structure design
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2022 ◽  
Vol 429 ◽  
pp. 132286
Weiqin Lu ◽  
Rongjun Zhang ◽  
Sam Toan ◽  
Ran Xu ◽  
Feiyi Zhou ◽  

2022 ◽  
pp. 1-10
Yohei Yamamoto ◽  
Jun Mitani

Abstract Origami techniques, as folding and unfolding, can be utilized in shrinkable structures. Especially when the crease pattern is rigid foldable, it can be treated as a mechanical linkage of rigid panels connected by hinges. Since rigid foldable crease patterns have the strong geometrical constraint of the facets not being able to stretch or bend, it is difficult to design new crease patterns, and variations of existing patterns are limited. However, it is known that there are cases where crease patterns can be made rigid foldable by adding some slits. This paper proposes a mechanical linkage that folds into a similar flat shape by adding slits. A method is presented of generating rigid foldable crease patterns in arbitrary polygons that fold smaller, and it is confirmed that structures that have a mechanism for shrinking can be generated from these crease patterns by using rigid thick panels and hinges.

Micromachines ◽  
2022 ◽  
Vol 13 (1) ◽  
pp. 111
Cheng Yang ◽  
Shuxiang Guo ◽  
Xianqiang Bao

Interventional surgical robots are widely used in neurosurgery to improve surgeons’ working environment and surgical safety. Based on the actual operational needs of surgeons’ feedback during preliminary in vivo experiments, this paper proposed an isomorphic interactive master controller for the master–slave interventional surgical robot. The isomorphic design of the controller allows surgeons to utilize their surgical skills during remote interventional surgeries. The controller uses the catheter and guidewire as the operating handle, the same as during actual surgeries. The collaborative operational structure design and the working methods followed the clinical operational skills. The linear force feedback and torque feedback devices were designed to improve the safety of surgeries under remote operating conditions. An eccentric force compensation was conducted to achieve accurate force feedback. Several experiments were carried out, such as calibration experiments, master–slave control performance evaluation experiments, and operation comparison experiments on the novel and previously used controllers. The experimental results show that the proposed controller can perform complex operations in remote surgery applications and has the potential for further animal experiment evaluations.

Small ◽  
2022 ◽  
pp. 2104469
Junbao Kang ◽  
Xiaohui Tian ◽  
Chenzheng Yan ◽  
Liying Wei ◽  
Lu Gao ◽  

Materials ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 478
Roman Hrytsak ◽  
Pawel Kempisty ◽  
Ewa Grzanka ◽  
Michal Leszczynski ◽  
Malgorzata Sznajder

The formation and diffusion of point defects have a detrimental impact on the functionality of devices in which a high quality AlN/GaN heterointerface is required. The present paper demonstrated the heights of the migration energy barriers of native point defects throughout the AlN/GaN heterointerface, as well as the corresponding profiles of energy bands calculated by means of density functional theory. Both neutral and charged nitrogen, gallium, and aluminium vacancies were studied, as well as their complexes with a substitutional III-group element. Three diffusion mechanisms, that is, the vacancy mediated, direct interstitial, and indirect ones, in bulk AlN and GaN crystals, as well at the AlN/GaN heterointerface, were taken into account. We showed that metal vacancies migrated across the AlN/GaN interface, overcoming a lower potential barrier than that of the nitrogen vacancy. Additionally, we demonstrated the effect of the inversion of the electric field in the presence of charged point defects VGa3− and VAl3− at the AlN/GaN heterointerface, not reported so far. Our findings contributed to the issues of structure design, quality control, and improvement of the interfacial abruptness of the AlN/GaN heterostructures.

Guangda Qiao ◽  
Hengyu Li ◽  
Xiaohui Lu ◽  
Jianming Wen ◽  
Tinghai Cheng

Piezoelectric stick-slip actuators (PSSAs) are famous for ultimate working condition adaptability, simple structure, and positioning accuracy. To meet the demand of industrial application, lots of PSSAs designed with flexure hinge mechanisms (FHMs-PSSAs) have been developed to realize the requirements of translational motion, rotational motion, multi-degree-of-freedom (multi-DOF) motion. The output performance of the FHMs-PSSAs has been greatly improved, including load capacity, speed, and accuracy; moreover, some approaches to solve the problem of the backward motion are provided as well. In this work, the working principle of FHMs-PSSAs is introduced, and the excitation signals applicable to FHMs-PSSAs are summarized. Based on the current research and development status, the progress of structure design of FHMs-PSSAs is introduced in accordance with translatory FHMs-PSSAs, rotary FHMs-PSSAs, and multi-DOF FHMs-PSSAs. Additionally, the developed analysis methods and design schemes to improve the performance are introduced, including theoretical analysis methods, consistency scheme of forward and reverse performance, suppression scheme of the backward motion, and improvement scheme of positioning accuracy. The significance of this work can be regarded as a further supplement to the previous review articles on the PSSAs, which will provide a reference and guidance for the future development of FHMs-PSSAs.

2022 ◽  
Vol 8 ◽  
Bing Duan ◽  
Bei Wu ◽  
Jin-hui Chen ◽  
Huanyang Chen ◽  
Da-Quan Yang

Innovative techniques play important roles in photonic structure design and complex optical data analysis. As a branch of machine learning, deep learning can automatically reveal the inherent connections behind the data by using hierarchically structured layers, which has found broad applications in photonics. In this paper, we review the recent advances of deep learning for the photonic structure design and optical data analysis, which is based on the two major learning paradigms of supervised learning and unsupervised learning. In addition, the optical neural networks with high parallelism and low energy consuming are also highlighted as novel computing architectures. The challenges and perspectives of this flourishing research field are discussed.

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