English

Microstructure-Dependent Particulate Filtration using Multifunctional Metallic Nanowire Foams

Applied Physics 2024-08-16 v1 Mesoscale and Nanoscale Physics

Abstract

The COVID-19 pandemic has shown the urgent need for the development of efficient, durable, reusable and recyclable filtration media for the deep-submicron size range. Here we demonstrate a multifunctional filtration platform using porous metallic nanowire foams that are efficient, robust, antimicrobial, and reusable, with the potential to further guard against multiple hazards. We have investigated the foam microstructures, detailing how the growth parameters influence the overall surface area and characteristic feature size, as well as the effects of the microstructures on the filtration performance. Nanogranules deposited on the nanowires during electrodeposition are found to greatly increase the surface area, up to 20 m2^{2}/g. Surprisingly, in the high surface area regime, the overall surface area gained from the nanogranules has little correlation with the improvement in capture efficiency. However, nanowire density and diameter play a significant role in the capture efficiency of PM0.3_{0.3} particles, as do the surface roughness of the nanowire fibers and their characteristic feature sizes. Antimicrobial tests on the Cu foams show a >99.9995% inactivation efficiency after contacting the foams for 30 seconds. These results demonstrate promising directions to achieve a highly efficient multifunctional filtration platform with optimized microstructures.

Keywords

Cite

@article{arxiv.2407.14946,
  title  = {Microstructure-Dependent Particulate Filtration using Multifunctional Metallic Nanowire Foams},
  author = {James Malloy and Erin Marlowe and Christopher J. Jensen and Isaac S. Liu and Thomas Hulse and Anne F. Murray and Daniel Bryan and Thomas G. Denes and Dustin A. Gilbert and Gen Yin and Kai Liu},
  journal= {arXiv preprint arXiv:2407.14946},
  year   = {2024}
}

Comments

25 pages, 5 figures, 1 table; 11 page of supplementary information with 7 figures

R2 v1 2026-06-28T17:48:24.786Z