The Need

Rare earth elements (REEs) are essential for advanced manufacturing, energy technologies, electronics, and defense applications, yet their separation remains one of the most challenging and costly steps in the supply chain. Conventional separation methods often require extensive processing, hazardous chemicals, and significant energy inputs. Emerging bio-based separation approaches show promise, but development is hindered by the difficulty of predicting and optimizing selective REE binding. Industry needs faster, more reliable tools to accelerate ligand discovery while reducing experimental cost and development risk.

The Technology

OSU engineers have developed a computational design platform that enables prediction and analysis of interactions between rare earth elements and peptide-based ligands in aqueous environments. The approach combines advanced molecular modeling with thermodynamic analysis to provide a quantitative assessment of binding performance while capturing the molecular factors that drive selectivity. By incorporating relevant solution conditions and producing experimentally validated predictions, the technology helps guide ligand design and optimization before laboratory synthesis and testing, significantly accelerating development workflows.

Commercial Applications

• Design and optimization of bio-based extractants for rare earth recovery and recycling.
• Development of peptide-enabled separation media for mining, hydrometallurgy, and industrial waste valorization.
• Computational screening of ligands for critical materials recovery from complex aqueous streams.
• Advanced materials discovery workflows for metal separations, remediation, and selective capture technologies.

Benefits/Advantages

• Reduces experimental trial-and-error by identifying promising ligand candidates prior to synthesis and testing.
• Provides predictive insight into selectivity mechanisms, supporting more rational and efficient ligand development.
• Applicable across multiple rare earth elements and ligand designs, enabling broad platform utility.
• Bridges computational modeling with real-world operating conditions, improving confidence in development decisions and accelerating commercialization.