Best of the Week: Two-Step Neural Model, the 78th International Symposium on Molecular Spectroscopy

This week, Spectroscopy published articles highlighting recent studies in several application areas in analytical spectroscopy, including biomedicine, astrochemistry, and agriculture. Key techniques highlighted in these articles include discrete frequency infrared (IR) imaging terahertz (THz) spectroscopy. Happy reading!

Describing Their Two-Step Neural Model: An Interview with Ayanjeet Ghosh and Rohit Bhargava

In this Q&A interview, Professors Ayanjeet Ghosh and Rohit Bhargava discuss their recent study introducing a two-step regressive neural network model that enhances discrete frequency infrared (IR) imaging for biomedical applications. Featured in Applied Spectroscopy, the model uses just seven wavenumbers to reconstruct high-resolution spectra and predict protein structures in tissue, outperforming traditional methods like PCA in both speed and interpretability (1). In this interview segment, Ghosh and Bhargava explain how machine learning (ML) improves data analysis and scalability, particularly in studying neurodegenerative diseases (1). This approach marks a significant advancement in IR imaging, enabling faster, more efficient tissue characterization for biomedical research.

Previewing the 78th International Symposium on Molecular Spectroscopy

The 78th International Symposium on Molecular Spectroscopy (ISMS) will be held June 23–27, 2025, at the University of Illinois Urbana-Champaign. This annual conference unites researchers, spectroscopists, and professionals to explore advancements in molecular spectroscopy (2). ISMS 2025 will feature plenary talks, six daily parallel sessions, Lunch-n-Learn events, and themed mini-symposia on astrochemistry, multidimensional spectroscopy, and large molecular clusters (2). Networking events include mixers, receptions, and a picnic, with dedicated gatherings for women and LGBTQIA+ attendees.

How THz and THz-Raman Spectroscopy Are Used in Drug Safety, Farming, and Mining

A new review article published in Optics & Laser Technology by researchers from IIT Delhi and the University of Queensland explores how Terahertz (THz) and low-wavenumber Raman spectroscopy are improving several key industries, including agriculture, drug analysis, and mining. These non-destructive techniques enhance pharmaceutical quality control by identifying molecular structures and polymorphs, optimize agriculture through precise crop and soil analysis, and improve mineral identification in mining (3). THz and THz-Raman spectroscopy offer complementary insights by probing electric fields and scattered photons, respectively, for deeper material analysis (3). Their article highlights the growing global interest in THz spectroscopy, which is becoming more common in scientific research and is being used more frequently (3). The authors advocate for integrated approaches and further research to unlock these tools’ full potential across sectors (3).

New Deep Learning AI Tool Decodes Minerals with Raman Spectroscopy

In a recent study, Chinese scientists have developed a deep learning model, DA-ConvLSTM, that enables fast, accurate mineral identification from Raman spectroscopy data (4). This new deep learning model, which was created by researchers at Zhejiang University and affiliated institutions, processes complex spectral information using dual-attention and memory mechanisms. It outperforms traditional methods, even with mixed or natural rock samples, and it is designed to improve transparency with Grad-CAM++ visualizations (4). This AI tool automates routine analysis, aiding decision-making in laboratories and planetary missions (4). The breakthrough promises smarter, autonomous field instruments and advances in geoscience and space exploration through the integration of AI and spectroscopy.

Multi-Analytical Study Reveals Complex History Behind Ancient Snake Motif in Argentine Rock Art

A recent study published in the Journal of Archaeological Science: Reports used scanning electron microscopy–energy dispersive X-ray spectroscopy (SEM-EDS) and micro-Raman spectroscopy to analyze a multi-headed snake painting at Argentina’s La Candelaria rock shelter. Once thought to be a singular image, microscopic and macroscopic analysis revealed three distinct painting events, suggesting the motif evolved over time (5). This challenges traditional interpretations of rock art as static and emphasizes the importance of combining field observations with advanced laboratory techniques (5). The study proposes that ancient imagery may reflect ongoing human interaction and reinterpretation, offering new insights into the cultural, spiritual, and social significance of prehistoric rock art (5).

References

1. Wetzel, W. Describing Their Two-Step Neural Model: An Interview with Ayanjeet Ghosh and Rohit Bhargava. Spectroscopy. Available at: https://www.spectroscopyonline.com/view/describing-their-two-step-neural-model-an-interview-with-ayanjeet-ghosh-and-rohit-bhargava (accessed 2025-05-20).
2. Wetzel, W. Previewing the 78th International Symposium on Molecular Spectroscopy. Spectroscopy. Available at: https://www.spectroscopyonline.com/view/previewing-the-78th-international-symposium-on-molecular-spectroscopy (accessed 2025-05-20).
3. Workman, Jr., J. How THz and THz-Raman Spectroscopy Are Used in Drug Safety, Farming, and Mining. Spectroscopy. Available at: https://www.spectroscopyonline.com/view/how-thz-and-thz-raman-spectroscopy-are-used-in-drug-safety-farming-and-mining (accessed 2025-05-20).
4. Workman, Jr., J. New Deep Learning AI Tool Decodes Minerals with Raman Spectroscopy. Spectroscopy. Available at: https://www.spectroscopyonline.com/view/new-deep-learning-ai-tool-decodes-minerals-with-raman-spectroscopy (accessed 2025-05-20).
5. Workman, Jr., J. Multi-Analytical Study Reveals Complex History Behind Ancient Snake Motif in Argentine Rock Art. Spectroscopy. Available at: https://www.spectroscopyonline.com/view/multi-analytical-study-reveals-complex-history-behind-ancient-snake-motif-in-argentine-rock-art (accessed 2025-05-20).