journal article·2025-02-10Open access

Mapping nanoparticle formation and substrate heating effects: a fluence-resolved approach to pulsed laser-induced dewetting

Artemisa Mazón-Martínez, Tupak García-Fernández, Marco Antonio Martínez-Fuentes, Citlali Sánchez-Aké

Nanotechnology· Volume 36· Issue 6

Abstract

Abstract This study investigates the fluence-dependent evolution of gold nanoparticles formed through single nanosecond pulsed laser dewetting of a gold thin film on a fused silica substrate. By employing a well-defined Airy-like laser spatial profile and reconstructing scanning electron microscope images across the irradiation spot into a panoramic view, we achieve a detailed continuous analysis of the nanoparticle formation process. Our morphological analysis, combined with finite element thermal simulations directly correlated with the applied fluence, identifies two distinct thresholds. The first threshold corresponds to the dewetting of the gold film at its melting point, resulting in large, sparse nanoparticles. The second threshold, where the substrate temperature reaches values near its melting point, leads to the formation of numerous small nanoparticles and a significant increase in coverage area. Notably, the formation of these small nanoparticles is attributed to substrate heating, which alters the interaction between the molten gold film and the substrate, increasing adhesion. Contact angle measurements of the nanoparticles confirm this change, revealing a shift in wettability, and highlighting the crucial role of substrate heating in modulating the interactions leading to nanoparticle formation. Our findings underscore the intricate interplay between laser fluence, material properties, and substrate interactions in pulsed laser dewetting, with the well-defined laser profile offering valuable insights into these dynamics.
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Research context

OpenAlex topics: Particle Dynamics in Fluid Flows · Fluid Dynamics and Thin Films · nanoparticles nucleation surface interactions

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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