Universal Murray’s law for optimised fluid transport in synthetic structures

Binghan Zhou, Qian Cheng, Zhuo Chen, Zesheng Chen, Dongfang Liang, Eric Anthony Munro, Guolin Yun, Yoshiki Kawai, Jinrui Chen, Tynee Bhowmick, Karthick Kannan Padmanathan, Luigi Giuseppe Occhipinti, Hidetoshi Matsumoto, Julian William Gardner, Bao-Lian Su and Tawfique Hasan ()
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Binghan Zhou: University of Cambridge
Qian Cheng: University of Cambridge
Zhuo Chen: University of Cambridge
Zesheng Chen: University of Cambridge
Dongfang Liang: University of Cambridge
Eric Anthony Munro: University of Cambridge
Guolin Yun: University of Cambridge
Yoshiki Kawai: Tokyo Institute of Technology
Jinrui Chen: University of Cambridge
Tynee Bhowmick: University of Cambridge
Karthick Kannan Padmanathan: University of Warwick
Luigi Giuseppe Occhipinti: University of Cambridge
Hidetoshi Matsumoto: Tokyo Institute of Technology
Julian William Gardner: University of Warwick
Bao-Lian Su: University of Namur
Tawfique Hasan: University of Cambridge

Nature Communications, 2024, vol. 15, issue 1, 1-11

Abstract: Abstract Materials following Murray’s law are of significant interest due to their unique porous structure and optimal mass transfer ability. However, it is challenging to construct such biomimetic hierarchical channels with perfectly cylindrical pores in synthetic systems following the existing theory. Achieving superior mass transport capacity revealed by Murray’s law in nanostructured materials has thus far remained out of reach. We propose a Universal Murray’s law applicable to a wide range of hierarchical structures, shapes and generalised transfer processes. We experimentally demonstrate optimal flow of various fluids in hierarchically planar and tubular graphene aerogel structures to validate the proposed law. By adjusting the macroscopic pores in such aerogel-based gas sensors, we also show a significantly improved sensor response dynamics. In this work, we provide a solid framework for designing synthetic Murray materials with arbitrarily shaped channels for superior mass transfer capabilities, with future implications in catalysis, sensing and energy applications.

Date: 2024
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DOI: 10.1038/s41467-024-47833-0

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