Related papers: Low-frequency noise parameter extraction method fo…
Naturally or artificially stacking extra layers on single layer graphene (SLG) forms few-layer graphene (FLG), which has attracted tremendous attention owing to its exceptional properties inherited from SLG and new features generated by…
Single-molecule sensing is at the core of modern biophysics and nanoscale science, from revolutionizing healthcare through rapid, low-cost sequencing to understanding various physical, chemical, and biological processes at their most basic…
Graph convolutional networks (GCNs) have achieved great success on graph-structured data. Many graph convolutional networks can be thought of as low-pass filters for graph signals. In this paper, we propose a more powerful graph…
The electronic properties of graphene are unique and are attracting increased attention to this novel 2-dimensional system. Its photonic properties are not less impressive. For example, this single atomic layer absorbs through direct…
Pruning is a model compression method that removes redundant parameters in deep neural networks (DNNs) while maintaining accuracy. Most available filter pruning methods require complex treatments such as iterative pruning, features…
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…
Link prediction (LP), inferring the connectivity between nodes, is a significant research area in graph data, where a link represents essential information on relationships between nodes. Although graph neural network (GNN)-based models…
The terahertz detection performance and operating regimes of graphene plasmonic field-effect transistors (FETs) were investigated by a hydrodynamic model. Continuous wave detection simulations showed that the graphene response sensitivity…
We study frequency-dependent current noise through a single-level quantum dot connected to ferromagnetic leads with non-collinear magnetization. We propose to use the frequency-dependent Fano factor as a tool to detect single-spin dynamics…
We present a high scale method to produce few layer graphene (FLG) based on the mechanical exfoliation of graphite and compare the obtained FLG with the one reported earlier arising from pencil lead ablation. Several things are modified and…
Automatic Modulation Recognition (AMR) is an essential part of Intelligent Transportation System (ITS) dynamic spectrum allocation. However, current deep learning-based AMR (DL-AMR) methods are challenged to extract discriminative and…
We report the first measurement of 1/f type noise associated with electronic spin transport, using single layer graphene as a prototypical material with a large and tunable Hooge parameter. We identify the presence of two contributions to…
Understanding and predicting interface diffusion phenomena in materials is crucial for various industrial applications, including semiconductor manufacturing, battery technology, and catalysis. In this study, we propose a novel approach…
In this paper, we propose a new regression-based algorithm to compute Graph Fourier Transform (GFT). Our algorithm allows different regularizations to be included when computing the GFT analysis components, so that the resulting components…
Graph sampling addresses the problem of selecting a node subset in a graph to collect samples, so that a K-bandlimited signal can be reconstructed in high fidelity. Assuming an independent and identically distributed (i.i.d.) noise model,…
Atomic Force Microscopy (AFM) in the tapping (intermittent contact) mode is a commonly used tool to measure the thickness of graphene and few layer graphene (FLG) flakes on silicon oxide surfaces. It is a convenient tool to quickly…
An extensive investigation of low frequency noise in single electron transistors as a function of gain is presented. Comparing the output noise with gain for a large number of bias points, it is found that the noise is dominated by external…
The mobility-degradation-based model for the drain-to-source or output resistance of a graphene field-effect-transistor is linearized here using a Taylor series approximation. This simplification is shown to be valid from magnitudes of the…
We study the photoresponse of graphene field effect transistors using scanning photocurrent microscopy in near and far field configurations, and we find that the response of graphene under a source-drain bias voltage away from the contacts…
Graph neural networks (GNNs) have demonstrated superior performance in collaborative recommendation through their ability to conduct high-order representation smoothing, effectively capturing structural information within users' interaction…