3D Metallic Nanowire Networks

Networks of interconnected magnetic nanowires offer an exciting platform to explore 3-dimensional (3D) nanomagnetism, where their structure, topology and frustration may be used as additional degrees of freedom to tailor the materials properties. We have achieved quasi-ordered metallic nanowire networks over cm-scale areas, using multiple angle ion-tracking and electrochemical deposition, with density as low as 40 mg/cm³ [1]. New magnetization reversal mechanisms in cobalt networks are captured by the first-order reversal curve (FORC) method, which demonstrate the evolution from strong demagnetizing dipolar interactions to intersections-mediated domain wall pinning and propagation, and eventually to shape-anisotropy dominated magnetization reversal. Such networks offer interesting potentials for 3D magnetic memory and logic applications, where the spin textures may be manipulated in a contactless fashion by chemisorption [2,3]. They also may be used to implement repeatable multi-state memristors in neuromorphic circuits, due to the expected discrete nature of domain wall motion through the intersecting networks. Interestingly, another random configuration of metallic nanowire networks has found applications in deep-submicron particulate filtration, relevant to combatting COVID-19 and air pollution, due to the extremely large surface areas and the excellent mechanical strength [4,5].

Work done in collaboration with Edward C. Burks, Dustin A. Gilbert, Gong Chen, Dhritiman Bhattacharya, James Malloy, Alberto Quintana, Christopher J. Jensen, Peyton D. Murray, Chad Flores, Thomas E. Felter, Supakit Charnvanichborikarn, Sergei O. Kucheyev, Jeffrey D. Colvin, Andreas Schmid, and Gen Yin.

[1] E. C. Burks, D. A. Gilbert, P. D. Murray, C. Flores, T. E. Felter, S. Charnvanichborikarn, S. O. Kucheyev, J. Colvin, G. Yin and Kai Liu, Nano Lett., 21, 716 (2021).

[2] G. Chen, A. Mascaraque, H.Y. Jia, B. Zimmermann, M. Robertson, R. Lo Conte, M. Hoffmann, M.A.G. Barrio, H.F. Ding, R. Wiesendanger, E. Michel, S. Blügel, A. Schmid, and Kai Liu, Sci. Adv. 6, eaba4924 (2020).

[3] G. Chen, M. Robertson, M. Hoffman, C. Ophus, A. L. F. Cauduro, R. Lo Conte, H. F. Ding, R. Wiesendanger, S. Blügel, A. K. Schmid, and Kai Liu, Phys. Rev. X, 11, 021015 (2021).

[4] J. Malloy, A. Quintana, C. J. Jensen, and Kai Liu, Nano Lett., 21, 2968 (2021).

[5] Phase 1 Winner of BRADA-NIOSH Mask Innovation Challenge: https://drive.hhs.gov/mask_challenge.html