Micro-stereolithography ($\mu$SL) is an advanced additive manufacturing technique that enables the fabrication of highly precise microstructures with fine feature resolution. One of the primary challenges in $\mu$SL is achieving and maintaining precise focus throughout the fabrication process. For the successful application of $\mu$SL, it is essential to maintain the sample surface within a focal depth of several microns. Despite the growing interest in auto-focus devices, limited attention has been directed towards auto-focus systems in image-based auto-focus microscope systems for precision $\mu$SL. To address this challenge, we propose an image-based auto-focus microscope system incorporating visual servo control. In the optical design, a transflective beam splitter is employed, allowing the laser beam to pass through for fabrication while reflecting the focused beam on the sample surface to the microscope and camera. Utilizing captured spot images and the Foucault knife-edge test, a deep learning-based laser spot image processing algorithm is developed to determine the focus position based on spot size and the number of spot pixels on both sides. Experimental results demonstrate that the proposed auto-focus system effectively determines the relative position of the focal point using the laser spot image and achieves auto-focusing through visual servo control.

In this work, the method of highly efficient conversion of l-rhamnose to 5-methylfurfural (MF) catalyzed by various catalysts in a biphasic system was developed. To enhance the MF yield, the effects of the catalyst species, reaction temperature (150–180 °C), extraction solvents and volume ratio of the extraction to the aqueous phase (0–5) on the conversion of l-rhamnose to MF were systematically investigated. Under optimal conditions, a high MF yield of 94% was achieved in the biphasic “diisopropyl ether (DIPE) + H₂O” system due to the fact that the extraction of MF to the DIPE phase significantly inhibits the condensation and degradation of MF in water. Finally, detailed reaction energetics and chemical structures of intermediates of the l-rhamnose dehydration to MF were investigated using the B3LYP level of theory and the SMD solvation model. It is evident that MF, which exhibits excellent chemical stability, harbors the potential to function as a bio-derived platform chemical within the domain of the green industry.

Wavelet transform is an important branch as a new theory in the history of mathematics. It is a signal analyzing and processing method in time-frequency domain, and has an excellent local character in time domain and frequency domain. Wavelet transform has led to many new wavelets applications in various fields such as signal detection, signal processing and image processing, and the hardware realization of wavelet transform algorithms receives more and more recognition. This paper introduces the principle of fast wavelet transform and the realizing method in DSP. The DSP instructions such as parallel multiply-accumulate instruction, circular addressing and repeating operation in TMS320C3X of, which are suitable to realize the wavelet algorithms, are described in detail. A framework of assemble language program for the calculation of scale expanding value is given out and the problem which should be paid attention to in the fast wavelet algorithms using DSP is discussed specially.