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.

Two-dimensional materials-based probabilistic synapses and reconfigurable neurons for measuring inference uncertainty using Bayesian neural networks.

Artificial neural networks have demonstrated superiority over traditional computing architectures in tasks such as pattern classification and learning. However, they do not measure uncertainty in predictions, and hence they can make wrong predictions with high confidence, which can be detrimental for many mission-critical applications. In contrast, Bayesian neural networks (BNNs) naturally include such uncertainty in their model, as the weights are represented by probability distributions (e.g. Gaussian distribution). Here we introduce three-terminal memtransistors based on two-dimensional (2D) materials, which can emulate both probabilistic synapses as well as reconfigurable neurons. The cycle-to-cycle variation in the programming of the 2D memtransistor is exploited to achieve Gaussian random number generator-based synapses, whereas 2D memtransistor based integrated circuits are used to obtain neurons with hyperbolic tangent and sigmoid activation functions. Finally, memtransistor-based synapses and neurons are combined in a crossbar array architecture to realize a BNN accelerator for a data classification task.

A Sparse and Spike-Timing-Based Adaptive Photoencoder for Augmenting Machine Vision for Spiking Neural Networks.

The representation of external stimuli in the form of action potentials or spikes constitutes the basis of energy efficient neural computation that emerging spiking neural networks (SNNs) aspire to imitate. With recent evidence suggesting that information in the brain is more often represented by explicit firing times of the neurons rather than mean firing rates, it is imperative to develop novel hardware that can accelerate sparse and spike-timing-based encoding. Here a medium-scale integrated circuit composed of two cascaded three-stage inverters and one XOR logic gate fabricated using a total of 21 memtransistors based on photosensitive 2D monolayer MoS2  for spike-timing-based encoding of visual information, is introduced. It is shown that different illumination intensities can be encoded into sparse spiking with time-to-first-spike representing the illumination information, that is, higher intensities invoke earlier spikes and vice versa. In addition, non-volatile and analog programmability in the photoencoder is exploited for adaptive photoencoding that allows expedited spiking under scotopic (low-light) and deferred spiking under photopic (bright-light) conditions, respectively. Finally, low energy expenditure of less than 1 µJ by the 2D-memtransistor-based photoencoder highlights the benefits of in-sensor and bioinspired design that can be transformative for the acceleration of SNNs.

An Annealing Accelerator for Ising Spin Systems Based on In-Memory Complementary 2D FETs.

Metaheuristic algorithms such as simulated annealing (SA) are often implemented for optimization in combinatorial problems, especially for discreet problems. SA employs a stochastic search, where high-energy transitions ("hill-climbing") are allowed with a temperature-dependent probability to escape local optima. Ising spin glass systems have properties such as spin disorder and "frustration" and provide a discreet combinatorial problem with a high number of metastable states and ground-state degeneracy. In this work, subthreshold Boltzmann transport is exploited in complementary 2D field-effect transistors (p-type WSe2 and n-type MoS2 ) integrated with an analog, nonvolatile, and programmable floating-gate memory stack to develop in-memory computing primitives necessary for energy- and area-efficient hardware acceleration of SA for Ising spin systems. Search acceleration of >800× is demonstrated for 4 × 4 ferromagnetic, antiferromagnetic, and spin glass systems using SA compared to an exhaustive search using a brute force trial at miniscule total energy expenditure of ≈120 nJ. The hardware-realistic numerical simulations further highlight the astounding benefits of SA in accelerating the search for larger spin lattices.

A biomimetic neural encoder for spiking neural network.

Spiking neural networks (SNNs) promise to bridge the gap between artificial neural networks (ANNs) and biological neural networks (BNNs) by exploiting biologically plausible neurons that offer faster inference, lower energy expenditure, and event-driven information processing capabilities. However, implementation of SNNs in future neuromorphic hardware requires hardware encoders analogous to the sensory neurons, which convert external/internal stimulus into spike trains based on specific neural algorithm along with inherent stochasticity. Unfortunately, conventional solid-state transducers are inadequate for this purpose necessitating the development of neural encoders to serve the growing need of neuromorphic computing. Here, we demonstrate a biomimetic device based on a dual gated MoS2 field effect transistor (FET) capable of encoding analog signals into stochastic spike trains following various neural encoding algorithms such as rate-based encoding, spike timing-based encoding, and spike count-based encoding. Two important aspects of neural encoding, namely, dynamic range and encoding precision are also captured in our demonstration. Furthermore, the encoding energy was found to be as frugal as ≈1-5 pJ/spike. Finally, we show fast (≈200 timesteps) encoding of the MNIST data set using our biomimetic device followed by more than 91% accurate inference using a trained SNN.

Wafer-Scale Epitaxial Growth of Unidirectional WS2 Monolayers on Sapphire.

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.

Benchmarking monolayer MoS2 and WS2 field-effect transistors.

Here we benchmark device-to-device variation in field-effect transistors (FETs) based on monolayer MoS2 and WS2 films grown using metal-organic chemical vapor deposition process. Our study involves 230 MoS2 FETs and 160 WS2 FETs with channel lengths ranging from 5 µm down to 100 nm. We use statistical measures to evaluate key FET performance indicators for benchmarking these two-dimensional (2D) transition metal dichalcogenide (TMD) monolayers against existing literature as well as ultra-thin body Si FETs. Our results show consistent performance of 2D FETs across 1 × 1 cm2 chips owing to high quality and uniform growth of these TMDs followed by clean transfer onto device substrates. We are able to demonstrate record high carrier mobility of 33 cm2 V-1 s-1 in WS2 FETs, which is a 1.5X improvement compared to the best reported in the literature. Our experimental demonstrations confirm the technological viability of 2D FETs in future integrated circuits.

Monolayer Vanadium-Doped Tungsten Disulfide: A Room-Temperature Dilute Magnetic Semiconductor.

Dilute magnetic semiconductors (DMS), achieved through substitutional doping of spin-polarized transition metals into semiconducting systems, enable experimental modulation of spin dynamics in ways that hold great promise for novel magneto-electric or magneto-optical devices, especially for two-dimensional (2D) systems such as transition metal dichalcogenides that accentuate interactions and activate valley degrees of freedom. Practical applications of 2D magnetism will likely require room-temperature operation, air stability, and (for magnetic semiconductors) the ability to achieve optimal doping levels without dopant aggregation. Here, room-temperature ferromagnetic order obtained in semiconducting vanadium-doped tungsten disulfide monolayers produced by a reliable single-step film sulfidation method across an exceptionally wide range of vanadium concentrations, up to 12 at% with minimal dopant aggregation, is described. These monolayers develop p-type transport as a function of vanadium incorporation and rapidly reach ambipolarity. Ferromagnetism peaks at an intermediate vanadium concentration of ~2 at% and decreases for higher concentrations, which is consistent with quenching due to orbital hybridization at closer vanadium-vanadium spacings, as supported by transmission electron microscopy, magnetometry, and first-principles calculations. Room-temperature 2D-DMS provide a new component to expand the functional scope of van der Waals heterostructures and bring semiconducting magnetic 2D heterostructures into the realm of practical application.

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.

Gaussian synapses for probabilistic neural networks.

The recent decline in energy, size and complexity scaling of traditional von Neumann architecture has resurrected considerable interest in brain-inspired computing. Artificial neural networks (ANNs) based on emerging devices, such as memristors, achieve brain-like computing but lack energy-efficiency. Furthermore, slow learning, incremental adaptation, and false convergence are unresolved challenges for ANNs. In this article we, therefore, introduce Gaussian synapses based on heterostructures of atomically thin two-dimensional (2D) layered materials, namely molybdenum disulfide and black phosphorus field effect transistors (FETs), as a class of analog and probabilistic computational primitives for hardware implementation of statistical neural networks. We also demonstrate complete tunability of amplitude, mean and standard deviation of the Gaussian synapse via threshold engineering in dual gated molybdenum disulfide and black phosphorus FETs. Finally, we show simulation results for classification of brainwaves using Gaussian synapse based probabilistic neural networks.

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.

Mobility Deception in Nanoscale Transistors: An Untold Contact Story.

Mobility is a critical parameter that is routinely used for benchmarking the performance of field-effect transistors (FETs) based on novel nanomaterials. In fact, mobility values are often used to champion nanomaterials since high-performance devices necessitate high mobility values. The current belief is that the contacts can only limit the FET performance and hence the extracted mobility is an underestimation of the true channel mobility. However, here, such misconception is challenged through rigorous experimental effort, backed by numerical simulations, to demonstrate that overestimation of mobility occurs in commonly used geometries and in nanomaterials for which the contact interface, contact doping, and contact geometry play a pivotal role. In particular, dual-gated FETs based on multilayer MoS2 and WSe2 are used as case studies in order to elucidate and differentiate between intrinsic and extrinsic contact effects manifesting in the mobility extraction. The choice of 2D layered transition metal dichalcogenides (TMDCs) as the semiconducting channel is motivated by their potential to replace and/or coexist with Si-based aging FET technologies. However, the results are equally applicable to nanotube- and nanowire-based FETs, oxide semiconductors, and organic-material-based thin-film FETs.

In Situ Optical Tracking of Electroablation in Two-Dimensional Transition-Metal Dichalcogenides.

Two-dimensional (2D) transition-metal dichalcogenides (TMDs) are a unique class of 2D materials possessing unique optoelectronic properties when exfoliated into mono- and few-layer sheets. Recently, electroablation (EA) has become of interest as a promising synthesis method for single-layer sheets of TMDs. Here, we introduce spectroelectrochemical micro-extinction spectroscopy (SE-MExS) as a high-throughput technique to study electrochemical thinning of TMDs as it occurs. This approach enables the parallel use of spectroscopy and imaging to nondestructively characterize 2D materials in situ. We unravel optoelectronics of the TMDs by observing changes in optical properties during EA. We find that the EA process for MoS2, WS2, MoSe2, and WSe2 occurs edge first, generating high density of edge sites. Our results show that stable monolayers of MoS2, WS2, and MoSe2 can be synthesized from bulk precursors by the EA process, while conversely, no WSe2 remains postablation.

Facile Electrochemical Synthesis of 2D Monolayers for High-Performance Thin-Film Transistors.

In this paper, we report high-performance monolayer thin-film transistors (TFTs) based on a variety of two-dimensional layered semiconductors such as MoS2, WS2, and MoSe2 which were obtained from their corresponding bulk counterparts via an anomalous but high-yield and low-cost electrochemical corrosion process, also referred to as electro-ablation (EA), at room temperature. These monolayer TFTs demonstrated current ON-OFF ratios in excess of 107 along with ON currents of 120 µA/µm for MoS2, 40 µA/µm for WS2, and 40 µA/µm for MoSe2 which clearly outperform the existing TFT technologies. We found that these monolayers have larger Schottky barriers for electron injection compared to their multilayer counterparts, which is partially compensated by their superior electrostatics and ultra-thin tunnel barriers. We observed an Anderson type semiconductor-to-metal transition in these monolayers and also discussed possible scattering mechanisms that manifest in the temperature dependence of the electron mobility. Finally, our study suggests superior chemical stability and electronic integrity of monolayers even after being exposed to extreme electro-oxidation and corrosion processes which is promising for the implementation of such TFTs in harsh environment sensing. Overall, the EA process proves to be a facile synthesis route offering higher monolayer yields than mechanical exfoliation and lower cost and complexity than chemical vapor deposition methods.

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.