Premium
Laser Generation of Sub‐Micrometer Wrinkles in a Chalcogenide Glass Film as Physical Unclonable Functions
Author(s) -
Martinez Paloma,
Papagiannouli Irene,
Descamps Dominique,
Petit Stéphane,
Marthelot Joël,
Lévy Anna,
Fabre Baptiste,
Dory JeanBaptiste,
Bernier Nicolas,
Raty JeanYves,
Noé Pierre,
Gaudin Jérôme
Publication year - 2020
Publication title -
advanced materials
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 10.707
H-Index - 527
eISSN - 1521-4095
pISSN - 0935-9648
DOI - 10.1002/adma.202003032
Subject(s) - physical unclonable function , materials science , laser , micrometer , chalcogenide , optoelectronics , key generation , fluence , amorphous solid , randomness , chalcogenide glass , nanometre , supercontinuum , nanotechnology , optics , computer science , key (lock) , wavelength , physics , composite material , photonic crystal fiber , chemistry , computer security , organic chemistry , statistics , mathematics , operating system , encryption
Laser interaction with solids is routinely used for functionalizing materials' surfaces. In most cases, the generation of patterns/structures is the key feature to endow materials with specific properties like hardening, superhydrophobicity, plasmonic color‐enhancement, or dedicated functions like anti‐counterfeiting tags. A way to generate random patterns, by means of generation of wrinkles on surfaces resulting from laser melting of amorphous Ge‐based chalcogenide thin films, is presented. These patterns, similar to fingerprints, are modulations of the surface height by a few tens of nanometers with a sub‐micrometer periodicity. It is shown that the patterns' spatial frequency depends on the melted layer thickness, which can be tuned by varying the impinging laser fluence. The randomness of these patterns makes them an excellent candidate for the generation of physical unclonable function tags (PUF‐tags) for anti‐counterfeiting applications. Two specific ways are tested to identify the obtained PUF‐tag: cross‐correlation procedure or using a neural network. In both cases, it is demonstrated that the PUF‐tag can be compared to a reference image (PUF‐key) and identified with a high recognition ratio on most real application conditions. This paves the way to straightforward non‐deterministic PUF‐tag generation dedicated to small sensitive parts such as, for example, electronic devices/components, jewelry, or watchmak.