Prediction of Statistical Distribution on Nanosheet FET by Geometrical Variability Using Various Machine Learning Models

Due to the aggressive scaling down of logic semiconductors, the difficulty of semiconductor component processes has increased. As the structure of components becomes more complex, the time and cost of processes and simulations have risen. Machine learning is now being used to analyze the electrical characteristics data of semiconductor components and apply the trained machine learning to next-generation semiconductor development. Machine learning trained on process data and simulation results can quickly and accurately predict which electrical characteristics change significantly when the component’s structure changes and which parameters have a significant impact on the electrical characteristic changes. This paper presents suitable machine learning models for analyzing and predicting the electrical characteristics (on-current ( $I_{on}$ ), off-current ( $I_{off}$ ), threshold voltage ( $V_{th}$ ), subthreshold swing (SS), and drain induced barrier lowering (DIBL)) and statistical distribution (mean and standard deviation of the electrical characteristics) resulting from geometrical variability (sheet thickness ( $T_{wire}$ ), sheet diameter ( $D_{wire}$ ), oxide thickness ( $T_{ox}$ ), gate length ( $L_{g}$ ), spacer length ( $L_{sp}$ ), gate metal work-function (WF)) in nanosheet field-effect transistor (NSFET), which are a next-generation logic device. Machine learning models, including regulation-based models (Ridge and LASSO) and tree-based models (decision tree (DT), random forest (RF), extreme gradient boost (XGBoost), and light gradient boost machine (LGBM)), are trained on technology computer-aided design (TCAD) simulation data. The LGBM more accurately predicts the electrical characteristics and statistical distribution of the NSFET than the other models. Additionally, we analyze the effect of geometrical variability on the NSFET based on feature importance

Output signals control of triboelectric nanogenerator with metal-dielectric-metal configuration through high resistance grounded systems

Toward a wide range of applications of triboelectric nanogenerator (TENG) as a power source, it is essential to develop a facile scheme to fabricate TENG with low output impedance by tuning the instantaneous output voltage without decreasing the output power. Here, we report a modified sliding-mode TENG, in which the flow of electrons between the grounded metal and the earth induces electric potential across a multilayered film consisting of dielectric/electrode/dielectric/electrode, confirmed by COMSOL simulation. By introducing a high resistance grounding method through the ground, the electron flow is slowed down, thereby decreasing the impedance at the maximum output power from 3 M omega to 0.6 M omega with an enhanced output power by two-fold, explained in terms of reduced charge loss. The new-type of the device makes the charging speed to a capacitor (1 mF) faster by more than two-fold. Based on this result, the generated output power from the rotating-type TENG is supplied to an electrochemical water-splitting system for hydrogen production. Results demonstrate that the applied voltage required to reach 40 mA/cm(2) is decreased to half of the initial voltage

Recent Advances in Triboelectric Nanogenerators: From Technological Progress to Commercial Applications.

Serious climate changes and energy-related environmental problems are currently critical issues in the world. In order to reduce carbon emissions and save our environment, renewable energy harvesting technologies will serve as a key solution in the near future. Among them, triboelectric nanogenerators (TENGs), which is one of the most promising mechanical energy harvesters by means of contact electrification phenomenon, are explosively developing due to abundant wasting mechanical energy sources and a number of superior advantages in a wide availability and selection of materials, relatively simple device configurations, and low-cost processing. Significant experimental and theoretical efforts have been achieved toward understanding fundamental behaviors and a wide range of demonstrations since its report in 2012. As a result, considerable technological advancement has been exhibited and it advances the timeline of achievement in the proposed roadmap. Now, the technology has reached the stage of prototype development with verification of performance beyond the lab scale environment toward its commercialization. In this review, distinguished authors in the world worked together to summarize the state of the art in theory, materials, devices, systems, circuits, and applications in TENG fields. The great research achievements of researchers in this field around the world over the past decade are expected to play a major role in coming to fruition of unexpectedly accelerated technological advances over the next decade

Recent advances in triboelectric nanogenerators: from technological progress to commercial applications

Serious climate changes and energy-related environmental problems are currently critical issues in the world. In order to reduce carbon emissions and save our environment, renewable energy harvesting technologies will serve as a key solution in the near future. Among them, triboelectric nanogenerators (TENGs), which is one of the most promising mechanical energy harvesters by means of contact electrification phenomenon, are explosively developing due to abundant wasting mechanical energy sources and a number of superior advantages in a wide availability and selection of materials, relatively simple device configurations, and low-cost processing. Significant experimental and theoretical efforts have been achieved toward understanding fundamental behaviors and a wide range of demonstrations since its report in 2012. As a result, considerable technological advancement has been exhibited and it advances the timeline of achievement in the proposed roadmap. Now, the technology has reached the stage of prototype development with verification of performance beyond the lab scale environment toward its commercialization. In this review, distinguished authors in the world worked together to summarize the state of the art in theory, materials, devices, systems, circuits, and applications in TENG fields. The great research achievements of researchers in this field around the world over the past decade are expected to play a major role in coming to fruition of unexpectedly accelerated technological advances over the next decade