Random Laser Spectral Fingerprinting of Lithographed Microstructures. Issue 4 (10th March 2021)

• Record Type: Journal Article
• Authors: Capocefalo, Angela; Quintiero, Eleonora; Bianco, Monica; Zizzari, Alessandra; Gentilini, Silvia; Conti, Claudio; Arima, Valentina; Viola, Ilenia; Ghofraniha, Neda
• Is Part Of: Advanced materials technologies. Volume 6:Issue 4(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-03-10
• Subjects: microfluidics -- random lasers -- self‐assembly -- soft lithography -- spectral fingerprint; Materials science -- Periodicals; Technological innovations -- Periodicals; Materials science; Technological innovations; Periodicals; 620.1105
• DOI: 10.1002/admt.202001037
• Languages: English
• ISSNs: 2365-709X

Abstract

Abstract: Coherent random lasers (RLs) originate from the resonant amplification of the light scattered by disordered media resulting in spiky emission spectra with well‐defined spectral signatures. Here coherent RL emission is proposed as a tool for identifying the spectral fingerprint of porous micro‐structured materials obtained by soft lithography techniques. The close control of the spatial patterns and structural characteristics of the scattering elements enable us to obtain stable and unique RL spectra distinctive of each lithographed device. The spectral emission has been thoroughly analyzed with respect to the morphology of the devices in terms of surface roughness and surface volume fraction, demonstrating that the packing of the scattering particles is the main factor in determining a RL emission characterized by multiple linewidths with a high level of coherence. The findings provide novel insights for the realization of miniaturized photonic devices with selectable optical features. Abstract : Here, coherent random laser emission is proposed as a tool for identifying the spectral fingerprint of porous micro‐structured materials realized by soft lithography techniques. The close control of the spatial patterns and morphology of the scattering elements determines fine emission spectra that are stable in time and unique to each sample.