The DOI matches its Crossref record; 122 of the 122 references it cites were found in a registry or an index.
Portable Spectroscopy
Abstract
Until very recently, handheld spectrometers were the domain of major analytical and security instrument companies, with turnkey analyzers using spectroscopic techniques from X-ray fluorescence (XRF) for elemental analysis (metals), to Raman, mid-infrared, and near-infrared (NIR) for molecular analysis (mostly organics). However, the past few years have seen rapid changes in this landscape with the introduction of handheld laser-induced breakdown spectroscopy (LIBS), smartphone spectroscopy focusing on medical diagnostics for low-resource areas, commercial engines that a variety of companies can build up into products, hyphenated or dual technology instruments, low-cost visible-shortwave NIR instruments selling directly to the public, and, most recently, portable hyperspectral imaging instruments. Successful handheld instruments are designed to give answers to non-scientist operators; therefore, their developers have put extensive resources into reliable identification algorithms, spectroscopic libraries or databases, and qualitative and quantitative calibrations. As spectroscopic instruments become smaller and lower cost, “engines” have emerged, leading to the possibility of being incorporated in consumer devices and smart appliances, part of the Internet of Things (IOT). This review outlines the technologies used in portable spectroscopy, discusses their applications, both qualitative and quantitative, and how instrument developers and vendors have approached giving actionable answers to non-scientists. It outlines concerns on crowdsourced data, especially for heterogeneous samples, and finally looks towards the future in areas like IOT, emerging technologies for instruments, and portable hyphenated and hyperspectral instruments.
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“A detailed discussion on handheld Raman spectroscopy is outside the scope of this paper, and interested readers can learn more on this topic with this excellent review by Crocombe [21].”
BackgroundMethodInfluentialBeć, K. B., Grabska, J., & Huck, C. W. (2021) · Journal of Pharmaceutical and Biomedical Analysis · doi:10.1016/j.jpba.2020.113686 · Cited by 81
Multimodal Material Classification for Robots using Spectroscopy and High Resolution Texture Imaging
Erickson, Z., Xing, E., Srirangam, B., Chernova, S., & Kemp, C. C. (2020) · 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros45743.2020.9341165 · Cited by 50
Metadata
- Authors
- Crocombe, R. A.
- Venue
- Applied Spectroscopy
- Publisher
- SAGE Publications
- Published
- 2018-10-18
- Volume
- 72
- Issue
- 12
- Pages
- 1701-1751
- ISSN
- 0003-7028 (ISSN-L)
- 1943-3530
- OpenAlex
- W2897761855
- Cited by
- 532
- References
- 122
- FWCI
- 28.39
- Type
- journal article
- Language
- en
- Open access
- closed
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