Hello, I'm

Fernando Fajardo-Rojas

Postdoctoral Researcher

Computational Materials Science • AI/ML for Materials • Autonomous Discovery

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J. Fernando Fajardo-Rojas
🔬 Materials 🤖 AI/ML ⚡ Energy 👩🏻‍🔬 Chemical Separations
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01. About Me

I am a postdoctoral researcher at the Colorado School of Mines, working in the Toberer Group.

I earned a PhD in Materials Science from Mines in 2025 under the guidance of Diego Gómez-Gualdrón, where I developed computational workflows to accelerate the discovery of new materials for energy-related applications.

Previously, I received a PhD in Engineering from Universidad de los Andes in Colombia, where I worked with Oscar Alvarez and Diego Pradilla on the experimental characterization of interfacial phenomena.

🎓
Expertise

Computational & Experimental

🔬
Research Focus

AI-driven materials discovery

💡

My Vision

I envision a future where AI-powered tools unlock the potential of autonomous experimentation to dramatically accelerate the design cycle of functional materials—transforming how we discover solutions for energy, sustainability, and beyond.

02. Research

My research focuses on harnessing the power of Artificial Intelligence and Machine Learning in fields where data is scarce or costly.

Physico-Chemical Material Representations

Integrating domain knowledge and physico-chemical insights into material representations to build more robust and interpretable ML models.

Feature Engineering Domain Knowledge

Transfer & Active Learning

Developing advanced training techniques to minimize the need for large labeled datasets—crucial for materials science where data generation is expensive.

Transfer Learning Active Learning

Interpretable AI Models

Creating models that uncover structure–property relationships, translating data into actionable insights for hypothesis-driven materials design.

Explainable AI Structure-Property

Autonomous Materials Discovery

Building tools that enable autonomous experimentation to accelerate the design cycle of functional materials for energy applications.

Automation High-Throughput

03. Publications

2026

Machine learning to design metal–organic frameworks: progress and challenges from a data efficiency perspective

D. Gómez-Gualdrón, T. G. de Vilas, K. Ardila, F. Fajardo-Rojas, A. Pak.

Mater. Horiz., 2026, Advance Article

Review
2025

Expert-Guided LLM Approach for Sequence-Aware Extraction of MOF Synthesis

X. Zhao, F. Fajardo-Rojas, J. Furst, K. Ardila, K. Langlois, Y. An, X. Hu, F. Uribe-Romo, D. Gómez-Gualdrón, J. Greenberg

ChemRxiv

Preprint
2025

Data-Driven Insights on the Impact of Functionalization on Metal–Organic Framework Free Energies

F. Fajardo-Rojas, R. Anderson, M. Li, R. Chang, D. A. Gómez-Gualdrón

Chem. Mater. 2025, 37, 15, 5502–5514

Paper Visualization Tool
2025

Highly Accurate and Fast Prediction of MOF Free Energy Via Machine Learning

A. Rubungo*, F. Fajardo-Rojas*, D. A. Gómez-Gualdrón, A. Dieng (* Equal contribution)

J. Am. Chem. Soc. 2025, 147, 52, 48035–48045

Paper MOFMinE (Database)
2025

Interactions of Common Synthesis Solvents with MOFs Studied via Free Energies of Solvation: Implications on Stability and Polymorph Selection

F. Fajardo-Rojas*, R. Anderson, K. Ardila, A. Pak, D. A. Gómez-Gualdrón

ChemRxiv (Accepted in Chemistry of Materials)

Preprint
2024

MOFs to Enhance Green NH3 Synthesis in Plasma Reactors: Hierarchical Computational Screening Enhanced by Iterative Machine Learning

T.W. Liu, F. Fajardo-Rojas, S. Addish, E. Martinez, D. A. Gómez-Gualdrón

ACS Appl. Mater. Interfaces 2024, 16, 49, 68506–68519

Paper
2024

Active learning of alchemical adsorption simulations; towards a universal adsorption model

E. Osaro, F. Fajardo-Rojas, G. Cooper, D. A. Gómez-Gualdrón, Y. J. Colón

Chem. Sci., 2024, 15, 17671-17684

Paper
2023

Framework-Topology-Controlled Singlet Fission in Metal–Organic Frameworks

S. Rajasree, J. Yu, F. Fajardo-Rojas, H. C. Fry, R. Anderson, X. Li, W. Xu, J. Duan, S. Goswami, K. Maindan, D. A. Gómez-Gualdrón, P. Deria

J. Am. Chem. Soc. 2023, 145, 32, 17678–17688

Paper
2023

Novel biosurfactants: Rationally designed surface-active peptides and in silico evaluation at the decane-water interface

J. Pérez-Bejarano, F. Fajardo-Rojas, O. Alvarez, J. Burgos, L. Reyes, D. Pradilla

Process Biochem. 125, 84-95

Paper
2023

Theoretical assessments of Pd–PdO phase transformation and its impacts on H2O2 synthesis and decomposition pathways

M. Vyas, F. Fajardo-Rojas, D. A. Gómez-Gualdrón, S. Kwon

Catal. Sci. Technol., 2023, 13, 3828-3848

Paper
2022

Deviation from Equilibrium Thermodynamics of an Asphaltene Model Compound during Compression–Expansion Experiments at Fluid–Fluid Interfaces

F. Fajardo-Rojas, O. Alvarez, J. Samaniuk, D. Pradilla

Langmuir 2021, 37, 5, 1799–1810

Paper
2022

Probing Interfacial Structure and Dynamics of Model and Natural Asphaltenes at Fluid–Fluid Interfaces

F. Fajardo-Rojas, D. Pradilla, O. Alvarez, J. Samaniuk

Langmuir 2020, 36, 27, 7965–7979

Paper
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04. Curriculum Vitae

2025 – Present

Postdoctoral Researcher

Colorado School of Mines • Toberer Group

AI/ML for materials discovery and autonomous experimentation

2020 – 2025

PhD in Materials Science

Colorado School of Mines

Advisor: Diego Gómez-Gualdrón
Focus: Computational workflows for materials discovery

Earlier

PhD in Engineering

Universidad de los Andes, Colombia

Advisors: Oscar Alvarez & Diego Pradilla
Focus: Experimental characterization of interfacial phenomena

Download Full CV

Get the complete curriculum vitae with full publication list, presentations, and awards.

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05. Get in Touch

Interested in collaboration, have questions about my research, or just want to connect? I'd love to hear from you.

Location

Colorado School of Mines
Golden, CO, USA

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