| Electrohydrodynamic printing technology is an emerging additive manufacturing printing technology that differs from traditional inkjet printing in that it achieves printing through the "pull" driving mode with electric field force,rather than the "push" driving mode.The jet diameter obtained by current fluid printing technology can reach the nanometer level,making it highly applicable in high-resolution printing fields such as microelectronics packaging and flexible circuits.Traditional Electrohydrodynamic printing is usually a continuous process,which lacks stable controllability despite high printing resolution.To address the shortcomings of traditional electrohydrodynamic printing technology and achieve stable,controllable high-resolution Electrohydrodynamic printing,this paper uses a combined theoretical analysis and numerical simulation approach to conduct in-depth research on on-demand Electrohydrodynamic printing technology.Firstly,a numerical simulation model of the on-demand current fluid printing droplet process is established using COMSOL Multiphysics coupling simulation software to explore the influence of process parameters on the on-demand electrohydrodynamic printing process.Secondly,a nozzle structure with a fiber core is improved and optimized to enhance printing resolution and stability.The impact of different fiber core structures on droplet printing processes is explored through modeling and analysis.Finally,a droplet diameter prediction model is established using a combination of machine learning and genetic algorithms,and process parameters are optimized.The specific research content and conclusions are as follows:1.A numerical simulation model of on-demand electrohydrodynamic printing droplets was established.Based on this model,the evolution of the cone jet is simulated,and the correctness of the model is verified by comparing the charge distribution and jet shape during the jet formation with the Collins model.The on-demand electrohydrodynamic printing numerical simulation model was explored to investigate the influence law of voltage value,air pressure value,liquid density,and liquid surface tension on the printed droplets.The results show that the droplet diameter first decreases and then stabilizes with increasing voltage in the voltage range of 5200V-5500V;the droplet diameter increases with increasing air pressure in the air pressure range of 750Pa-950 Pa.When the material density is less than800Kg/m3,satellite drops are likely to occur;when the surface tension is less than 0.02N/m,jet instability will occur to form multi-jet patterns.A dimensionless parameter Pi value is defined as the judgment basis that on-demand electrohydrodynamic printing can carry out stable printing of single droplets,and the conclusion is summarized by multiple sets of data analysis that stable on-demand printing of droplets can be achieved when 3<Pi<10.Finally,the feasibility of on-demand electrohydrodynamic printing was verified by building an experimental platform.2.An improved fiber-core structured printing nozzle was developed.The following results have been obtained from the COMSOL simulation model and calculations: the fibercore structured nozzle effectively solved the satellite droplet problem encountered when printing low-density and low-viscosity materials,thus improving the stability of the printing process;compared to no fiber-core structure,the fiber-core structured nozzle could produce smaller droplet diameters,thus effectively increasing the printing resolution.Additionally,the wettability of the fiber-core surface and the length of the fiber-core had a significant impact on the liquid flow within the nozzle.As the wettability decreased,the liquid tended to contract under the influence of surface tension rather than spread and wet the surface,resulting in greater resistance to the flow.The length of the fiber-core affected the loss of kinetic energy as the liquid flowed and wet the fiber-core.Longer fiber-cores led to larger wetting distances,greater energy loss,and shorter jet lengths.Within the fiber-core length range of 0.65 mm to 0.80 mm,the droplet diameter decreased with increasing length.3.A numerical simulation-based precision prediction model and process parameter optimization method for electrohydrodynamic printing were established.Five prediction models were built using four machine learning algorithms: linear regression,support vector regression,random forest regression,and multi-layer perceptron regression to predict the relationship between five process parameters and droplet diameter.Through model performance evaluation,the support vector regression model was selected as the best algorithm for predicting accuracy.For the support vector regression model,the SEGA algorithm was used for process parameter optimization,and the results were compared with those of the classic genetic algorithm(SGA);the results showed that SEGA had better global convergence and achieved more expected optimization target values.Finally,When the voltage value is 5600 V,the air pressure is 993 Pa,the pulse width is 0.6ms,the fiber core length is 0.6mm,and the fiber core wetting angle is 32 °,the optimal process parameter combination obtained by SEGA optimization was used for numerical simulation calculation,with a target value of 0.0798 mm.The numerical simulation result was 0.0812 mm,with an error of 1.75%,which verified the reliability of the SEGA optimization algorithm. |
