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Steve To

dblp:116/6495 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2012
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Robot manipulation · 100%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Electronic design automation · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation › micro/nano manipulation
nanomanipulation
0.112012
Automated nanomanipulation for nano device construction · ICRA 2012
Electronic design automation
nanofabrication
0.012012
Automated nanomanipulation for nano device construction · ICRA 2012

Methods — techniques the papers use, named apart from their topics

scanning electron microscope manipulation · 0.3nanowire contact printing · 0.3
YearPublicationVenuePosition
2012 Automated nanomanipulation for nano device construction
abstract
Nanowire field-effect transistors (nano-FETs) are nano devices capable of highly sensitive, label-free sensing of molecules. However, significant variations in sensitivity across devices can result from poor control over device parameters, such as nanowire diameter and the number of electrode-bridging nanowires. This paper presents a fabrication approach that uses wafer-scale nanowire contact printing for throughput and uses automated nanomanipulation for precision control of nanowire number and diameter. The process requires only one photolithography mask. Using nanowire contact printing and post processing (i.e., nanomanipulation inside scanning electron microscope), we are able to produce devices all with a single nanowire and similar diameters at a speed of ∼1 min/device with a success rate of 95% (n=500). This technology represents a seamless integration of wafer-scale microfabrication and automated nanorobotic manipulation for producing nano-FET sensors with consistent response across devices.
Yan Liang Zhang, Jason H. Li, Steve To, Yong Zhang 0046, Xutao Ye, Yu Sun 0001
ICRA3