Automated optimization of double heater convective polymerase chain reaction devices based on CFD simulation database and artificial neural network model

Abstract

This paper presents a framework for automated optimization of double-heater convective PCR (DH-cPCR) devices by developing a computational fluid dynamics (CFD) simulation database and artificial neural network (ANN) model. The optimization parameter space that includes the capillary tube geometries and the heater sizes of DH-cPCR is established, and a database consisting of nearly 10,000 CFD simulations is constructed. The database is then used to train a two-stage ANN models that select practically relevant data for modeling and predict PCR device performance. The trained ANN model is then combined with the gradient-based and the heuristics optimization approaches to search for optimal device configuration that possesses the shortest DNA doubling time. The entire design process including model meshing and configuration, parallel CFD computation, database organization, and ANN training and utilization is fully automated. Case studies confirm that the proposed framework can successfully find the optimal device configuration with an error of less than 0.3 s, and hence, representing a cost-effective and rapid solution of DH-cPCR device design.

Multi-fidelity surrogate-based optimization for microfluidic concentration gradient generator design

“…Performing design optimization for µCGG requires automated simulation (Hong et al. , 2021; Shu et al.…”

“…2.1.3 Automated simulations. Performing design optimization for mCGG requires automated simulation (Hong et al, 2021;Shu et al, 2021), that is, all the simulations need to be invoked and controlled by the MFSBO process, which in the present work is implemented in the MATLAB environment (www.mathworks.com). The details of the automated simulation are given as follows.…”

Nitrite enhanced detection from saliva by simple geometrical modifications of paper-based micromixers

“…Gravity is ignored in the studies. With these assumptions, the mass conservation equation for incompressible fluids can be coupled to Darcy’s law for each phase, as follows (Hong et al 2021 ; Karimi et al 2021 ; Hao et al 2021 ): where is the paper permeability, is the fluid viscosity, is the substrate porosity, and ∇p is the pressure gradient. These expressions can be combined and employed for calculating the pressure field.…”

Graphene Based Printable Conductive Wax for Low‐Power Thermal Actuation in Microfluidic Paper‐Based Analytical Devices

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