CALISO-ML – Calcium Isotope Analysis via Optical Spectroscopy and Machine Learning Data Analysis

• Applicant: Dr. Carlos Abad
• Subject Area: Analytical Chemistry
• Term: since 2025
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 567565274

Calcium (Ca) isotopes serve as powerful markers for comprehending geological, environmental, and biological processes. However, current analytical methods face technical challenges. This project aims to develop a novel machine learning-based approach for Ca isotope analysis utilizing high-resolution optical spectroscopy to study the intricate electronic spectra of diatomic calcium-containing molecules, CaX (X = H, F, Cl, Br, I). The project addresses the challenges of analyzing spectra with six stable calcium isotopes and one radioisotope and develops a new method to generate CaX molecules in situ, using the advantageous large isotopic shift caused by the respective change in the reduced mass. Simulations of the molecular spectra will provide higher precision, necessitating the measurement and prediction of molecular constants. Subsequently, a machine learning algorithm will be developed to deconvolute the CaX spectrum and achieve precise isotopic ratio determinations. CALISO-ML anticipates establishing a rapid, precise, and cost-effective method for calcium isotope analysis that minimizes matrix interferences, paving the way for broad applications in geology, environmental science, and medicine. Potential impact areas include probing constraints of paleoclimate, tracing calcium flux in ecosystems, unraveling calcium's essential biological functions in bone-related diseases, and nuclear waste management.

• DFG Programme: Research Grants
• International Connection: USA
• Co-Investigators: Dr. Kristin Vogel; Dr. Jochen Vogl
• Cooperation Partners: Professor Mitchio Okumura, Ph.D.; Professor Dr. Timothy C. Steimle; Professor Dr. Francois Tissot