2025 AIChE Annual Meeting

Analyzing the Effects of Particle Size and UV Irradiation on Industry-Specific Biochar for Methylene Blue Uptake, Via Camera-Based AI Models

This study examines the effect of particle size distribution and ultraviolet (UV) irradiation on industry-specific biochar, aiming to enhance its use as an adsorbent for the organic pollutant methylene blue. Biochar has the ability to uptake organic molecules for application in various fields. Biochar's high porosity, large surface area, and low price have garnered attention in fields such as agriculture, materials, energy, and environment. While biochar is known for its adsorption capabilities, the role of ultraviolet (UV) irradiation on industry-specific biochar for the uptake of pollutants has yet to be investigated. In this study, biochar was obtained from a wood milling company as a byproduct of renewable biomass processing. Such char was modified under UV irradiation and used in batch sorption studies. These studies examined the kinetics and equilibrium adsorption of methylene blue (MB) on pristine biochar with varying particle sizes and UV-modified biochar. The kinetics and equilibrium performance of pristine and UV-irradiated biochar in adsorbing methylene blue were evaluated using Langmuir and the Freundlich isotherm models, as well as pseudo-first and pseudo-second-order kinetic models. Biochar performance was compared with the performance of activated carbon, an analogous carbon-rich molecule, to gauge biochar's viability as a sustainable alternative. Notably, the study incorporates a novel approach by employing camera-based computations combined with artificial intelligence to create a model that can accurately predict the particle size and performance of specific biochars. This study found that Ultraviolet Irradiation of pristine biochar increased the average adsorption capabilities compared to untreated materials. Extended UV exposure may negatively affect morphology, causing a reduction in the uptake of methylene blue. Smaller particle sizes of biochar increase the overall available surface area of the sorbent and have a positive influence on the uptake of methylene blue. The employment of artificial intelligence achieved perfect binary size classification and a 78% accuracy for low, medium, and high adsorption classifications. The models show a strong baseline for future use of Artificial Intelligence as analytical devices.