tag: UNSW Sydney

Technical Paper Roundup: November 21
By Liz Allan - 21 Nov, 2023 - Comments: 0

New technical papers recently added to Semiconductor Engineering’s library: [table id=167 /] More Reading Technical Paper Library home » read more

High-Speed Sparse Scanning Kelvin Probe Force Microscopy
By Technical Paper Link - 14 Nov, 2023 - Comments: 0

A technical paper titled “High-speed mapping of surface charge dynamics using sparse scanning Kelvin probe force microscopy” was published by researchers at Oak Ridge National Laboratory, (ORNL), Sungkyunkwan University, Case Western Reserve University, Flinders University, Bedford Park, and UNSW Sydney. Abstract: "Unraveling local dynamic charge processes is vital for progress in diverse... » read more

Week In Review: Design, Low Power
By Jesse Allen - 20 Jan, 2023 - Comments: 0

Worldwide semiconductor revenue increased 1.1% in 2022 to $601.7 billion, up from $595 billion in 2021, according to preliminary results from Gartner. The combined revenue of the top 25 semiconductor vendors increased 2.8% in 2022 and accounted for 77.5% of the market. The memory segment posted a 10% revenue decrease. Analog showed the strongest growth, up 19% from 2021, followed by discretes, ... » read more

Week In Review: Manufacturing, Test
By Karen Heyman - 24 Jun, 2022 - Comments: 0

Notes from the fabs Intel warned the “scope and pace" of the Ohio fab buildout could be impacted due to U.S. Congress’ inaction on funding the $52 billion CHIPS Act. The facility was announced in January with an initial phase investment of more than $20 billion with a larger expansion up to $100 billion over the next decade. The initial phase is not expected to be impacted, other than a de... » read more

Improving Machine Learning-Based Modeling of Semiconductor Devices by Data Self-Augmentation
By Technical Paper Link - 24 Mar, 2022 - Comments: 0

Abstract: "In the electronics industry, introducing Machine Learning (ML)-based techniques can enhance Technology Computer-Aided Design (TCAD) methods. However, the performance of ML models is highly dependent on their training datasets. Particularly in the semiconductor industry, given the fact that the fabrication process of semiconductor devices is complicated and expensive, it is of grea... » read more

  • Sponsors

About

Navigation

Connect With Us

Copyright ©2013-2024 SMG   |  Terms of Service  |  Privacy Policy