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Direct ink writing (DIW) is an extrusion-based additive manufacturing technology. It has gained wide attentions in both industry and research because of its simple design and versatile platform. In electric-field-assisted Direct Ink Writing (eDIW) processes, an external electric field is added between the nozzle and the printing substrate to manipulate the ink-substrate wetting dynamics and therefore optimize the ink printability. eDIW was found effective in printing liquids that are typically difficult to print in the conventional DIW processes. In this paper, an eDIW process modeling system based on machine learning (ML) algorithms is developed. The system is found effective in predicting eDIW printing geometry under varied process parameter settings. Image processing approaches to collect experiment data are developed. Accuracies of different machine learning algorithms for predicting printing results and trace width are compared and discussed. The capabilities, applications and limitations of the presented machine learning-based modeling approach are presented.

 

Abstract This study successfully integrates acoustic patterning with the Two-Photon Polymerization (TPP) process for printing nanoparticle–polymer composite microstructures with spatially varied nanoparticle compositions. Currently, the TPP process is gaining increasing attention within the engineering community for the direct manufacturing of complex three-dimensional (3D) microstructures. Yet the full potential of TPP manufactured microstructures is limited by the materials used. This study aims to create and demonstrate a novel acoustic field-assisted TPP (A-TPP) process, which can instantaneously pattern and assemble nanoparticles in a liquid droplet, and fabricate anisotropic nanoparticle–polymer composites with spatially controlled particle–polymer material compositions. It was found that the biggest challenge in integrating acoustic particle patterning with the TPP process is that nanoparticles move upon laser irradiation due to the photothermal effect, and hence, the acoustic assembly is distorted during the photopolymerization process. To cure acoustic assembly of nanoparticles in the resin through TPP with the desired nanoparticle patterns, the laser power needs to be carefully tuned so that it is adequate for curing while low enough to prevent the photothermal effect. To address this challenge, this study investigated the threshold laser power for polymerization of TPP resin (Pthr) and photothermal instability of the nanoparticle (Pthp). Patterned nanoparticle–polymer composite microstructures were fabricated using the novel A-TPP process. Experimental results validated the feasibility of the developed acoustic field-assisted TPP process on printing anisotropic composites with spatially controlled material compositions. 

Abstract Recently, many studies have investigated additive manufacturing (AM) of hierarchical surfaces with high surface area/volume (SA/V) ratios, and their performance has been characterized for applications in next-generation functional devices. Despite recent advances, it remains challenging to design and manufacture high SA/V ratio structures with desired functionalities. In this study, we established the complex correlations among the SA/V ratio, surface structure geometry, functionality, and manufacturability in the two-photon polymerization (TPP) process. Inspired by numerous natural structures, we proposed a 3-level hierarchical structure design along with the mathematical modeling of the SA/V ratio. Geometric and manufacturing constraints were modeled to create well-defined three-dimensional hierarchically structured surfaces with a high accuracy. A process flowchart was developed to design the proposed surface structures to achieve the target functionality, SA/V ratio, and geometric accuracy. Surfaces with varied SA/V ratios and hierarchy levels were designed and printed. The wettability and antireflection properties of the fabricated surfaces were characterized. It was observed that the wetting and antireflection properties of the 3-level design could be easily tailored by adjusting the design parameter settings and hierarchy levels. Furthermore, the proposed surface structure could change a naturally hydrophilic surface to near-superhydrophobic. Geometrical light trapping effects were enabled and the antireflection property could be significantly enhanced (> 80% less reflection) by the proposed hierarchical surface structures. Experimental results implied the great potential of the proposed surface structures for various applications such as microfluidics, optics, energy, and interfaces.