Low-dimensional ZnO, possessing well-defined side facets and optical gain properties, has emerged as a promising material to develop ultraviolet coherent light sources. However, the realization of electrically driven ZnO homojunction luminescence and laser devices is still a challenge due to the absence of a reliable p-type ZnO. Herein, the sample of p-type ZnO microwires doped by Sb (ZnO:Sb MWs) was synthesized individually. Subsequently, the p-type conductivity was examined using a single-MW field-effect transistor. Upon optical pumping, a ZnO:Sb MW showing a regular hexagonal cross-section and smooth sidewall facets can feature as an optical microcavity, which is evidenced by the achievement of whispering-gallery-mode lasing. By combining an n-type ZnO layer, a single ZnO:Sb MW homojunction light-emitting diode (LED), which exhibited a typical ultraviolet emission at a wavelength of 379.0 nm and a line-width of approximately 23.5 nm, was constructed. We further illustrated that strong exciton-photon coupling can occur in the as-constructed p-ZnO:Sb MW/n-ZnO homojunction LED by researching spatially resolved electroluminescence spectra, contributing to the exciton-polariton effect. Particularly, varying the cross-sectional dimensions of ZnO:Sb wires can further modulate the exciton-photon coupling strengths. We anticipate that the results can provide an effective exemplification to realize reliable p-type ZnO and tremendously promote the development of low-dimensional ZnO homojunction optoelectronic devices.

The stiffness of a spindle at high speeds has a significant effect on the quality of the cutting surface and the machining accuracy. However, the spindle stiffness is difficult to be detected directly when the spindle is rotating, and the measured stiffness values are usually coupled with other parts of the spindle–tool system (such as toolholder, spindle–toolholder joint, tool). This paper presents a comprehensive method to deal with the stiffness modeling, identification, and measuring of a rotating spindle. Based on the deflection equation and the principle of superposition, the stiffness model is derived, for a spindle–tool system including a spindle, a specially manufactured toolholder, and a spindle–toolholder joint. A three-step identification algorithm is proposed to decouple and identify the actual spindle stiffness value. First, when the spindle is static, the stiffness values of the shaft, toolholder, and joint are obtained by using the least-squares method. Second, when the spindle is rotating, the stiffness values of the rear bearings and front bearings are identified based on the spindle error analysis method. Third, the stiffness values of the spindle under different rotating conditions are calculated based on the identification results from the previous two steps. Furthermore, the stiffness model and identification algorithm are verified experimentally on an instrumented spindle. The static stiffness value of the same spindle is also measured and compared with the stiffness value under rotating conditions subsequently. This work is useful and can be utilized as a guide for spindle stiffness testing and spindle performance evaluation to spindle manufacturers.

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In order to solve the problem of precision optimization design of CNC machine tools, this paper proposes an optimized allocation method of machine tool tolerance parameters that takes into account the slight deformation of the machine tool. First, establish a tolerance-based geometric error prediction model, and establish a spatial motion error model based on the theory of multi-body systems(MBS); Homogeneously, perform finite element analysis(FEA) on the CNC internal cylindrical compound grinding machine to obtain the slight deformation of the machine tool, and apply the result to the optimal tolerance allocation In the constraint conditions, the final optimal allocation plan is obtained; Finally, the genetic algorithm is used to simulate and analyze the plan, and the optimal tolerance allocation result is obtained. The result shows that most of the tolerance parameters have been relaxed, which means that the machine tool’s manufacturing cost. Through experiments, it is verified that the optimized machine tool machining accuracy pass rates are 98.5%, 98.25%, and 97.85%, respectively. Therefore, the optimal allocation method of tolerances that considers small deformations proposed in this paper is effective.

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