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The purpose of this paper is to explore the synergistic lubrication of MoS₂ particles with different morphologies.

The synergistic lubrication of MoS₂ particles with different morphologies is evaluated using a four‐fall tribometer in liquid paraffin.

Results show that the morphology of MoS₂ has an influence on the tribological properties of MoS₂. Both MoS₂ nano‐balls and nano‐platelets function as lubrication additives in liquid paraffin better than MoS₂ micro‐platelets do. It is also found that there is a synergistic lubrication between two different morphologies of MoS₂. The composite MoS₂ additives with different morphologies can improve the wear resistance and friction reduction of liquid paraffin more than each of them singly does. The synergistic lubrication between two different MoS₂ morphologies results from the cooperation of their different lubrication mechanism.

The paper reveals a synergistic lubrication between two different MoS₂ structures. It is very advantageous and practical to partly displace nano‐MoS₂ with micro‐MoS₂.

As the complex influencing factors for financing decisions and limited information at the early project stage often render inappropriate financing mode and scheme (FMS) selection in the large-scale urban rail transit (URT) field, this study aims to identify the multiple influencing factors and establish a revised case-based reasoning (CBR) model by drawing on experience in historical URT projects to provide support for effective FMS decisions.

Our research proposes a two-phase, five-step CBR model for FMS decisions. We first establish a case database containing 116 large-scale URT projects and a multi-attribute FMS indicator system. Meanwhile, grey relational analysis (GRA), the entropy-revised G1 method and the time decay function have been employed to precisely revise the simple CBR model for selecting high-similarity cases. Then, the revised CBR model is verified by nine large-scale URT projects and a demonstration project to prove its decision accuracy and effectiveness.

We construct a similarity case indicator system of large-scale URT projects with 11 indicators across three attributes, in which local government fiscal pressure is considered the most influential indicator for FMS decision-making. Through the verification with typical URT projects, the accuracy of our revised CBR model can reach 89%. The identified high-similarity cases have been confirmed to be effective for recommending appropriate financing schemes matched with a specific financing mode.

This is the first study employing the CBR model, an artificial intelligence approach that simulates human cognition by learning from similar past experiences and cases to enhance the accuracy and reliability of FMS decisions. Based on the characteristics of the URT projects, we revise the CBR model in the case retrieval process to achieve a higher accuracy. The revised CBR model utilizes expert experience and historical information to provide a valuable auxiliary tool for guiding the relevant government departments in making systematic decisions at the early project stage with limited and ambiguous project information.

Megaprojects can play a crucial role in achieving Sustainable Development Goals (SDGs) and tackling Global Challenges. However, they are often criticized for their massive resource consumption, poor cost/time performance and significant social-environmental impacts, including irreversible environmental damage. This study aims to chart the evolution of research on megaprojects sustainability and to offer a roadmap for future developments.

This study adopted a systematic literature review (SLR) to identify emerging themes and gaps. This study follows a three-step process of planning, conducting and reporting, based on the Tranfield approach. The overview of megaprojects sustainability research was captured through bibliometric analysis. In addition, content analysis was carried out to reveal the development of this field and get an insight into the future directions towards sustainability transition.

This study provides a longitudinal, in-depth analysis of megaprojects sustainability studies. Drawing on sustainability science and project management theories, we introduce a three-dimensional analytical framework consisting of sustainability, scope and stakeholder. This framework explains the evolution of megaprojects sustainability research from sustainability of megaprojects, to sustainability for megaprojects and then to sustainability by megaprojects. Three future avenues are proposed: (1) SDGs orientation at multi-level; (2) scope enlargement at temporal and spatial scales and (3) inclusive development for stakeholders.

This research contributes to the literature by providing a comprehensive and forward-looking analysis of megaprojects sustainability research. The framework and three research agendas provide a comprehensive picture of megaproject sustainability research; the agenda for future research is intended to inspire more studies and disruptive actions towards sustainability transition.