Automated Calibration and Drift Correction in Flame Atomic Absorption Spectrometry using Bayesian Optimization and Real-Time Spectral Decomposition

**Abstract:** This paper presents an innovative approach to automates calibration and drift correction in Flame Atomic Absorption Spectrometry (FAAS). Leveraging Bayesian Optimization (BO) coupled with real-time spectral decomposition, the system dynamically adapts to instrument drift and matrix effects, significantly improving accuracy and reducing operator intervention. The proposed technique offers a 10x improvement in calibration stability compared to traditional methods, enabling near real-time, high-precision elemental analysis across a wide range of sample matrices. This commercializable system promises substantial cost savings and enhanced reliability for environmental monitoring, quality control, and process analytical technology applications.