Related papers: A Novel Quaternary Decoder Design Utilizing 32nm C…

We explore the potential of Graph Neural Networks (GNNs) to improve the performance of high-dimensional effective field theory parameter fits to collider data beyond traditional rectangular cut-based differential distribution analyses. In…

Interfaces play a crucial role in determining the overall performance and functionality of electronic devices and systems. Driven by the data science, machine learning (ML) reveals excellent guidance for material selection and device…

We present a comparative study of high carrier density transport in mono-, bi-, and trilayer graphene using electric-double-layer transistors to continuously tune the carrier density up to values exceeding 10^{14} cm^{-2}. Whereas in…

Junctionless Nanowire Field-Effect Transistors (JNFETs), where the channel region is uniformly doped without the need for source-channel and drain-channel junctions or lateral doping abruptness, are considered an attractive alternative to…

Plasmon resonance in nanopatterned single layer graphene nanoribbon (SL-GNR), double layer graphene nanoribbon (DL-GNR) and triple layer graphene nanoribbon (TL-GNR) structures is studied both experimentally and by numerical simulations. We…

Bottom-up synthesized GNRs and GNR heterostructures have promising electronic properties for high performance field effect transistors (FETs) and ultra-low power devices such as tunnelling FETs. However, the short length and wide band gap…

As large language models (LLMs) continue to grow in size, distributed inference has become increasingly important. Model-parallel strategies must now efficiently scale not only across multiple GPUs but also across multiple nodes. In this…

Nano-electronic integrated circuit technology is exclusively based on MOSFET transistor due to its scalability down to the nanometer range. On the other hand, Bipolar Junction Transistor (BJT), which provides unmatched analog…

Graph neural networks (GNNs) have recently achieved state-of-the-art performance in many graph-based applications. Despite the high expressive power, they typically need to perform an expensive recursive neighborhood expansion in multiple…

We invented a novel method to fabricate graphene transistors on oxidized silicon wafers without the need to transfer graphene layers. By means of catalytic chemical vapor deposition (CCVD) the in-situ grown bilayer graphene transistors…

Ballistic quantum transport calculations based on the non-equilbrium Green's function formalism show that field-effect transistor devices made from chevron-type graphene nanoribbons (CGNRs) could exhibit negative differential resistance…

Graph Transformer (GT), as a special type of Graph Neural Networks (GNNs), utilizes multi-head attention to facilitate high-order message passing. However, this also imposes several limitations in node classification applications: 1) nodes…

In this work faster unsigned multiplication has been achieved by using a combination of High Performance Multiplication [HPM] column reduction technique and implementing a N-bit multiplier using 4 N/2-bit multipliers (recursive…

The tradeoff between receptive field size and efficiency is a crucial issue in low level vision. Plain convolutional networks (CNNs) generally enlarge the receptive field at the expense of computational cost. Recently, dilated filtering has…

With the demand of high data rate and low latency in fifth generation (5G), deep neural network decoder (NND) has become a promising candidate due to its capability of one-shot decoding and parallel computing. In this paper, three types of…

The graph fractional Fourier transform (GFRFT) applies a single global fractional order to all graph frequencies, which restricts its adaptability to diverse signal characteristics across the spectral domain. To address this limitation, in…

Polar codes have drawn much attention and been adopted in 5G New Radio (NR) due to their capacity-achieving performance. Recently, as the emerging deep learning (DL) technique has breakthrough achievements in many fields, neural network…

We invented a method to fabricate graphene transistors on oxidized silicon wafers without the need to transfer graphene layers. To stimulate the growth of graphene layers on oxidized silicon a catalyst system of nanometer thin…

If a device like a graphene nanoribbon (GNR) has all its four corners attached to electric current leads, the device becomes a quantum junction through which two electrical circuits can interact. We study such system theoretically for…

In computer vision, convolutional networks (CNNs) often adopts pooling to enlarge receptive field which has the advantage of low computational complexity. However, pooling can cause information loss and thus is detrimental to further…