Best of the Week: Reflecting on SciX 2025, Recent Research in Chemometrics and AI

This week, Spectroscopy published a variety of articles highlighting recent studies in several application areas. Key techniques highlighted in these articles include optical spectroscopy, chemometrics, artificial intelligence (AI), and scanning electron microscopy–energy dispersive spectroscopy (SEM-EDS). Happy reading!

One Month Later: Reflecting on the 2025 SciX Conference

The 2025 SciX Conference, which is organized by the Federation of Analytical Chemistry and Spectroscopy Societies (FACSS), was held in Covington, Kentucky, from October 5–10 this year. One of the main highlights from the conference was the presentation of the Emerging Leader in Molecular Spectroscopy Award to Lingyan Shi of the University of California, San Diego, for her work in optical spectroscopy and metabolic imaging (1). Shi’s plenary talk addressed her multimodal nanoscopy platform that combines Raman and fluorescence techniques to study cellular metabolism (1). This article also reflects on the various networking opportunities that students and professionals took advantage of at the conference, and how it fostered collaboration and inspiration across the analytical sciences community (1).

Recent Research in Chemometrics and AI for Spectroscopy, Part I: Foundations, Definitions, and the Integration of Artificial Intelligence in Chemometric Analysis

Recently, Spectroscopy executive editor Jerome Workman Jr. highlighted the recent research in chemometrics and AI for spectroscopy. Part I of this two-part series focused on the integration of AI in chemometric analysis, providing an overview of the key foundations in this space. Traditional chemometric methods, such as principal component analysis (PCA) and partial least squares (PLS) regression are now enhanced by machine learning (ML), deep learning, and generative AI, which automate feature extraction and handle nonlinear data (2). The review defines core AI concepts, model types, and data structures, emphasizing their roles in improving spectral analysis, prediction, and interpretability (2). Together, AI and chemometrics enable faster, more accurate, and data-driven chemical analysis across diverse scientific applications (2).

Recent Research in Chemometrics and AI for Spectroscopy, Part II: Emerging Applications, Explainable AI, and Future Trends

In Part II of his examination of recent research in chemometrics and AI for spectroscopy, Jerome Workman Jr. dives into how these tools are improving accuracy and interpretability across diverse applications. He discusses how innovations in explainable AI, generative modeling, and multimodal deep learning are key to advancing spectroscopic analyses (3). Meanwhile, AI platforms like SpectrumLab and SpectraML are crucial for standardization and reproducibility in AI-driven chemometrics (3). Future directions emphasize integrating large language models and physics-informed neural networks for automated spectral interpretation.

What are Ultrahot Jupiters? Insights from the JWST

A recent study published in Nature Astronomy by Navjot Kumar and colleagues at the Council of Scientific and Industrial Research (India) used the National Aeronautics and Space Administration (NASA)’s James Webb Space Telescope (JWST) to create the first three-dimensional spectroscopic map of exoplanet WASP-18b’s atmosphere (4). This “ultrahot Jupiter,” with temperatures exceeding 2000 °C, showed weaker temperature gradients than predicted, suggesting hydrogen dissociation and nightside clouds help redistribute heat. The map revealed a blazing hotspot rich in titanium and vanadium oxides and a cooler surrounding ring (4). These findings provide new insight into the chemical and thermal dynamics shaping the atmospheres of distant, extreme exoplanets.

New Insights into Corrosion Threats in Solar Panels

A new review published in the International Journal of Molecular Sciences by Felipe M. Galleguillos Madrid and colleagues from the Universidad de Antofagasta (Chile) examined how corrosion threatens solar panel performance and longevity (5). The study highlights the use of scanning electron microscopy–energy dispersive spectroscopy (SEM-EDS) to analyze corrosion at the microscopic level, revealing how moisture and contaminants damage photovoltaic materials. Corrosion decreases energy conversion efficiency, weakens structures, and raises maintenance costs. The authors emphasize developing anticorrosive nanocoatings, improved encapsulants, and AI-driven monitoring systems as crucial strategies for enhancing solar panel durability and ensuring a more sustainable renewable energy future.

References

1. Wetzel, W. One Month Later: Reflecting on the 2025 SciX Conference. Spectroscopy. Available at: https://www.spectroscopyonline.com/view/one-month-later-reflecting-on-the-2025-scix-conference (accessed 2025-11-6).
2. Workman, Jr., J. Recent Research in Chemometrics and AI for Spectroscopy, Part I: Foundations, Definitions, and the Integration of Artificial Intelligence in Chemometric Analysis. Spectroscopy. Available at: (accessed 2025-11-6).
3. Workman, Jr., J. Recent Research in Chemometrics and AI for Spectroscopy, Part II: Emerging Applications, Explainable AI, and Future Trends. Spectroscopy. Available at: https://www.spectroscopyonline.com/view/recent-research-in-chemometrics-and-ai-for-spectroscopy-part-ii-emerging-applications-explainable-ai-and-future-trends (accessed 2025-11-6).
4. Wetzel, W. What are Ultrahot Jupiters? Insights from the JWST. Spectroscopy. Available at: https://www.spectroscopyonline.com/view/what-are-ultrahot-jupiters-insights-from-the-jwst (accessed 2025-11-6).
5. Wetzel, W. New Insights into Corrosion Threats in Solar Panels. Spectroscopy. Available at: https://www.spectroscopyonline.com/view/new-insights-into-corrosion-threats-in-solar-panels (accessed 2025-11-6).