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The expected excellent tribological performance of high-entropy alloys (HEAs) is rarely achieved due to the absence of self-lubricating ability on the worn surface. In particular, the situation is more challenging in HEAs with face-centered cubic structure because of the inferior yield strength when used in dry sliding conditions. Unlike conventional soft-solid lubricants, which deteriorate the mechanical properties of HEA matrix, in this study we demonstrate in a protocol model alloy that the proper incorporation of few-layer graphene as reinforcement in CoCrFeNiMn can lead to both surface strengthening and lubrication. This is achieved by a partially chemical interface reaction between graphene and HEA via a tunable fabrication process, resulting in a reduction of wear rate and friction coefficient of 86.03% and 23.87%, respectively. As a result of the interfacial in-situ carbide strengthening together with the self-lubrication of graphene, this tailored composite structure also exhibits superior tribological properties over most HEA-based self-lubrication composites. Besides, the subsurface structure evolution and deformation mechanisms that influence the wear resistance are systematically clarified through microscopic exploration and atomistic simulation. The present study presents an effective strategy for the development of innovative HEA composites suitable for safety-critical applications, which overcomes the inherent compromise and achieves exceptional tribological performance, i.e., self-lubricating and anti-wear. [Display omitted] • The self-lubricating graphene reduces wear rate to an order of magnitude. • The wear rate of Gr/HEA composite surpasses most FCC-structured HEAs. • The in-situ carbides alter the plastic deformation mode from planar to wavy slips. • The graphene significantly alters the plowing and adhesion mechanisms during wear. [ABSTRACT FROM AUTHOR]

A growing body of observational studies and Mendelian Randomisation analyses suggest an increased risk of Alzheimer's disease and dementia following COVID-19 infection. However, evidence on the potential association between COVID-19 and vascular dementia, which is plausible given the vascular complications of COVID-19 infection, is still limited. In this study, we conducted a two-sample Mendelian Randomisation analysis to examine the potential causal relationship between COVID-19 phenotypes and the risk of vascular dementia, using summary data from large-scale GWASs. The two-sample Mendelian Randomisation analysis did not detect any significant associations of COVID-19 infection, COVID-19 hospitalisation, or critical COVID-19 with the risk of vascular dementia, with weighted average β values of −0.29 (95% CI: −0.84, 0.26; p = 0.301), −0.12 (95% CI: −0.36, 0.13; p = 0.345), and −0.07 (95% CI: −0.23, 0.09; p = 0.374), respectively. Our findings do not support the hypothesis that vascular dementia is one of the long-term sequelae of COVID-19. [ABSTRACT FROM AUTHOR]