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Computational study of the interactions of surfactant molecules with gold nanostructures

Grant number: 21/03516-4
Support type:Scholarships in Brazil - Scientific Initiation
Effective date (Start): June 01, 2021
Effective date (End): April 01, 2023
Field of knowledge:Physical Sciences and Mathematics - Chemistry - Physical-Chemistry
Principal researcher:André Farias de Moura
Grantee:Davi Augusto Mattoso
Home Institution: Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil
Associated research grant:13/07296-2 - CDMF - Center for the Development of Functional Materials, AP.CEPID
Associated scholarship(s):21/11813-9 - Computational characterization of surfactant structures on gold surfaces by graph theory, BE.EP.IC


The present research project describes the computational investigation of the interactions of a cationic surfactant (CTAB) with gold surfaces. CTAB is a widely used surfactant in the processes of synthesis, stabilization and post-synthetic modification of gold nanostructures, but whose mechanisms on a molecular level are not fully understood as yet. The project aims to perform molecular dynamics simulations of different colloidal surfactant structures interacting with certain gold crystalline facets, with detailed and realistic models. However, the available force fields to describe the interactions of gold and adsorbed molecules have not been developed to reproduce the free energy of adsorption, becoming necessary to first validate the free energy of adsorption of the molecules of interest on the gold surfaces. Such validation will be done by comparing the free energy values obtained with force fields and the values obtained with quantum potential. When the validation step of the potentials used is over, molecular dynamics simulations will be performed for realistic model systems of colloidal CTAB structures (micelles, monolayers and bilayers) and different gold nanoparticles. The proposal also foresees a scientific visit to the University of Michigan, according to the specific project attached, with the focus of the internship in the research group of Professor Nicholas Kotov to apply machine learning and artificial intelligence methodologies to obtain graphs capable of describing the complexity patterns of these interfacial structures.

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