Best of the Week: Chewing Gum with SERS, Soil Carbon Analysis, Lithium-Ion Battery Research

This week, Spectroscopy published various articles that covered many topics in analytical spectroscopy. This week’s articles touch upon several important application areas such as environmental analysis and clinical diagnostics. Several key techniques are highlighted, including surface-enhanced Raman spectroscopy (SERS), diffuse reflectance spectroscopy (DRS), and near-infrared (NIR) spectroscopy. Below, we’ve highlighted some of the most popular articles, according to our readers and subscribers. Happy reading!

Evaluating Micro- and Nanoplastics from Chewing Gum with SERS

At Queen’s University Belfast, Cuong Cao and his team investigated microplastics (MPs) and nanoplastics (NPs) released from chewing gum base plastic. Using automated Raman spectroscopy for MPs and nanoparticle-on-film surface-enhanced Raman spectroscopy (NPoF SERS) for NPs, they demonstrated the potential of these techniques for detecting environmental pollutants (1). Coupled with handheld Raman instruments, this approach could serve as a portable, on-site screening tool (1). Their preliminary study highlights the versatility of these methods for pollutant analysis and environmental monitoring. Cao discussed this innovative work and its implications in a paper featured by Spectroscopy (1).

Advancing Soil Carbon Analysis Post-Wildfire with Spectroscopy and Machine Learning

Wildfires are fueled by natural and human causes. They are known to devastate ecosystems, destroy vegetation, and alter the soil organic carbon (SOC) (2). A study by the University of Oviedo explored post-wildfire SOC dynamics using diffuse reflectance spectroscopy (DRS) and machine learning (ML). DRS, a rapid, non-destructive technique, combined with ML, highlighted critical spectral regions, especially in the near-infrared (NIR) range, linked to SOC and clay content (2). Quantile random forest (QRF) emerged as the most effective algorithm for predicting stable SOC fractions (2). The integration of DRS with remote sensing technologies like drones and satellites offers scalable, cost-effective monitoring to improve wildfire management and environmental conservation.

New SERS-Microfluidic Platform Classifies Leukemia Using Machine Learning

Leukemia, a hematological cancer causing nearly 24,000 U.S. deaths annually, requires rapid, accurate subtype classification for effective treatment (3). Traditional diagnostic methods, like flow cytometry and PCR, lack speed and sensitivity. Researchers from Southeast University developed a novel platform combining SERS, machine learning (ML), and microfluidic chips (3). This compact system captures leukemia cells rapidly using aptamer-functionalized substrates, achieving up to 90% capture efficiency (3). SERS nanoprobes generated precise spectral data for phenotyping, whereas ML algorithms classified subtypes with 98.6% accuracy, reducing diagnostic time to under an hour (3). Though probe libraries and automation need further refinement, this platform offers a promising, cost-effective solution for precise, rapid leukemia diagnostics, with potential applications in other multi-subtype diseases.

Real-Time Monitoring of Zika Virus Vaccine Production Using NIR Spectroscopy

A recent study conducted by researchers at Universidade de São Paulo explores using near-infrared (NIR) spectroscopy to enhance the monitoring of Zika virus-like particle (VLP) vaccine production. VLP vaccines, which are hypoallergenic and non-infectious, are promising tools against Zika, a virus spread by Aedes mosquitoes that can cause severe birth defects (4). Using a recombinant baculovirus/Sf9 insect cell platform in bioreactors, the team combined NIR spectroscopy with partial least squares (PLS) and artificial neural networks (ANNs) for real-time, non-invasive analysis of critical bioprocess parameters (4). This approach improved precision and aligns with efforts to optimize vaccine production, offering hope for better responses to global health challenges.

Agilent Presents Awards to 3 Professors for Lithium-Ion Battery Research

Agilent Technologies awarded its 2025 Solutions Innovation Research Awards (SIRA) to Professors Anders Bentien (Aarhus University), Walter Gössler (University of Graz), and Gregory Offer (Imperial College London) for advancements in battery technology. Each received access to Agilent instruments to support their research. Bentien uses atomic spectroscopy to study flow battery systems, Gössler focuses on improving lithium-ion battery recycling, and Offer analyzes gas emissions to address battery degradation (5). Established in 2023, SIRA promotes impactful academic applications of Agilent’s products in energy storage and sustainability, showcasing the company’s commitment to advancing research in materials science and global energy challenges (5).

References

1. Chasse, J. Evaluating Micro- and Nanoplastics from Chewing Gum with SERS. Spectroscopy. Available at: https://www.spectroscopyonline.com/view/evaluating-micro--and-nanoplastics-from-chewing-gum-with-sers (accessed 2025-01-16).
2. Wetzel, W. Advancing Soil Carbon Analysis Post-Wildfire with Spectroscopy and Machine Learning. Spectroscopy. Available at: https://www.spectroscopyonline.com/view/advancing-soil-carbon-analysis-post-wildfire-with-spectroscopy-and-machine-learning (accessed 2025-01-16).
3. Workman, Jr., J. New SERS-Microfluidic Platform Classifies Leukemia Using Machine Learning. Spectroscopy. Available at: https://www.spectroscopyonline.com/view/new-sers-microfluidic-platform-classifies-leukemia-using-machine-learning (accessed 2025-01-16).
4. Wetzel, W. Real-Time Monitoring of Zika Virus Vaccine Production Using NIR Spectroscopy. Spectroscopy. Available at: https://www.spectroscopyonline.com/view/real-time-monitoring-of-zika-virus-vaccine-production-using-nir-spectroscopy (accessed 2025-01-16).
5. Wetzel, W. Agilent Presents Awards to 3 Professors for Lithium-Ion Battery Research. Spectroscopy. Available at: https://www.spectroscopyonline.com/view/agilent-presents-awards-to-3-professors-for-lithium-ion-battery-research (accessed 2025-01-16).