Bio-inspired gas sensing: boosting performance with sensor optimization guided by “machine learning”

Abstract

We analyze the capabilities of natural and fabricated photonic three-dimensional nanostructures as sensors for the detection of different gaseous species.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jan 01, 2020
Source ID
10.1039/d0fd00035c

Entities

People

  • Andrei Kolmakov
  • Bing Cheng
  • J. Brewer
  • M. A. Carpenter
  • N. Houlihan
  • Radislav Potyrailo

Organizations

  • Defense Advanced Research Projects Agency
  • GE Global Research
  • National Energy Technology Laboratory
  • National Institute of Standards and Technology
  • SUNY Polytechnic Institute
  • United States Army

Tags

Fields of Study

  • Physics

Readers

  • Distributed Systems and Data Platform Development
  • Molecular Photonics/Laser Physics
  • Nanoscale Plasmonic Nanotechnology

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks
  • Microelectronics
  • Microelectronics - Microelectromechanical Systems