Evidence map›Paper›PMID 40657199›Full record

ReviewSmall science2025

Advances in MEMS, Optical MEMS, and Nanophotonics Technologies for Volatile Organic Compound Detection and Applications.

Dongxiao Li, Hong Zhou, Zhihao Ren, Chengkuo Lee

Abstract readReview
In one paragraph

Review in Small science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. A Generative AI-Assisted Piezo-MEMS Ultrasound Device for Plant Dehydration Monitoring.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
  6. Article
  7. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Dongxiao LiDepartment of Electrical and Computer Engineering National University of Singapore Singapore 117583 Singapore.
Hong ZhouDepartment of Electrical and Computer Engineering National University of Singapore Singapore 117583 Singapore.
Zhihao RenDepartment of Electrical and Computer Engineering National University of Singapore Singapore 117583 Singapore.
Chengkuo LeeDepartment of Electrical and Computer Engineering National University of Singapore Singapore 117583 Singapore.ORCID https://orcid.org/0000-0002-8886-3649

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Volatile organic compounds (VOCs) are a class of organic compounds with high vapor pressure and low boiling points, widely present in both natural environments and human activities. VOCs released from various sources not only contribute to environmental pollution but also pose threats to ecosystems and human health. Moreover, some VOCs are considered biomarkers in exhaled breath and can be utilized to identify various diseases. Therefore, monitoring and controlling VOC emissions and concentrations are crucial for safeguarding the environment and human health. In recent years, significant advancements have been achieved in micro-electromechanical system (MEMS)-based sensing and optical sensing technologies, offering new avenues for VOC detection. This article provides a comprehensive overview of research progress in MEMS and optical VOC sensors, focusing on their sensing mechanisms and classifications. It then discusses the role of artificial intelligence in enhancing VOC identification and quantification, as well as trends toward sensor miniaturization and intelligence. Furthermore, the article highlights the diverse applications of VOC sensors in medical diagnostics, agricultural food testing, and the Internet of Things. Finally, it emphasizes the opportunities and challenges associated with MEMS and optical VOC sensors, providing valuable insights for practical applications.

Indexed as

artificial intelligenceelectronic nosehealthInternet of Thingsphotonic nosesensorsvolatile organic compounds

Identifiers

PMID40657199
PMCPMC12245038

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.