Development of a calibration system for microfluidic devices

• Grant number: 25/06357-5
• Support Opportunities: Scholarships abroad - Research Internship - Post-doctor
• Start date: August 01, 2025
• End date: July 31, 2026
• Field of knowledge: Interdisciplinary Subjects
• Principal Investigator: Antonio Riul Júnior
• Grantee: Carla Daniela Boeira
• Supervisor: Henrique Leonel Gomes
• Host Institution: Instituto de Física Gleb Wataghin (IFGW). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Institution abroad: Universidade de Coimbra (UC), Portugal
• Associated to the scholarship: 22/08216-1 - Development of advanced sensing devices for soil analysis using nanomaterials:"Microfluidic Electronic Tongue", BP.PD

Abstract

The increasing global demand for food puts pressure on agricultural productivity, which can lead to the expansion of cultivated land and, consequently, to severe environmental impacts. Improving the efficiency in the use of natural resources and the quality of agricultural production, without deforestation or soil degradation, is essential to meet this growing demand. One promising approach is the controlled distribution of macronutrients through prior mapping of planting areas. However, this is often limited by the high costs of laboratory analyses over large areas. As a result, excessive fertilizer application is common. Smart sensing technologies can help improve in-situ monitoring with minimal human intervention, enabling faster decision-making.In this context, microfluidic electronic tongues have emerged as a promising tool due to their ability to detect and differentiate soil samples diluted in water, without any pre-processing. Advances in nanotechnology, such as the Glancing Angle Deposition (GLAD) technique, have enabled the formation of metallic nitrides with tunable electrical and mechanical properties-key features for the development of more robust and adaptable sensing units.Our proposal is to implement a system with two parallel microchannels in the experimental setup, aiming for real-time calibration during measurements. This will facilitate the recognition of macronutrients using our electronic tongue, generating more robust data before applying supervised machine learning algorithms (such as decision trees and random forests). Ultimately, this contributes to more efficient remote monitoring and faster decision-making in agricultural fields.