Yamil Colon

Visiting Assistant Professor

University of Notre Dame

United States

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About

Yamil Colon is a Visiting Assistant Professor at the University of Notre Dame, USA. His research primarily focuses on computational tools and techniques in material science, particularly in the areas of drug screening, electrostrictive properties of ionic liquids, and the adsorption mechanisms in metal-organic frameworks. His recent articles explore the integration of machine learning with physical chemistry, the role of electrostatic configurations, and the development of high-throughput analysis methods.

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Teaching Assistant

University of Notre Dame

UNITED STATES

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Yamil Colon

Research Interests

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About

Articles (20)

Automated High-Content, High-Throughput Spatial Analysis Pipeline for Drug Screening in 3D Tumor Spheroid Inverted Colloidal Crystal Arrays

Next-Generation Computational and Experimental Tools for Understanding Nucleation and Growth of Metal–Organic Frameworks

Structure–Property Relationship for the Electrostrictive Properties of Ionic Liquids

Expanding Cluster, Enhancing Adsorption: Investigating the Role of Electrostatic Configurations on Water Vapor Adsorption

Harmonizing Adsorption and Diffusion in Active Learning Campaigns of Gas Separations in a MOF

Considerations in the use of machine learning force fields for free energy calculations

DynaMate: leveraging AI-agents for customized research workflows

Open-source generation of sigma profiles: impact of quantum chemistry and solvation treatment on machine learning performance

Understanding stable adsorption states in flexible soft porous coordination polymers through free energy profiles

Free Energy Profiles of Monomeric Species in MOFs for Predicting Thermal Stability of MOF–Polymer Systems

Semi-empirical Haken–Strobl model for molecular spin qubits

Active Learning for Adsorption Simulations: Evaluation, Criteria Analysis, and Recommendations for Metal–Organic Frameworks

Activity coefficient acquisition with thermodynamics‐informed active learning for phase diagram construction

Transfer Learning Facilitates the Prediction of Polymer–Surface Adhesion Strength

Understanding the Correlation Between Structure and Entangled Photon Pair Properties with Metal–Organic Frameworks

Molecular Dynamics Simulation of the Influence of External Electric Fields on the Glass Transition Temperature of the Ionic Liquid 1-Ethyl-3-methylimidazolium Bis(trifluoromethylsulfonyl)imide

Machine Learning Identification of Organic Compounds Using Visible Light

Atomistic simulation of soft porous coordination polymers

Understanding Structure–Property Relationships of MOFs for Gas Sensing through Henry’s Constants

Active learning for efficient navigation of multi-component gas adsorption landscapes in a MOF

Collaborators (6)

Ubaldo M Córdova-Figueroa

Yichun Wang

Meenesh Singh

Samanvaya Srivastava

Edward Maginn

Hyunsu Jeon

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