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The aim of this study is to examine when and why employee creative behavior leads to unethical pro-organizational behavior (UPB). Drawing on research on moral licensing, we argue that the relationship between employee creative behavior and UPB is indirectly mediated by moral licence.

The data were collected from 214 employees and their immediate supervisors, and the theoretical hypotheses were tested by correlation and a hierarchical regression analysis.

We found that: (1) employee creative behavior is positively correlated with their moral credentials and moral credits; (2) it supported the mediating role of moral credentials between creative behavior and UPB but did not support the relationship between creative behavior and UPB through moral credits and (3) the indirect relationship between creative behavior and UPB is strengthened through moral credentials when perceptions of organizational valuing of creativity are high.

This study responds to calls from researchers to explore more detrimental outcomes of creativity, and we extend existing research by empirically showing that creativity can promote some unethical pro-organizational behavior. We also contribute to explore the mediated role of moral licensing and the moderated role of the perceived organizational valuing of creativity to explain the creative behavior–UPB relationship.

Based on the pursuit of improving the temperature endurance capabilities of conventional superalloys for hot-end components, this paper aims to investigate the failure mechanisms of yttria-stabilized zirconia (YSZ) coatings fabricated by the atmospheric plasma spraying method at 1220 °C and 1260 °C.

Thermal spraying techniques are applied to produce thermal barrier coatings (TBCs) that offer superior thermal insulation, thermal shock resistance and thermal stability. The oxidation kinetics, the propagation patterns of cracks and the phase stability prior to failure of the coating were analyzed in detail.

The failure of coatings during static isothermal oxidation process is caused by slow crack initiation and propagation in the densification stage. External stress induces rapid initiation and propagation of cracks, leading to coating phase transformation. Cracks create pathways for oxygen diffusion and accelerate the growth of oxide layers.

This work aims to provide reliability data on the failure of TBCs, elucidate the high-temperature service characteristics of TBCs and provide theoretical basis for its performance improvement under extreme conditions.

This paper aims to focus on the research progress of intelligent self-healing anti-corrosion coatings in the aviation field in the past few years. The paper provides certain literature review supports and development direction suggestions for future research on intelligent self-healing coatings in aviation.

This mini-review uses a systematic literature review process to provide a comprehensive and up-to-date review of intelligent self-healing anti-corrosion coatings that have been researched and applied in the field of aviation in recent years. In total, 64 articles published in journals in this field in the last few years were analysed in this paper.

The authors conclude that the incorporation of multiple external stimulus-response mechanisms makes the coatings smarter in addition to their original self-healing corrosion protection function. In the future, further research is still needed in the research and development of new coating materials, the synergistic release of multiple self-healing mechanisms, coating preparation technology and corrosion monitoring technology.

To the best of the authors’ knowledge, this is one of the few systematic literature reviews on intelligent self-healing anti-corrosion coatings in aviation. The authors provide a comprehensive overview of the topical issues of such coatings and present their views and opinions by discussing the opportunities and challenges that self-healing coatings will face in future development.

The purpose of this study is to prepare trivalent chromium conversion (TCC) film on the Zn-Ni electrodeposited film on the surface of 2024 aluminum alloy and to ensure that the TCC film has good corrosion resistance and electrical conductivity.

The morphology of the TCC film was studied by scanning electron microscopy, and the elemental composition of the TCC film was characterized by X-ray energy dispersive spectroscopy. The TCC film was tested and the roughness was analyzed by 3D morphology (white light interference). The electrochemical behavior and corrosion resistance of TCC films were studied by the Tafel polarization curve and electrochemical impedance spectroscopy, and the conductivity was tested.

The TCC films were uniformly black and bright in appearance and were mainly compounds of Zn, Ni and Cr with O. The electrochemical impedance of the TCC film is larger than that of the Zn-Ni film, the corrosion current (I_corr) is smaller than that of the Zn-Ni film and the corrosion potential (E_corr) is larger than that of the Zn-Ni film, which has excellent corrosion resistance. TCCs were performed on the appropriate size of the shell sample, and the resistance of the shells was 1.5 mVDC, which meets the total resistance requirements of the test standard for composite connector accessories.

In this study, TCC film was successfully prepared on the Zn-Ni coating on the surface of 2024 aluminum alloy. The TCC film has good corrosion resistance and electrical conductivity.

This paper aims to propose a new ultrasonic detection method for stainless steel weld defects based on complex synergetic convolutional calculation to solve two problems in the ultrasonic detection of austenitic stainless steel weld defects. These include ignoring the nonlinear information of the imaginary part in the complex domain of the signal and the correlation information between the amplitude of the real part and phase of the imaginary part and subjective dependence of diagnosis model parameters.

An ultrasonic detection method for weld defects based on complex synergetic convolution calculation is proposed in this paper to address the above issues. By mapping low-density, 1D detection samples to a complex domain space with high representation richness, a multi-scale and multilevel complex synergetic convolution calculation model (CSCC) is designed to match and transform samples to mine amplitude changes, phase shifts, weak phase angle changes and amplitude-phase correlation features deeply from the detection signal. This study proposed an Elite Sine-Cosine Sobol Sampling Dung Beetle Optimization Algorithm, and the detection model CSCC achieves global adaptive matching of key hyperparameters in 19 dimensions. Finally, a regulative complex synergetic convolutional calculation model is constructed to achieve high-performance detection of weld defects.

Through experiments on a self-developed Taiyuan intelligent detection and information processing weld defect dataset, the results show that the method achieves a detection accuracy of 92% for five types of weld defects: cracks, porosity, slag inclusion and unfused and unwelded components, which represent an average improvement of 11% relative to comparable models. This method is also validated with the PhysioNet electrocardiogram public dataset, which achieves better detection performance relative to the other models.

This method provides a theoretical basis and technical reference for developing and applying intelligent, efficient and accurate ultrasonic defects detection technology.