Impedimetric sensor and machine learning for in-situ monitoring of nanoparticles

• Grant number: 18/24214-3
• Support Opportunities: Scholarships in Brazil - Doctorate
• Effective date (Start): August 01, 2019
• Effective date (End): July 31, 2023
• Field of knowledge: Physical Sciences and Mathematics - Chemistry - Analytical Chemistry
• Principal Investigator: Renato Sousa Lima
• Grantee: Larissa Fernanda Ferreira
• Host Institution: Centro Nacional de Pesquisa em Energia e Materiais (CNPEM). Ministério da Ciência, Tecnologia e Inovação (Brasil). Campinas , SP, Brazil

Abstract

The poor reproducibility of nanomaterials synthesis and functionalization is the greatest challenge facing the development of nanotechnologies. Therefore, by taking up the increasing demand for scaling up the production of these materials and the impact of their surface chemistry on the applications, the construction of simple, fast, and portable sensors for ex-situ and in-situ quality control of nanomaterials is highly desirable. In this regard, this project is intended to develop a new single response microfluidic electronic tongue (e-tongue) for the quality control of silica nanoparticles (SiO2NPs). Poly(dimethylsiloxane) (PDMS) devices will be fabricated by a cleanroom-free method and the sensor will consist of an association of electric double-layer capacitors in parallel. Graphite pencil cores will be used in a pioneering way as sensitive probes of an e-tongue. Without surface chemical modification, these cores will guarantee signal variance (essential for tongue sensitivity) because of their specific graphite/clay ratios. The fabrication of the sensor will be cheap and fast. Regarding its applications, which will be performed in a smartphone-controlled portable potentiostat, the ex-situ monitoring of the surface chemistry of SiO2NPs will be conducted as a function of the functionalization extension with folic acid, a bioreactor used for specific interactions with cancer cells. In addition, we will conduct microfluidic synthesis and in-situ monitoring of SiO2NPs according to their concentration, size, homogeneity, and colloidal stability. The PDMS devices will be applied for the synthesis of SiO2NPs under turbulence flow conditions. This flow increases the mixing efficiency and reduces the axial dispersion. As a consequence, such a method may be a potential alternative on microfluidic synthesis techniques described in the literature by taking into account the advantages from the device fabrication and from the high throughput production of homogenous SiO2NPs. (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

FERREIRA, LARISSA F.; GIORDANO, GABRIELA F.; GOBBI, ANGELO L.; PIAZZETTA, MARIA H. O.; SCHLEDER, GABRIEL R.; LIMA, RENATO S.. Real-Time and In Situ Monitoring of the Synthesis of Silica Nanoparticles. ACS SENSORS, v. 7, n. 4, p. 13-pg., 2022-04-22. (18/24214-3)

NICOLICHE, CAROLINE Y. N.; DE OLIVEIRA, RICARDO A. G.; SILVA, GIULIA S.; FERREIRA, LARISSA F.; RODRIGUES, IAN L.; FARIA, RONALDO C.; FAZZIO, ADALBERTO; CARRILHO, EMANUEL; DE PONTES, LETICIA G.; SCHLEDER, GABRIEL R.; et al. Converging Multidimensional Sensor and Machine Learning Toward High-Throughput and Biorecognition Element-Free Multidetermination of Extracellular Vesicle Biomarkers. ACS SENSORS, v. 5, n. 7, p. 8-pg., 2020-07-24. (17/02317-2, 18/24214-3, 14/50867-3, 17/18139-6)

GIORDANO, GABRIELA F.; FERREIRA, LARISSA F.; BEZERRA, ITALO R. S.; BARBOSA, JULIA A.; COSTA, JULIANA N. Y.; PIMENTEL, GABRIEL J. C.; LIMA, RENATO S.. Machine learning toward high-performance electrochemical sensors. ANALYTICAL AND BIOANALYTICAL CHEMISTRY, v. 415, n. 18, p. 10-pg., 2023-01-13. (20/09102-4, 18/24214-3)