1,721,003 research outputs found
Electrical Resistance Tomography of Conductive Thin Films
Full text linkThe electrical resistance tomography (ERT) technique is applied to the measurement of sheet conductance maps of both uniform and patterned conductive thin films. Images of the sheet conductance spatial distribution and local conductivity values are obtained. Test samples are tin-oxide films on glass substrates, with electrical contacts on the sample boundary. Some samples are deliberately patterned in order to induce null conductivity zones of known geometry, while others contain higher conductivity inclusions. Four-terminal resistance measurements among the contacts are performed with a scanning setup. The ERT reconstruction is performed by a numerical algorithm based on the total variation regularization and the L-curve method. ERT correctly images the sheet conductance spatial distribution of the samples. The reconstructed conductance values are in good quantitative agreement with independent measurements performed with the van der Pauw and the four-point probe methods
A simple algorithm to find the L-curve corner in the regularisation of ill-posed inverse problems
Full text linkWe propose a simple algorithm to locate the 'corner' of an L-curve, a function often used to select the regularisation parameter for the solution of ill-posed inverse problems. The algorithm involves the Menger curvature of a circumcircle and the golden section search method. It efficiently finds the regularisation parameter value corresponding to the maximum positive curvature region of the L-curve. The algorithm is applied to some commonly available test problems and compared to the typical way of locating the l-curve corner by means of its analytical curvature. The application of the algorithm to the data processing of an electrical resistance tomography experiment on thin conductive films is also reported
Electrical Resistance Tomography on thin films: Sharp conductive profiles
No full textIn this paper Electrical Resistance Tomography is applied to recover maps of sheet conductance of commercial metal-oxide thin films, chosen as test material. Results are compared to nominal specifications and van der Pauw, four-point probe measurements. It is shown how Electrical Resistance Tomography can measure with good accuracy the nominal conductance value in uniform samples and also identify resistivity inhomogeneities in altered samples. The choice of the reconstruction algorithm is also briefly discussed
New IEC standards for the measurement of sheet resistance on large-area graphene using the van der Pauw and the in-line four-point probe methods
Full text linkGraphene has evolved from a scientific research subject to an industrial product, in need of a normative basis for its key control characteristics. Recently two new IEC technical specifications that establish standardized procedures for assessing the sheet resistance R S of monolayer graphene have been published. These new standards, part of the IEC TS 62607-6-xx series, outline protocols for employing two contact methods: i) van der Pauw, and ii) in -line four -point probe. In the following we present and discuss illustrative examples of the scientific experiments designed and performed to inform the standardization process behind the presented standards. In particular we report about the investigation of mechanical contacting of chemical -vapor -deposited monolayer graphene and the measurement of the R S in cm 2 area graphene samples with non uniform resistivity distributions. This paper includes an overview of the broader IEC context, detailing the key steps in the development of the standards themselves
A correlation noise spectrometer for flicker noise measurement in graphene samples
Full text linkWe present a high-resolution digital correlation spectrum analyzer for the measurement of low frequency resistance fluctuations in graphene samples. The system exploits the cross-correlation method to reject the amplifiers' noise. The graphene sample is excited with a low-noise DC current. The output voltage is fed to two two-stage low-noise amplifiers connected in parallel; the DC signal component is filtered by a high-pass filter with a cutoff frequency of 34 mHz. The amplified signals are digitized by a two-channel synchronous ADC board; the cross-periodogram, which rejects uncorrelated amplifiers' noise components, is computed in real time. As a practical example, we measured the noise cross-spectrum of graphene samples in the frequency range from 0.153 Hz to 10 kHz, both in two- and four-wire configurations, and for different bias currents. We report here the measurement setup, the data analysis and the error sources
A Multiterminal Setup for Complex Dynamics Characterization and Unconventional Computing in Self-Organizing Memristive Networks
Full text linkThe recent growing interest in neuromorphic architectures based on emergent dynamics of self-organizing memristive networks has posed some challenges regarding the spatiotemporal characterization of these multiterminal systems. This work presents a versatile measurement platform specifically designed for the characterization of memristive nanowire networks and for testing the implementation of unconventional computing paradigms in these systems. By integrating an FPGA controlled, parallel multiterminal array of source-measure units with a custom fixture based on spring-loaded electrodes, the system allows for real-time, reconfigurable voltage and current measurements across 16 terminals without hardware reconnections. The platform supports seamless transition between conventional two-terminal characterization, multiterminal characterization and testing computational properties in the framework of physical reservoir computing. Local conductance measurements, voltage mapping, and real-time dynamic monitoring offer unique insights into the spatiotemporal behavior of the networks. Furthermore, we show that the system enables to correlate electrical properties of the multiterminal network in terms of conductance matrices and voltage maps with computational performances, allowing also adaptive control over the network's operating state. The here reported setup provides a versatile platform for computing at the matter level (i.e., in materia) with multiterminal systems based on self-organizing memristive networks
Ottimizzazione del processo di produzione e di caratterizzazione elettrica di dispositivi in grafene
No full textL'obiettivo di questo report è di riassumere i recenti sviluppi che la produzione di dispositivi in grafene ha avuto all'interno dei laboratori INRiM. Lo studio è stato effettuato su grafene di origine commerciale realizzato attraverso la tecnica della Chemical Vapor Deposition (CVD) su rame e poi successivamente trasferito su un supporto isolante (SiO2). Migliorando alcuni aspetti del processo è stato osservato , per la prima volta in istituto su grafene da CVD su rame, il punto di inversione di portatori di carica in dispositivi prodotti nei laboratori del QR e in Nanofacility. Il processo ottimizzato è stato poi testato preliminarmente (i risultati infatti non saranno inseriti in questo resoconto) su campioni prodotti in INRiM tramite CVD su cobalto, lasciando presagire che i risultati non siano dovuti al materiale utilizzato ma al miglioramento del processo. The aim of this report is to summarize the recent developments that the production of graphene devices has had in the INRiM laboratories. The study was carried out on commercial graphene grown by Chemical Vapor Deposition (CVD) on Cu and then transferred on an insulating support (SiO2). The Dirac point has been measured, for the first time in INRiM on CVD grown graphene devices produced in the QR laboratories and in Nanofacility Piemonte. The optimized process was then tested previously (in fact, the results will not be included in this report) on samples produced in INRiM via CVD on Co. As a consequence the results seems not to be due to the material used, but to the improvements of the process
Tomography of memory engrams in self-organizing nanowire connectomes
Full text linkAbstract Self-organizing memristive nanowire connectomes have been exploited for physical (in materia) implementation of brain-inspired computing paradigms. Despite having been shown that the emergent behavior relies on weight plasticity at single junction/synapse level and on wiring plasticity involving topological changes, a shift to multiterminal paradigms is needed to unveil dynamics at the network level. Here, we report on tomographical evidence of memory engrams (or memory traces) in nanowire connectomes, i.e., physicochemical changes in biological neural substrates supposed to endow the representation of experience stored in the brain. An experimental/modeling approach shows that spatially correlated short-term plasticity effects can turn into long-lasting engram memory patterns inherently related to network topology inhomogeneities. The ability to exploit both encoding and consolidation of information on the same physical substrate would open radically new perspectives for in materia computing, while offering to neuroscientists an alternative platform to understand the role of memory in learning and knowledge
Emerging Spatiotemporal Dynamics in Multiterminal Neuromorphic Nanowire Networks Through Conductance Matrices and Voltage Maps
Full text linkSelf-organizing memristive nanowire (NW) networks are promising candidates for neuromorphic-type data processing in a physical reservoir computing framework because of their collective emergent behavior, which enables spatiotemporal signal processing. However, understanding emergent dynamics in multiterminal networks remains challenging. Here experimental spatiotemporal characterization of memristive NW networks dynamics in multiterminal configuration is reported, analyzing the activation and relaxation of network’s global and local conductance, as well as the inherent spatial nonlinear transformation capabilities. Emergent effects are analyzed i)during activation, by investigating the spatiotemporal dynamics of the electric field distribution across the network through voltage mapping; ii) during relaxation, by monitoring the evolution of the conductance matrix of the multiterminal system. The multiterminal approach also allowed monitoring the spatial distribution of nonlinear activity, demonstrating the impact of different network areas on the system’s information processing capabilities. Nonlinear transformation tasks are experimentally performed by driving the network into different conductive states, demonstrating the importance of selecting proper operating conditions for efficient information processing. This work allows a better understanding of the local nonlinear dynamics in NW networks and their impact on the information processing capabilities, providing new insights for a rational design of self-organizing neuromorphic systems
Smart Glasses for Visually Evoked Potential Applications: Characterisation of the Optical Output for Different Display Technologies
Full text linkOff-the-shelf consumer-grade smart glasses are being increasingly used in extended reality and brain–computer interface applications that are based on the detection of visually evoked potentials from the user’s brain. The displays of these kinds of devices can be based on different technologies, which may affect the nature of the visual stimulus received by the user. This aspect has substantial impact in the field of applications based on wearable sensors and devices. We measured the optical output of three models of smart glasses with different display technologies using a photo-transducer in order to gain insight on their exploitability in brain–computer interface applications. The results suggest that preferring a particular model of smart glasses may strongly depend on the specific application requirements
- …
