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In this work, we demonstrate a dual-gated (DG) MoS2 field effect transistors (FETs) in which the degraded switching performance of multilayer MoS2 can be compensated by the DG structure. It produces large current density (>100 {\mu}A/{\mu}m…
The need for a high-performance transceiver with high Signal to Noise Ratio (SNR) has driven the communication system to utilize the latest technique identified as oversampling systems. It was the most economical modulator and decimation in…
Power limiters are essential devices in modern radio frequency (RF) communications systems to protect highly sensitive input channels from large incoming signals. Nowadays-used semiconductor limiters suffer from high electronic noise and…
We have fabricated suspended few layer (1-3 layers) graphene nanoribbon field effect transistors from unzipped multiwall carbon nanotubes. Electrical transport measurements show that current-annealing effectively removes the impurities on…
The carrier density in tens of nanometers thick graphite samples (multi-layer-graphene, MLG) has been modified by applying a gate voltage ($V_g$) perpendicular to the graphene planes. Surface potential microscopy shows inhomogeneities in…
Conditional random fields (CRFs) have been shown to be one of the most successful approaches to sequence labeling. Various linear-chain neural CRFs (NCRFs) are developed to implement the non-linear node potentials in CRFs, but still keeping…
Modern vision backbones for 3D medical imaging typically process dense voxel grids through parameter-heavy encoder-decoder structures, a design that allocates a significant portion of its parameters to spatial reconstruction rather than…
In this work, we have implemented an accurate machine-learning approach for predicting various key analog and RF parameters of Negative Capacitance Field-Effect Transistors (NCFETs). Visual TCAD simulator and the Python high-level language…
Graphene, due to its unique electronic structure favoring high carrier mobility, is considered a promising material for use in high-speed electronic devices in the post-silicon electronic era. For this reason, experimental research on…
This paper introduces a highly efficient greedy decoding algorithm for Transducer-based speech recognition models. We redesign the standard nested-loop design for RNN-T decoding, swapping loops over frames and labels: the outer loop…
In graphene nanoribbons (GNRs), the lateral confinement of charge carriers opens a band gap, the key feature to enable novel graphene-based electronics. Successful synthesis of GNRs has triggered efforts to realize field-effect transistors…
Recently it has been shown that deep learning-based image compression has shown the potential to outperform traditional codecs. However, most existing methods train multiple networks for multiple bit rates, which increases the…
Graph Neural Networks (GNNs) use a fully-connected layer to extract features from the nodes of a graph and aggregate these features using message passing between nodes, combining two distinct computational patterns: dense, regular…
Gate-all-around (GAA) nanowire (NW) field-effect transistor (FET) is a promising device architecture due to its superior gate controllability than that of the conventional FinFET architecture. The significantly higher electron mobility of…
We present an analytical device model for a field-effect transistor based on a heterostructure which consists of an array of nanoribbons clad between the highly conducting substrate (the back gate) and the top gate controlling the…
This paper analyzes the design and competitiveness of four neural network (NN) architectures recently proposed as decoders for forward error correction (FEC) codes. We first consider the so-called single-label neural network (SLNN) and the…
Graphene nanoribbons (GNRs) are a family of one-dimensional (1D) materials carved from graphene lattice. GNRs possess high mobility and current carrying capability, sizable bandgap, and versatile electronic properties tailored by the…
Graphene is a famous truly two-dimensional (2D) material, possessing a cone-like energy structure near the Fermi level and treated as a gapless semiconductor. Its unique properties trigger researchers to find applications of it. The gapless…
Multi-view multi-label feature selection aims to identify informative features from heterogeneous views, where each sample is associated with multiple interdependent labels. This problem is particularly important in machine learning…
The recent fabrication of graphene nanoribbon (GNR) field-effect transistors poses a challenge for first-principles modeling of carbon nanoelectronics due to many thousand atoms present in the device. The state of the art quantum transport…