The aim of this paper is to compare the mechanical property and machinability of Polyetheretherketone (PEEK) and 30 wt% carbon-fibers reinforced Polyetheretherketone (PEEK CF 30). The method of nano-indentation is used to investigate the microscopic mechanical property. The evolution of load with displacement, Young’s modulus curves and hardness curves are analyzed. The results illustrate that the load-displacement curves of PEEK present better uniformity, and the variation of Young’s modulus and hardness of PEEK both change smaller at the experimental depth. The machinability between PEEK and PEEK CF 30 are also compared by the method of single-point diamond turning (SPDT), and the peak-to-valley value (PV) and surface roughness (Ra) are obtained to evaluate machinability of the materials after machining. The machining results show that PEEK has smaller PV and Ra, which means PEEK has superior machinability.

Amphiphilic copolymers can self-assemble into nano-objects in aqueous solution. However, the self-assembly process is usually performed in a diluted solution (<1 wt%), which greatly limits scale-up production and further biomedical applications. With recent development of controlled polymerization techniques, polymerization-induced self-assembly (PISA) has emerged as an efficient approach for facile fabrication of nano-sized structures with a high concentration as high as 50 wt%. In this review, after the introduction, various polymerization method-mediated PISAs that include nitroxide-mediated polymerization-mediated PISA (NMP-PISA), reversible addition-fragmentation chain transfer polymerization-mediated PISA (RAFT-PISA), atom transfer radical polymerization-mediated PISA (ATRP-PISA), and ring-opening polymerization-mediated PISA (ROP-PISA) are discussed carefully. Afterward, recent biomedical applications of PISA are illustrated from the following aspects, i.e., bioimaging, disease treatment, biocatalysis, and antimicrobial. In the end, current achievements and future perspectives of PISA are given. It is envisioned that PISA strategy can bring great chance for future design and construction of functional nano-vehicles.

Compound sinusoidal grid surface with nanometric finish plays a significant role in modern systems and precision calibrator, which can make the systems smaller, the system structure more simple, reduce the cost, and promote the performance of the systems, but it is difficult to design and fabricate by traditional methods. In this paper, a compound freeform surface constructed by a paraboloidal base surface and sinusoidal grid feature surface is designed and machined by slow tool servo (STS) assisted with single point diamond turning (SPDT). A novel combination of the constant angle and constant arc-length method is presented to optimize the cutting tool path. The machining error prediction model is analyzed for fabricating the compound sinusoidal grid surface. A compound sinusoidal grid surface with 0.03 mm amplitude and period of 4 is designed and cutting process is simulated by use of MATLAB software, machining experiment is done on ultra-precision machine tool, the surface profile and topography are measured by Taylor Hobson and Keyence VR-3200, respectively. After dealing with the measurement data of compound freeform surface, form accuracy 4.25 μm in Peak Village value (PV), and surface roughness 89 nm in Ra are obtained for the machined surface. From the theoretical analysis and experimental results, it can be seen that the proposed method is a reasonable choice for fabricating the compound sinusoidal grid surface.

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The application of silicon carbide (SiC) is often limited due to its low machining efficiency and unpredictability about the results of the grinding process. The aim of this paper is to set up finite element analysis models (FEM) about microgrinding process of SiC, to study the change processes about tangential and normal grinding force which can lead to stress and strain inside SiC material under different grinding parameters, and to predict the results before the grinding process. Adaptive remeshing technique is used to minimize the computational time without sacrificing the accuracy of the results in the simulation of SiC grinding process. The research results can be used to choose reasonable grinding parameters based on the required surface quality.