Inverse design of Bézier curve-based mechanical metamaterials with programmable negative thermal expansion and negative Poisson's ratio via a data augmented deep autoencoder.

Controlling stress and deformation induced by thermo-mechanical stimulation in high-precision mechanical systems can be achieved by mechanical metamaterials (MM) exhibiting negative thermal expansion (NTE) and negative Poisson's ratio (NPR). However, the inverse design of MM exhibiting a wide range of arbitrary target NTEs and NPRs is a challenging task due to the low design flexibility of analytical methods and parametric studies based on numerical simulation. In this study, we propose Bézier curve-based programmable chiral mechanical metamaterials (BPCMs) and a deep autoencoder-based inverse design model (DAIM) for the inverse design of BPCMs. Through iterative transfer learning with data augmentation, DAIM can generate BPCMs with a curved rib shape inaccessible with the Bézier curve, which improves the inverse design performance of the DAIM in the data sparse domain. This approach decreases the mean absolute error of NTE and NPR between the inverse design target and the numerical simulation results of inverse designed BPCMs on the data-sparse domain by 79.25% and 83.33% on average, respectively. A 3D-printed BPCM is validated experimentally and exhibits good coincidence with the target NTE and NPR. Our proposed BPCM and the corresponding inverse design framework enable the inverse design of BPCMs with NTE in the range of -1100 to 0 ppm K-1 and NPR in the range of -0.6 to -0.1. Furthermore, programmable thermal deformation modes with a fixed Poisson's ratio are realized by combining various inverse designed BPCM unit cells. BPCMs and the DAIM for their inverse design are expected to improve the mechanical robustness of high-precision mechanical systems through tunable modulation of thermo-mechanical stimulation.

Correlation between Cellular Structure Morphology and Anisotropic Yield in Additively Manufactured Stainless Steel 316L.

Additively manufactured austenitic stainless steel 316L is composed of a cellular structure, which has a directionality, and is observed with a different morphology depending on the observation direction. The cellular structure morphology that appears with a high probability in grains with a specific grain orientation is determined. Taylor factor, which is calculated by considering grain orientation, is related to cellular structure morphology due to the directional cellular structure in additively manufactured austenitic stainless steel 316L. The Taylor factor affects the mechanical properties. The yield strength of additively manufactured SUS316L can be explained by the correlation between cellular structure morphology, grain orientation, and Taylor factor.

Electrospray mode discrimination with current signal using deep convolutional neural network and class activation map.

The electrospray process has been extensively applied in various fields, including energy, display, sensor, and biomedical engineering owing to its ability to generate of functional micro/nanoparticles. Although the mode of the electrospray process has a significant impact on the quality of micro/nano particles, observing and discriminating the mode of electrospray during the process has not received adequate attention. This study develops a simple automated method to discriminate the mode of the electrospray process based on the current signal using a deep convolutional neural network (CNN) and class activation map (CAM). The solution flow rate and applied voltage are selected as experimental variables, and the electrospray process is classified into three modes: dripping, pulsating, and cone-jet. The current signal through the collector is measured to detect the deposition of electrospray droplets on the collector. The 1D CNN model is trained using frequency data converted from the current data. The model exhibits excellent performance with an accuracy of 96.30%. Adoption of the CAM configuration enables the model to provide a discriminative cue for each mode and elucidate the decision-making process of the CNN model.

Morphological and Chemical Analysis of Various Disposable Acupuncture Needles Used in South Korea.

Objectives: The Korean Industrial Standard (KS) for sterile acupuncture needles was established in 2009 based on research on the quality control of acupuncture needles. We aimed to determine the quality of acupuncture needles available in South Korea in 2021 by examining their surface condition and chemical composition using field-emission scanning electron microscopy (FE-SEM) and energy-dispersive X-ray spectroscopy (EDS). Methods: In South Korea, there are 23 brands of acupuncture needles, and we examined 10-15 needles from each brand, resulting in a total of 285 needles. The microstructures of the needles were assessed by SEM. Using SEM images, we evaluated the acupuncture needle tips for the following defects/aspects scratches, lumps, detached coating, bent tip, and tip sharpness. EDS was used to determine the chemical composition of the selected acupuncture needles. Results: Overall, 88.4% of 285 needles were found to have at least one type of abnormality. The most frequently observed abnormalities were scratches and dents on the surface (68.1%), followed by detached coating (63.2%), and lumps (61.8%); blunt tips were observed in about 24% of them. Of 252 needles with at least one defect, 86.9% had two or more types of defects. The ratio of the number of needles with any defect to that of needles without any defect varied among brands, ranging from 50% to 100%. Regarding foreign materials, higher proportions of Si and O were observed on the needles, indicating incomplete or detached silicone coating. Conclusion: The quality of acupuncture needles varied among brands, suggesting that further improvements can be made through various inspection methods.

Fiber-optic OCT sensor guided "SMART" micro-forceps for microsurgery.

A handheld Smart Micromanipulation Aided Robotic-surgery Tool (SMART) micro-forceps guided by a fiber-optic common-path optical coherence tomography (CP-OCT) sensor is presented. A fiber-optic CP-OCT distance and motion sensor is integrated into the shaft of a micro-forceps. The tool tip position is manipulated longitudinally through a closed loop control using a piezoelectric motor. This novel forceps design could significantly enhance safety, efficiency and surgical outcomes. The basic grasping and peeling functions of the micro-forceps are evaluated in dry phantoms and in a biological tissue model. As compared to freehand use, targeted grasping and peeling performance assisted by active tremor compensation, significantly improves micro-forceps user performance.

A new method of fabricating robust freeform 3D ceramic scaffolds for bone tissue regeneration.

Fabrication of three-dimensional (3D) scaffolds with appropriate mechanical properties and desired architecture for promoting cell growth and new tissue formation is one of the most important efforts in tissue engineering field. Scaffolds fabricated from bioactive ceramic materials such as hydroxyapatite and tricalcium phosphate show promise because of their biological ability to support bone tissue regeneration. However, the use of ceramics as scaffold materials is limited because of their inherent brittleness and difficult processability. The aim of this study was to create robust ceramic scaffolds, which have a desired architecture. Such scaffolds were successfully fabricated by projection-based microstereolithography, and dilatometric analysis was conducted to study the sintering behavior of the ceramic materials. The mechanical properties of the scaffolds were improved by infiltrating them with a polycaprolactone solution. The toughness and compressive strength of these ceramic/polymer scaffolds were about twice those of ceramic scaffolds. Furthermore, the osteogenic gene expression on ceramic/polymer scaffolds was better than that on ceramic scaffolds. Through this study, we overcame the limitations of previous research on fabricating ceramic scaffolds and these new robust ceramic scaffolds may provide a much improved 3D substrate for bone tissue regeneration.