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Interlayer carrier scattering hampers electrical conduction in two-dimensional layered nanostructures. Extenuated carrier scattering is observed in a double-layered graphene system with hexagonal boron nitride (h-BN) as an interposer. Raman spectrum shows signature peaks with enhanced sharpness as compared with that of bilayer graphene. The density functional theory simulation shows degenerate energy...
Resistive memory (ReRAM) shows promise for use as an analog synapse element in energy-efficient neural network algorithm accelerators. A particularly important application is the training of neural networks, as this is the most computationally-intensive procedure in using a neural algorithm. However, training a network with analog ReRAM synapses can significantly reduce the accuracy at the algorithm...
Analog resistive memories promise to reduce the energy of neural networks by orders of magnitude. However, the write variability and write nonlinearity of current devices prevent neural networks from training to high accuracy. We present a novel periodic carry method that uses a positional number system to overcome this while maintaining the benefit of parallel analog matrix operations. We demonstrate...
Memristor crossbars support efficient realizations of spiking and non-spiking neural networks designs. In most of these designs off-chip/ex-situ training is used to set/update the state of the memrisitve devices. However, there is a growing need to design an efficient on-chip/in-situ learning for mobile autonomous systems. In this research, we propose an on-chip learning accelerator, known as Ziksa,...
Nonvolatile redox transistors (NVRTs) based upon Li‐ion battery materials are demonstrated as memory elements for neuromorphic computer architectures with multi‐level analog states, “write” linearity, low‐voltage switching, and low power dissipation. Simulations of backpropagation using the device properties reach ideal classification accuracy. Physics‐based simulations predict energy costs per “write”...
We demonstrate a chemical-vapor-deposition (CVD)-based approach for the direct synthesis of graphene on insulator with high-dielectric-constant (high-κ). Rutile titanium dioxide (TiO 2 ), an insulator with reported k value of 80–125, is selected as the growth-initiating layer for graphene. A two-step CVD process is shown to grow graphene directly on TiO 2 crystals or exfoliated ultrathin...
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