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This study examines the mechanical properties and wear mechanisms of magnesium (Mg) metal matrix composites reinforced with titanium (Ti) and silicon carbide (SiC) particles. Three different composite formulations were investigated: Mg-30 wt% Ti (A), Mg-25 wt% Ti-5 wt.% SiC (NB), Mg-20 wt% Ti-10 wt% SiC (NC), and Mg-15 wt% Ti-15 wt% SiC (ND). These composites were fabricated through ball milling and spark plasma sintering (SPS). The incorporation of SiC particles significantly enhanced grain refinement and phase formation within the composites. Density analysis revealed that the actual densities of the composites were lower than the theoretical values, with Composite A exhibiting the highest actual density of 2.15 g/cm³ and the lowest porosity of 16.31%. The introduction of SiC particles increased porosity, with Composite NB displaying the highest porosity at 30.58%. Hardness testing indicated that Composite NC, containing 10 wt% SiC, achieved the highest hardness of 137 HV. In contrast, Composite ND, with 15 wt% SiC, showed a reduced hardness of 115 HV, attributed to increased porosity and potential SiC particle agglomeration. Wear behavior was evaluated using a pin-on-disc tribometer. Weight loss measurements indicated that Composite A had the lowest weight loss (1.1–2.1 mg), while Composite NB experienced the highest weight loss (2.8–8.3 mg) due to increased porosity. Composite NC demonstrated a balance with moderate weight loss (2.0–3.8 mg). The coefficient of friction (COF) varied with SiC content and applied loads (2, 4, and 8 N), with Composite A demonstrating the lowest COF values (2.3–2.8) and stable performance across different loads. Composite NB exhibited higher COF values (3.5–4) and significant fluctuations due to elevated porosity and the presence of SiC particles. Composite NC showed better wear resistance and more stable COF values (2.5–2.9) compared to NB and ND.

[Purpose/Significance] The research on libraries' artificial intelligence (AI) readiness and the influencing factors can help those libraries that are not ready to use AI technology to improve relevant conditions, so as to be ready to adopt AI technology for the first time. It can also help the libraries that have used AI technology to further improve the existing conditions, so as to be ready to upgrade or fully apply AI technology. This paper summarizes the influencing factors of libraries' AI readiness and constructs a theoretical model consisting of 1 core category, 4 main categories and 10 categories. [Method/Process] This paper uses an in-depth interview and grounded theory to construct the theoretical model of influencing factors. The basic process is as follows: To define the main concepts, design the outline of the in-depth interview, obtain the original data through the interview, open up the code of the original resources to form a series of initial concepts and cluster them into categories, encode the categories on the main axis to form several main categories, selectively encode the main categories to form a core category, and establish the relationship between categories. The model and hypotheses are verified by questionnaire and structural equation model. [Results/Conclusions] The results show that 9 of the 10 hypotheses proposed in the paper are valid. The nine factors including AI awareness, AI acceptance, AI value perception, AI application experience, data scale, leadership attention, innovation atmosphere, management mechanism and competitive pressure have a positive impact on a library's readiness to adopt AI. The positive impact of leadership attention is the largest, and the positive impact of competitive pressure is the smallest. The theoretical model needs to be further revised. Leaders' attention, AI application experience, AI acceptance, AI awareness and innovation atmosphere are the main influencing factors of the library's AI readiness. Accordingly, this paper gives the following suggestions. Firstly, library leaders are suggested to actively understand the latest technological progress in the field of library business, organize human resources to regularly evaluate the library's AI readiness and deploy the AI system in time. Secondly, libraries provide necessary AI training for their staff, and help them improve their awareness and acceptance of AI. Thirdly, libraries create a strong innovation atmosphere, stimulate the innovation enthusiasm of employees, and encourage employees to explore the possibility of integrating AI technology with their job tasks through various ways.

Despite the importance of physical understanding of interfacial thermal conductance (G) for metal/graphene (Gr)/dielectric interfaces, there exists a large discrepancy regarding the role of dielectric substrates in thermal transport across graphene interfaces in previous studies. In this work, we experimentally investigate the impact of dielectric substrates on thermal transport across metal/Gr/dielectric interfaces through accurately measuring G for various Al/Gr/dielectric interfaces over a temperature range of 80–300 K, using both standard time-domain thermoreflectance (TDTR) and differential TDTR. We find that G of Al/Gr/dielectric falls within the range of 29–36 MW m−2 K−1 at room temperature and displays notably weak substrate dependence even with the dielectric Debye temperature ranging from 500 to 1050 K. This substrate independence is attributed to the dominant role of phonon transmission at metal/Gr interfaces in thermal transport across metal/Gr/dielectric interfaces, and the insignificant impacts of phonon density of states overlap on G for Gr/dielectric interfaces. Moreover, through the comparison of our measured G for both Gr/crystalline-Al2O3 and Gr/amorphous-Al2O3, we demonstrate that contrary to previous predictions, the crystalline and amorphous forms of dielectrics do not play a substantial role in thermal transport across graphene interfaces. Our work fills the gap in experimental data on G for metal/Gr/dielectric interfaces and provides valuable insights into physical understanding of thermal transport mechanisms across such interfaces. [ABSTRACT FROM AUTHOR]

Previous studies have established the use of various blue pigments, including both local and imported varieties, in the decoration of architecture in ancient China. However, the application of these pigments in local religious architecture has been understudied. In this study, the chemical analysis of ultramarine blue pigments was conducted on a mural painting retrieved from Yongle Taoist Temple in ancient China. The results showed that both imported and local pigments were used individually in the initial drawing period of the Yuan Dynasty (AD 1271–1368), whereas they were mixed in a later restoration in the Qing Dynasty (AD 1636–1912). Of particular significance, the analysis revealed the presence of lapis lazuli in a local religious relic of the Yuan Dynasty for the first time. Further analysis of the elemental proportions and associated minerals led to speculation about the origin of the lapis lazuli, which is believed to have come from Badakhshan, the northeastern region of Afghanistan, and been transported to Central China through the Silk Road. This finding shed light on the trade routes and usage of these pigments in the construction of religious architecture from the Yuan to the Qing dynasties. [ABSTRACT FROM AUTHOR]

Carbon fiber reinforced polymer (CFRP) has a wide range of applications in aerospace, automobile, marine, and other industries, due to its remarkable mechanical properties and lightweight. It can enhance the performance of the structural components and has been presented to be a good alternative over conventional materials. Adhesive bonding has been widely employed, and research studies on the surface modification of CFRP have been conducted to improve the load resistance of adhesive bonding, of which atmospheric pressure (AP) plasma is the most preferred method. However, there is still a lack of study on the effectiveness and strategies of AP plasma surface modification. To gain more insight, possible sources that would have influence on the adhesive bonding were analyzed by preparation of different surface configurations of CFRP. It is confirmed that AP plasma can increase the surface polarity and wettability of the carbon fiber surface. It can contribute to the removal of surface contamination element as well. Although the surface morphology and surface roughness before and after the AP plasma treatment does not show noticeable changes, the single‐lap shear strength of the contaminated samples can be effectively improved. This study validates that AP plasma is effective on surface contamination removal and bonding quality improvement, which provides a potential alternative for the adhesive bonding improvement and surface modification of carbon fiber. Highlights: Surface polarity and wettability increase of CFRP by AP plasma.Surface contamination removal and bonding quality improvement by AP plasma.AP plasma provides a potential alternative method for adhesive bonding pre‐treatment.AP plasma surface modification mechanism analysis via surface characterization. [ABSTRACT FROM AUTHOR]