Memristor Platforms for Pattern Recognition Memristor Theory, Systems and Applications

In the last decade a large scientific community has focused on the study of the memristor. The memristor is thought to be by many the best alternative to CMOS technology, which is gradually showing its flaws. Transistor technology has developed fast both under a research and an industrial point of view, reducing the size of its elements to the nano-scale. It has been possible to generate more and more complex machinery and to communicate with that same machinery thanks to the development of programming languages based on combinations of boolean operands. Alas as shown by Moore’s law, the steep curve of implementation and of development of CMOS is gradually reaching a plateau. It is clear the need of studying new elements that can combine the efficiency of transistors and at the same time increase the complexity of the operations. Memristors can be described as non-linear resistors capable of maintaining memory of the resistance state that they reached. From their first theoretical treatment by Professor Leon O. Chua in 1971, different research groups have devoted their expertise in studying the both the fabrication and the implementation of this new promising technology. In the following thesis a complete study on memristors and memristive elements is presented. The road map that characterizes this study departs from a deep understanding of the physics that govern memristors, focusing on the HP model by Dr. Stanley Williams. Other devices such as phase change memories (PCMs) and memristive biosensors made with Si nano-wires have been studied, developing emulators and equivalent circuitry, in order to describe their complex dynamics. This part sets the first milestone of a pathway that passes trough more complex implementations such as neuromorphic systems and neural networks based on memristors proving their computing efficiency. Finally it will be presented a memristror-based technology, covered by patent, demonstrating its efficacy for clinical applications. The presented system has been designed for detecting and assessing automatically chronic wounds, a syndrome that affects roughly 2% of the world population, through a Cellular Automaton which analyzes and processes digital images of ulcers. Thanks to its precision in measuring the lesions the proposed solution promises not only to increase healing rates, but also to prevent the worsening of the wounds that usually lead to amputation and death

Resistive Switching and Charge Transport in Laser-Fabricated Graphene Oxide Memristors: A Time Series and Quantum Point Contact Modeling Approach

This work investigates the sources of resistive switching (RS) in recently reported laser-fabricated graphene oxide memristors by means of two numerical analysis tools linked to the Time Series Statistical Analysis and the use of the Quantum Point Contact Conduction model. The application of both numerical procedures points to the existence of a filament connecting the electrodes that may be interrupted at a precise point within the conductive path, resulting in resistive switching phenomena. These results support the existing model attributing the memristance of laser-fabricated graphene oxide memristors to the modification of a conductive path stoichiometry inside the graphene oxide.The authors thank the support of the Spanish Ministry of Science, Innovation and Universities under projects TEC2017-89955-P, TEC2017-84321-C4-3-R, MTM2017-88708-P and project PGC2018-098860-B-I00 (MCIU/AEI/FEDER, UE), and the predoctoral grant FPU16/01451

Memristors

This Edited Volume Memristors - Circuits and Applications of Memristor Devices is a collection of reviewed and relevant research chapters, offering a comprehensive overview of recent developments in the field of Engineering. The book comprises single chapters authored by various researchers and edited by an expert active in the physical sciences, engineering, and technology research areas. All chapters are complete in itself but united under a common research study topic. This publication aims at providing a thorough overview of the latest research efforts by international authors on physical sciences, engineering, and technology,and open new possible research paths for further novel developments

Low-power emerging memristive designs towards secure hardware systems for applications in internet of things

Emerging memristive devices offer enormous advantages for applications such as non-volatile memories and in-memory computing (IMC), but there is a rising interest in using memristive technologies for security applications in the era of internet of things (IoT). In this review article, for achieving secure hardware systems in IoT, low-power design techniques based on emerging memristive technology for hardware security primitives/systems are presented. By reviewing the state-of-the-art in three highlighted memristive application areas, i.e. memristive non-volatile memory, memristive reconfigurable logic computing and memristive artificial intelligent computing, their application-level impacts on the novel implementations of secret key generation, crypto functions and machine learning attacks are explored, respectively. For the low-power security applications in IoT, it is essential to understand how to best realize cryptographic circuitry using memristive circuitries, and to assess the implications of memristive crypto implementations on security and to develop novel computing paradigms that will enhance their security. This review article aims to help researchers to explore security solutions, to analyze new possible threats and to develop corresponding protections for the secure hardware systems based on low-cost memristive circuit designs

Memcapacitors

Mestrado em Engenharia Eletrónica e TelecomunicaçõesThe present work aims to continue the study of memory devices, initiated with the prediction of the existence of memristors by Leon Chua in 1971, with the study and characterization of memcapacitors as a semiconductor two-terminal device, characterized by the non-linear relation between charge and voltage, which also present the ability to remember the voltage or charge that passes through the device, graphically represented by a graphic with hysteresis characteristics, also presenting a variable capacitance in function of the charge applied in its terminals. Here, a characterizationof the response functions to a sinusoidal periodic input with variable frequency to three mathematical models of memcapacitive systems is performed: given a memcapacitor in series with an ac input voltage source, the respective hysteresis charge-voltage plots are studied by simulations in the MATLAB environment. Next, a classification of the hysteresis plots in function of its geometry is performed, given that the crossing of such graph in the (0.0) point defines it as a type I or type II hysteresis loop. The analysis continues with the morphological identification of the area of the hysteresis curve of the first model, by varying amplitude and frequency of the input source, in such a way to compare the other models with the ideal one, as well as to take the critical frequencis from which the memcapacitance becomes constant, and thus the system becomes linear, by making the hysteresis curve to become a straight line. The area of the first model was taken by calculations with the Green theorem.O presente trabalho propõe-se a continuar o estudo dos dispositivos de memória, iniciado com a predição dos memristors por Leon Chua em 1971, por meio do estudo e caracterização dos memcapacitores como dispositivos semicondutores de dois terminais, caracterizados pela relação não linear entre carga e tensão, que apresentam capacidade de recordar a tensão ou corrente que passa pelo dispositivo, graficamente representado em forma de um gráfico com características de histerese, aprensentando também capacitância variável em função da carga aplicada em seus terminais. Aqui, uma caracterização das funções de resposta a uma entrada periódica sinusoidal com frequência variável, para três modelos matemáticos de sistemas memcapacitivos, é realizada: dado um memcapacitor em série com uma tensão de entrada ac, estuda-se as respectivas funções de histerese carga-tensão por meio de simulação em MATLAB. Em seguida, é realizada uma classificação das curvas de histerese em função da sua geometria, em que a passagem do gráfico no ponto (0,0), de origem dos planos, o define como tipo I ou tipo II. A análise prossegue com a identificação morfológica da área das curvas de histerese obtidas dos primeiro modelo teóricos em causa, variando-se, para isso, amplitude e frequência de entradas, de modo a se comparar os outros dois modelos restantes com este modelo ideal, ao mesmo tempo em que se deseja obter as frequências críticas de cada modelo, ou seja, as frequências e amplitudes a partir das quais a memcapacitância torna-se constante, e o sistema em causa, linear, fazendo então a curva de histerese degenerar para uma reta. A área do primeiro modelo foi calculada através de um algoritmo que calcula a área da curva por meio do Teorema de Green

Fabrication and Pseudo-Analog Characteristics of Ta2O5 -Based ReRAM Cell

Memristori on yksi elektroniikan peruskomponenteista vastuksen, kondensaattorin ja kelan lisäksi. Se on passiivinen komponentti, jonka teorian kehitti Leon Chua vuonna 1971. Kesti kuitenkin yli kolmekymmentä vuotta ennen kuin teoria pystyttiin yhdistämään kokeellisiin tuloksiin. Vuonna 2008 Hewlett Packard julkaisi artikkelin, jossa he väittivät valmistaneensa ensimmäisen toimivan memristorin. Memristori eli muistivastus on resistiivinen komponentti, jonka vastusarvoa pystytään muuttamaan. Nimens mukaisesti memristori kykenee myös säilyttämään vastusarvonsa ilman jatkuvaa virtaa ja jännitettä. Tyypillisesti memristorilla on vähintään kaksi vastusarvoa, joista kumpikin pystytään valitsemaan syöttämällä komponentille jännitettä tai virtaa. Tämän vuoksi memristoreita kutsutaankin usein resistiivisiksi kytkimiksi. Resistiivisiä kytkimiä tutkitaan nykyään paljon erityisesti niiden mahdollistaman muistiteknologian takia. Resistiivisistä kytkimistä rakennettua muistia kutsutaan ReRAM-muistiksi (lyhenne sanoista resistive random access memory). ReRAM-muisti on Flash-muistin tapaan haihtumaton muisti, jota voidaan sähköisesti ohjelmoida tai tyhjentää. Flash-muistia käytetään tällä hetkellä esimerkiksi muistitikuissa. ReRAM-muisti mahdollistaa kuitenkin nopeamman ja vähävirtaiseman toiminnan Flashiin verrattuna, joten se on tulevaisuudessa varteenotettava kilpailija markkinoilla. ReRAM-muisti mahdollistaa myös useammin bitin tallentamisen yhteen muistisoluun binäärisen (”0” tai ”1”) toiminnan sijaan. Tyypillisesti ReRAM-muistisolulla on kaksi rajoittavaa vastusarvoa, mutta näiden kahden tilan välille pystytään mahdollisesti ohjelmoimaan useampia tiloja. Muistisoluja voidaan kutsua analogisiksi, jos tilojen määrää ei ole rajoitettu. Analogisilla muistisoluilla olisi mahdollista rakentaa tehokkaasti esimerkiksi neuroverkkoja. Neuroverkoilla pyritään mallintamaan aivojen toimintaa ja suorittamaan tehtäviä, jotka ovat tyypillisesti vaikeita perinteisille tietokoneohjelmille. Neuroverkkoja käytetään esimerkiksi puheentunnistuksessa tai tekoälytoteutuksissa. Tässä diplomityössä tarkastellaan Ta2O5 -perustuvan ReRAM-muistisolun analogista toimintaa pitäen mielessä soveltuvuus neuroverkkoihin. ReRAM-muistisolun valmistus ja mittaustulokset käydään läpi. Muistisolun toiminta on harvoin täysin analogista, koska kahden rajoittavan vastusarvon välillä on usein rajattu määrä tiloja. Tämän vuoksi toimintaa kutsutaan pseudoanalogiseksi. Mittaustulokset osoittavat, että yksittäinen ReRAM-muistisolu kykenee binääriseen toimintaan hyvin. Joiltain osin yksittäinen solu kykenee tallentamaan useampia tiloja, mutta vastusarvoissa on peräkkäisten ohjelmointisyklien välillä suurta vaihtelevuutta, joka hankaloittaa tulkintaa. Valmistettu ReRAM-muistisolu ei sellaisenaan kykene toimimaan pseudoanalogisena muistina, vaan se vaati rinnalleen virtaa rajoittavan komponentin. Myös valmistusprosessin kehittäminen vähentäisi yksittäisen solun toiminnassa esiintyvää varianssia, jolloin sen toiminta muistuttaisi enemmän pseudoanalogista muistia.The memristor is one of the fundamental circuit elements in addition to a resistor, capacitor and an inductor. It is a passive component whose theory was postulated by Leon Chua in 1971. It took over 30 years before any known physical examples were discovered. In 2008 Hewlett Packard published an article where they manufactured a device which they claimed to be the first memristor found. The memristor, which is a concatenation of memory resistor, is a resistive component that has an ability to change its resistance. It can also remember its resistance value without continuous current or voltage. Typically, a memristor has at least two resistance states that can be altered. This is the reason why memristors are also called resistive switches. Resistive switches can be used in memory technologies. A memory array that has been built using resistive switches is called ReRAM (resistive random access memory). ReRAM, like Flash memory, is a non-volatile memory that can be programmed or erased electrically. Flash memories are currently used e.g. in memory sticks. However, compared to Flash, ReRAM has faster operating speed and lower power consumption, for instance. It could potentially replace current memory standards in future. A ReRAM memory cell can also store multiple bits instead of binary operation (”0” or ”1”). Typically there exists multiple intermediate resistance states between ReRAM’s limiting resistances that could be utilized. Such memory could be called analog, if the amount of intermediate states is not limited to discrete levels. Analog memories make it possible to build artificial neural networks (ANN) efficiently, for instance. ANNs try to model the behaviour of brain and to perform tasks that are difficult for traditional computer programs such as speech recognition or artificial intelligence. This thesis studies the analog behaviour of Ta 2 O 5 -based ReRAM cell. Manufacturing process and measurement results are presented. The operation of ReRAM cell is rarely fully analog as there exists limited amount of intermediate resistance states. This is the reason why operation is called pseudo-analog. Measurement results show that a single ReRAM cell is suitable for binary operation. In some cases, a single cell can store multiple resistance values but there exists significant variance in resistance states between subsequent programming cycles. The proposed ReRAM cell cannot operate as pseudo-analog ReRAM cell in itself as it needs an external current limiting component. Improving the manufacturing process should reduce the variability such that the operation would be more like a pseudo-analog memory.Siirretty Doriast

Stochastic Memory Devices for Security and Computing

With the widespread use of mobile computing and internet of things, secured communication and chip authentication have become extremely important. Hardware-based security concepts generally provide the best performance in terms of a good standard of security, low power consumption, and large-area density. In these concepts, the stochastic properties of nanoscale devices, such as the physical and geometrical variations of the process, are harnessed for true random number generators (TRNGs) and physical unclonable functions (PUFs). Emerging memory devices, such as resistive-switching memory (RRAM), phase-change memory (PCM), and spin-transfer torque magnetic memory (STT-MRAM), rely on a unique combination of physical mechanisms for transport and switching, thus appear to be an ideal source of entropy for TRNGs and PUFs. An overview of stochastic phenomena in memory devices and their use for developing security and computing primitives is provided. First, a broad classification of methods to generate true random numbers via the stochastic properties of nanoscale devices is presented. Then, practical implementations of stochastic TRNGs, such as hardware security and stochastic computing, are shown. Finally, future challenges to stochastic memory development are discussed

Developing a Skin Phantom for the Testing of Biowearables

There is a demonstrated need in the biowearables industry for a benchtop model that can accurately emulate the perspiration mechanism and corresponding impedance vs. frequency spectra of skin. This model, or skin phantom, could increase the efficiency and accuracy of early-stage testing of biowearables, as well as minimize animal, human, and cadaver testing. The objective of this project is to develop a skin phantom that can emulate the perspiration mechanism and impedance spectrum behavior of human skin for the testing of biowearables in the 2,000 - 20,000 Hz range. We also endeavored to create computer-simulated models to aid in the optimization of our phantom. We designed a three-layered, PDMS-based physical model based off of the skin’s sweat duct and pore structure that closely matched skin’s impedance vs. frequency behavior. Our computer simulations validated our understanding of the material properties that made our phantom a good match for human skin. While we were unable to complete all desired experiments due to campus closure, we were successful in designing and building a skin phantom that accurately mimicked the desired skin properties, while also being reusable, non-toxic, and easily manufacturable. Further experiments should be done to validate and improve our computer simulations and mathematical models. Further manipulation of our skin phantom’s factors should be done to match the skin’s impedance vs. frequency behavior more closely