Abstract: Gas detection technologies are essential tools in maintaining safety and environmental standards across various applications. Through advanced sensors and analytical techniques, these systems aim to quickly detect and classify molecular content in an env ironment, providing valuable insights for early warning and effective response to incidents. In this work, we present the development of miniaturized, multiplexed, and connected electronic nose (e-nose) based on impedance spectroscopy technology. Our pla tform has been tested and optimized to process electrical responses of 15 conductimetric cells, each cell is tuned using a drop-casted conducting polymer poly(3-hexylthiophene) and 14 different triflate salts. The recognition of various solvents vapor (a cetone, methanol, isopropanol, water, ethanol and blends of the last two at various concentrations) relies on a Deep-Convolutional Neural Network based on a back propagation algorithm with two hidden layers of 64 and 32 neurons respectively. The achieved experimental results show an effective classification for the e-nose data to discriminate the alcoholic blends by type and composition, with high classification accuracy (~96%).

Abstract: CLD (Chlordecone) is a persistent organic pollutant (POP) of great concerns due toxicity and environmental persistence. To this end, we study organic electrochemical transistors (OECT) featuring biological probes to detect CLD. Here, we report a strategy for immobilizing a D09 VHH receptor, which detects CLD-biot in water. WCA (Water Contact Angle), AFM, XPS and FTIR confirm the successful immobilization of D09 on a surface operating as gate electrode sensitive to the presence of CLD-biot in the transfe r characteristic.

Abstract: Over the past few years, organic electronics - and especially organic mixed ionic electronic conductors (OMIECs) - has taken bio sensing and neuromorphic applications to a whole new level. However, one of the major limitations of the mainstream technolog ies today is that electronic circuits need to be pre-shaped according to the intended use and the expected outcome. This top-down approach, far from being flexible/adaptive, does not really make the most of the resources at hand, as it is hard to predict precisely where cells will be located. To counter that, we can either choose to increase the density and the number of electrodes, so that the entire area would be mapped, or shift from a top-down to a bottom-up approach which would allow for a more enl ightened decision-making process. Recently, the electrodeposition of PEDOT:PSS has been explored as a novel technique to grow conducting polymer films and fibers on non-conductive substrates. The work of Janzakova and coworkers took that concept a step f urther by using electropolymerization of EDOT as a way to create freestanding dendritic-like conductive fibers in a 3D environment, paving the way for in operando material modification, and in fine bottom-up fabrication routes that would be more adaptive and allow for more flexibility. Moreover, it was lately showed that these objects could work as Organic Electrochemical Transistors (OECTs). Here, we explore the possibility of growing dendritic-like PEDOT fibers on Multielectrode Arrays (MEAs) via elec tropolymerization of EDOT. Electrophysiological measurements are based on the capacitive coupling between cells and the electrode material. In comparison with local electrodes, the dendritic objects present spatially distributed impedance due to the exte nsions of their dendritic branches interacting with the biological environment. We investigate the relation between morphology and impedance in these dendritic-like fibers by using a non-conventional Electrochemical Impedance Spectroscopy (EIS) setup tha t will allow us to apply a potential difference between the two ends of the dendrites, thus studying how biasing them can affect their behavior. Moreover, it appears that dendritic fibers can be considered both as passive electrodes as well as active dev ices. We explore the use of these two strategies in the context of electrophysiological measurements. Finally, the ability to record biological signals results from the interaction between cells and an electrode. Unconventional objects such as dendrites present spatio-temporal filtering properties that could affect the recording of such signals. We investigate how tuning the impedance of a dendrite might be used to record efficiently bio-signals.

Abstract: The development of electronic devices such as microelectrode arrays (MEAs), used to record extracellularly simultaneous electrical activity of large populations of neurons is blooming. To enhance the quality of the recordings, the use of electrode made o f conducting polymer such as PEDOT has recently emerged for optimizing the performance of microelectrodes due to its mixed ionic electronic conduction, biocompatibility and low impedance. However, the extent to which these new interfaces can help the alg orithmic pipelines of spike sorting, i.e. turning extracellular potentials into individual spike trains remains unexplored. To address this issue, we checked if the physical positions of the neurons could be reliably inferred from extracellular electrica l recordings obtained by MEAs, and thus be exploited by downstreams spike sorting algorithms. To do so, we combine high resolution images of neuronal tissues and dense recordings performed via high performant electropolymerized electrodes based MEAs. Fir stly, we report the use of EDOT electropolymerization to tune post-fabrication material and geometrical parameters of passive microelectrodes. The process optimizes the cell/electrode interface by decreasing its impedance and improving its affinity with neurons: results demonstrate a better biocompatibility and improved signal-to-noise ratio (SNR) (up to 40 dB). Thanks to the higher SNR, we were able to detect more cells in comparison with gold electrodes from the same neural network by using spike sort ing. Hence, the higher number of cells detected will lead into more accurate analysis of the localization of the active neurons on top of MEA. Secondly, by using these high performant MEAs, we investigated the possibility to accurately estimate the posit ions of the neurons solely from extracellular recordings by studying the correlation between electrical activity (obtained via spike sorting), optical imaging (Fluorescent) and Scanning Electron Microscopy (SEM) of neural networks cultured on MEAs. By us ing the SpykingCircus software to spike sort the extracellular recordings, we estimated the positions of the neurons either by using the center of mass of their electrical signatures, or by inferring the positions assuming cells would behave as monopoles . By superposition of the fluorescent and the SEM images, we compared the observed physical positions of the neurons with the ones predicted by the two aforementioned methods. This approach showed the high accuracy of the monopole hypothesis compared to the center of mass. In this work, we showed how the use of a material engineering technique for optimizing state of art MEAs can enhance the quality of the recordings. Hence, the correlation of these high quality recordings with optical imaging paves the way towards new algorithmic possibilities for spike sorting algorithms that could make use of a more reliable estimation of neuronal positions.

Abstract: Conducting polymers can sense gases, however, it is mostly the dopant that dictates which ones: Here we show that a single conducting polymer discriminates gas-phase water, from ethanol, from acetone, on demand, by varying the nature of its dopant. Seven triflate salts are evaluated as mild to strong p-dopants for poly(3-hexylthiophene) in sensing micro-arrays. Based on the nature of the salts, each material shows a dynamical pattern of polymer conductance modulation that is specific to the exposed solv ent vapors. By multivariate data analysis, we show that the two mildest ones used in an array can be trained to reliably discriminate the three gases, proving that integrating one single conducting polymer suffices to build the input layer of a resistive nose. Moreover, the study points out the existence of tripartite donor-acceptor charge-transfer complexes responsible for chemo-specific molecular sensing. By showing that molecular acceptors have duality to either p-dope and co ordinate volatile electron donors, such behavior can be used to unravel the role of frontier orbital overlapping in organic semiconductors and the formation of charge-transfer complexes in molecular semiconductors.

Abstract: We have adapted a "peel-off" process to structure stacked organic semiconductors (conducting polymers or small molecules) and metal layers for diode microfabrication. The fabricated devices are organic diode rectifier in a coplanar waveguide structure. U nlike conventional lithographic process, this technique does not lead to destroy organic active layers since it does not involve harsh developer or any non-orthogonal solvent that alter the functionality of subsequentially deposited materials. This proce ss also involves recently reported materials, as a p-dopant of an organometallic electron acceptor Copper(II) trifluoromethanesulfonate, that play the role of hole injection layer in order to enhance the performances of the diode. Comparatively to self-a ssembled monolayers based optimized structures, the fabricated diodes show higher reproducibility and stability. High rectification ratio for realized pentacene and poly(3-hexylthiophene) diodes up to 10^6 has been achieved. Their high frequency response has been evaluated by performing theoretical simulations. The results predict operating frequencies of 200 MHz and 50 MHz for pentacene and P3HT diode rectifiers respectively, with an input oscillating voltage of 2 V peak-to-peak, promising for RFID dev ice applications or for GSM band energy harvesting in low-cost IoT objects.

Abstract:

Abstract: Organic electrochemical transistors (OECTs) offer a powerful functionality for both sensing and neuro-inspired electronics with still much to understand on their time-dependent behavior. OECTs based on PEDOT:PSS conducting polymer h ave revealed two distinctive operation regimes of a device: a low frequency and a higher frequency regimes dominated by the conductance of the polymer and of the gating electrolyte, respectively. However, the systematically observed non-idealities in t he impedance spectra over the large frequency range and ionic concentrations caused by both the materials and the device complexity cannot be explained by simple models. We report on modeling of OECTs by an optimized equivalent circuit model that takes into account the frequency dependence of the device impedance from 1 Hz to 1 MHz for a large ionic concentration range (10^-4 - 1 M) and various chemical nature of the ions. Based on experimental data for KCl(aq) and CaCl2(aq). the model explains the time dependency of the OECT as a whole and discusses the sensibility of new introduced elements pseudo-capacitance and inductance to concentration and voltage to understand the local physics. In particular, the observed concentrat ion-dependent negative phase change in the impedance suggests an inductive contribution to the device impedance due to the doping/dedoping process in the organic layer driven by the applied harmonic voltage as an underlying mechanism . The introduction of these non-redundant elements and the study of their behaviors as function of ionic concentration and applied voltage give a more detailed picture of the OECT working principles at a specific time domains which are highly relevant for multi-parametric ion sensing and neuromorphic computing.

Abstract: Astroglial ion channels and calcium signalling play a central role in the physiology and pathophysiology of the Central Nervous System. In this context, increasing efforts are needed to generate innovative tool s for monitoring astrocytes biochemical or bioelectrical activity in vitro and in vivo. Organic field effect devices have a great potential for generating advanced biomedical tools to enable real-time recording and manipulation of communicati on signals between neural cells. We previously reported on transparent Organic Cell Stimulating and Sensing Transistors (O-CSTs) that provide bidirectional stimulation and recording of primary neurons. The transparency of the device also all ows the optical imaging of the modulation of the astroglial calcium signalling bioelectrical activity. Here we explore O-CST functionality to stimulate, evoke and control astroglial calcium signalling and whole cell conductance in primary cultured astrocytes. We found thatprimary astroglial cells can adhere, grow and differentiate on the perylene based field-effect transistor. Furthermore does the organic material preserve astrocytes electrophysiological properties. W e show, that the O-CST provides stimulation and thereby evokes intracellular astrocytic calcium response, which can be determined by calcium imaging. The evoked signal was blocked by carbenoxolone and Ruthenium red, thus suggesting i nvolvement of Connexins and TRPV channels. By means of patch-clamp analyses, we explore the effect of the stimulation on the whole-cell conductance of patched astrocytes. We found that the stimulation lead to an exclusive increase in the inward current that could be prevented by application of Ruthenium Red prior to stimulation. This finding suggests a contribution of the transient receptor potential (TRP) channels, of which TRPV-4 has been shown in former studies to mediate Ca2+ influx in astrocytes. Molecular modelling of field distribution obtained by O-CST is also in agreement with experimental data. Our organic cell stimulating and sensing device paves the way to a new generation of devices for stimulation, manipulation and recording of astroglial cells' bioelectrical activity in vitro.

Abstract: Organic electronic is up to now the most promising technology in order to realize opto electronic devices suitable on flexible substrates, which can open new markets on plastic-based products. Nevertheless, to compete classic technologies on already exis ting markets, organic electronic needs to improve several of its electrical performances among others. Doping organic semiconductors is one strategy to optimize electrical conductivity on organic materials but is still very limiting compared to inorganic , and understanding the complex mechanism between dopant and organic semiconductor is a prerequisite for their optimization. Even if the experience shows classic dopants to be redox-active chemicals (Cs, Li, O₂), the redox activity of some che micals is no prerequisite for doping. Despite its strong reducing property, Cr₂(tfa)₄ has been demonstrated to be a p-dopant for its Lewis acidity. Cr₂(tfa)₄ presents an air-sensitivity due to the redox-activit y of the core, which implies that the conception of Lewis acids and bases, stable under oxidizing or reducing conditions,can result in potential air-stable materials which would dope organic semiconductors by the formation of hybrid charge-transfer compl exes.