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Recent Advances in Infrared Spectroscopy and Imaging as Sensing Techniques
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Recent Advances in Infrared Spectroscopy and Imaging as Sensing Techniques

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Optical Sensors".

Deadline for manuscript submissions: 25 July 2026 | Viewed by 4819

Special Issue Editors

Dr. Agnieszka Banas

E-Mail Website
Guest Editor
Singapore Synchrotron Light Source, National University of Singapore, 5 Research Link, Singapore 117603, Singapore
Interests: forensic applications of infrared spectroscopy, including post-blast explosives detection and the analysis of latent fingerprints to identify trace materials; application of sub-micron Optical Photothermal Infrared (O-PTIR) spectroscopy to the authentication of documents, paints, and artistic artifacts; investigation of food fraud using novel infrared-based techniques for label-free and objective classification of biological materials; FTIR, O-PTIR, AFM-IR, XAFS, SRIXE, and PIXE methods
Dr. Krzysztof Banas

E-Mail Website
Guest Editor
Singapore Synchrotron Light Source, National University of Singapore, 5 Research Link, Singapore 117603, Singapore
Interests: spectral and hyperspectral data processing; application of machine learning in spectroscopy; implementation of FAIR guiding principles for scientific data management; open science; application of spectroscopic techniques for the analysis and authentication of paints, gems, pigments, food and biological materials; Fourier Transform Infrared (FTIR) spectroscopy; Optical Photothermal Infrared (O-PTIR) spectroscopy; X-ray Fluorescence (XRF) spectroscopy and X-ray tomography

Special Issue Information

Dear Colleagues,

Infrared (IR) spectroscopy and imaging have proven to be indispensable tools across a broad range of scientific and industrial applications. This powerful technique has become a cornerstone in laboratories worldwide, facilitating critical advancements in materials analysis, biomedical diagnostics, environmental monitoring, and beyond.

We are pleased to invite you to contribute to a forthcoming Special Issue of Sensors, entitled “Recent Advances in Infrared Spectroscopy and Imaging as Sensing Techniques”. This Special Issue will focus on recent breakthroughs and innovative applications of IR spectroscopy and imaging technologies, particularly their role as sensing techniques in various fields.

We welcome original research articles, short communications, and comprehensive reviews that explore advances in the development and application of IR spectroscopy and imaging in areas including, but not limited to, the following:

  • Materials science and characterization;
  • Biomedical diagnostics and non-invasive sensing;
  • Environmental sensing and pollution monitoring;
  • Industrial process control and monitoring;
  • Emerging trends in hyperspectral and multispectral IR imaging;
  • Cultural heritage analysis and art objects authentication.

We invite you to submit your manuscript and share your latest research in this rapidly evolving field. All submissions will undergo rigorous peer review to ensure the highest standards of scientific quality and impact.

Dr. Agnieszka Banas
Dr. Krzysztof Banas
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

 

Keywords

  • infrared (IR) spectroscopy and imaging
  • O-PTIR
  • AFM-IR
  • materials science
  • biomedical applications
  • cultural heritage
  • forensics

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Published Papers (3 papers)

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Research

16 pages, 3246 KB  
Article
Chemical Heterogeneity Assessment of Authentic Edible Bird’s Nests Using Multimodal FTIR Spectroscopy: A Foundation for Future Authentication Strategies
by Dung Manh Ho, Agnieszka M. Banas, Krzysztof Banas, Utkarsh Mali and Mark B. H. Breese
Sensors 2026, 26(5), 1491; https://doi.org/10.3390/s26051491 - 27 Feb 2026
Viewed by 480
Abstract
Edible Bird’s Nest (EBN) is a highly prized food product, making it a frequent target for economic adulteration. Consequently, robust quality assurance is paramount to protect consumers and ensure market integrity. A significant barrier to effective quality control, however, is an incomplete understanding [...] Read more.
Edible Bird’s Nest (EBN) is a highly prized food product, making it a frequent target for economic adulteration. Consequently, robust quality assurance is paramount to protect consumers and ensure market integrity. A significant barrier to effective quality control, however, is an incomplete understanding of the natural chemical variability within authentic EBN. This variability, influenced by factors such as geographical origin, bird species, and post-harvest processing, can confound analytical measurements and complicate the definition of a standard reference. This study provides an existence proof in a defined cohort, characterizing microscale chemical heterogeneity in authentic A. fuciphagus EBN. We employed a multi-modal Fourier Transform Infrared (FTIR) spectroscopy approach, integrating transmission, macro-attenuated total reflectance (ATR), and high-resolution micro-ATR chemical imaging. A diverse set of validated, authentic EBN samples was analyzed using unsupervised Principal Component Analysis (PCA) to explore the data structure. Our results reveal significant and previously unquantified spectral heterogeneity, particularly in protein and glycoprotein-related regions. In our cohort, the chemical signatures of authentic EBN do not collapse to a single, uniform profile but span a broad, multi-dimensional continuum. This inherent variability presents a critical challenge for conventional quality control methods that rely on simplistic, single-spectrum standards, which may lead to the misclassification of genuine products. By establishing a robust chemical baseline for the authentic class, this work provides the foundational data essential for developing next-generation authentication models capable of reliably distinguishing this natural variance from deliberate adulteration. Full article
(This article belongs to the Special Issue Recent Advances in Infrared Spectroscopy and Imaging as Sensing Techniques)
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19 pages, 3515 KB  
Article
IR Spectroscopy as a Diagnostic Tool in the Recycling Process and Evaluation of Recycled Polymeric Materials
by Kaiyue Hu, Luigi Brambilla and Chiara Castiglioni
Sensors 2025, 25(19), 6205; https://doi.org/10.3390/s25196205 - 7 Oct 2025
Cited by 1 | Viewed by 2060
Abstract
Driven by environmental concerns and aligned with the principles of the circular economy, urban plastic waste—including packaging materials, disposable items, non-functional objects, and industrial scrap—is increasingly being collected, recycled, and marketed as a potential substitute for virgin polymers. However, the use of recycled [...] Read more.
Driven by environmental concerns and aligned with the principles of the circular economy, urban plastic waste—including packaging materials, disposable items, non-functional objects, and industrial scrap—is increasingly being collected, recycled, and marketed as a potential substitute for virgin polymers. However, the use of recycled polymers introduces uncertainties that can significantly affect both the durability and the further recyclability of the resulting products. This paper demonstrates how spectroscopic analysis in the mid-infrared (MIR) and near-infrared (NIR) regions can be applied well beyond the basic identification of the main polymeric component, typically performed during the sorting stage of recycling processes. A detailed interpretation of spectral data, based on well-established correlations between spectroscopic response and material structure, enables the classification of recycled polymers according to specific physicochemical properties, such as chemical composition, molecular architecture, and morphology. In this context, infrared spectroscopy not only provides a reliable comparison with the corresponding virgin polymer references but also proves particularly effective in assessing the homogeneity of recycled materials and the reproducibility of their properties—factors not inherently guaranteed due to the variability of input sources. As a case study, we present a robust protocol for determining the polypropylene content in recycled polyethylene samples. Full article
(This article belongs to the Special Issue Recent Advances in Infrared Spectroscopy and Imaging as Sensing Techniques)
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11 pages, 1211 KB  
Article
Simultaneous Classification of Objects with Unknown Rejection (SCOUR) Using Infra-Red Sensor Imagery
by Adam Cuellar, Daniel Brignac, Abhijit Mahalanobis and Wasfy Mikhael
Sensors 2025, 25(2), 492; https://doi.org/10.3390/s25020492 - 16 Jan 2025
Cited by 1 | Viewed by 1483
Abstract
Recognizing targets in infra-red images is an important problem for defense and security applications. A deployed network must not only recognize the known classes, but it must also reject any new or unknown objects without confusing them to be one of the known [...] Read more.
Recognizing targets in infra-red images is an important problem for defense and security applications. A deployed network must not only recognize the known classes, but it must also reject any new or unknown objects without confusing them to be one of the known classes. Our goal is to enhance the ability of existing (or pretrained) classifiers to detect and reject unknown classes. Specifically, we do not alter the training strategy of the main classifier so that its performance on known classes remains unchanged. Instead, we introduce a second network (trained using regression) that uses the decision of the primary classifier to produce a class conditional score that indicates whether an input object is indeed a known object. This is performed in a Bayesian framework where the classification confidence of the primary network is combined with the class-conditional score of the secondary network to accurately separate the unknown objects from the known target classes. Most importantly, our method does not require any examples of OOD imagery to be used for training the second network. For illustrative purposes, we demonstrate the effectiveness of the proposed method using the CIFAR-10 dataset. Ultimately, our goal is to classify known targets in infra-red images while improving the ability to reject unknown classes. Towards this end, we train and test our method on a public domain medium-wave infra-red (MWIR) dataset provided by the US Army for the development of automatic target recognition (ATR) algorithms. The results of this experiment show that the proposed method outperforms other state-of-the-art methods in rejecting the unknown target types while accurately classifying the known ones. Full article
(This article belongs to the Special Issue Recent Advances in Infrared Spectroscopy and Imaging as Sensing Techniques)
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