Related papers: Dissertation Machine Learning in Materials Science…
Carbon Nanotube (CNT) appears as a promising candidate to shrink field-effect transistors (FET) to the nanometer scale. Extensive experimental works have been performed recently to develop the appropriate technology and to explore DC…
Carbon nanotube field-effect transistors (CNT FETs) have been proposed as possible building blocks for future nano-electronics. But a challenge with CNT FETs is that they appear to randomly display varying amounts of hysteresis in their…
A new DC thermal model of Carbon Nanotube Field Effect Transistors (CNTFETs) is proposed. The model is based on a number of fitting parameters depending on bias conditions by third order polynomials. The model includes three thermal…
Carbon nanotube field-effect transistors (CNFETs) are promising candidates for building energy-efficient digital systems at highly-scaled technology nodes. However, carbon nanotubes (CNTs) are inherently subject to variations that reduce…
Three-terminal devices with conduction channels formed by quasi-metallic carbon nanotubes (CNT) are shown to operate as nanotube-based field-effect transistors under strong magnetic fields. The off-state conductance of the devices varies…
We present a data-calibrated compact model of carbon nanotube (CNT) field-effect transistors (CNFETs) including contact resistance, direct source-to-drain and band-to-band tunneling currents. The model captures the effects of dimensional…
We presents a data-calibrated compact model of carbon nanotube (CNT) field-effect transistors (CNFETs) based on the virtual-source (VS) approach, describing the intrinsic current-voltage and charge-voltage characteristics. The features of…
Carbon nanotube field-effect transistor (CNTFET) refers to a field-effect transistor that utilizes a single carbon nanotube or an array of carbon nanotubes as the channel material instead of bulk silicon in the traditional MOSFET structure.…
We report density-functional theory (DFT), atomistic simulations of the non-equilibrium transport properties of carbon nanotube (CNT) field-effect transistors (FETs). Results have been obtained within a self-consistent approach based on the…
Efficient and controlled charge transport in networks of semiconducting single-walled carbon nanotubes is the basis for their application in electronic devices, especially in field-effect transistors and thermoelectrics. The recent advances…
We present a pipeline for predicting mechanical properties of vertically-oriented carbon nanotube (CNT) forest images using a deep learning model for artificial intelligence (AI)-based materials discovery. Our approach incorporates an…
Tensile tests at room temperature are performed using molecular dynamics on all configurations of single-walled carbon nanotubes up to 4 nm in diameter. Distributions of the Young's modulus, Poisson's ratio, ultimate tensile strength and…
We perform systematic numerical simulations for carbon nanotube (CNT) film microstrip antennas to fabricate flexible and durable applications in terms of various device design parameters. The selection of appropriate materials for…
A fresh look on carbon-based transistor channel materials like single-walled carbon nanotubes (CNT) and graphene nanoribbons (GNR) in future electronic applications is given. Although theoretical predictions initially promised that GNR…
In this work, we simulate the expected device performance and the scaling perspectives of Carbon nanotube Field Effect Transistors (CNT-FETs), with doped source and drain extensions. The simulations are based on the self-consistent solution…
In this study, we propose Explainable Multimodal Machine Learning (EMML), which integrates the analysis of diverse data types (multimodal data) using factor analysis for feature extraction with Explainable AI (XAI), for carbon nanotube…
Carbon nanotubes (CNTs - long tubular carbon nanostructures) belong to the best electron field emitting materials. Based on the experimentally determined electron density in the dual hot filament/DC plasma deposition system the electric…
We develop new transfer learning algorithms to accelerate prediction of material properties from ab initio simulations based on density functional theory (DFT). Transfer learning has been successfully utilized for data-efficient modeling in…
Owing to their distinct properties, carbon nanotubes (CNTs) have emerged as promising candidate for field emission devices. It has been found experimentally that the results related to the field emission performance show variability. The…
Carbon fiber and graphene-based nanostructures such as carbon nanotubes (CNTs) and defective structures have extraordinary potential as strong and lightweight materials. A longstanding bottleneck has been lack of understanding and…