Imma Capriello

REEactor – The Metal-Ligand Data Company REEactor is a European deep-tech startup developing an automated, AI-guided high-throughput discovery platform for novel metal-binding molecules and sustainable separation technologies. Our research combines multicomponent reaction (MCR) chemistry, acoustic droplet ejection (ADE), miniaturized high-throughput experimentation, advanced analytical methods, and machine learning. Our scientific objective is to accelerate the discovery and optimization of selective ligands for the separation, recovery, and purification of critical raw materials, rare earth elements, battery metals, and precious metals. Research and Innovation Expertise REEactor brings together complementary expertise in: Multicomponent reaction chemistry: Rapid generation of structurally diverse molecular libraries, including complex ligands with multiple metal-coordination sites. Automated and miniaturized synthesis: Acoustic droplet ejection technology for high-throughput chemical experimentation at nanoliter and microliter scales. High-throughput screening: Experimental characterization of metal-binding properties, selectivity, and separation performance. Artificial intelligence and machine learning: Active learning, molecular property prediction, and data-driven optimization of ligand structures. Sustainable chemistry: Development of resource-efficient separation methods that reduce chemical consumption, waste, and environmental impact. Research Interests and MSCA Collaboration Opportunities REEactor is particularly interested in participating in Marie Skłodowska-Curie Actions (MSCA) Doctoral Networks and collaborative research and training initiatives at the interface of chemistry, artificial intelligence, automation, and materials science. We are seeking academic and industrial partners with complementary expertise in coordination chemistry, computational chemistry, machine learning, analytical chemistry, hydrometallurgy, metal recycling, and process engineering. Potential doctoral research topics include: AI-guided discovery of selective ligands for rare earth and critical metal separation. Autonomous experimentation and closed-loop molecular optimization. Development of multicomponent reactions for complex metal-binding architectures. High-throughput screening of metal–ligand interactions. Integration of molecular discovery with industrial separation and recycling processes. Sustainable chemistry and resource-efficient recovery of critical raw materials. Contribution to MSCA Consortia REEactor can contribute an industrial perspective to interdisciplinary doctoral training through collaborative research projects, industrial secondments, technology transfer, entrepreneurship training, and exposure to commercially relevant challenges in critical raw materials. Our goal is to establish strong academic–industrial partnerships that connect fundamental molecular science, artificial intelligence, and automation with practical challenges in sustainable metal recovery. Our Vision REEactor aims to transform metal separation chemistry from a predominantly empirical development process into an automated, predictive, and data-driven molecular discovery discipline, contributing to sustainable resource management, circular economy technologies, and European strategic autonomy in critical raw materials. REEactor MANTRA - Separation is the transformation of complexity into value