In this study, the burr and slot widths formed after the micro-milling process of Inconel 718 alloy were investigated using a rapid and accurate image processing method. The measurements were obtained using a user-defined subroutine for image processing. To determine the accuracy of the developed imaging process technique, the automated measurement results were compared against results measured using a manual measurement method. For the cutting experiments, Inconel 718 alloy was machined using several cutting tools with different geometry, such as the helix angle, axial rake angle, and number of cutting edges. The images of the burr and slots were captured using a scanning electron microscope (SEM). The captured images were processed with computer vision software, which was written in C++ programming language and open-sourced computer library (Open CV). According to the results, it was determined that there is a good correlation between automated and manual measurements of slot and burr widths. The accuracy of the proposed method is above 91%, 98%, and 99% for up milling, down milling, and slot measurements, respectively. The conducted study offers a user-friendly, fast, and accurate solution using computer vision (CV) technology by requiring only one SEM image as input to characterize slot and burr formation.

Acoustic micromanipulation technologies are a set of versatile tools enabling unparalleled micromanipulation capabilities. Several characteristics put the acoustic micromanipulation technologies ahead of most of the other tweezing methods. For example, acoustic tweezers can be adapted as non-invasive platforms to handle single cells gently or as probes to stimulate or damage tissues. Besides, the nature of the interactions of acoustic waves with solids and liquids eliminates labeling requirements. Considering the importance of highly functional tools in biomedical research for empowering important discoveries, acoustic micromanipulation can be valuable for researchers in biology and medicine. Herein, we discuss the potential of acoustic micromanipulation technologies from technical and application points of view in biomedical research.

Precise control of fluid flows in microfluidics is crucial for various applications in lab-on-a-chip and pointof-care diagnostics. Standard bench-top equipment for providing this capability are syringe pumps. However, high cost of these systems limit their availability in low resourced laboratories. There are various open-sourced alternative syringe pump systems that can be fabricated and assembled using 3D printing, but they lack versatile control and flow rate characterization that are required for microfluidic applications. We report a simple and cost-effective approach to control an open-source multi-channel syringe pump. Simultaneous and adjustable flow control, and detailed characterization of the volume flow rates for different syringe volumes are also demonstrated.

The cell counting process is an important procedure for various cell and cell-related research applications. Many life science-related studies examine the cells to compare results concerning cell numbers and variations. Most of the related studies are conducted using manual counting methods. However, manual counting is difficult, time-consuming, and fallible. This study proposes an automated cell counting software using computer vision (CV) technology and experimental investigation for automated cell and bacterium counting. The software processes images for calculating cell/bacterium count, concerning pre-defined user parameters. In the experiments, cell and bacteria calculations are tested for single and mixed variations. Experimental results are examined by comparing manual and automated cell counting results. The accuracy of the software is found for calculating the cell count of a single and mixed cell/bacteria solution to be 99% and 98%, respectively. Also, the software can process video and camera streams in real-time. The computerized method is a good alternative due to providing accurate results and minimizing user-related errors. open-sourced CV software can be used in biomedical and fundamental biological research studies for rapidly determining target cell numbers.

Carbon fiber-reinforced plastics (CFRPs) have been specially developed to enhance the performance of commercial and military aircraft because of their strength, high stiffness-to-density ratios, and superior physical properties. On the other hand, fasteners and joints of CFRP materials may be weak due to occurring surface roughness and delamination problems during drilling operations. This study’s aim is to investigate the drilling characterization of CFRPs with different drilling parameters and cutting tools. Drilling tests were performed with the Taguchi orthogonal array design (L18: 2^1 3^3). Tests were conducted with three levels of cutting speed (15, 30, 45 m/min), three levels of feed rate (0.05, 0.1, 0.2 mm/rev), two levels of drill diameter (3 and 5 mm), and three different types of drills (two twist drills with a point angle of 138° and 120° and one brad drill). Thrust forces were recorded during drilling tests, and afterwards surface roughness and hole delamination were measured. Obtained results were analyzed with Taguchi and two-way ANOVA. The general tendency was that low cutting speed, high feed rate, and small diameter drill caused an increase in thrust force. Surface roughness decreases with increasing tool diameter, decreasing feed, and cutting speed. Delamination factors of the samples dropped depending on decreasing thrust force levels. Remarkably, it is possible to control the delamination factor values via better surface quality. The brad drill and larger point angle have a negative effect on the drilling quality of CFRPs. According to all results, the cutting speed of 45 m/min and feed rate of 0.05 mm/rev using a type II drill having a 120° point angle and 5 mm diameter (12th trial) and the cutting speed of 30 m/min and feed rate of 0.05 mm/rev using a type II drill having a 120° point angle and 3 mm diameter (2nd trial) were determined as optimum drilling conditions.