Analysis and optimization of microfluidic systems for real-time detection of nutrients in soil based on computational fluid dynamics and response surface methodology

Microfluidics is turning out to be essential for the advancement of scientific research, healthcare, and various other applications due to its ability to provide precise control, miniaturization, and integration of fluid samples. Existing research shows a considerable growth rate in the utilization of microfluidics-based techniques, especially in the biomedical field for disease detection, drug analysis, cell analysis, and more. However, the development of microfluidic systems for soil nutrition testing applications is still a challenging task due to the need for micro scale dimensions and a high degree of precision during the fabrication and detection of soil nutrients. The present investigation aims to find the most suitable design for the microfluidic chip that can control and detect microfluid containing soil nutrients, especially nitrites, effectively. To achieve this goal, the parameters of different microchannel (MC) specimens, such as snug height, channel width, obstacle pitch, mean mixture pressure, wall shear stress, strain rate, and total pressure, are analyzed. In addition, the Response Surface Methodology (RSM) is introduced to statistically authenticate the obtained simulation data. As a result, the present investigation proposes the optimal MC design with optimal parameters: snug height of 0.35 mm, channel width of 1.54 mm, obstacle pitch of 2.5 mm, mean mixture pressure of 0.24 MPa, wall shear stress of 1.1 Pa, strain rate of 2259 s⁻¹, and total pressure of 1.42 MPa. Moreover, the functionality of the proposed microfluidic chip was calibrated and predicted using the Deep Neural Network-based Modified Sea Horse Optimizer (DNN-MSHO) algorithm, confirming the presence of nitrites in the used soil samples in a range of 2.81–4.18 ppm, which again proves the efficiency and trustworthiness of the proposed microfluidic chip design and its usability in real soil testing applications.