TRLUP – AI-Driven Biomass Intelligence: Unlocking High-Value Applications from Waste

Biomass, derived from a wide array of organic materials including agricultural residues (e.g., crop stalks, leaves, and fruit peels) and forestry residues (e.g., stumps, branches, and leaves), offers a scalable and renewable feedstock for developing sustainable bio-based products across the energy, materials, and environmental sectors. Through thermochemical conversion techniques, value-added
products such as biochar, bio-oil, and syngas can be generated from organic waste. These products have shown promising applications in areas such as contaminant adsorption and soil remediation. Developing suitable products for new applications or specific biomass types often requires long cycles of trial-and-error experimentation due to the complexity and variability of feedstocks and processing conditions. As a result, the efficient and targeted utilization of biomass remains a significant challenge. To address this, the project leverages cutting-edge AI techniques, particularly large language models, to develop a biomass-specific knowledge base aimed at identifying high-value utilization pathways and expanding viable application scenarios. This project seeks to revolutionize biomass utilization by building an intelligent knowledge system for biomass research and application through large language models. The primary objective is commercialization by embedding this intelligent system into digital tools or platforms that support biomass product recommendation, scenario-specific planning, and decision-making for industrial partners.

Faculty Supervisor:

Tyler Charlebois

Student:

Partner:

DMZ Ventures Inc

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Humber Institute of Technology and Advanced Learning

Program: