Before circuit design can begin on any advanced semiconductor manufacturing process, the electrical behavior of the devices — transistors, diodes, resistors — must be described accurately in so-called ...

Accurate models of scattering and noise parameters of transistors are instrumental in facilitating design procedures of microwave devices such as low-noise amplifiers. Yet, data-driven modeling of ...

Spiking neural networks (SNNs) have immense potential due to their utilization of synaptic plasticity and ability to take advantage of temporal correlation and low power consumption. The leaky ...

A tandem neural network capable of inferring key physical parameters of semiconductor materials from simple transistor measurements has been developed, as reported by researchers from the Institute of ...

The T2B transistor to behavioral conversion software is suitable for analyzing combined signal and power integrity effects in today’s high-speed designs. It is important technology because, according ...

Field-effect transistors are key components of sensors, electrical circuits, or data storage devices. The transistors used to date have been mainly based on inorganic semiconductors such as silicon.

A new technical paper, “A Device-Physics-Informed Artificial Neural Network Approach for Thermal-Aware I-V and C-V Modeling of GAA FETs,” was published by researchers at National Yang Ming Chiao Tung ...

Models are critical for IC design. Without them, it’s impossible to perform analysis, which in turn limits optimizations. Those optimizations are especially important as semiconductors become more ...

NVIDIA CUDA-X libraries and AI models are accelerating TSMC workloads across lithography, transistor and process simulation, advanced process control and fab operations optimization. TSMC is using ...