Nency P. Domingues
Papers
2
Total Citations
30
H-Index
2
About
Nency P. Domingues is a rising researcher at the forefront of materials chemistry, specializing in the accelerated discovery and optimization of metal-organic frameworks (MOFs). Her work uniquely bridges computational machine learning and experimental synthesis, with a primary focus on the Al-PMOF system. Domingues’s major contribution is the development of a novel methodology that employs genetic algorithms to systematically navigate complex synthesis conditions, dramatically reducing the trial-and-error typical in MOF fabrication. Her most-cited paper, “Using genetic algorithms to systematically improve the synthesis conditions of Al-PMOF” (2022), has garnered 26 citations, demonstrating its immediate impact on the field. This work introduces a “synthetic conditions finder” that intelligently pinpoints optimal parameters for producing high-quality Al₂(OH)₂TCPP, a porphyrin-based MOF with potential in photocatalysis and gas storage. By automating the optimization process, Domingues is paving the way for more efficient, data-driven materials design. Her research stands as a compelling example of how artificial intelligence can revolutionize traditional synthetic chemistry, offering a powerful toolkit for researchers seeking to rapidly develop advanced functional materials.
Research Focus
Key Achievements
Top Papers
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