Qifei Wang

Nanomaterials mimicking the nano-features of bones and offering unique smart functions are promising for better bone fracture repair. This review provides an overview of the current state-of-the-art research in developing and using nanomaterials for better bone fracture repair. This review begins with a brief introduction of bone fracture repair processes, then discusses the importance of vascularization, the role of growth factors in bone fracture repair, and the failure of bone fracture repair. Next, the review discusses the applications of nanomaterials for bone fracture repair, with a focus on the recent breakthroughs such as nanomaterials leading to precise immobilization of growth factors at the molecular level, promoting vascularization without the use of growth factors, and re-loading therapeutic agents after implantation. The review concludes with perspectives on challenges and future directions for developing nanomaterials for improved bone fracture repair.

Single domain generalization aims to learn a model that performs well on many unseen domains with only one domain data for training. Existing works focus on studying the adversarial domain augmentation (ADA) to improve the model’s generalization capability. The impact on domain generalization of the statistics of normalization layers is still underinvestigated. In this paper, we propose a generic normalization approach, adaptive standardization and rescaling normalization (ASR-Norm), to complement the missing part in previous works. ASR-Norm learns both the standardization and rescaling statistics via neural networks. This new form of normalization can be viewed as a generic form of the traditional normalizations. When trained with ADA, the statistics in ASR-Norm are learned to be adaptive to the data coming from different domains, and hence improves the model generalization performance across domains, especially on the target domain with large discrepancy from the source domain. The experimental results show that ASR-Norm can bring consistent improvement to the state-of-the-art ADA approaches by 1.6%, 2.7%, and 6.3% averagely on the Digits, CIFAR-10-C, and PACS benchmarks, respectively. As a generic tool, the improvement introduced by ASR-Norm is agnostic to the choice of ADA methods.

Both oil spill and heavy-metal ions in the industrial wastewater cause severe problems for aquatic ecosystem and human health. In the present work, the electrospun superamphiphilic SiO2–TiO2 porous nanofibrous membranes (STPNMs) comprised of intrafiber mesopores and interfiber macropores are modified by an amino-silanization reaction, which affords the membrane (ASTPNMs) the ability to simultaneously remove the oil contaminants and the water-soluble heavy-metal ions from wastewater. The underwater superoleophobicity of ASTPNMs facilitates the highly efficient separation of water and various oils, even emulsifier-stabilized emulsion. Meanwhile, an optimal modification time (15 min, ASTPNM-15) is important for maintaining the under-oil superhydrophilicity of the membrane, based on which the oil contaminant in membrane can be easily cleaned by water alone, showing excellent self-cleaning performance. The adsorption of Pb2+ over ASTPNM-15 reaches equilibrium at around 20 min, and the monolayer adsorption capacity is 142.86 mg g–1 at pH = 5 at 20 °C. In the breakthrough processes, the permeation volume of ASTPNM-15 for the purification of Pb2+ (5 ppm, pH = 5) reaches 160 mL when the concentration of Pb2+ in the filtrate increases to 0.05 ppm. The separation efficiencies of ASTPNM-15 for simulated wastewater containing both oil spill and various heavy-metal ions (Pb2+, Cr3+, Ni2+) are larger than 99.5%. In addition, the separation capacity keeps stable over five purification–regeneration cycles without obvious decrease, proving excellent recyclability and reusability of ASTPNM-15 for practical applications.

Particulate matter (PM) discharged along with the rapid industrialization and urbanization hazardously threatens ecosystems and human health. Membrane-based filtration technology has been proved to be an effective approach to capture PM from the polluted air. However, the fabrication of filtration membranes with excellent reusability and antibacterial activity has rarely been reported. Herein, the flexible multifunctional porous nanofibrous membranes were fabricated by embedding Ag nanoparticles into the electrospun porous SiO2–TiO2 nanofibers via an impregnation method, which integrated the abilities of PM filtration and antibacterial performance. Compared with the reported air filters, the resultant membrane (Ag@STPNM) with high surface polarity and porous structure possessed the low density, high removal efficiency, and small pressure drop. For instance, the removal efficiency and the pressure drop of Ag@STPNM with a basis weight of only 3.9 g m–2 for PM2.5 reached 98.84% and 59 Pa, respectively. In terms of the excellent thermal stability of Ag@STPNM, the adsorbed PM could be removed simply by a calcination process. The filtration performance of Ag@STPNM kept stable during five purification–regeneration cycles and the long-time filtration for 12 h, exhibiting excellent recyclability and durability. Furthermore, the embedded Ag nanoparticles could achieve the effective resistance to the breeding of bacteria on Ag@STPNM, giving the bacteriostatic rate of 95.8%. Therefore, Ag@STPNM holds promising potentials as a highly efficient, reusable, and antibacterial air filter in the practical purification of the indoor environment or personal air.