Related papers: CVD grown bilayer MoS2 based artificial optoelectr…
Photonic neuromorphic computing promises revolutionary advances in parallel and high-speed processing, yet a key challenge persists: co-integrating nonlinearity, dense connectivity, and intrinsic memory monolithically to enable…
Emerging non-volatile memory (NVM), or memristive, devices promise energy-efficient realization of deep learning, when efficiently integrated with mixed-signal integrated circuits on a CMOS substrate. Even though several algorithmic…
The optical and electronic properties of 2D semiconductors are intrinsically linked via the strong interactions between optically excited bound species and free carriers. Here we use near-field scanning microwave microscopy (SMM) to image…
The operation of an integrated two-dimensional complementary metal-oxide-semiconductor inverter with well-matched input/output voltages is reported. The circuit combines a few-layer MoS2 n-MOSFET and a black phosphorus (BP) p-MOSFET…
Monolayer transition metal dichalcogenides (TMDCs), like MoS$_2$, MoSe$_2$, WS$_2$, and WSe$_2$, feature direct bandgaps, strong spin-orbit coupling, and exciton-polariton interactions at the atomic scale, which could be harnessed for…
The separation of the data capture and analysis in modern vision systems has led to a massive amount of data transfer between the end devices and cloud computers, resulting in long latency, slow response, and high power consumption.…
A time-domain analog-weighted-sum calculation model based on a pulse-width modulation (PWM) approach is proposed. The proposed calculation model can be applied to any types of network structure including multi-layer feedforward networks. We…
We report on electronic transport in dual-gate, artificially stacked bilayer graphene field effect transistors (BiGFETs) fabricated from large-area chemical vapor deposited (CVD) graphene. The devices show enhanced tendency to current…
We propose an oscillatory neural network implemented with two-dimensional tantalum disulfide devices operating in the change density wave regime at room temperature. An elementary cell of the network consists of two 1T-TaS2 devices…
Among newly discovered two-dimensional (2D) materials, semiconducting ultrathin sheets of MoS2 show potential for nanoelectronics. However, the carrier mobility in MoS2 is limited by scattering from surface impurities and the substrate. To…
Hybrid graphene photoconductor/phototransistor has achieved giant photoresponsivity, but its response speed dramatically degrades as the expense due to the long lifetime of trapped interfacial carriers. In this work, by intercalating a…
Monolayer Molybdenum disulfide (MoS2), a two-dimensional crystal with a direct bandgap, is a promising candidate for 2D nanoelectronic devices complementing graphene. There have been recent attempts to produce MoS2 layers via chemical and…
Classical computing is beginning to encounter fundamental limits of energy efficiency. This presents a challenge that can no longer be solved by strategies such as increasing circuit density or refining standard semiconductor processes. The…
On-chip integration of highly anisotropic two-dimensional (2D) materials offers new opportunities for realizing high performance polarization selective devices. Obtaining optimized designs for such devices requires extensively sweeping…
The high contact resistance between MoS$_2$ and metals hinders its potential as an ideal solution for overcoming the short channel effect in silicon-based FETs at sub-3nm scales. We theoretically designed a MoS$_2$-based transistor,…
Electronic and dielectric properties of vapor-phase grown MoS_{2} have been investigated in metal/MoS_{2}/silicon capacitor structures by capacitance-voltage and conductancevoltage techniques. Analytical methods confirm the MoS_{2} layered…
Phase change memory (PCM) is an emerging data storage technology, however its programming is thermal in nature and typically not energy-efficient. Here we reduce the switching power of PCM through the combined approaches of filamentary…
Memristive circuit elements constitute a cornerstone for novel electronic applications, such as neuromorphic computing, called to revolutionize information technologies. By definition, memristors are sensitive to the history of electrical…
Neuromorphic computing promises to transform the current paradigm of traditional computing towards Non-Von Neumann dynamic energy-efficient problem solving. Thus, dynamic memory devices capable of simultaneously performing nonlinear…
Conventional neuro-computing architectures and artificial neural networks have often been developed with no or loose connections to neuroscience. As a consequence, they have largely ignored key features of biological neural processing…