The DOI matches its Crossref record.
Instrumentation for trace detection of high explosives
Abstract
There is at present an urgent need for trace detection of high explosives, with applications to screening of people, packages, luggage, and vehicles. A great concern, because of recent terrorist activities, is for the development of methods that might allow detection and identification of explosives at a stand off distance. Nearly every analytical chemical method has been or is being applied to this problem. This review outlines the properties of explosives that might be utilized in detection schemes, discusses sampling issues, presents recent method developments with particular attention to detection limits, speed of analysis, and portability, and looks towards future developments.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Fluorescence based explosive detection: from mechanisms to sensory materials
Sun, X., Wang, Y., & Lei, Y. (2015) · Chemical Society Reviews · doi:10.1039/c5cs00496a · Cited by 1,243
Nanosensors for trace explosive detection
Senesac, L., & Thundat, T. G. (2008) · Materials Today · doi:10.1016/s1369-7021(08)70017-8 · Cited by 368
Paper-Based SERS Swab for Rapid Trace Detection on Real-World Surfaces
Lee, C. H., Tian, L., & Singamaneni, S. (2010) · ACS Applied Materials & Interfaces · doi:10.1021/am1009875 · Cited by 365
Khatua, S., Goswami, S., Biswas, S., Tomar, K., Jena, H. S., & Konar, S. (2015) · Chemistry of Materials · doi:10.1021/acs.chemmater.5b01773 · Cited by 258
Review of Gravimetric Sensing of Volatile Organic Compounds
McGinn, C. K., Lamport, Z. A., & Kymissis, I. (2020) · ACS Sensors · doi:10.1021/acssensors.0c00333 · Cited by 152
Metadata
- Authors
- Moore, D. S.
- Venue
- Review of Scientific Instruments
- Publisher
- AIP Publishing
- Published
- 2004-08-01
- Volume
- 75
- Issue
- 8
- Pages
- 2499-2512
- ISSN
- 0034-6748 (ISSN-L)
- 1089-7623
- OpenAlex
- W2027020123
- Cited by
- 812
- References
- 0
- FWCI
- 24.15
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Instrumentation for trace detection of high explosives. https://app.cochat.ai/papers/10.1063/1.1771493
- The paper
- Moore, D. S. (2004). Instrumentation for trace detection of high explosives. Review of Scientific Instruments. https://doi.org/10.1063/1.1771493
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
