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arxiv: 2605.04599 · v1 · submitted 2026-05-06 · ⚛️ physics.chem-ph

On Electropolymerized Fingerprints and their Potential for Identification and Encryption

Antoine Baron , Luc Brulin , Corentin Scholaert , Yannick Coffinier , Fabien Alibart , S\'ebastien Pecqueur This is my paper

Pith reviewed 2026-05-08 16:55 UTC · model grok-4.3

classification ⚛️ physics.chem-ph
keywords electropolymerizationconducting polymersstochastic patternsphysical fingerprintssolution identificationencryptionelectrochemical processesdendrites
0
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The pith

Electropolymerization of conducting polymers produces stochastic patterns characteristic of the solution's chemical content.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The authors demonstrate that applying an electrochemical process to polymerize conducting materials on surfaces yields irregular textures including spots, rosettes, and marbled designs. These textures retain enough specificity to the growth conditions, especially the solution chemistry, that statistical methods can match them back to their source. This finding suggests a simple way to create physical markers that carry identity information without needing complex equipment. If scalable, it could let users produce custom tags for authentication or data storage on everyday items like glass or electronic chips.

Core claim

The 1D morphogenesis of conducting polymer dendrites on wires translates on 2D surfaces to highly heterogeneous coatings of dark spots, rosettes or marbled patterns. Despite their inherent stochasticity, these patterns are characteristic of the physical conditions they grew in, and particularly of the chemical content of the electroactive solution used for their electropolymerization. A statistical study demonstrates that these patterns could be used as fingerprints to physically tag the identity of a solution within a specific class.

What carries the argument

The 2D translation of 1D conducting polymer dendrite growth into heterogeneous surface coatings with optical, electrical, and chemical contrast

If this is right

  • Patterns can identify the identity of a solution within a specific class using statistical methods.
  • The process allows generation of personal tags on glass slides or micro-chips.
  • Physically-encrypted personal information can be engraved for various applications.
  • This provides a low-cost technology exploiting the balance between control and stochasticity.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Combining the different contrasts could enable verification through multiple independent channels for higher security.
  • Similar stochastic pattern generation might apply to other electrochemical or physical deposition methods for new tagging systems.
  • The approach mirrors biological pattern formation, potentially inspiring hybrid bio-inspired identification tech.

Load-bearing premise

The patterns' stochasticity does not erase their connection to specific chemical conditions enough to prevent reliable statistical identification.

What would settle it

An experiment where patterns from two different solutions in the same class are statistically indistinguishable, or where repeated runs with the same solution produce non-matching patterns, would disprove the fingerprinting capability.

Figures

Figures reproduced from arXiv: 2605.04599 by Antoine Baron, Corentin Scholaert, Fabien Alibart, Luc Brulin, S\'ebastien Pecqueur, Yannick Coffinier.

Figure 1
Figure 1. Figure 1: Setup, mechanism and structures | a, Experimental setup for the electrogeneration of disordered stains of conducting polymer on the bottom of a two-electrode stack, sandwiching an electro-active aqueous electrolyte containing EDOT, BQ and the NaPSS salt. b, Photograph of three different growths electrogenerated on the same gold surface with the same electrolyte and the same voltage pattern, but different s… view at source ↗
Figure 2
Figure 2. Figure 2: Parametric study of the electrogenerated polymer patterns | a, Pulse-width modulated waveform inputted between both substrates to electrogenerate the polymer patterns on the bottom substrate. b1–b6, Influence of the duty cycle at 5% (b1, after 1’00"), 10% (b2, after 0’30"), 15% (b3, after 0’15"), 20% (b4, after 0’10"), 25% (b5, after 0’05") and 30% (b6, after 0’05"). c1–c6, Influence of the pulse size of t… view at source ↗
Figure 3
Figure 3. Figure 3: Effect of the interelectrode distance on the average size of the electrogenerated patterns | a–b, Definition of the interelectrode distance e, controlled by the staking of spacers with specific thicknesses between both electrodes (the photograph b displays glass coverslips used as spacers, and a semi-transparent top-electrode). d–f, Microscope images of three growths generated with the same electroactive e… view at source ↗
Figure 4
Figure 4. Figure 4: Controlled disorder with a periodically structured cathode | a–b, Impact of the cathode (top￾electrode) on the morphological control of the electrogenerated patterns at the bottom electrode (in b, a photograph of the honeycomb-structured gold cathode used in the following experiment). c, Microscope picture of the electrochemical system containing the honeycomb-structured cathode (periodicity: 1/366 µm-1). … view at source ↗
Figure 5
Figure 5. Figure 5: Electrochemical growth on a rough surface | a–b, Impact of the anode (bottom electrode) on the morphological control of the electrogenerated patterns (in b, photograph of a commercial ENIG coated copper electrodes on FR4, where the electrochemical growths were performed). c–d, Microscope images of two electrochemical growths performed under the same conditions of voltage and concentrations (V = 5 V, 50% du… view at source ↗
Figure 6
Figure 6. Figure 6: Dependence of morphological patterns on the chemical composition of an electroactive aqueous electrolyte solution. | a–b, Impact of the electroactive solution on the morphology of the electrogenerated patterns (in b, photograph of a vial of glycerol used as a water-miscible viscous cosolvent, in which the electrochemical growths were performed). c–g, Microscope images of five electrogenerated patterns grow… view at source ↗
Figure 7
Figure 7. Figure 7: Exploiting electropolymerized fingerprints to engrave the information of a solution composition | As conducting polymer patterns are unique and specific to the chemical composition of a solution, the following study proposes to test their potential as fingerprints to classify them by chemical composition on two levels (representative of a lab test to identify true positive and true negative liquid samples)… view at source ↗
Figure 8
Figure 8. Figure 8: Information compression and concentration classification with electropolymerized fingerprints | a, 48 microscope pictures of conducting polymer patterns on a common gold substrate, electrogenerated (V = 5 V, 50% duty cycle, f = 1 kHz) with a solution (1 mM NaPSS, 10 mM EDOT, 10 mM BQ), containing either 10% (marked with a green dot) or 20% (marked with a red dot) of glycerol as a co-solvent in water. b–c, … view at source ↗
Figure 9
Figure 9. Figure 9: Recognizing an electropolymerized fingerprint under different optical and physical perturba￾tions | a, Three different cases were studied to evaluate the persistence of the chemical identity on a fingerprint, when conducting polymer patterns are photographed in different conditions: (1) 12 microscope pictures of a single conducting polymer pattern (previously studied in view at source ↗
read the original abstract

While human technology is ruled by determinism, biological systems exploit a subtle balance of control and stochasticity. This balance, evident in the morphogenesis of textural patterns imprinted on leaves, fur or skin can help hierarchize organisms both as a representative of their species and as unique individuals. In this study, we identified that, by exploiting electrochemistry, it is possible to generate such versatile but specific textures, to imprint patterns of a conducting polymer on a conducting substrate. It is shown that the 1D morphogenesis of conducting polymer dendrites on wires translates, on 2D surfaces, as highly heterogeneous coatings of dark spots, rosettes or marbled patterns. Despite their inherent stochasticity, these patterns are characteristic of the physical conditions they grew in, and particularly of the chemical content of the electroactive solution used for their electropolymerization. A statistical study demonstrates that these patterns could be used as fingerprints to physically tag the identity of a solution within a specific class. By the identification of a new electrochemical process which allows generating physical fingerprints with optical, electrical and chemical contrast on an electrode, this research paves the way toward a disruptive low-cost technology which could allow any end-user to generate personal tags on a glass slide or on a micro-chip, to engrave physically-encrypted personal information for various applications.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

1 major / 0 minor

Summary. The manuscript describes the electropolymerization of conducting polymers on 2D conducting substrates to generate heterogeneous patterns including dark spots, rosettes, and marbled textures. These patterns exhibit optical, electrical, and chemical contrast. The authors assert that, despite inherent stochasticity, the patterns are characteristic of the physical conditions and particularly the chemical content of the electroactive solution, as demonstrated by a statistical study, enabling their use as fingerprints for identification and encryption. The work proposes this as a basis for low-cost, user-generated physical tags on glass slides or microchips.

Significance. If the statistical demonstration is validated with appropriate quantitative metrics, the identification of this electrochemical process could provide a novel route to physical identifiers that combine stochastic generation with chemical specificity. This approach exploits a controlled balance of determinism and randomness, potentially enabling accessible multi-modal tagging and encryption technologies with low cost and broad applicability.

major comments (1)
  1. The abstract states that 'a statistical study demonstrates that these patterns could be used as fingerprints to physically tag the identity of a solution within a specific class.' No details are provided on pattern quantification (e.g., image descriptors or spatial statistics), replicate counts, intra- vs. inter-class variance, or classifier performance/error rates. This information is load-bearing for the central claim that stochasticity does not preclude reliable identification and encryption.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for their constructive review and for recognizing the potential significance of our approach to generating physical identifiers. We have carefully addressed the major comment below by expanding the quantitative details in the revised manuscript.

read point-by-point responses

  1. Referee: The abstract states that 'a statistical study demonstrates that these patterns could be used as fingerprints to physically tag the identity of a solution within a specific class.' No details are provided on pattern quantification (e.g., image descriptors or spatial statistics), replicate counts, intra- vs. inter-class variance, or classifier performance/error rates. This information is load-bearing for the central claim that stochasticity does not preclude reliable identification and encryption.

    Authors: We agree that the central claim requires explicit quantitative support and that the original manuscript did not provide sufficient methodological details on the statistical analysis. In the revised version, we have added a dedicated subsection describing the image quantification pipeline (including texture descriptors and spatial statistics), the replicate counts used, direct comparisons of intra-class versus inter-class variance, and the performance metrics (including error rates) of the classifier employed to demonstrate identification within solution classes. These additions are now incorporated in the Methods and Results sections to make the evidence for the fingerprinting application fully transparent. revision: yes

Circularity Check

0 steps flagged

No significant circularity in experimental claims

full rationale

The paper describes an experimental electrochemical process for generating stochastic patterns on electrodes and asserts that a statistical study shows these patterns can serve as fingerprints characteristic of the solution's chemical content. No equations, mathematical derivations, fitted parameters, or self-citations appear in the abstract or described claims. The central assertions rest on empirical observation and statistics rather than any reduction of outputs to inputs by construction, self-definition, or load-bearing self-reference. This is a standard self-contained empirical result with no detectable circular steps.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

The central claim rests on observed translation of 1D dendritic growth to 2D patterns and their dependence on chemical conditions, presented as experimental facts rather than derived from first principles.

axioms (2)
  • domain assumption The 1D morphogenesis of conducting polymer dendrites on wires translates, on 2D surfaces, as highly heterogeneous coatings of dark spots, rosettes or marbled patterns.
    Stated as an observed translation in the study.
  • ad hoc to paper Despite their inherent stochasticity, these patterns are characteristic of the physical conditions they grew in, and particularly of the chemical content of the electroactive solution.
    This is the load-bearing premise enabling the fingerprint claim.

pith-pipeline@v0.9.0 · 5555 in / 1461 out tokens · 142731 ms · 2026-05-08T16:55:15.872257+00:00 · methodology

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