scispace - formally typeset
X

Xiao Wu

Researcher at University of Michigan

Publications -  18
Citations -  179

Xiao Wu is an academic researcher from University of Michigan. The author has contributed to research in topics: Capacitor & Charge pump. The author has an hindex of 5, co-authored 16 publications receiving 106 citations.

Papers
More filters
Journal ArticleDOI

A 20-pW Discontinuous Switched-Capacitor Energy Harvester for Smart Sensor Applications

TL;DR: Based on the key observation that energy source efficiency is higher than charge pump efficiency, this work presents a discontinuous harvesting technique that decouples the two efficiencies for a better tradeoff and achieves >40% end-to-end efficiency.
Proceedings ArticleDOI

A 0.04MM 3 16NW Wireless and Batteryless Sensor System with Integrated Cortex-M0+ Processor and Optical Communication for Cellular Temperature Measurement

TL;DR: This paper demonstrates a complete wireless sensor node for accurate cellular temperature measurement that includes a fully programmable Cortex-M0+ processor, custom SRAM, optical energy harvesting, 2-way communication, and a subthreshold temperature sensor.
Proceedings ArticleDOI

5.2 Energy-Efficient Low-Noise CMOS Image Sensor with Capacitor Array-Assisted Charge-Injection SAR ADC for Motion-Triggered Low-Power IoT Applications

TL;DR: This work adopts motion-detection triggering of full-array capture where MD is performed on a heavily subsampled frame to enable continuous low-power operation and addresses the full-frame capture energy itself needs to be addressed.
Journal ArticleDOI

Energy-Efficient Motion-Triggered IoT CMOS Image Sensor With Capacitor Array-Assisted Charge-Injection SAR ADC

TL;DR: A low-power image sensor with a motion-based triggering feature for the Internet of Things (IoT) applications and a column-parallel capacitor array-assisted charge-injection SAR ADC that achieves 10b operation with readout noise of 226 is proposed.
Proceedings ArticleDOI

IoT 2 — the Internet of Tiny Things: Realizing mm-Scale Sensors through 3D Die Stacking

TL;DR: The challenges and solutions to 3D-stacked mm-scale design are surveyed, highlighting low-power circuit issues ranging from low- power SRAM and miniature neural network accelerators to radio communication protocols and analog interfaces.