SOURCE-LINKED INTELLIGENCE

Atomistic Modeling of Advanced Porous Materials for Energy, Environment, and Biomedical Applications

CORDIS · observation · Publication date unknown

will create a materials intelligence ecosystem for precisely assessing guest storage and transport properties of all MOFs by combining state-of-the-art atomistic calculations, molecular simulations, machine learning, and data science, integrated with past and future experiments. I will focus on ten critical guest molecules to address the key societal challenges of our world: hydrogen and methane to use MOFs for clean energy storage; ammonia, carbon monoxide, carbon dioxide, nitrous oxide to use MOFs for capturing toxic gas and combatting global warming; fluorouracil, methotrexate, nitrogen, oxygen to use MOFs as nanocarriers for anti-cancer drug therapy and biomedicine. The ground-breaking gains of my project will include the creation of the worlds first database for guest storage and transport properties of millions of MOFs; accurate assessments of new technologies by precise MOF-application matching; and generating design guidelines for high-performing MOFs to accelerate discovery of new materials. My novel methodology synergizing theory and data-driven science will greatly extend

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recordType

award

status

SIGNED

region

EU

value

2000000

unit

EUR