V
Vladislav Vashchenko
Researcher at National Semiconductor
Publications - 225
Citations - 1670
Vladislav Vashchenko is an academic researcher from National Semiconductor. The author has contributed to research in topics: Electrostatic discharge & Snapback. The author has an hindex of 18, co-authored 218 publications receiving 1637 citations. Previous affiliations of Vladislav Vashchenko include Texas Instruments & Katholieke Universiteit Leuven.
Papers
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Proceedings ArticleDOI
Accelerated aging system for prognostics of power semiconductor devices
TL;DR: In this article, an accelerated aging system for gate-controlled power transistors is presented for the understanding of the effects of failure mechanisms, and the identification of leading indicators of failure which are essential in the development of physics-based degradation models and RUL prediction.
Journal ArticleDOI
High holding voltage cascoded LVTSCR structures for 5.5-V tolerant ESD protection clamps
TL;DR: In this paper, a new design concept for the control of the holding voltage of LVTSCR ESD protection structures by realizing a negative feedback in the p emitter is presented.
Proceedings ArticleDOI
Accelerated aging with electrical overstress and prognostics for power MOSFETs
TL;DR: In this paper, a prognostics-based health management of power MOSFETs undergoing accelerated aging through electrical overstress at the gate area is presented, and a prognostic algorithm for prediction of the future state of health of the device is presented.
Patent
Laser powered clock circuit with a substantially reduced clock skew
TL;DR: A synchronous clock signal is generated in a large number of local clock circuits at the same time by exposing photoconductive regions in each local clock circuit to a pulsed light source that operates at a fixed frequency as mentioned in this paper.
Proceedings ArticleDOI
Prognostics of power MOSFET
TL;DR: In this paper, the authors demonstrate how to apply prognostics to power MOSFETs (metal oxide field effect transistor) by using thermal cycling to age devices and Gaussian process regression.