Integrated machine learning and laser spectral analysis of penny composition across the 20th century

Using Laser-Induced Breakdown Spectroscopy (LIBS) as an analytical tool coupled with a Nd:YAG 1064 laser, the presence of metals in circulated (1934-1958 & 2005-2014) and uncirculated mint-condition pennies (1970-2009) can be determined. When analyzing metal composition, excited metal atoms and ions (e.g. Cu) in LIBS spectra can be identified. Using Machine Learning (ML) algorithms, a set of atomic emission peaks were compiled to identify specific metals in sample pennies. Discrepancies between the metal content in empirical data and the theoretical values reported by the US Mint may indicate socioeconomic conditions of various historical eras. Integrating LIBS and ML, this research project recruits high school students for hands-on learning at the intersection of physics, chemistry, data science, history, and socioeconomics.