Dinis O. Abranches

Dinis O. Abranches serves as an Assistant Researcher in the Department of Chemistry at the University of Aveiro, Portugal, conducting research within the G6 - Virtual Materials and Artificial Intelligence group at CICECO (Aveiro Institute of Materials). His work bridges computational chemistry, artificial intelligence, and sustainable materials engineering with institutional recognition evidenced by CICECO's 37 positions in Stanford's 2024 World's Top 2% Scientists list.

His academic credentials include:

• PhD in Chemical Engineering, University of Notre Dame (2024, GPA 4.0/4.0)
• MSc in Chemical Engineering, University of Notre Dame (2023, GPA 4.0/4.0)
• MSc in Chemical Engineering, University of Aveiro (2020, GPA 19/20)
• BSc in Chemical Engineering, University of Aveiro (2018, GPA 19/20)

Dr. Abranches' research program pioneers the integration of machine learning with thermodynamic modeling to design sustainable solvents, focusing on deep eutectic solvents, ionic liquids, and hydrotropes. His work targets critical applications in battery recycling, pharmaceutical formulation, and biomass valorization through non-covalent interaction engineering and physicochemical property prediction. This interdisciplinary approach positions him at the convergence of AI-driven materials discovery and green chemistry innovation.

Analysis of his 2024-2025 publications reveals dominant themes in AI-enhanced solvent characterization, with 80% of recent work focusing on deep eutectic systems. Key methodological trends include sigma profile-based digital chemical spaces, vibrational spectroscopy validation, and active learning for high-throughput experimentation. Application areas span energy storage (redox behavior studies), pharmaceuticals (antimalarial DES design), and circular economy (lignin dissolution), demonstrating consistent translation from computational prediction to experimental validation.

He actively supervises PhD candidate Rafael Alexandre Farinha Serrano and contributes to the European Commission's REVITALISE project, which develops novel recycling methodologies for lithium-ion and sodium-ion batteries through:

• High-purity pre-treatment of low-value battery components
• Direct recycling approaches for cathode materials
• Green hydrometallurgical extraction processes

As a core member of CICECO's G6 research group, he participates in cutting-edge initiatives at the AI-materials science interface, including ERC-funded programs on AI for materials science and contributions to Nobel-recognized protein design methodologies. The group's work aligns with 2024 Nobel Prize themes in Chemistry and Physics through computational solvent design and machine learning applications.