Evaluation and Selection of Materials for Particulate Matter MEMS Sensors by Using Hybrid MCDM Methods

Chi Yo Huang, Pei-Han Chung, Joseph Z. Shyu, Yao-Hua Ho, Chao- Hsin Wu, Ming-Che Lee, Ming-Jenn Wu

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Air pollution poses serious problems as global industrialization continues to thrive. Since air pollution has grave impacts on human health, industry experts are starting to fathom how to integrate particulate matter (PM) sensors into portable devices; however, traditional micro-electro-mechanical systems (MEMS) gas sensors are too large. To overcome this challenge, experts from industry and academia have recently begun to investigate replacing the traditional etching techniques used on MEMS with semiconductor-based manufacturing processes and materials, such as gallium nitride (GaN), gallium arsenide (GaAs), and silicon. However, studies showing how to systematically evaluate and select suitable materials are rare in the literature. Therefore, this study aims to propose an analytic framework based on multiple criteria decision making (MCDM) to evaluate and select the most suitable materials for fabricating PM sensors. An empirical study based on recent research was conducted to demonstrate the feasibility of our analytic framework. The results provide an invaluable future reference for research institutes and providers.
Original languageEnglish
Article number3451
JournalSustainability
Volume10
Issue number10
DOIs
StatePublished - 27 Sep 2018

Keywords

  • particulate matter (PM); PM2.5; sensors; micro electro mechanic systems (MEMS); multiple criteria decision making (MCDM)
  • DECISION-MAKING METHODS; TECHNOLOGY-ASSESSMENT; GALLIUM NITRIDE; POLICY; INFORMATION; MANAGEMENT; SYSTEMS; MODEL; GAAS; CONSEQUENCES

Fingerprint Dive into the research topics of 'Evaluation and Selection of Materials for Particulate Matter MEMS Sensors by Using Hybrid MCDM Methods'. Together they form a unique fingerprint.

Cite this