Labyrinthine Microstructures with a High Dipole Moment Boron Complex for Molecular Physically Unclonable Functions

TL;DR

Researchers created a new molecule with unique properties that form complex patterns useful for secure authentication and anti-counterfeiting.

Contribution

A new high dipole-moment molecule and a simple fabrication method for creating high-entropy PUF patterns.

Findings

The molecule InIm-BF2 forms amorphous PUF patterns with disordered, short-range interactions.

Labyrinthine patterns exhibit excellent PUF characteristics and rich entropy for secure authentication.

Deep-learning methods directly authenticate the complex features of the patterns.

Abstract

The design and development of novel molecular-physically
unclonable functions (PUFs) with advanced encoding characteristics
and ease of fabrication have recently attracted attention in cryptography,
secure authentication, and anticounterfeiting. Here, we report the
development of a new high dipole-moment small molecule, InIm-BF2, a difluoroborate complex of an indolyl-imine ligand, and
the fabrication of unique labyrinthine patterns through a facile two-step
thin film process under ambient conditions. The new molecule has a
dipolar, coplanar π-backbone and arranges in the solid state
with antisymmetric cofacial π-stackings (3.86 Å). These
properties, along with short C–H···π contacts
(2.74–2.88 Å) and nonclassical C–H···F
hydrogen bonds (2.47–2.51 Å) (23.4% and 11.5% of the Hirshfeld
surfaces, respectively), drive the formation of amorphous molecular PUF patterns with disordered, short-range interactions.
Spin-coating followed by thermal annealing at a moderate temperature
produces nanoscopic molecular thin films with intricate labyrinthine
patterns. These patterns, characterized by interconnected, irregularly
shaped, micron-sized (≈50–100 μm) features, exhibit
excellent PUF characteristics, verified through advanced image analysis
and computational algorithms. Unlike randomly positioned isolated
features in classical binarized keys, the interconnected labyrinthine
patterns possess rich entropy and complex features, directly authenticated
via deep-learning methodologies. Our work not only demonstrates a
facile, promising approach to fabricating unique high-entropy PUF
patterns but also provides critical insights into designing advanced
molecular materials for next-generation security applications.

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