Best of the Week: Hyperspectral Imaging, Spaceborne Biomarkers, FT-IR Microscopy
Top articles published this week include an article on classifying space debris, a report on a new fiber-dispersive Raman spectrometer, and an examination of Fourier transform infrared (FT-IR) microscopy.
This week, Spectroscopy published various articles that covered many topics in analytical spectroscopy. This week’s articles feature techniques including hyperspectral imaging, Raman spectroscopy, FT-IR microscopy, and atomic spectroscopic techniques. Below, we’ve highlighted some of the most popular articles, according to our readers and subscribers. Happy reading!
In the latest “Chemometrics of Spectroscopy” column, Jerome Workman, Jr. and Howard Mark discuss the development of an expert calibration system (ECS) for spectroscopic-based process analytical chemistry. The ECS would automate the creation of high-quality calibration models, reducing the need for extensive chemometrics knowledge while leveraging users' domain expertise (1). By offering automated tools and guidance, ECS aims to streamline the calibration process, improve calibration transfer, enhance operator efficiency, and ensure consistent, reliable analytical results (1). This concept revisits discussions from nearly three decades ago, highlighting the potential impact of ECS on modern analytical chemistry practices (1).
This article examines global trends in critical raw materials (CRM) research and the role of atomic spectroscopy (AS) techniques—such as ICP-MS, ICP-OES, and X-ray analysis—in identifying and quantifying CRMs in complex industrial and environmental matrices. It highlights the challenges of CRM recovery from sources like rare earth elements (REEs) in water leaching residues, coal fly ash, acid mine drainage, and platinum-group elements in sewage sludge (2). The article also reviews the effectiveness of various AS techniques throughout the CRM recovery process and addresses current challenges and solutions in these analytical methods (2).
A New Methodology for Identifying and Classifying Space Debris
This article discusses a study published in Scientific Reports that investigates the use of hyperspectral imaging (HSI) for classifying objects in increasingly crowded outer space. Conducted by Massimiliano Vasile and his team at the University of Strathclyde, the research focuses on analyzing hyperspectral signatures to determine the material composition of space objects (3). The study combines machine learning with least-squares matching to address challenges such as material weathering and gaps in spectral libraries, highlighting HSI's potential for improving space object identification and the need for further validation (3).
New Fiber-Dispersive Raman Spectrometer Breaks Ground in Spaceborne Biomarker Detection
In a recent study, researchers from Humboldt-Universität zu Berlin and the German Aerospace Center (DLR) demonstrated a new way to detect low-density biological matter in space. By using an advanced fiber-dispersive Raman spectrometer (FDRS), scientists can seek to find out new information about the possibility of extraterrestrial life (4). This FDRS uses a single-photon detector and a dispersive optical fiber element, marking a significant improvement in in-situ Raman spectroscopy with enhanced sensitivity and reliability (4).
FT-IR Microscopy: Sampling by Transmission
This article discusses the three primary approaches in Fourier transform infrared (FT-IR) microscopy: transmission, reflection, and attenuated total reflectance (ATR). It emphasizes the importance of proper sample preparation, especially for transmission microscopy, where sample thickness is critical (5). The article explains the Beer-Lambert Law, which relates sample absorption to thickness, and the potential issues of over-absorption in spectral analysis (5). Techniques for preparing thin samples, including the use of salt windows, compression cells, and epoxy mounting, are detailed to ensure accurate data collection (5).
References
(1) Workman, Jr., J. Are We There Yet? Is There Such a Thing as an Expert Calibration System for Vibrational Spectroscopy? Spectroscopy 2024, 39 (6), 12–14, 30.
(2) Thomas, G. The Application of Atomic Spectroscopy Techniques in the Recovery of Critical Raw Materials from Industrial Waste Streams, Part II. Spectroscopy 2024, 39 (6), 8–11.
(3) Wetzel, W. A New Methodology for Identifying and Classifying Space Debris. Spectroscopy. Available at: https://www.spectroscopyonline.com/view/a-new-methodology-for-identifying-and-classifying-space-debris (accessed 2024-08-22).
(4) Workman, Jr., J. New Fiber-Dispersive Raman Spectrometer Breaks Ground in Spaceborne Biomarker Detection. Spectroscopy. Available at: https://www.spectroscopyonline.com/view/new-fiber-dispersive-raman-spectrometer-breaks-ground-in-spaceborne-biomarker-detection (accessed 2024-08-22).
(5) Bradley, M. S. FT-IR Microscopy: Sampling by Transmission. Spectroscopy 2024, 39 (6), 22–24.
Artificial Intelligence Accelerates Molecular Vibration Analysis, Study Finds
July 1st 2025A new review led by researchers from MIT and Oak Ridge National Laboratory outlines how artificial intelligence (AI) is transforming the study of molecular vibrations and phonons, making spectroscopic analysis faster, more accurate, and more accessible.
Toward a Generalizable Model of Diffuse Reflectance in Particulate Systems
June 30th 2025This tutorial examines the modeling of diffuse reflectance (DR) in complex particulate samples, such as powders and granular solids. Traditional theoretical frameworks like empirical absorbance, Kubelka-Munk, radiative transfer theory (RTT), and the Hapke model are presented in standard and matrix notation where applicable. Their advantages and limitations are highlighted, particularly for heterogeneous particle size distributions and real-world variations in the optical properties of particulate samples. Hybrid and emerging computational strategies, including Monte Carlo methods, full-wave numerical solvers, and machine learning (ML) models, are evaluated for their potential to produce more generalizable prediction models.
Polystyrene and UVC Sterilization Tested with Spectroscopy and Luminescence Tools
June 25th 2025A team of researchers from Spanish institutions has found that polystyrene used in healthcare packaging shows strong resistance to UVC sterilization, with minimal chemical degradation detected using FT-IR and Raman spectroscopy.
