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An engine component made from 1Cr18Ni9Ti alloy to be used underwater was the subject of the present research investigation.

A stereomicroscope, a metallurgical microscope, a microhardness tester and an electron energy dispersion spectroscope were used to observe cross-sections of the alloy’s microstructure at different locations, as well as its overall corrosion behavior.

The corrosion of the 1Cr18Ni9Ti alloy, attributed to welding, cold processing and plastic deformation processes, was investigated together with an analysis of the chemical composition of the corrosion products and microsclerometry of the cross-sections. It was revealed that defects such as shrinkage cavities and porosity, often were observed to occur in the welding fusion zone. During cold processing treatments, work hardening was induced in the surface layer. Corrosion products consisted of oxides, chlorides and sulfides, with oxides as the dominant component. The high chromium content of d-ferrite had resulted in chromium depletion in nearby phase boundaries, which had led to oxidation and corrosion at these boundaries. As the electrode potential of d-ferrite is different to that of austenite, it is possible for a galvanic couple to develop between the two phases, leading to differential rates of corrosion attack.

Methods are proposed to improve corrosion resistance by improving the quality of the surface overlaying processes and by adopting special surface treatment techniques.

Strain sensing characteristic of carbon nanotubes has been established in the past at nanoscale. In this study, it is shown that the carbon nanotube film sensors, made up of randomly oriented carbon nanotubes, can be used as strain sensors at macro level. A nearly linear trend between the change in voltage, measured using a movable four point probe, and strains, measured using conventional electrical strain gage, indicates the potential of such carbon nanotube films for measuring flexural strains at macro level. Isotropic strain sensing capability of the carbon nanotube film sensors, due to randomly oriented carbon nanotubes, allows multidirectional and multi‐location measurements.

Modern construction projects are increasingly complex and rely heavily on multi-discipline collaboration, and this leads to a more and more decentralized project-based structure widely adopted in the construction industry. While job satisfaction (JS) and job performance (JP) have been heavily studied previously, few considered the impact of organizational structure and none investigated the relationship between the organizational decentralization degree with JS and JP. This research aims to fill this research gap and investigate the impacts of organizational decentralization degree on JS and JP and facilitate a better project management practice for large-scale construction projects.

This research firstly establishes four hypotheses based on the literature review on general project-based organizations, then the hypotheses are tested by a survey covering 25 large complex construction projects in China. A hierarchical linear model analysis was carried out to analyze the survey data and to study the relationships between organizational decentralization degree, job satisfaction and job performance.

Analysis results show that projects' employees' JS and JP are positively correlated with the construction project organizations' decentralization degree, respectively. The decentralization degree has a higher impact on JS than on JP. Employees' JP is positively correlated with their JS, and a higher decentralization degree leads to a more significant positive impact that JS puts on JP.

The findings are new evidence of how construction organization structure and its decentralization degree can affect project employees' JS and JP. This research provides valuable guidance for the industry's management practice and is particularly important for large, complex and highly decentralized construction projects.

This paper aims to investigate the relationship linking hard technology innovation with the high-quality development (HDP) of SRDI firms. SRDI firms are typically classified as medium-sized to moderately scaled businesses renowned for their specialized, refinement, differentiation and innovation (SRDI), with a focus on providing exceptional products or services to gain a competitive advantage in specific market segments. These firms are dedicated to expanding market share and enhancing innovation capacities both locally and globally. The research also aims to scrutinize the contextual effects of digital transformation within this framework.

Hard technology innovation consists of three essential components: innovative characteristics, newly developed technology-based intellectual property rights and the volume of R&D initiatives. The evaluation of HDP was performed utilizing the entropy method, with a specific emphasis on assessing value creation and value management capabilities. Subsequently, this study explores the impact of technological innovation on the HDP of firms using a dual-dimension fixed effects model.

Every aspect of hard technology innovation is essential for promoting the HDP of businesses. The digital transformation of businesses exerts a heterogeneous moderating influence in this process. This is evident in the constructive impact on the connection between innovation attributes and the volume of fruitful R&D initiatives, as well as the HDP of firms. Conversely, the moderating effect is deemed insignificant in the association between new technology-based intellectual property and HDP.

This research delves deeper into the underlying mechanisms that underlie the promotion of HDP through hard technology innovation, thereby expanding the scope of our exploration on the HDP of SRDI firms. It establishes a theoretical framework and practical directives for achieving enhanced development quality amidst the evolving landscape of digital transformation within firms.

This paper aims to provide a review on the process of additive manufacturing of ceramic materials, focusing on partial and full melting of ceramic powder by a high-energy laser beam without the use of binders.

Selective laser sintering or melting (SLS/SLM) techniques are first introduced, followed by analysis of results from silica (SiO₂), zirconia (ZrO₂) and ceramic-reinforced metal matrix composites processed by direct laser sintering and melting.

At the current state of technology, it is still a challenge to fabricate dense ceramic components directly using SLS/SLM. Critical challenges encountered during direct laser melting of ceramic will be discussed, including deposition of ceramic powder layer, interaction between laser and powder particles, dynamic melting and consolidation mechanism of the process and the presence of residual stresses in ceramics processed via SLS/SLM.

Despite the challenges, SLS/SLM still has the potential in fabrication of ceramics. Additional research is needed to understand and establish the optimal interaction between the laser beam and ceramic powder bed for full density part fabrication. Looking into the future, other melting-based techniques for ceramic and composites are presented, along with their potential applications.

The rise of artificial intelligence (AI) applications has driven enterprises to provide many intelligent services to consumers. For instance, customers can use chatbots to make relevant inquiries and seek solutions to their problems. Despite the development of customer service chatbots years ago, they require significant improvements for market recognition. Many customers have reported negative experiences with customer service chatbots, contributing to resistance toward their use. Therefore, this study adopts the innovation resistance theory (IRT) perspective to understand customers’ resistance to using chatbots. It aims to integrate customers’ negative emotions into a predictive behavior model and examine users’ functional and psychological barriers.

In this study, we collected data from 419 valid individuals and used structural equation modeling to analyze the relationships between resistance factors and negative emotions.

The results confirmed that barrier factors affect negative emotions and amplify chatbot resistance influence. We discovered that value and risk barriers directly influence consumer use. Moreover, both functional and psychological barriers positively impact negative emotions.

This study adopts the innovation resistance theory perspective to understand customer resistance to using chatbots, integrates customer negative emotions to construct a predictive behavior model and explores users’ functional and psychological barriers. It can help in developing online customer service chatbots for e-commerce.