Zhengyan Zhang

Soft electrothermal actuators have attracted increasing attention in soft robotics and wearable systems due to their simple structure, low driving voltage, and ease of integration. However, traditional designs based on homogeneous or layered composites often suffer from interfacial failure and limited deformation modes, restricting their long-term stability and actuation versatility. In this study, we present a programmable soft electrothermal actuator based on a functionally graded structure composed of polydimethylsiloxane (PDMS)/multiwalled carbon nanotube (MWCNTs) composite material and an embedded EGaIn conductive circuit. Rheological and mechanical characterization confirms the enhancement of viscosity, modulus, and tensile strength with increasing MWCNTs content, confirming that the gradient structure improves mechanical performance. The device shows excellent actuation performance (bending angle up to 117°), fast response (8 s), and durability (100 cycles). The actuator achieves L-shaped, U-shaped, and V-shaped bending deformations through circuit pattern design, demonstrating precise programmability and reconfigurability. This work provides a new strategy for realizing programmable, multimodal deformation in soft systems and offers promising applications in adaptive robotics, smart devices, and human–machine interfaces.

Laser Powder Bed Fusion (LPBF) presents a more extensive allowable design complexity and manufacturability compared with the traditional manufacturing processes by depositing materials in a layer-wised manner. However, the process variability in the LPBF process induces quality uncertainty and inconsistency. Specifically, the mechanical properties, e.g., tensile strength, are hard to be predicted and controlled in the LPBF process. Much research has recently been reported exploring the qualitative influence of single/two process parameters on tensile strength. In fact, mechanical properties are comprehensively affected by multiple correlated process parameters with unclear and complex interactions. Thus, the study on the quantitative process-quality model of the metal LPBF process is urgently needed to provide an enough-strength component via the metal LPBF process. Recent progress in artificial intelligence (AI) and machine learning (ML) provides new insight into quality prediction in terms of computational accuracy and speed. However, the predictive model quality through the traditional AL/ML is heavily determined by the training data size, and the experimental analysis can be expansive on LPBF. This paper explores the comprehensive effect of the tensile strength of 316L stainless-steel parts on LPBF and proposes a valid quantitative predictive model through a novel self-growing machine-learning framework. The self-growing framework can autonomously expand and classify the growing dataset to provide a high-accuracy prediction with fewer input data. To verify this predictive model of tensile strength, specimens manufactured by the LPBF process with different group process parameters (laser power, scanning speed, and hatch spacing) are collected. The experimental results validate the predicted tensile strengths within a less than 3% deviation.

Resonant walking with preferred gait features is a self-optimized consequence of long-term human locomotion. Minimal energy expenditure can be achieved in this resonant condition. This unpowered multi-joint soft exoskeleton is designed to test whether: (1) there is an obvious improvement in preferred speed and other gait features; (2) resonant walking still exists with exoskeleton assistance. Healthy participants (N = 7) were asked to perform the following trials: (1) walking at 1.25 m/s without assistance (normal condition); (2) walking at 1.25 m/s with assistance (general condition); (3) walking at preferred speed with assistance (preferred condition); (4) walking at the speed in trial (3) without assistance (comparison condition). Participants walked at the preferred frequency and ±10% of it. An average 21% increase in preferred speed was observed. The U-shaped oxygen consumption and lower limb muscle activity curve with the minimum at preferred frequency indicated that the resonant condition existed under the preferred condition. Average metabolic reductions of 4.53% and 7.65% were found in the preferred condition compared to the general and comparison condition, respectively. These results demonstrate that the resonant condition in assisted walking could benefit energy expenditure and provide a new perspective for exoskeleton design and evaluation.

Conventional lower-limb rehabilitation robots cannot provide in-time rehabilitation training for stroke patients in the acute stage due to their large size and mass as well as their complex wearing process. Aiming to solve the problems, first, a novel hybrid end-traction lower-limb rehabilitation robot (HE-LRR) was designed as the lower-limb rehabilitation requirement of patients in the acute stage, in this paper. The usage of (2-UPS + U)&(R + RPS)&(2-RR) hybrid mechanism and a mirror motion actuator had the advantages of compact structure, large working space and short wearing time to the HE-LRR. Then, the mobility of the HE-LRR was calculated and the motion property was analyzed based on screw theory. Meanwhile, the trajectory planning of the HE-LRR was carried out based on MOTOmed^® motion training. Finally, the motion capture and surface electromyography (sEMG) signal acquisition experiments in the MOTOmed motion training were performed. The foot trajectory experimental effect and the lower-limb muscle groups activation rules were studied ulteriorly. The experimental results showed that the HE-LRR achieved good kinematic accuracy and lower limb muscle groups training effect, illustrating that the HE-LRR possessed good application prospects for the lower-limb rehabilitation of patients in the acute stage. This research could also provide a theoretical basis for improving the standardization and compliance of lower-limb robot rehabilitation training.

Electrohydrodynamic (EHD) printing has great potential to be used in the field of electronic industry, precision optics and biological engineering. However, it is still a challenge to achieve a high scaling ratio for line patterns production by EHD jet printing technique, which can effectively prevent the needles to be blocked. In this paper, the influence of the key process parameters on the line width of EHD jet printing was investigated. The printing needle with the inner diameter of 890 μm was used, and the line with width of 3.02 μm was printed by optimizing the parameters. The scaling ratio between the needle inner diameter and the printed line width was up to 295 times. At the same time, the function model between the flow rate and printed line width of PVP/PEO composite was deduced. The error was found to be less than 1% by the verification of experiments. By utilizing this model, the printed line width can be predicted by controlling the flow rate, which will greatly improve the work efficiency. By controlling the flow rate, the goal of printing on demand can be realized. The proposed method and model can provide support for the fabrication of micro‐nano scale structure.

Nanofluidic devices with two-dimensional nanochannels have many applications in biology and chemistry, however, it is still a challenge to develop a low-cost and simple method for fabricating nano-masks that can be used to produce two-dimensional nanochannels. In this paper, a novel low-cost and simple method, based on UV lithography and oxygen plasma, was proposed to fabricate nano-mask. The influence of exposure time on the photoresist mesas was investigated in the ultraviolet lithography process. The parameters of RF power and treatment time on the width reduction of photoresist mesas were analyzed by the oxygen plasma. In our work, in order to increase the efficiency controllability of photoresist removal, a RF power of 90 W, a pressure of oxygen plasma 60 Pa, and the time division method were adopted to remove photoresist by oxygen plasma. Finally, nano-patterns of photoresist mesas with bottom width of 330 nm were successfully fabricated. The proposed method provides a low-cost way to produce high-throughput two-dimensional nanochannels.

Bioceramics have frequent use in functional restoration of hard tissues to improve human well-being. Additive manufacturing (AM) also known as 3D printing is an innovative material processing technique extensively applied to produce bioceramic parts or scaffolds in a layered perspicacious manner. Moreover, the applications of additive manufacturing in bioceramics have the capability to reliably fabricate the commercialized scaffolds tailored for practical clinical applications, and the potential to survive in the new era of effective hard tissue fabrication. The similarity of the materials with human bone histomorphometry makes them conducive to use in hard tissue engineering scheme. The key objective of this manuscript is to explore the applications of bioceramics-based AM in bone tissue engineering. Furthermore, the article comprehensively and categorically summarizes some novel bioceramics based AM techniques for the restoration of bones. At prior stages of this article, different ceramics processing AM techniques have been categorized, subsequently, processing of frequently used materials for bone implants and complexities associated with these materials have been elaborated. At the end, some novel applications of bioceramics in orthopedic implants and some future directions are also highlighted to explore it further. This review article will help the new researchers to understand the basic mechanism and current challenges in neophyte techniques and the applications of bioceramics in the orthopedic prosthesis.