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Abstract 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. 

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. 

Abstract 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. 

Abstract 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.