Fernando Pardo Pardo

Assistant Professor

Universidad de Cantabria

Spain

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About

Fernando Pardo Pardo is an Assistant Professor at Universidad de Cantabria, Spain. His research focuses on sustainable absorption refrigeration, gas separation performance of membranes, and the solubility of refrigerants in ionic liquids. Recent publications highlight his work on biomass-derived solvents, hydrofluorocarbons, and membrane technology for refrigerant recovery.

Articles (10)

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2025

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2025

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2025

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2024

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2024

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2024

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2023

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2023

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2023

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2022

Collaborators (6)

Andrew Foster

The University of Manchester

UNITED KINGDOM

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Gabriel Zarca

Associate Professor

Universidad de Cantabria

SPAIN

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Peter Budd

Professor of Polymer Chemistry

The University of Manchester

UNITED KINGDOM

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Ane Urtiaga

Professor

Universidad de Cantabria

SPAIN

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Jesus Esteban Serrano

The University of Manchester

UNITED KINGDOM

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Jesus Angel Miguel

Professor

Universidad de Valladolid

SPAIN

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Fernando Pardo Pardo

Research Interests

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Contact this professor

About

Articles (10)

Gas separation performance of branched PIM-1 thin-film composite hollow fiber membranes

Biomass-Derived Solvents and Low-GWP Refrigerants as Working Fluids for Sustainable Absorption Refrigeration

An NMR study of hydrofluorocarbon mixed-gas solubility and self-diffusivity in the ionic liquid 1-ethyl-3-methylimidazolium dicyanamide

6FDA-polyimide thin-film composite hollow fiber membranes for hydrofluorocarbons and CO2 separations

Solubility of difluoromethane (R-32) and pentafluoroethane (R-125) in 1-alkyl-3-methylimidazolium tricyanomethanide ionic liquids

Assessment of organic solvents for 2,5-furandicarboxylic acid (FDCA) and distribution in water/cyclohexanone biphasic system

In the quest for ionic liquid entrainers for the recovery of R-32 and R-125 by extractive distillation under rate-based considerations

Polymer/ionic liquid pilot scale membrane prototype for the recovery of difluoromethane (R-32) from refrigerant mixtures

Outstanding performance of PIM-1 membranes towards the separation of fluorinated refrigerant gases

Machine learning for predicting the solubility of high-GWP fluorinated refrigerants in ionic liquids

Collaborators (6)

Andrew Foster

Gabriel Zarca

Peter Budd

Ane Urtiaga

Jesus Esteban Serrano

Jesus Angel Miguel

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