has remained elusive primarily due to the inaccessibility of (a) necessary time scales via standard atomistic simulations and (b) required spatiotemporal resolution in experiments. Here, we take advantage of supervised machine learning, in situ high-resolution transmission electron microscopy (HRTEM) and molecular dynamics (MD) simulations to overcome these limitations. We combine genetic algorithms (GA) with MD to investigate the extended structure of point defects, their dynamical evolution, and their role in inducing the phase transition between the semiconducting (2H) and metallic (1T) phase in monolayer MoS2. GA-based structural optimization is used to identify the long-range structure of randomly distributed point defects (sulfur vacancies) for various defect densities. Regardless of the density, we find that organization of sulfur vacancies into extended lines is the most energetically favorable. HRTEM validates these findings and suggests a phase transformation from the 2H-to-1T phase that is localized near these extended defects when exposed to high electron beam doses. MD simulations elucidate the molecular mechanism driving the onset of the 2H to 1T transformation and indicate that finite amounts of 1T phase can be retained by increasing the defect concentration and temperature. This work significantly advances the current understanding of defect structure/evolution and structural transitions in 2D TMDs, which is crucial for designing nanoscale devices with desired functionality.

Neurotransmitter release in chemical synapses is fundamental to diverse brain functions such as motor action, learning, cognition, emotion, perception, and consciousness. Moreover, improper functioning or abnormal release of neurotransmitter is associated with numerous neurological disorders such as epilepsy, sclerosis, schizophrenia, Alzheimer’s disease, and Parkinson’s disease. We have utilized hysteresis engineering in a back-gated MoS2 field effect transistor (FET) in order to mimic such neurotransmitter release dynamics in chemical synapses. All three essential features, i.e., quantal, stochastic, and excitatory or inhibitory nature of neurotransmitter release, were accurately captured in our experimental demonstration. We also mimicked an important phenomenon called long-term potentiation (LTP), which forms the basis of human memory. Finally, we demonstrated how to engineer the LTP time by operating the MoS2 FET in different regimes. Our findings could provide a critical component toward the design ...

A defect-controlled approach for the nucleation and epitaxial growth of WSe

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. Chemica...

Structural defects govern various physical, chemical, and optoelectronic properties of two-dimensional transition-metal dichalcogenides (TMDs). A fundamental understanding of the spatial distribution and dynamics of defects in these low-dimensional systems is critical for advances in nanotechnology. However, such understanding has remained elusive primarily due to the inaccessibility of (a) necessary time scales via standard atomistic simulations and (b) required spatiotemporal resolution in experiments. Here, we take advantage of supervised machine learning, in situ high-resolution transmission electron microscopy (HRTEM) and molecular dynamics (MD) simulations to overcome these limitations. We combine genetic algorithms (GA) with MD to investigate the extended structure of point defects, their dynamical evolution, and their role in inducing the phase transition between the semiconducting (2H) and metallic (1T) phase in monolayer MoS

The isolation of graphene in 2004 from graphite was a defining moment for the "birth" of a field: two-dimensional (2D) materials. In recent years, there has been a rapidly increasing number of papers focusing on non-graphene layered materials, including transition-metal dichalcogenides (TMDs), because of the new properties and applications that emerge upon 2D confinement. Here, we review significant recent advances and important new developments in 2D materials "beyond graphene". We provide insight into the theoretical modeling and understanding of the van der Waals (vdW) forces that hold together the 2D layers in bulk solids, as well as their excitonic properties and growth morphologies. Additionally, we highlight recent breakthroughs in TMD synthesis and characterization and discuss the newest families of 2D materials, including monoelement 2D materials (i.e., silicene, phosphorene, etc.) and transition metal carbide- and carbon nitride-based MXenes. We then discuss the doping and functionalization of 2D materials beyond graphene that enable device applications, followed by advances in electronic, optoelectronic, and magnetic devices and theory. Finally, we provide perspectives on the future of 2D materials beyond graphene.

Neurotransmitter release in chemical synapses is fundamental to diverse brain functions such as motor action, learning, cognition, emotion, perception, and consciousness. Moreover, improper functioning or abnormal release of neurotransmitter is associated with numerous neurological disorders such as epilepsy, sclerosis, schizophrenia, Alzheimer's disease, and Parkinson's disease. We have utilized hysteresis engineering in a back-gated MoS

In this article, we demonstrate enhanced electron and hole transport in few-layer phosphorene field effect transistors (FETs) using titanium as the source/drain contact electrode and 20 nm SiO2 as the back gate dielectric. The field effect mobility values were extracted to be ∼38 cm(2)/Vs for electrons and ∼172 cm(2)/Vs for the holes. On the basis of our experimental data, we also comprehensively discuss how the contact resistances arising due to the Schottky barriers at the source and the drain end effect the different regime of the device characteristics and ultimately limit the ON state performance. We also propose and implement a novel technique for extracting the transport gap as well as the Schottky barrier height at the metal-phosphorene contact interface from the ambipolar transfer characteristics of the phosphorene FETs. This robust technique is applicable to any ultrathin body semiconductor which demonstrates symmetric ambipolar conduction. Finally, we demonstrate a high gain, high noise margin, chemical doping free, and fully complementary logic inverter based on ambipolar phosphorene FETs.

The effect of diameter variation on electrical characteristics of long-channel InAs nanowire metal-oxide-semiconductor field-effect transistors is experimentally investigated. For a range of nanowire diameters, in which significant band gap changes are observed due to size quantization, the Schottky barrier heights between source/drain metal contacts and the semiconducting nanowire channel are extracted considering both thermionic emission and thermally assisted tunneling. Nanowires as small as 10 nm in diameter were used in device geometry in this context. Interestingly, while experimental and simulation data are consistent with a band gap increase for decreasing nanowire diameter, the experimentally determined Schottky barrier height is found to be around 110 meV irrespective of the nanowire diameter. These observations indicate that for nanowire devices the density of states at the direct conduction band minimum impacts the so-called branching point. Our findings are thus distinctly different from bulk-type results when metal contacts are formed on three-dimensional InAs crystals.