[HTML][HTML] Overview of emerging semiconductor device model methodologies: From device physics to machine learning engines

X Li, Z Wu, G Rzepa, M Karner, H Xu, Z Wu… - Fundamental …, 2024 - Elsevier
Advancements in the semiconductor industry introduce novel channel materials, device
structures, and integration methods, leading to intricate physics challenges when …

Machine learning-powered compact modeling of stochastic electronic devices using mixture density networks

J Hutchins, S Alam, DS Rampini, BG Oripov… - Scientific Reports, 2024 - nature.com
The relentless pursuit of miniaturization and performance enhancement in electronic
devices has led to a fundamental challenge in the field of circuit design and simulation-how …

Design Space Exploration for Threshold Switch Assisted Memristive Memory

S Alam, MM Islam, J Hutchins, N Cady… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Here we present a variation-aware design space analysis for threshold switch (TS) assisted
memristive memory. TS is augmented in series with the standard one-transistor one-resistor …

Hyperparameter Optimization on CNN Using Hyperband for Fault Identification in Wind Turbine High-Speed Shaft Gearbox Bearing

SM Gbashi, OO Olatunji, PA Adedeji… - … Computer and Energy …, 2023 - ieeexplore.ieee.org
Given the adverse operating regime of the wind turbine gearbox, fault recognition models for
components need to be optimized for reliable operation. However, selection of optimal …

Machine Learning Based Compact Model Design for Reconfigurable FETs

M Reuter, J Wilm, A Kramer… - IEEE Journal of the …, 2024 - ieeexplore.ieee.org
In integrated circuit design compact models are the abstraction layer which connects
semiconductor physics and circuit simulation. Established compact models like BSIM …

Reimagining Sense Amplifiers: Harnessing Phase Transition Materials for Current and Voltage Sensing

MM Islam, S Alam, MA Jahangir, GS Rose… - arXiv preprint arXiv …, 2023 - arxiv.org
Energy-efficient sense amplifier (SA) circuits are essential for reliable detection of stored
memory states in emerging memory systems. In this work, we present four novel sense …

Accelerating Machine Learning-Based Memristor Compact Modeling Using Sparse Gaussian Process

Y Shintani, M Inoue, M Shintani - 2024 Design, Automation & …, 2024 - ieeexplore.ieee.org
Research on dedicated circuits for multiply and accumulate processing, which is vital to
machine learning (ML), using memristors has attracted considerable attention. However …

Efficient nanoscale device modeling using artificial neural networks with TensorFlow and Keras libraries in Python

AK Singh, R Palanisamy, AK Jain - Signal Processing with Python …, 2024 - iopscience.iop.org
This chapter presents the potential approach of developing artificial neural networks (ANNs)
for the efficient modeling framework of multigate Field Effect Transistors (MuGFETs). The …

[PDF][PDF] Fundamental research

J Li, C ZHOU, R FENG, P HONG, T WANG… - Food and …, 2016 - researchgate.net
abstract Offshore carbon capture, utilization, and storage (CCUS) is to capture CO2 from
emission sources and then inject the captured CO2 into sub-seabed geological reservoirs …