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Nano graphitic-carbon nitride (g-C₃N₄) is an emerging lubrication technology with excellent performance and significant potential for future applications. This study aims to investigate the effect of nano g-C₃N₄ as a lubricant additive on the wear performance of bearing steel disk.

Various mass fractions of g-C₃N₄ were introduced into the base oil. Combining tribological testing, rheological testing and surface analysis methods, the anti-wear properties and lubrication mechanisms were analyzed.

Transmission electron microscopy images revealed that the size of the nanoparticles of g-C₃N₄ ranges from 10 to 100 nm. Phase analysis of the g-C₃N₄ sample was conducted using X-ray diffraction. Further, 1.0% mass fraction of g-C₃N₄ in the base oil provides excellent anti-wear and friction-reducing performance. Compared to the base oil alone, it reduces the average friction coefficient by 63.8% and decreases the wear rate by 43.1%, significantly reducing the depth and width of the wear scar. Energy-dispersive X-ray spectroscopy and scanning electron microscope analysis revealed that the oil sample containing nano g-C₃N₄ can form a lubricating film on the sliding surface of bearing steel after wear, which enhances the lubricating properties of the base oil.

The synergistic effect of the base oil and nanoparticles reduces friction and wear and is expected to extend the service life of bearing steel. These findings suggest that incorporating nano g-C₃N₄ as a lubricant additive offers significant potential for improving the performance of mechanical components.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-12-2024-0456/

Given the current friction and wear challenges faced by automobile parts and bearings, this study aims to identify a novel texture for creating anti-friction and wear-resistant surfaces. This includes detailing the preparation process with the objective of mitigating friction and wear in working conditions.

Femtosecond laser technology was used to create a mango-shaped texture on the surface of GCr15 bearing steel. The optimized processing technology of the texture surface was obtained through adjusting the laser scanning speed. The tribological behavior of the laser-textured surface was investigated using a reciprocating tribometer.

The friction coefficient of the mango-shaped texture surface is 25% lower than that of the conventional surface, this can be attributed to the reduced contact area between the friction ball and the micro-textured surface, leading to stress concentration at the extrusion edge and a larger stress distribution area on the contact part of the ball and disk compared to the conventional surface and the function of the micro-texture in storing wear chips during the sliding process, thereby reducing secondary wear.

The mango-shaped textured surface in this study demonstrates effective solutions for some of the friction and wear issues, offering significant benefits for equipment operation under light load conditions.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2024-0127/

The purpose of this study is to explore the interfacial adhesion between superhydrophobic coatings FC-X (X = 1%, 2%, 3%, 4% and 5%) and the concrete substrate, along with the impact of FC-X on the water repellency characteristics of the concrete substrate.

One synthetic step was adopted to prepare novel F-SiO₂ NP hybrid fluororesin coating. The impact of varying mass fractions of F-SiO₂ NPs on the superhydrophobicity of FC-X was analyzed and subsequently confirmed through water contact angle (WCA) measurements. Superhydrophobic coatings were simply applied to the concrete substrate using a one-step spraying method. The interfacial adhesion between FC-X and the concrete substrate was analyzed using tape pasting tests and abrasion resistance measurements. The influence of FC-X on the water repellency of the concrete substrate was investigated through measurements of water absorption, impermeability and electric flux.

FC-4% exhibits excellent superhydrophobicity, with a WCA of 157.5° and a sliding angle of 2.3°. Compared to control sample, FC-X exhibits better properties, including chemical durability, wear resistance, adhesion strength, abrasion resistance, water resistance and impermeability.

This study offers a thorough investigation into the practical implications of enhancing the durability and water repellency of concrete substrates by using superhydrophobic coatings, particularly FC-4%, which demonstrates exceptional superhydrophobicity alongside remarkable chemical durability, wear resistance, adhesion strength, abrasion resistance, water resistance and impermeability.

Through the examination of the interfacial adhesion between FC-X and the concrete substrate, along with an assessment of FC-X’s impact on the water repellency of the concrete, this paper provides valuable insights into the practical application of superhydrophobic coatings in enhancing the durability and performance of concrete materials.

Green consumption is conducive to global sustainable development. This study aims to explore how social norms (i.e. descriptive norms and injunctive norms) impact green consumption attitude and behavior. It examines the mediating role of impression management and the moderating role of self-construal.

We conduct two online experiments to collect data. A total of 1,070 Chinese consumers participate in Study 1. Study 2 involves 541 Chinese consumers.

The results show that descriptive norms and injunctive norms stimulate consumers’ impression management, which then promotes green consumption attitude and behavior. When an individual is more predisposed to interdependent self-construal, descriptive norms are more effective in activating impression management and then affecting green consumption attitude and behavior.

Social norms are an effective intervention measure for green consumption. Its influence process is complex. However, previous studies mainly identified the mediating role of personal norms. Other mediating mechanisms and boundary conditions are still unclear. This study identifies the mediating role of impression management and the moderating role of self-construal. It sheds new light on how social norms impact green consumption.

The application of galvanized steel is widespread across industries due to its protective zinc coating that protects against atmospheric corrosion. However, previous studies have primarily focused on long-term corrosion rates rather than the full-scale corrosion behavior of the zinc. This paper aims to study the full-scale corrosion evolution of galvanic steel under simulated marine atmospheric environment using real-time EIS measurement.

Electrochemical impedance spectroscopy (EIS) provides an advanced method in monitoring such behavior. Therefore, the EIS method has been used to conduct a comprehensive investigation on the corrosion behavior of galvanic steel in a full-time manner.

The results indicate that the corrosion process of galvanic steel can be divided into three stages: an initial stage with an increased corrosion rate, a subsequent stage with a reduced corrosion rate, and finally a third stage with the lowest and constant corrosion rate. The evolution of corrosion resistance is closely related to changes in composition and structure of the patina layer. In the initial stage, galvanized steel undergoes the formation of soluble ZnCl₂ and needle-like Zn₅(OH)₈Cl₂·H₂O, which promotes the generation and maintenance of an electrolyte layer, consequently leading to an increase in corrosion rate. With prolonged corrosion time, there is a continuous accumulation of Zn₅(OH)₈Cl₂·H₂O within the patina layer, which reduces the content of soluble components and promotes the development of a denser inner layer, thus enhancing corrosion resistance.

This work holds significance in the monitoring of corrosion, understanding the evolution of corrosion and predicting the lifespan of galvanized steel.

The construction and real estate sectors are vital to national economies, but traditional construction methods often lead to challenges such as safety risks, noise and environmental pollution. While intelligent construction is believed to mitigate these issues, there is a lack of solid empirical evidence on whether it truly benefits the general public. This paper seeks to explore the societal benefits of intelligent construction from the public’s perspective, addressing this research gap.

The research adopts a two-step approach. First, topic mining is conducted to identify topics closely related to the public’s daily life, such as environmental impact, construction traffic management and construction technologies. These topics are then analyzed through sentiment analysis using a bidirectional long short-term memory model with attention mechanism to determine whether the public has a favorable view of these aspects of intelligent construction, indirectly demonstrating the benefits to the public.

The primary topics identified include “industry development,” “technology enterprise,” “construction equipment,” “intelligent technology,” “environmental protection,” “robots” and “construction traffic management.” Sentiment analysis shows that public sentiment is overwhelmingly positive across all topics and regions, with “environmental protection,” “construction traffic management” and “robots” receiving the most favorable reactions.

This study provides empirical evidence of the societal benefits of intelligent construction from the public’s viewpoint using social media data. The results highlight the need for continued promotion and adoption of intelligent construction due to its positive impact on society.

This study aims to examine the impact of investment in innovation, market structure and competitive position on the supermarket value chain in the USA.

This paper used secondary data from Economatica® for the period 2010–2020, encompassing 83 firms within the US supermarket value chain, resulting in 913 observations for each model covariate. The data were analyzed through structural equation modeling, using the partial least squares (PLS) approach, using SMARTPLS® software.

The results indicate that both market structure and investment in innovation have a significant impact on a firm’s competitive position. Specifically, a more concentrated market structure is associated with a weaker competitive position, whereas higher levels of investment in innovation correspond to a stronger competitive position. However, no significant relationship was found between investment in innovation and market structure.

This study is limited to the Economatica® database, from which this paper selected a sample of firms within the US supermarket value chain. This paper recommend future research to compare data from other countries or sectors. For the three-dimensional model, this paper used constructs with indicators of investment, performance and market concentration; however, this paper suggests incorporating additional variables to enhance the model’s robustness.

An analysis of market structure and its impact on competitive positioning offers valuable insights for managers regarding the strategic dimensions of the supermarket industry. Integrating the effects of investment in innovation into business strategies can enhance long-term economic benefits. Adopting a value chain perspective further facilitates the examination of market equilibrium and competitive positioning within the supermarket industry.

The findings of this study can help prevent the adoption of misguided strategies that fail to foster business growth. By highlighting the significant impact of innovation on performance, while considering the competitive dynamics within the supermarket industry, the study provides a deeper understanding of the risks faced by various firms across the value chain and the dual nature of competition within the sector. Moreover, it reinforces the relevance of research on economic sustainability and supports the development of effective growth strategies for firms.

While most studies focus on hypotheses examining the relationships between innovation and competitive positioning or between innovation and market structure, this study introduces a three-dimensional model that uses structural equation modeling to test these interconnections simultaneously. Furthermore, it extends the analysis by incorporating the value chain as a central component, using a diverse sample of firms directly linked to the core operations of the supermarket industry.

This study analyses the direct and indirect impacts of risks on the service-oriented construction supply chain and its resilience during disruptions.

We utilised the service-dominant logic, contingency and information processing theories to identify service-oriented construction supply chain characteristics and risk behaviours during turbulent times.

Our analysis of 285 construction companies with a strong service orientation revealed that the proposed risk model explains a 33.6% variance in supplier performance, 46.4% operational performance, 47.1% customer satisfaction and 46.5% financial performance. Our findings highlight the importance of effectively monitoring risks in service-oriented construction supply chains and examining complex networks in which risk variables impact construction supply chain performance.

This study examines the influence mechanisms between risks and actors’ performance in construction supply chains, taking a service-oriented perspective.

Previous studies emphasise the risks that construction companies encounter from disruptions, such as maintaining operations and enhancing performance. Nevertheless, the research still needs to establish the transmission mechanism of the simultaneous impact (direct and indirect) of all forms of risk on supply chain performance.

Monitoring of the quality of precast concrete (PC) components is crucial for the success of prefabricated construction projects. Currently, quality monitoring of PC components during the construction phase is predominantly done manually, resulting in low efficiency and hindering the progress of intelligent construction. This paper presents an intelligent inspection method for assessing the appearance quality of PC components, utilizing an enhanced you look only once (YOLO) model and multi-source data. The aim of this research is to achieve automated management of the appearance quality of precast components in the prefabricated construction process through digital means.

The paper begins by establishing an improved YOLO model and an image dataset for evaluating appearance quality. Through object detection in the images, a preliminary and efficient assessment of the precast components' appearance quality is achieved. Moreover, the detection results are mapped onto the point cloud for high-precision quality inspection. In the case of precast components with quality defects, precise quality inspection is conducted by combining the three-dimensional model data obtained from forward design conversion with the captured point cloud data through registration. Additionally, the paper proposes a framework for an automated inspection platform dedicated to assessing appearance quality in prefabricated buildings, encompassing the platform's hardware network.

The improved YOLO model achieved a best mean average precision of 85.02% on the VOC2007 dataset, surpassing the performance of most similar models. After targeted training, the model exhibits excellent recognition capabilities for the four common appearance quality defects. When mapped onto the point cloud, the accuracy of quality inspection based on point cloud data and forward design is within 0.1 mm. The appearance quality inspection platform enables feedback and optimization of quality issues.

The proposed method in this study enables high-precision, visualized and automated detection of the appearance quality of PC components. It effectively meets the demand for quality inspection of precast components on construction sites of prefabricated buildings, providing technological support for the development of intelligent construction. The design of the appearance quality inspection platform's logic and framework facilitates the integration of the method, laying the foundation for efficient quality management in the future.

The COVID-19 pandemic and the corresponding control measures have harmed the mental health of professionals working in the construction industry. Existing research has also indicated that demographic characteristics are leading variables causing differences in individual’s perceptions on mental health and psychosocial hazardous factors. Combining these, this research aims to compare the differences and similarities of the perceived mental health outcomes and psychosocial hazards among construction professionals with different demographic characteristics during the pandemic.

Using a questionnaire survey, data were collected from 531 construction professionals working in Chinese construction companies, which were analyzed quantitatively using mean score comparative analysis, Mann–Whitney U test and Kruskal–Wallis H test, as well as Spearman’s correlation analysis.

The results indicate that construction professionals with different ages, years of working experience and positions are exposed to different psychosocial hazards, resulting in different mental health conditions during the pandemic. Age and years of working experience are also strong predictors of the level of depression and anxiety experienced by construction professionals; that is, mental ill health tends to decrease with the increase of age and experience. Male department/unit heads, working in a company office environment for a private company and aged 31–40 years old with 11–20 years of working experience, tend to have the best mental health condition. In contrast, psychosocial hazards are more likely to produce the most serious impact on male site-based construction professionals working for a state-owned company, either with less than one year of working experience or in a senior management position.

Despite the significant contribution of the construction industry to the global economy, the differences and similarities of the mental health outcomes and psychosocial hazards among construction professionals with different demographic characteristics during the pandemic remain unknown. This research, therefore, reveals the mental health outcomes and psychosocial hazard impacts among different types of construction professionals during the pandemic. Specifically, this research unveils the important personal characteristics which are closely associated with poor mental health and the stronger impacts of psychosocial hazards on the mental health of construction professionals during the pandemic. The results are valuable for governments and construction companies to formulate targeted mental health intervention strategies during future public health emergencies.