Mirko Prezioso

University of California, Santa Barbara | UCSB · Department of Electrical and Computer Engineering

The development of neuromorphic devices is a pivotal step in the pursuit of low‐power artificial intelligence. A synaptic analog is one of the building blocks of this vision. The synaptic behavior of molecular La0.7Sr0.3MnO3/tris(8‐hydroxyquinolinato)gallium/AlOx/Co spintronic devices is studied, where the conductance plays the role of the synaptic...

We present a comprehensive phenomenological model for the crossbar integrated metal-oxide continuous-state memristors. The model consists of static and dynamic equations, which are obtained by fitting a large amount of experimental data, collected on several hundred devices. Model describes the average devices’ I-V characteristics as well as their...

The key operation in stochastic neural networks, which have become the state-of-the-art approach for solving problems in machine learning, information theory, and statistics, is a stochastic dot-product. While there have been many demonstrations of dot-product circuits and, separately, of stochastic neurons, the efficient hardware implementation co...

The understanding of magnetoresistance (MR) in organic spin valves (OSVs) based on molecular semiconductors is still incomplete after its demonstration more than a decade ago. While carrier concentration may play an essential role in spin transport in these devices, direct experimental evidence of its importance is lacking. We probed the role of ch...

The understanding of magnetoresistance (MR) in organic spin valves (OSVs) based on molecular semiconductors is still incomplete after its demonstration more than a decade ago. While carrier concentration may play an essential role in spin transport in these devices, direct experimental evidence of its importance is lacking. We probed the role of ch...

Spiking neural networks, the most realistic artificial representation of biological nervous systems, are promising due to their inherent local training rules that enable low-overhead online learning, and energy-efficient information encoding. Their downside is more demanding functionality of the artificial synapses, notably including spike-timing-d...

We present a comprehensive phenomenological model for the crossbar integrated metal-oxide continuous-state memristors. The model consists of static and dynamic equations, which are obtained by fitting a large amount of experimental data, collected on several hundred devices. The static equation describes the device current, at non-disturbing voltag...

The development of large resistive random-access memory (ReRAM) circuits depends on the availability of predictive models of their memristive cells. If progress has been made in understanding the physics of such nanodevices in the last 10 years, developing compact models, required by EDA simulation tools, that are accurate but yet fast to simulate...

The progress in the field of neural computation hinges on the use of hardware more efficient than the conventional microprocessors. Recent works have shown that mixed-signal integrated memristive circuits, especially their passive ('0T1R') variety, may increase the neuromorphic network performance dramatically, leaving far behind their digital coun...

The understanding of spin injection and transport in organic spintronic devices is still incomplete, with some experiments showing magnetoresistance and others not detecting it. We have investigated the transport properties of a large number of tris-(8-hydroxyquinoline)aluminum-based organic spintronic devices with an electrical resistance greater...

Hardware-intrinsic security primitives employ instance-specific and process-induced variations in electronic hardware as a source of cryptographic data. Among various emerging technologies, memristors offer unique opportunities in such security applications due to their underlying stochastic operation. Here we show that the analogue tuning and nonl...

Potential advantages of analog- and mixed-signal nanoelectronic circuits, based on floating-gate devices with adjustable conductance, for neuromorphic computing had been realized long time ago. However, practical realizations of this approach suffered from using rudimentary floating-gate cells of relatively large area. Here, we report a prototype 2...

This corrects the article DOI: 10.1038/srep42429.

Limitations of currently dominating von Neumann architectures have pushed the research toward brain-inspired solutions like neural networks to reach new levels of computing efficiency. While these highly parallelized architectures have achieved outstanding performances at software level, their hardware implementation is still a challenging problem...

Silicon (Si) based complementary metal-oxide semiconductor (CMOS) technology has been the driving force of the information-technology revolution. However, scaling of CMOS technology as per Moore’s law has reached a serious bottleneck. Among the emerging technologies memristive devices can be promising for both memory as well as computing applicatio...

We report a monolithically integrated 3-D metal-oxide memristor crossbar circuit suitable for analog, and in particular, neuromorphic computing applications. The demonstrated crossbar is based on Pt/Al <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> O <sub xmlns:mml="http://www.w3.org/1998/Math...

The rapidly expanding hardware-intrinsic security primitives are aimed at addressing significant security challenges of a massively interconnected world in the age of information technology. The main idea of such primitives is to employ instance-specific process-induced variations in electronic hardware as a source of cryptographic data. Among the...

We have fabricated and successfully tested an analog vector-by-matrix multiplier, based on redesigned 10x12 arrays of 55 nm commercial NOR flash memory cells. The modified arrays enable high-precision individual analog tuning of each cell, with sub-1% accuracy, while keeping the highly optimized cells, with their long-term state retention, intact....

We experimentally demonstrate classification of 4x4 binary images into 4 classes, using a 3-layer mixed-signal neuromorphic network ("MLP perceptron"), based on two passive 20x20 memristive crossbar arrays, board-integrated with discrete CMOS components. The network features 10 hidden-layer and 4 output-layer analog CMOS neurons and 428 metal-oxide...

We have designed, fabricated, and successfully tested a prototype mixed-signal, 28x28-binary-input, 10-output, 3-layer neuromorphic network ("MLP perceptron"). It is based on embedded nonvolatile floating-gate cell arrays redesigned from a commercial 180-nm NOR flash memory. The arrays allow precise (~1%) individual tuning of all memory cells, havi...

The monolithic three-dimensional integration of memory and logic circuits could dramatically improve the performance and energy efficiency of computing systems. Some conventional and emerging memories are suitable for vertical integration, including highly scalable metal-oxide resistive switching devices (“memristors”). However, the integration of...

We introduce an innovative approach to the simultaneous control of growth mode and magnetotransport properties of manganite thin films, based on an easy-to-implement film/substrate interface engineering. The deposition of a manganite seed layer and the optimization of the substrate temperature allows a persistent bi-dimensional epitaxy and robust f...

It is a well-established fact that Artificial neural networks have superior performance in many information processing tasks. It is also know that by scaling up the size of the network it is possible to have better performance and richer functionality. However, large neural networks are challenging to implement in software and customized hardware a...

Artificial neural networks have been receiving increasing attention due to their superior performance in many information processing tasks. Typically, scaling up the size of the network results in better performance and richer functionality. However, large neural networks are challenging to implement in software and customized hardware are generall...

Monolithic three-dimensional integration of memory and logic circuits could dramatically improve performance and energy efficiency of computing systems. Some conventional and emerging memories are suitable for vertical integration, including highly scalable metal-oxide resistive switching devices (memristors), yet integration of logic circuits prov...

Synapses, the most numerous elements of neural networks, are memory devices. Similarly to traditional memory applications, device density is one of the most essential metrics for large-scale artificial neural networks. This application, however, imposes a number of additional requirements, such as the continuous change of the memory state, so that...

Metal-oxide memristors have emerged as promising candidates for hardware implementation of artificial synapses - the key components of high-performance, analog neuromorphic networks - due to their excellent scaling prospects. Since some advanced cognitive tasks require spiking neuromorphic networks, which explicitly model individual neural pulses (...

Despite all the progress of semiconductor integrated circuit technology, the extreme complexity of the human cerebral cortex makes the hardware implementation of neuromorphic networks with a comparable number of devices exceptionally challenging. One of the most prospective candidates to provide comparable complexity, while operating much faster an...

We investigated the growth mechanism of pentacene thin films on La0.7Sr0.3MnO3. A diffusion limited, thermally activated growth was found. Pentacene molecules formed flat islands that were a few microns in size and whose growth during deposition showed a strong anisotropy. We extracted a nucleation energy of 0.65 ± 0.05 eV and a diffusion barrier e...

We present a novel method of delivering a low-concentration (<15%) ozone beam to an ultra-high vacuum environment for the purpose of cleaning and dosing experimental samples through oxidation processing. The system described is safe, low-cost, and practical and overcomes the limitations of ozone transport in the molecular flow environment of high o...

Ultrathin manganite films are widely used as active electrodes in organic spintronic devices. In this study, a scanning tunnelling microscopy (STM) investigation with atomic resolution revealed previously unknown surface features consisting of small non-stoichiometric islands. Based upon this evidence, a new mechanism for the growth of these comple...

We propose a model for the consistent interpretation of the transport behavior of manganese perovskites in both the metallic and insulating regimes. The concept of polarons as charge carriers in the metallic ferromagnetic phase of manganites also solves the conflict between transport models, which usually neglects polaron effects in the metallic ph...

Nanoparticles (NPs) embedded in a conductive or insulating matrix play a key role in memristors and in flash memory devices. However, the role of proximity to the interface of isolated NPs has never been directly observed nor fully understood. Here we show that a reversible local switching in tunnel conductivity can be achieved by applying an appro...

Transport characterizations of epitaxial La0.7Sr0.3MnO3 thin films in the thickness range 5-40 nm and 25-410 K temperature interval have been accurately collected. We show that taking into account polaronic effects allows to achieve the best ever fitting of the transport curves in the whole temperature range. The Current Carriers Density Collapse p...

Introduction Magnetoresistive Phenomena in Organic Semiconductors Applications of Organic Spintronics Future Developments

This chapter describes the experimental achievement which adds conceptually new features to a standard memristor principle. It shows that electrically controlled magnetoresistance can be achieved in organic devices by combining magnetic bistability, GMR effect, and memristive effects. The chapter discusses the La0.7Ca0.3MnO3/ PrBa2Cu3O7/ La0.7Ca0.3...

Memristors are one of the most promising candidates for future information and communications technology (ICT) architectures. Two experimental proofs of concept are presented based on the intermixing of spintronic and memristive effects into a single device, a magnetically enhanced memristor (MEM). By exploiting the interaction between the memrista...

We report on the optimisation of the growth conditions of manganite La0.7Sr0.3MnO3 (LSMO) thin films prepared by Channel Spark Ablation (CSA). CSA belongs to pulsed electron deposition methods and its energetic and deposition parameters are quite similar to those of pulsed laser deposition. The method has been already proven to provide manganite fi...

We investigate spin precession (Hanle effect) in the prototypical organic spintronic giant magnetoresistance (GMR) device La0.7Sr0.3MnO3(LSMO)/tris(8-hydroxyquinoline)(Alq3)/AlOx/Co. The Hanle effect is not observed in measurements taken by sweeping a magnetic field at different angles from the plane of the device. As possible explanations we discu...

A nanomemristor based on SiO(2) is fabricated in situ with spatial control at the nanoscale. The proposed system exhibits peculiar properties such as the possibility to be regenerated after being stressed or damaged and the possibility to expose the metal and the oxide interfaces by removing the top electrodes.

In this work a multifunctional organic spintronic device is demonstrated using Tris(8-hydroxyquinolinato) aluminium (Alq3) based vertical spin valves with manganite and cobalt electrodes. The device showed a non-volatile electrical switching with dramatic effects on the spin transport behavior. The multifunctionality is illustrated together with a...

Organic semiconductors are emerging materials in the field of spintronics. Successful achievements include their use as a tunnel barrier in magnetoresistive tunnelling devices and as a medium for spin-polarized current in transport devices. In this paper, we give an overview of the basic concepts of spin transport in organic semiconductors and pres...

A multifunctional organic spintronic device is demonstrated using tris(8-hydroxyquinolinato) aluminium (Alq(3))-based vertical spin valves with manganite and cobalt electrodes. The device shows a nonvolatile electrical switching with dramatic effects on the spin transport behavior. The interplay of electrical and magnetic bistabilities enables the...

Artifacts can originate from the inherent shortcomings of the cross bar configuration, when the resistance of the device is small compared to that of one of the electrodes. This is particularly relevant to the field of organic spintronics, in which at least one recent work overlooked this effect. We use a simplified one-dimensional resistor model a...

In this work we present the results of an electrical and structural characterization of molecular beam epitaxy (MBE) grown InAs/In0.15Ga0.85As quantum dot (QD) structures having InAs coverages of 2.0 and 3.0 ML that are, respectively, below and above the expected critical value for QD ripening in the InAs/GaAs system. The samples have been investig...

We present a study on the effects of quantum dot coverage on the properties of InAs dots embedded in GaAs and in metamorphic In0.15Ga0.85As confining layers grown by molecular beam epitaxy on GaAs substrates. We show that redshifted emission wavelengths exceeding 1.3μm at room temperature were obtained by the combined use of InGaAs confining layers...

InAs/GaAs quantum dot (QD) structures were grown by molecular beam epitaxy (MBE) with InAs coverages θ continuously graded from 1.5 ML to 2.9 ML. A critical coverage of 2.23 ML is found, above which the islands undergo ripening, which causes a fraction of quantum dots to increase in size and to eventually relax through the formation of pure, edge-t...

We report a detailed study of InAs/GaAs quantum dot (QD) structures grown by molecular beam epitaxy with InAs coverages theta continuously graded from 1.5 to 2.9 ML. The effect of coverage on the properties of QD structures was investigated by combining atomic force microscopy, transmission electron microscopy, x-ray diffraction, photoluminescence,...

The apparent C-V profiles and the deep levels in GaAs/InAs/GaAs quantum dot nanostructure, have been investigated by space charge spectroscopy techniques (C-V and DLTS). Accumulation peaks and/or depletion of free carriers at the QDs plane are observed under the considered growth parameters. It is shown that, both in the cap and at the QD-layer/cap...

An ultra‐high vacuum electron beam co‐evaporation technique was used to obtain SmCo5 thin films, Co/SmCo5/Co trilayers and a SmCo5/57Fe bilayers. Grazing incidence X‐ray diffraction analysis showed that the deposition technique is able to give components with the correct stoichiometry and free from spurious phases. Magneto‐Optical Kerr effect meas...

Co/Fe multilayers were electron-beam evaporated in ultrahigh vacuum onto quartz substrates keeping the Co layer thickness (10 nm) constant and changing that of Fe (10-30 nm). For Fe layer thicknesses up to 24 nm, the magnetization substantially lies in the film plane and shows a uniaxial magnetic anisotropy. The coercive field measured along the ea...

In this work, InAs(QD)/GaAs(001) structures are analyzed in order to identify the conditions for plastic strain relaxation via dislocations. To this aim samples with a continuously varying coverage, going from 1.5 to 2.9 ML, have been studied mainly by means of electrical characterization and with the fundamental support of structural TEM analysis,...