Severe bone damage from diseases, including extensive trauma, fractures, and bone tumors, cannot self-heal, while traditional surgical treatment may bring side effects such as infection, inflammation, and pain. As a new biomaterial with controllable mechanical properties and biocompatibility, hydrogel is widely used in bone tissue engineering (BTE) as a scaffold for growth factor transport and cell adhesion. In order to make hydrogel more suitable for the local treatment of bone diseases, hydrogel preparation methods should be combined with synthetic materials with excellent properties and advanced technologies in different fields to better control drug release in time and orientation. It is necessary to establish a complete method to evaluate the hydrogel’s properties and biocompatibility with the human body. Moreover, establishment of standard animal models of bone defects helps in studying the therapeutic effect of hydrogels on bone repair, as well as to evaluate the safety and suitability of hydrogels. Thus, this review aims to systematically summarize current studies of hydrogels in BTE, including the mechanisms for promoting bone synthesis, design, and preparation; characterization and evaluation methods; as well as to explore future applications of hydrogels in BTE.

No abstract

Solid polymer electrolytes (SPEs) can alleviate the safety issues existing in commercialized lithium ion batteries with liquid electrolyte. However, the low room-temperature ionic conductivity and poor mechanical properties of current polymer electrolyte hinder its practical applications. Herein, a composite solid polymer electrolyte consisting of poly­(ethylene oxide) (PEO), the solid plasticizer succinonitrile (SN), and a 3D framework glass fiber (GF) with high ionic conductivity and good mechanical property is proposed. The optimized composite electrolyte PEO–SN25–LiTFSI10–GF has a room-temperature ionic conductivity of 2.85 × 10–4 S cm–1, which is 100 times higher than that of pristine PEO. An electrochemical window up to 5.5 V and a tensile strength of over 8 MPa are also exhibited by the optimized composite electrolyte. The solid-state LiFePO4/PEO–SN25–LiTFSI10–GF/Li battery shows good cyclic performance with a capacity retention of 98.5% after 100 cycles at 0.2 C under room temperature, demonstrating a promising polymer composite electrolyte for the next-generation solid-state lithium batteries with high energy density and high safety.

First-principles calculations have been performed on the electronic structures for Ru n ͑n =2-14͒ clusters. The calculations show that square represents the basic unit in the growth of Ru n clusters. For the stability, odd-even oscillation with respect to the cluster size is observed. Correspondingly, those clusters comprising integer number of square units are magic clusters with high stability. Simple cubic growth mode is detected with cluster size increasing, in line with latest publication. However, for some clusters, such as Ru 13 , more stable structures different from previous calculated results have been found. The calculated magnetic moment for the ground state of Ru 13 ͑0.15 B /atom͒ agrees better with experimental observation ͑Ͻ0.29 B /atom͒ than those obtained before. The current optimized new structure is also found to be favored for some other 13-atom 4d transition metal clusters, such as Tc 13 . Our findings may thoroughly resolve a long standing discrepancy between theories and experiments and contribute basic data for design of novel catalysts.

An exoskeleton robot is an external structural mechanism with joints and links corresponding to those of the human body. When it is worn, it transmits torques from actuators through rigid exoskeletal links to the human joints. We have been developing exoskeleton robots for assisting the motions of physically weak persons such as elderly or disabled in daily life. In this paper, we propose an electromyogram (EMG) based control (i.e., control based on the skin surface EMG signals of the user) for the exoskeleton robot to assist physically weak person's lower-limb motions. The skin surface EMG signals are mainly used as the input information for the controller. In order to generate flexible and smooth motions and take into account the changing EMG signal levels according to the physical and psychological conditions of the user, fuzzy-neuro control method has been applied for the controller. The experimental results show the effectiveness of the designed EMG-based controller for the power-assist.