Prediction of Deposition Rate in Meniscus‐Confined Electrodeposition Based on Parameter Optimization Algorithm

Abstract

Meniscus‐confined electrodeposition (MCED) is a potential approach to fabricate 3D metallic microstructures and can be used in microelectromechanical systems, optoelectronics, and flexible electrical interconnections. However, deposition efficiency and the quality of the microstructures obtained by this method on optimal parameters are identified by a large number of comparative experiments, resulting in high cost and inefficient practices. For this reason, herein, the fabrication process of metal microstructures by MCED simulation and optimizes parameters affecting deposition quality and rate is investigated. First, the finite‐element method is used to simulate the voltage and copper ion concentration identifies the target range. Then, the electrodeposition rate 1 × 10−7 m s−1 is set as the target value. The best applicable values of 0.29 V and 0.46 m are obtained after optimizing the voltage and copper ion concentration that affects the quality of deposited microstructures and rate of MCED based on the genetic algorithm (GA), cuckoo search (CS) algorithm, and support vector regression (SVR) algorithm. Finally, simulations and experiments are carried out according to the optimized parameters values. The results show that the maximum error of deposition rate is 7.9%. This study pioneers a new approach to achieving efficient and high‐quality deposition by MCED.