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Creating diverse microparticle patterns on a large scale enhances the performance and efficiency of biochemical analytics. Current techniques exhibit limitations in achieving diverse microparticle patterns on a large scale, primarily focusing on patterning particles of the same type with limited flexibility and accessibility. Moreover, accessibility to patterned particles without a fixed formation poses additional challenges. Herein, in this work, we introduce a novel robotic micropatterning system designed to address these challenges. The system facilitates the selection, batch transferring, patterning, and encapsulation of microparticles using negative dielectrophoresis (nDEP)-tweezers, enabling large-scale microparticle patterning on a hydrogel. A multielectrode chip was mounted on a micromanipulator to serve as the nDEP tweezers, and the microparticles scattering on the substrate could be trapped and displaced to different positions on a substrate with an array of holes for large-scale pattern generation. Photosensitive hydrogel was employed for microparticle pattern encapsulation. The effects of configuring different experimental parameters on the patterning efficiency were evaluated and analyzed. Experiments were conducted to explore the stability and performance of the micropatterns. Various patterns with hydrogel encapsulation were created using different color polystyrene microbeads (orange, blue, and green) with varying sizes (50, 100, and 125 μm) under the adjusted environment. Results demonstrate the successful creation of large-scale microbead patterns in a specified form and their encapsulation into an extractable hydrogel using the proposed nDEP tweezer system. The proposed system can be potentially applied to diverse bioparticles for analysis.

Fourier ptychographic microscopy (FPM) is a recently developed computational imaging technique that can achieve both high-resolution and a wide field-of-view via a sequence of low-resolution images. FPM is a complex iterative process, and it is difficult to meet the needs of rapid reconstruction imaging with the conventional FPM deployed on general purpose processors. In this paper, we propose a high-performance heterogeneous field-programmable gate array (FPGA) architecture based on the principle of full pipeline and the data-flow structure for the iterative reconstruction procedure of FPM. By optimizing the architecture network at gate-level logic circuits, the running time of the FPGA-based FPM reconstruction procedure is nearly 20 times faster than conventional methods. Our proposed architecture can be used to develop FPM imaging equipment that meets resource and performance requirements.