Jose Cortes / Mathematics / Faculty Mentor: Andrzej Korzeniowski
Accurate soil carbon measurement is essential for sustainable agriculture and effective emission management. Traditional methods such as core harvesting followed by dry combustion provide precise results but are time-consuming, costly, and labor-intensive. This project explores a rapid, non-invasive alternative using Mobile Inelastic Neutron Scattering (MINS) technology, which detects soil carbon on-site by analyzing gamma radiation emitted from neutron interactions with carbon atoms.
We simulate the MINS process using the Monte Carlo Neutron Particle Simulator (MCNP6.2), modeling various soil mixtures with carbon concentrations ranging from 0% to 30%. Several data analysis methods were applied to interpret the resulting energy spectra, including classical approaches and advanced fitting techniques. Peak Fitting, particularly with a linear baseline, emerged as the most accurate method, achieving a mean squared error as low as 7.56 × 10⁻⁶, with predictions showing strong correlation to true carbon concentrations.
This study demonstrates the viability of MINS as a field-deployable tool for soil carbon assessment and sets the stage for further research under more complex conditions and varied neutron emission.
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