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    Quantifying humidity effects on commensurability-dependent friction in bilayer graphene: A generalized registry index model

    Binyang Shao1, Xiaoyan Ren1, Kun Liu1, Lili Zhang1, Yigang Cao1, Xingju Zhao1,2,*, and Shunfang Li1,2,†

    • *Contact author: zhaoxingju@zzu.edu.cn
    • †Contact author: sflizzu@zzu.edu.cn

    Phys. Rev. B 113, 115402 – Published 2 March, 2026

    DOI: https://doi.org/10.1103/1tvv-kc9n

    Abstract

    Deciphering the atomistic mechanism governing humidity-dependent interfacial friction remains a fundamental challenge across physics, chemistry, medicine, and materials science. Here, we employ first-principles calculations to systematically investigate the frictional behaviors of bilayer graphene (BLG) with varying interfacial water (H2O) coverage, with a particular focus on the contrasting responses of commensurate and incommensurate contacts. Our findings reveal a striking dichotomy: As H2O coverage increases to approximately 0.4 monolayer, commensurate BLG interfaces experience a dramatic reduction in friction, reaching a minimum, whereas incommensurate contacts exhibit a moderate increase in friction, peaking near 0.6 monolayer. Beyond these critical humidity cites, friction in commensurate systems gradually increases toward a saturation regime, while incommensurate systems display a declining trend before plateauing. To validate these distinct behaviors, we establish a generalized registry index framework that extends the conventional registry index [N. Marom et al., Phys. Rev. Lett. 105, 046801 (2010)] by explicitly incorporating (i) interlayer-distance-dependent vdW interactions modulated by water intercalation, (ii) humidity-induced commensurate-incommensurate phase transitions, and (iii) molecular pinning sites imparted by confined H2O molecules within the BLG heterostructure. Collectively, this work not only reveals the atomistic mechanism of humidity as an effective tuning parameter for frictional control in two-dimensional materials but also provides a robust descriptor with predictive power for the rational design of adaptive, environment-responsive nanolubrication systems.

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