Abstract: If electronics drives only electrons to charge electrodes, natural systems learn by moving matter to evolve. Morphogenesis in sessile organisms can be seen both as a fabrication process and as an operative mechanism. However, intricating manufacturing an d programming functionalities in electronic hardware is not conventional. In this study, we experimentally implement such a concept of an evolutionary electrical system using a neuro-inspired electronic nose as a model, to store a history of sensory data in the physical properties of the electrical interconnects of sensing elements. Triggered only by volatile molecule exposures, different sensing elements change instantaneously and reversibly their impedance, so pulse voltages enable the electrochemical growth of conducting polymer dendrites. The strength of the evolving interconnects is specific to the sensing materials and to the nature of volatile molecules to which they are exposed. The dendritic growths occur exclusively when exposed to volatile s amples, and stop immediately after interrupting the exposure. The capability of such "passive memory" was also assessed by simulating a network architecture, which showed that this way of storing information should greatly diminish the fabrication comple xity of a highly dense sensing array while realistically enabling its calibration to classify user-specific environment exposures. By demonstrating that memory in electronics can be a concept linked to manufacturing like in living organisms, this study s hows that low material resources and low voltage fabrication processes based on electrochemistry can be exploited for practical electronic applications in future-emerging sensing technologies.
Baron A., Hafsi B., Hernández-Balaguera E., Pecqueur S.*
Abstract: The brain exploits electrochemistry both to process chemical information and to fabricate itself: two functionalities that silicon cannot achieve by itself. In a complementary approach, this presentation reports on a few elements suggesting that electrop olymerization on a chip is a way to gather sufficiently rich chemistries on a miniaturized electronic nose, and that "letting" sensors connect during an application could be a solution for electronics to self-manufacture, reducing its environmental footp rint, while unlocking unprecedented computing functionalities beyond charging and discharging memory cells. By controlling the electrochemical growth of conducting polymers on micro-electrode arrays in a microliter sized droplet, conducting polymers with various chemistries can be confined additively at a micrometer scale on conductimetric devices. Since conducting polymers are both macromolecular materials and doped semiconductors, they intrinsically feature both chemical detection and electrical trans duction, like G-coupled proteins on olfactory receptor neurons, to generate relevant information on a sugar-cube sized electronic nose. Electropolymerization allows growing films on devices, but also interconnecting them with an incredibly versatile way. Branching out from electrodes, conducting polymer dendrites grow by the action of voltage pulses. The temporality of the voltage and the chemistry of their growth medium allow them to form various sizes and shapes, which program their equivalent circuit deeply through their structural evolution. Because polymers can drive both electrons and ions, their fractal structure relates to diffusion-limited capacitive decays, offering a second degree of freedom, unexploited in analog electronics, to program the fading memory time window of a dendritic junction between neighboring devices. By embedding such bio-inspired functionalities as neurogenesis and morphogenesis into electronics, conducting polymers electrochemistry could greatly contribute in fabricatin g electronic chips in a more sustainable manner while unlocking new programming functionalities to generate and process information.
Pecqueur S., Baron A., Viala A., Moustiez P., Guérin D., Dargent T., Hernández-Balaguera E.
Abstract: Understanding the electrical mechanisms underlying artificial synaptic plasticity is essential for neuromorphic engineering. This work presents a unified electrical perspective connecting the simple bioelectrochemical dendrites and the greater complexity of memristors as complementary platforms for studying memory effects in artificial brain-inspired synapses. First, we show how conducting polymer dendrites exhibit fractional-order transient responses arising from coupled ionic and electrochemical proce sses, reproducing key features of synaptic plasticity such as history-dependent dynamics and synaptic learning behavior during morphogenesis. Similar electrical signatures are observed in halide perovskite memristors, where ion migration and charge accum ulation govern conductance modulation and short-/long-term potentiation. By combining Impedance Spectroscopy and transient analysis, we explain the electrical tools for quantifying the physics-based memory effects across biology and neuromorphic engineer ing. This electrical approach bridges bioelectrochemistry and neuromorphic hardware, offering new insights into the physical origins of synaptic functionality while providing practical guidance for the design and interpretation of next-generation brain-i nspired electronic systems.
Hernández-Balaguera E., Baron A., Pecqueur S., Bisquert J.
Abstract: Machine olfaction is still not embedded in portable devices. Relationships between electronic materials and chemical environments are hard to decipher to build phenomenologic models that formalize smells' and odors' subjectivity. Also, machine olfaction requires norms to generate large datasets: a generic technology, easy to manufacture and integrable to the broadest range of electronic devices must be identified. To this aim, this study reports on relevant materials to be processed on cost-effective el ectronic noses. Using a single water soluble conducting polymer but sensitized with various p-dopants deposited directly on the circuit board, solvent vapors are successfully recognized on a USB-powered small-sized prototype. The chosen doped polymers ar e easy and safe to process, particularly sensitive to water, but successfully discriminate moist from acetone and ethanol vapors. Diversifying the nature of the doping metal salts increases the prototype receptive field and allows better identification o f the nature of volatile chemical compounds. This study contributes to identifying relevant materials to be processed in an easy way on electronic circuits to implement machine olfaction in portable IoT systems, by the use of various mildly doped conduct ing polymers. By its statistical approach, this study also raises several hypotheses on the physical origin of the sensitivity of a specific class of polymers which transport both electrons and ions. The development of such cost-effective platform allows effectively to compare the performances of multiple materials in a reproducible and systematical way, to ease multi-material performance screening supported by multivariate data analysis.
Kenne Koudjou S., Delarue M., Kingoum Taka A., Baron A., Hafsi B., Pecqueur S.*
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 conducti ng 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 ar e 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 p hysically 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.
Baron A., Brulin L., Scholaert C., Coffinier Y., Alibart F., Pecqueur S.*
Abstract: Understanding and reproducing the brain's ability to store and process information remains a central challenge in neuromorphic engineering. Here, we identify the physical origin and provide a phenomenological interpretation of memory effects underlying s ynaptic-like plasticity, realized in brain-inspired electrochemical dendrites, from fractional calculus. Using hybrid ion-electron conduction pathways, such artificial dendrites exhibit anomalous transient responses arising from the complex dynamics of i onic diffusion and electronic transport across the nanostructured interfaces, effectively embedding history-dependent behavior in the electrochemical junctions. These insights show that the constant phase element (CPE) is more than a simple fitting const ruct used commonly in Electrochemistry: It provides a fundamental description of multiscale transients, capturing the complex dynamical behavior associated with memory effects and their analogy to synaptic functionality. Beyond the classical Mittag-Leffl er responses obtained under previous equilibrium conditions, the hereditary behavior behind artificial synaptic activity emerges as fractional-order dynamics with cumulative Mittag-Leffler patterns in the current responses, offering a natural platform fo r understanding device-level short- and long-term potentiation effects. Our approach, faithfully captured by a quantitative physical model validated through experiments and simulations, encodes past-state memory in neuromorphic devices, bridging physical processes and system-level modeling while enabling dendrite-inspired circuits capable of learning and temporal information processing.
Baron A.*, Pecqueur S., Hernández-Balaguera E.*
Abstract: Conducting polymer dendrite (CPD) morphogenesis is an electrochemical process that enables in materio evolving intelligence in wetware devices. During CPD morphogenesis, voltage transients drive the physical evolution of electrically conductive structure s, thereby programming their filtering properties as nonlinear analog devices. Either studied as an electrochemical experiment or as neuromorphic devices, the dependence of the electrical properties of the electrogenerated structures on the chemical comp osition of their growth environment is still unreported. In this study, we report the existing intrication between the nature and concentration of the electrolytes, electroactive compounds and co-solvents and the electrical and the electrochemical proper ties of CPDs in an aqueous electrolyte. CPDs exhibit various chemical sensitivities in water: Their morphology is highly dependent on the nature of the chemical resources available in their environment. The selection of these resources therefore critical ly influences morphogenesis. In addition, the concentration of the different electrochemical species have varying impacts on growth dynamics, conditioning the balance between thermodynamic and kinetic control on polymer electrosynthesis. By correlating t he dependencies of these evolving objects with the availability of the chemical resources in an aqueous environment, this study offers guidelines to tune the degree of evolution of electronic materials in water and highlights potential avenues for their application. Such evolving hardware is envisioned to exploit the chemical complexity of real-world environments as part of information processing technologies.
Baron A., Scholaert C., Guérin D., Coffinier Y., Alibart F., Pecqueur S.*
Abstract: Electropolymerization under an alternating-current results in the formation of conducting polymers dendrites (CPDs), that conduct both ionic matter and electronic charges simultaneously, offering features from both the worlds of electronics and electroch emistry. Versatile, they can be grown in various electrolytes to develop classes of electronic components that are evolvable and process information using mass-transfer mechanisms. By self-healing or resorbing, CPD have the potential to enable new functi onalities in conventional electronic systems with low material and energy costs, making them a promising avenue for bio-inspired information processing. They also offer a simple, low-voltage alternative to address the ongoing problem of high manufacturin g costs in the microelectronics industry. In this work, we investigate the control of poly(3,4-ethylenedioxythiophene) (PEDOT) based CPD morphology through electrolyte chemistry and its impact on impedance patterns in a two-electrode system, particularly in relation to their observed constant phase element (CPE) behavior. We also explore how morphology influences the charge/discharge dynamics when the dendritic connection is not yet completed. Specifically, it is shown that the electrical parameters of the CPDs, extracted by fitting the transient curves using the Mittag-Leffler function, are defined early during the growth, and that thicker CPDs will allow longer relaxation times. By changing the voltage pulse duration in the growth signal, one has the refore the ability to tune both the characteristic times and the non-ideality of a CPD charge. Ultimately, we aim to demonstrate the applicability of these concepts for programming sensors and integrating neuro-inspired functionalities into electronic no ses, which exploit electrochemistry for the recognition of complex environmental patterns.
Baron A., Scholaert C., Hernández-Balaguera E., Guérin D., Moustiez P., Coffinier Y., Alibart F., Pecqueur S.
Abstract: Conducting polymers are used in conductimetric transducers for many sensing technologies. On arrays, sensitive surfaces feature a large variety of materials: A clean process must be used to co-integrate them without threatening each material's integrity. As electrochemical technique, electropolymerization coats electrically-conductive materials with specific chemistries only on polarized electrodes without contaminating all others. As bottom-up deposition technique, it can be used to coat high-density a rrays at scales that are compatible with micro-electronics. The last decade has also shown the emergence of highly miniaturized potentiostat-galvanostat-impedance platforms, featuring all the necessary resources to communicate with external systems. Ther efore, material electrodeposition and impedimetric readout could practically be performed at very small dimensions and concomitantly on the same circuit board. Here, we present preliminary results on the use of miniaturized impedance analyzers and potent iostats to electropolymerize conducting polymers on a circuit board and to exploit electropolymerized coatings on arrays of microsensors, integrated into a miniaturized prototype. In a loop where a single circuit can supervise both its own manufacturing and its own environmental analysis, the study aims at paving the way for IoT objects embedding electrochemistry and machine-learning resources to support autonomously multi-material selections for electronic noses and tongues conception, directly on a bo ard.
Routier L., Toledo Nauto M., Guérin D., Moustiez P., Baron A., Lmimouni K., Coffinier Y., Hafsi B., Pecqueur S.
Abstract: In the recent challenge to decentralize microelectronics manufacturing (Eur Chip Act) while keeping our commitment to lower our environmental footprint (Eur Green Deal), processes to manufacture electronics must be additive and personalized. To this aim, electropolymerization on a chip could be a turning point to reinvent semiconductor deposition, not exploiting precious ores but synthetic precursors, additively with low wastes and energy consumption at manufacture, in ambient using electrochemistry. If electropolymerization is mastered on large-sized electrodes (mm2), materials behave however far differently at the micrometer scale, where isolated electropolymerized particles with large surface-over-volume ratio are destabilized, from electrode coatin gs to colloidal suspensions in the electrolyte. In this study, we investigate on structure-property relationships between the composition of an electrolyte (electroactive oligothiophenes solubilized in low volatility and toxicity solvents), the arrangeme nt of co-integrated quasi-reference (Ag) and counter (Pt/Au) microelectrodes to stabilize conducting polymer coatings locally on each working microelectrodes in an array of sensing elements. The coatings' electrical and morphological properties are highl y depending on the electrolytes and the set of monomers co-deposited at the same voltage. Important selections have to be made in regards to monomers' oxidation potential, their solubility in specific solvents and polymers' electroactivity, which control s both the electrical property of the sensors and the stability of the material in an iterative deposition process. By mastering electropolymerization on a chip, electrochemistry shall unlock a true bottleneck for multi-material co-integration to manufac ture highly integrated electronic noses and tongues.
Moustiez P., Guérin D., Baron A., Pecqueur S.
Abstract: Conventional electronics is founded on a paradigm where shaping perfect electrical elements is done at the fabrication plant, so as to make devices and systems identical, "eternally immutable". In nature, morphogenic evolutions are observed in most livin g organisms and exploit topological plasticity as a low-resource mechanism for in operando manufacturing and computation. Often fractal, the resulting topologies feature inherent disorder: a property which is never exploited in conventional electronics m anufacturing, while necessary for data generation and security in software. In this study, we present how such properties can be exploited to implement long-term and evolvable synaptic plasticity in an electronic hardware. The rich topology of conducting polymer dendrites (CPDs) is exploited to program the non-ideality of their electrochemical capacitances containing constant-phase-elements. Their evolution through structural changes alters the characteristic time constants for them to charge and discha rge with the applied voltage stimuli. Under a train of voltage spikes, the evolvable current relaxation of the electrochemical systems promotes short-term plasticity with timescales ranging from milliseconds to seconds. This large window depends on the t emporality of the voltage pulses used for reading, but also on the structure of a pair of CPDs on two electrodes, grown by voltage pulses. This study demonstrates how relevant physically transient and non-ideal electrochemical components can be exploited for unconventional electronics, with the aim to mimic a universal property of living organisms which could barely be replicated in a silicon monocrystal.
Baron A., Hernández-Balaguera E., Scholaert C., Alibart F., Pecqueur S.*
Abstract: Conducting Polymer Dendrites (CPD) can engrave sophisticated patterns of electrical interconnects in their morphology, networking input with output nodes, from low-voltage spikes and with very minimal amounts of resources: they may unlock in operando man ufacturing functionalities for an electronics framework using metamorphism conjointly with electron transport as part of the information processing. The relationship between their structure and the information transport is still however very unclear and hinders the exploitation of the versatility of their morphologies to store and process electrodynamic information. This study details the evolution of CPD's circuit parameters with their growth and shape. By the means of electrochemical impedance spectro scopy (EIS), multiple distributions of relaxation times (DRT) are evidenced and evolve specifically upon growth. Correlations are established between the dispersive capacitance of dendritic morphologies and their growth duration, independently from exoge nous physical variables, such as distance, multi-component evaporation or aging. Deviation of the anomalous capacitance from the conventional Debye dielectric relaxation can be programmed within the morphology, as the growth controls the dispersion coeff icient of the dendrite's constant-phase elements relaxation. These results suggest that the fading-memory time window of pseudo-capacitive interconnects can practically be conditioned using electrogenerated CPD morphogenesis as an in materio learning mec hanism. This study confirms the perspective of using electrochemistry for unconventional electronics, engraving information with low voltage events in the physics of conducting polymer objects, and storing information in their morphology, accessible by i mpedance spectral analysis.
Baron A., Hernández-Balaguera E., Pecqueur S.*
Abstract: Contributions of organic semiconducting materials to electronics are particularly hard to assess: As macromolecular organizations, they have low enthalpy so they can be processed in soft conditions and they have resilience to deformation. However, for th e same reason, they have also broader density of energy states and more instabilities than silicon in ambient. Controlling matter's order at low scale and its properties for as long as possible were always golden standards for microelectronics. Neverthel ess, in a time where brain functioning rises even more as a source of inspiration, shall it still be so? Here are presented clues on how physical property dispersions may be relevant features for information generator nodes to recognize patterns. In a co ntext where the information to recognize is not trivial to physically define, no model can rule sensors' classification a priori. Despite this, broadening the conducting polymer temporal responses in a sensing array allows recognizing dynamical voltage p atterns, or broadening conducting polymer's chemistry in a sensing array enlarges a classifier's perception field to recognize solvent vapors in air. By the nature of property dispersions in regards to the information to recognize, physical variabilities (structural and chemical) can be assets to exploit for pattern recognition and not necessarily drawbacks to bypass for hardware manufacturing. The brain architecture is also transient: a part of the processed information is engraved in its topology, sho wing that a hardware classifier can make use of physical instabilities as part of its programing, by forming new connections in a nodal architecture. Some evidences are also presented here, on how dendritic morphogenesis of a conducting polymer can be a mean to store past voltage experiences in the impedance between nodes in a topology. Very distinct electrochemical features appear in the readout impedance information after growth and these features are to be associated with the shape of a voltage wave inputted on the junction. By the physical implementation of materials' disorder and transience in electronics devices, it is expected that organic semiconductors will integrate essential ingredients in future-emerging information generator nodes beyond s ensors: from embedded random information generating resources to evolving abilities in information classification architectures.
Pecqueur S., Baron A., Scholaert C., Toledo Nauto M., Moustiez P., Routier L., Guérin D., Lmimouni K., Coffinier Y., Hafsi B., Alibart F.
Abstract: Conducting Polymer Dendrites (CPD) are truly inspiring for unconventional electronics that shapes topological circuitries evolving upon an application. Driven by electrochemical processes, an electrochemical impedance rules signal propagation from one no de to another. However, clear models dictating their behavior in an electroactive electrolyte have not been identified yet. In this study, we investigate on CPD in an aqueous electrolyte by impedance spectroscopy to unify their signal transport with an e lectrical model, aiming to define a circuit simulation block to integrate these objects in systems for in materio information processing.
Baron A., Hernández-Balaguera E., Pecqueur S.
Abstract: In electronics, circuits are predefined for a lifetime. Fabricating always the same with highly stable components is a real advantage for mass production. However when technologies are no longer up to date, electronic devices can only be discarded, poorl y recycled, because they cannot adapt. Living organisms, on the other hand, are constantly evolving. They learn and interact with their environment, and when doing so, brain-neurons or tree-roots grow with appearent disorder but a surprising way to learn to exploit local ressources. The way they branch out can be described as morphogenesis and is the symbol of a natural intelligence, too complex to modelize. While conventional electronics seeks to eliminate disorder and variability, we hypothesize that it is possible to make use of it in a novel electronics that uses electrochemistry to mimic biological processes for adaptation. In this study, we will discuss on morphogenesis of a conducting polymer (PEDOT:PSS) through the AC electropolymerization of E DOT in water. The dendritic objects exhibit various morphologies, differing in their thicknesses and number of branches. Their growth mechanism involves diffusion and electromigration of charged species within the solution. We also present the first resu lts characterizing a connection of those objects in the frequency domain, where various dynamics can be observed due to specific mechanisms at the different interfaces. The electropolymerization of EDOT offers an inexpensive way to grow directed connecti ons with a specific impedance to connect components in a system by voltage activation. It could be used to address the limits of the current electronics in terms of cost and flexibility while taking a form that is closer to what can be found in nature.
Abstract: Identifying relevant machine-learning features for multi-sensing platforms is both an applicative limitation to recognize environments and a necessity to interpret the physical relevance of transducers' complementarity in their information processing. Pa rticularly for long acquisitions, feature extraction must be fully automatized without human intervention and resilient to perturbations without increasing significantly the computational cost of a classifier. In this study, we investigate the relative r esistance and current modulation of a 24-dimensional conductimetric electronic nose, which uses the exponential moving average as a floating reference in a low-cost information descriptor for environment recognition. In particular, we identified that dep ending on the structure of a linear classifier, the 'modema' descriptor is optimized for different material sensing elements' contributions to classify information patterns. The low-pass filtering optimization leads to opposite behaviors between unsuperv ised and supervised learning: the latter one favors longer integration of the reference, allowing to recognize five different classes over 90%, while the first one prefers using the latest events as its reference to cluster patterns by environment nature . Its electronic implementation shall greatly diminish the computational requirements of conductimetric electronic noses for on-board environment recognition without human supervision.
Haj Ammar W., Boujnah A., Baron A., Boubaker A., Kalboussi A., Lmimouni K., Pecqueur S.*
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