Perspective: Organic electronic materials and devices for neuromorphic engineering

Neuromorphic computing and engineering has been the focus of intense research efforts that have been intensified recently by the mutation of Information and Communication Technologies (ICT). In fact, new computing solutions and new hardware platforms are expected to emerge to answer to the new needs and challenges of our societies. In this revolution, lots of candidates technologies are explored and will require leveraging of the pro and cons. In this perspective paper belonging to the special issue on neuromorphic engineering of Journal of Applied Physics, we focus on the current achievements in the field of organic electronics and the potentialities and specificities of this research field. We highlight how unique material features available through organic materials can be used to engineer useful and promising bioinspired devices and circuits. We also discuss about the opportunities that organic electronic are offering for future research directions in the neuromorphic engineering field

Cation Discrimination in Organic Electrochemical Transistors by Dual Frequency Sensing

In this work, we propose a strategy to sense quantitatively and specifically cations, out of a single organic electrochemical transistor (OECT) device exposed to an electrolyte. From the systematic study of six different chloride salts over 12 different concentrations, we demonstrate that the impedance of the OECT device is governed by either the channel dedoping at low frequency and the electrolyte gate capacitive coupling at high frequency. Specific cationic signatures, which originates from the different impact of the cations behavior on the poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) polymer and their conductivity in water, allow their discrimination at the same molar concentrations. Dynamic analysis of the device impedance at different frequencies could allow the identification of specific ionic flows which could be of a great use in bioelectronics to further interpret complex mechanisms in biological media such as in the brain.Comment: Full text and supporting informatio

Concentration-control in all-solution processed semiconducting polymer doping and high conductivity performances

Simultaneously optimizing performances, processability and fabrication cost of organic electronic materials is the continual source of compromise hindering the development of disruptive applications. In this work, we identified a strategy to achieve record conductivity values of one of the most benchmarked semiconducting polymers by doping with an entirely solution-processed, water-free and cost-effective technique. High electrical conductivity for poly(3-hexylthiophene) up to 21 S/cm has been achieved, using a commercially available electron acceptor as both a Lewis acid and an oxidizing agent. While we managed water-free solution-processing a three-time higher conductivity for P3HT with a very affordable/available chemical, near-field microscopy reveals the existence of concentration-dependent higher-conductivity micro-domains for which furthermore process optimization might access to even higher performances. In the perpetual quest of reaching higher performances for organic electronics, this work shall greatly unlock applications maturation requiring higher-scale processability and lower fabrication costs concomitant of higher performances and new functionalities, in the current context where understanding the doping mechanism of such class of materials remains of the greatest interest

A Temporal Filter to Extract Doped Conducting Polymer Information Features from an Electronic Nose

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. Particularly 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 on the relative resistance 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 depending 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 unsupervised 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 clusterize 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

Reservoir Computing for Sensing - an Experimental Approach

International audienceThe increasing popularity of machine learning solutions puts increasing restrictions on this field if it is to penetrate more aspects of life. In particular, energy efficiency and speed of operation is crucial, inter alia in portable medical devices. The Reservoir Computing (RC) paradigm poses as a solution to these issues through foundation of its operation the reservoir of states. Adequate separation of input information translated into the internal state of the reservoir - whose connections do not need to be trained - allow to simplify the readout layer thus significantly accelerating the operation of the system. In this paper, the theoretical basis of RC was first described, followed by a description of its individual variants, their development and state-of-the-art applications in chemical sensing and metrology: detection of impedance changes and ion sensing. Presented results indicate applicability of reservoir computing for sensing and validating the SWEET algorithm experimentally

On a generic theory of the organic electrochemical transistor dynamics

In the recent years, the organic electrochemical transistors (OECT) have attracted considerable attention for biosensing applications due to the biocompatibility of their materials and their low operating voltages. Upon exposure to an electrolyte, the drain current becomes ion-dependent. This can be exploited for sensing ion applications. To facilitate the process of designing such powerful ion sensing devices one needs the ability to simulate the transient dynamical behavior of many OECT elements connected in a network. We have developed a generic theoretical model of the OECT element that can be used for such purposes. Our OECT element resembles a typical FET three-port element with the response function parameterized with an additional time-dependent variable, T, which describes how far the element operates from the stationary state. We have constructed a dynamical equation that describes how T changes in time when the element is exposed to arbitrary external voltages. This makes the element model highly interoperable with generic electrical circuit simulators. We provide an example of possible numerical implementation using the modified nodal analysis. We tested the underlying theoretical assumptions by comparing model predictions with experimental data and found a reasonable agreement. Our model describes the typical current spikes observed in the literature

Reservoir Computing for Sensing - an Experimental Approach

International audienceThe increasing popularity of machine learning solutions puts increasing restrictions on this field if it is to penetrate more aspects of life. In particular, energy efficiency and speed of operation is crucial, inter alia in portable medical devices. The Reservoir Computing (RC) paradigm poses as a solution to these issues through foundation of its operation the reservoir of states. Adequate separation of input information translated into the internal state of the reservoir - whose connections do not need to be trained - allow to simplify the readout layer thus significantly accelerating the operation of the system. In this paper, the theoretical basis of RC was first described, followed by a description of its individual variants, their development and state-of-the-art applications in chemical sensing and metrology: detection of impedance changes and ion sensing. Presented results indicate applicability of reservoir computing for sensing and validating the SWEET algorithm experimentally

High Rectification Ratio in Polymer Diode Rectifier through Interface Engineering with Self-Assembled Monolayer

In this work, we demonstrate P3HT (poly 3-hexylthiophene) organic rectifier diode both in rigid and flexible substrate with a rectification ratio up to 106. This performance has been achieved through tuning the work function of gold with a self-assembled monolayer of 2,3,4,5,6-pentafluorobenzenethiol (PFBT). The diode fabricated on flexible paper substrate shows a very good electrical stability under bending tests and the frequency response is estimated at more than 20 MHz which is sufficient for radio frequency identification (RFID) applications. It is also shown that the low operating voltage of this diode can be a real advantage for use in a rectenna for energy harvesting systems. Simulations of the diode structure show that it can be used at GSM and Wi-Fi frequencies if the diode capacitance is reduced to a few pF and its series resistance to a few hundred ohms. Under these conditions, the DC voltages generated by the rectenna can reach a value up to 1 V

Significance of Plankton Community Structure and Nutrient Availability for the Control of Dinoflagellate Blooms by Parasites: A Modeling Approach

Dinoflagellate blooms are frequently observed under temporary eutrophication of coastal waters after heavy rains. Growth of these opportunistic microalgae is believed to be promoted by sudden input of nutrients and the absence or inefficiency of their natural enemies, such as grazers and parasites. Here, numerical simulations indicate that increasing nutrient availability not only promotes the formation of dinoflagellate blooms but can also stimulate their control by protozoan parasites. Moreover, high abundance of phytoplankton other than dinoflagellate hosts might have a significant dilution effect on the control of dinoflagellate blooms by parasites, either by resource competition with dinoflagellates (thus limiting the number of hosts available for infection) or by affecting numerical-functional responses of grazers that consume free-living parasite stages. These outcomes indicate that although both dinoflagellates and their protozoan parasites are directly affected by nutrient availability, the efficacy of the parasitic control of dinoflagellate blooms under temporary eutrophication depends strongly on the structure of the plankton community as a whole

Precision of neuronal localization in 2D cell cultures by using high-performance electropolymerized microelectrode arrays correlated with optical imaging

International audienceRecently, the development of electronic devices to extracellularly record the simultaneous electrical activities of numerous neurons has been blooming, opening new possibilities to interface and decode neuronal activity. In this work, we tested how the use of EDOT electropolymerization to tune post-fabrication materials could optimize the cell/electrode interface of such devices. Our results showed an improved signal-to-noise ratio, better biocompatibility, and a higher number of neurons detected in comparison with gold electrodes. Then, using such enhanced recordings with 2D neuronal cultures combined with fluorescent optical imaging, we checked the extent to which the positions of the recorded neurons could be estimated solely via their extracellular signatures. Our results showed that assuming neurons behave as monopoles, positions could be estimated with a precision of approximately tens of micrometers