The critical information regarding the semiconductor manufacturing can be provided based on the wafer map defect patterns. Automatic wafer map defect identification with machine learning methods has recently received increasing attention. The wafer map defect recognition problem can be tackled in two steps. Firstly, hybrid features including Radon-based features, density-based features, and autoencoder-based features are extracted. Then two novel large-margin extreme learning machine (LM-ELM) methods are proposed for wafer map defect recognition. Compared with classical extreme learning machines, these approaches take the large absolute/relative margin constraint on the regression target vector into consideration, resulting in two novel ELM variants referred to as large-absolute-margin extreme learning machine (LAM-ELM) and large-relative-margin extreme learning machine (LRM-ELM). The convexity of the proposed methods is proved which can guarantee the unique optimal solution. Furthermore, the algorithms to solve both LAM-ELM and LRM-ELM are provided and convergence analysis of the presented algorithms are conducted. The experiments show that the proposed methods performs better than other competing approaches with an accuracy of 98.26% on the WM-811K dataset.

To benefit tissue removal and postoperative rehabilitation, increased efficiency and accuracy and reduced operating force are strongly required in the osteotomy. A novel elliptical vibration cutting (EVC) has been introduced for bone cutting compared with conventional cutting (CC) in this paper. With the assistance of high-speed microscope imaging and the dynamometer, the material removals of cortical bone and their cutting forces from two cutting regimes were recorded and analysed comprehensively, which clearly demonstrated the chip morphology improvement and the average cutting force reduction in the EVC process. It also revealed that the elliptical vibration of the cutting tool could promote fracture propagation along the shear direction. These new findings will be of important theoretical and practical values to apply the innovative EVC process to the surgical procedures of the osteotomy.

Bone cutting with high performance material removal is critical for enhancing orthopedic surgery. Ultrasonically assisted cutting (UAC) is an advanced process with the potential to improve the material removal. However, strain and other intermediate variables in bone cutting are difficult to obtain because of the lack of suitable measurement methods, especially for high-frequency vibration-assisted cutting. In this study, digital image correlation (DIC) analysis was applied for the first time to investigate the full-field strain map and the mechanism of crack development during conventional cutting (CC) and ultrasonically assisted cutting of cortical bone. A novel method for calculating cutting and thrust forces under the mixed fracture mode of bone was also proposed. Extensive experimental results showed that the average strain and strain rate of cortical bone decreased after the application of UAC, but the maximum transient strain rate in UAC was greater than that in CC, and the crack-affected area and shear band width in UAC were smaller than those in CC. In addition, the strain parameters obtained by the DIC analysis were used to calculate the cutting and thrust forces in the hybrid fracture mode. The calculated values of forces matched well (over 90%) with the measured results, indicating the strong feasibility of DIC applications in orthogonal bone cutting research. This study has significant theoretical and practical value since it reveals the fracture mechanism of cortical bone in UAC, demonstrates a non-contact full-field measurement method for tissue strain calculation, and provides inspiration for optimizing the design of innovative orthopedic instruments.

This paper introduces a pioneering approach that combines ex situ synthesis with advanced manufacturing to develop ZIF-67-PA12 Nylon composites with mixed-matrix membranes (MMMs), with the goal of enhancing hydrogen storage systems. One method involves producing MOF-PA12 composite powders through an in situ process, which is then commonly used as a base powder for powder bed fusion (PBF) to fabricate various structures. However, developing the in situ MOF-PA12 matrix presents challenges, including limited spreadability and processability at higher MOF contents, as well as reduced porosity due to pore blockage by polymers, ultimately diminishing hydrogen storage capacity. To overcome these issues, PBF is employed to form PA12 powder into films, followed by the ex situ direct synthesis of ZIF-67 onto these substrates at loadings exceeding those typically used in conventional MMM composites. In this study, ZIF-67 mass loadings ranging from 2 to 30 wt.% were synthesized on both PA12 powder and printed film substrates, with loadings on printed PA12 films extended up to 60 wt.%. ZIF-67-PA12-60(f) demonstrated a hydrogen capacity of 0.56 wt.% and achieved 1.53 wt.% for ZIF-67-PA12-30(p); in comparison, PA12 exhibited a capacity of 0.38 wt.%. This was undertaken to explore a range of ZIF-67 Metal–organic frameworks (MOFs) to assess their impact on the properties of the composite, particularly for hydrogen storage applications. Our results demonstrate that ex situ-synthesized ZIF-67-PA12 composite MMMs, which can be used as a final product for direct application and do not require the use of in situ pre-synthesized powder for the PBF process, not only retain significant hydrogen storage capacities, but also offer advantages in terms of repeatability, cost-efficiency, and ease of production. These findings highlight the potential of this innovative composite material as a practical and efficient solution for hydrogen storage, paving the way for advancements in energy storage technologies.

Modern-day microtomy requires high precision equipment to thinly section biological tissues. The sectioned tissue must be of good quality not showing cutting tracks or so-called artefacts. The quality of these sections is dependent on the blade wear, which is related to the hardness of the tissue sample, cutting angle and cutting speed. A test rig has been designed and manufactured to allow these parameters to be controlled. This has allowed for the blade wear to be analysed and quantified, and this has been completed for both ultrasonically assisted and conventional cutting. The obtained results showed a 25.2% decrease in average blade roughness after 38 cuts when using the ultrasonically assisted cutting regime. The data also showed no adverse effect on the quality of the slides produced when using this cutting methodology. Finally, the cutting force measured for both cutting regimes showed that ultrasonically assisted cutting required less force compared to conventional cutting. With the reduction of surface roughness and force, it is possible to state that ultrasonically assisted cutting reduces the wear of the blade, thereby increasing the life of the blades. An increase of just 10% in blade life would yield a cost saving of approximately 25% thereby reducing the environmental and financial impact of microtomy.