From biomaterial-based data storage to bio-inspired artificial synapse

The implementation of biocompatible and biodegradable information storage would be a significant step toward next-generation green electronics. On the other hand, benefiting from high density, multifunction, low power consumption and multilevel data storage, artificial synapses exhibit attractive future for built-in nonvolatile memories and reconstructed logic operations. Here, we provide a comprehensive and critical review on the developments of bio-memories with a view to inspire more intriguing ideas on this area that may finally open up a new chapter in next-generation consumer electronics. We will discuss that biomolecule-based memory employed evolutionary natural biomaterials as data storage node and artificial synapse emulated biological synapse function, which is expected to conquer the bottleneck of the traditional von Neumann architecture. Finally, challenges and opportunities in the aforementioned bio-memory area are presented

Non-volatile organic memory devices: from design to applications

The research activity described in the attached dissertation focused on the development, fabrication and characterization of new non-volatile memory elements based on organic technology. During the last few decades, organic materials based devices have attracted considerable interest due to their great potential for future electronic systems. Low fabrication costs, high mechanical flexibility and versatility of the chemical structure, good scalability and easy processing are the unique advantages of organic electronics. As memory devices are essential elements of any kind of electronic system, the development of organic memory devices is fundamental in order to extend the application of organic materials to different electronic circuits. Research on organic electronic memories is currently at a rapid growth stage, since it is recognized that they may be an alternative or supplementary to the conventional memory technologies. Despite considerable progress in the advancement of novel memory technologies in recent years, some challenging tasks still need to be resolved. The Ph.D. research activity of this thesis is related to the still -opened challenges in the organic memories technologies. In particular, it focused mainly on the study, development, fabrication and characterization of new non-volatile organic memory elements based on resistive switching. The activity has been carried out in the frame of the European project “HYbrid organic/inorganic Memory Elements for integration of electronic and photonic Circuitry” (HYMEC), which involved the University of Cagliari during the last three years. The project goal was to realize new hybrid inorganic/organic resistive memory devices with functionality far beyond the state of the art. A complementary activity on transistor-based organic memory devices has been also carried out and described in this thesis. As regards resistive memory devices, the research activity included design, fabrication and testing of a novel non-volatile memory device based on the combination of an air-stable organic semiconductor and metal nanoparticles. This topic required the development of technology and procedures for easy and reliable production of devices as well as the definition of measurement protocols. The proposed structure was thoroughly characterized by morphological techniques, which allowed to interpret the resistive switching mechanisms in terms of formation and rupture of metallic filaments inside the organic layer assisted by the metal NPs. The obtained performances are the best reported so far in literature, and, to our knowledge, the statistics analysis is the largest ever reported for organic-based resistive memories. The developed technology was then successfully applied on flexible plastic substrates. The definition of technological processes for the reliable fabrication of high performance printed organic memory devices was also carried out: this work clearly demonstrates the real possibility of fabricating high performance printed memory elements. A significant effort was also devoted to the development of basic memory/sensor systems entirely fabricated on plastic substrates. The suitability of organic non-volatile memory devices for the detection and the storage of external parameters was demonstrated. The results definitely demonstrated the feasibility of the proposed technology for the fabrication of systems including organic memories for their final application in different industrial processes, including e-textile and smart packaging. As regards transistor memory devices, highly flexible Organic Field-Effect Transistor (OFET)-based memory elements with excellent mechanical stability and high retention time were developed. As main innovation with respect to the state of the art, low voltage operation of the OFET-based memory was investigated. Such an activity was also related to the development of reliable measurement procedure

전자 장치 내 국부적 전계 향상을 위한 나노 구조체

학위논문(박사) -- 서울대학교대학원 : 공과대학 화학생물공학부, 2021.8. 조재영.The goal of this dissertation is to investigate effect of nanostructures for local electric field enhancement in electronic devices and to provide experimental and theoretical bases for their practical use. Resistive random access memory (RRAM) is a data storage device that can be modulated its resistance states by external electrical stimuli. The electric field generated by the applied potential difference between the two electrodes acts as the driving force to switch the resistance states, so controlling the electric field within the device can lead to improved operational performance and reliability of the device. Even though considerable progress has been made through significant efforts to control the electric field within the device, selectively enhancing the electric field in the intended position for stable and uniform resistive switching behavior is still challenging. Engineered metal structures in the RRAM can efficiently manipulate the electric field. As the radius of the metal structures decreases, the charge density increases, generating electric field enhancements in confined region. To minimize the radius of the metal structure and thus to greatly increase the electric field in a local area, we introduced a nanoscale metal structure into the RRAM. First, pyramid-structured metal electrode with a sharp tip was used to achieve a tip-enhanced electric field, and the effect of the enhanced electric field on the resistive switching behaviors of the device was investigated. Based on numerical simulation and experimental results, we confirmed that pyramidal electrode with a tip radius of tens of nanometers can selectively enhance the electric field at the tip. The tip-enhanced electric field can facilitate the thermochemical reaction in transition metal oxide-based RRAMs and efficiency of charge injection and transport in organic-based RRAMs, as well as provide position selectivity during formation of conductive filament. The resulting RRAM exhibited reliable resistive switching behavior and highly improved device performance compared with conventional RRAM with planar electrode. As another approach to enhance the electric field within the resistive switching layer, we prepared spherical nanostructures via self-assembled block copolymer (BCP)/metal compound micelles. BCP and metal precursors were dissolved in aqueous media for use as BCP/metal compound micelles. These micelles were used as complementary resistive switch (CRS) layers of the memory device and the mechanism of CRS behavior was investigated. The spherical metal nanostructures can improve the electric fields, promoting a resistive switching mechanism based on electrochemical metallization. The resulting CRS memory exhibited reliable resistive switching behavior with four distinct threshold voltages in both cycle-to-cycle and cell-to-cell tests. Also, the conduction and resistive switching mechanism are experimentally demonstrated through the the analysis of the current–voltage data plot and detemination of the temperature coefficient of resistance. Overall, we pursued efficient engineering of metal nanostructures capable of manipulating electric fields for improving the operational performance and reliability of memory devices. There is no doubt that the commercialized RRAM will become popular in the near future after overcoming all the challenges of RRAM through continuous interest and research. We believe that these results will not only contribute to the significant advancement of all electronic devices, including RRAM, but will also help promote research activities in the electronic device field.본 논문의 목적은 나노 구조체를 통한 전자 장치 내 국부적 전계 향상 효과를 조사하고, 이의 실제 사용을 위한 실험 및 이론적 기반을 제공하는 것이다. 저항변화메모리 (resistive random access memory) 는 외부 전기 자극에 의해 저항 상태를 변화 시킬 수 있는 데이터 저장 장치이다. 두 전극 사이에 인가된 전위차에 의해 생성된 전기장은 저항 상태를 전환시키는 구동력으로써 작용하므로, 전자 장치 내에서 전기장을 제어하면 장치의 성능과 신뢰성을 향상시킬 수 있다. 장치 내에서 전기장을 제어하려는 많은 노력을 통해 상당한 진전이 있었지만, 안정적이고 균일한 저항 변화 거동을 위해 의도된 위치에서 전기장을 선택적으로 향상시키는 일은 아직 도전적 과제이다. 구조화된 금속을 저항변화메모리에 접목시킴으로써 전기장을 효율적으로 조작할 수 있다. 금속 구조체의 반경이 감소함에 따라 전하 밀도가 증가하여 국부적 영역에서 전기장이 향상된다. 이 논문에서는 금속 구조체의 반경을 최소화하여 국부적으로 전기장을 크게 향상시키기 위해 저항변화메모리에 나노스케일의 금속 구조체를 도입하였다. 첫 번째로, 팁 강화 (tip-enhanced) 전기장 효과를 달성하기 위해 날카로운 팁을 가지는 피라미드 금속 구조체를 전극으로 사용하였으며, 강화된 전기장이 소자의 저항 변화 거동에 미치는 영향을 조사하였다. 유한요소모델링과 실험결과를 바탕으로, 수십 나노 미터의 팁 반경을 가지는 피라미드 구조체 전극이 팁 부근에서 전기장을 국소적으로 향상시킬 수 있음을 확인하였다. 팁 강화 전기장은 전이 금속 산화물-기반 저항변화메모리에서 열화학 (thermochemical) 반응을 촉진시키고 유기-기반 저항변화메모리에서 전하 주입 (charge injection) 및 수송 (transport) 효율성을 향상시킬 뿐 아니라, 선택적인 위치에서만 전도성 필라멘트 (conductive filament)를 형성시킬 수 있었다. 그 결과 피라미드 구조체 저항변화메모리는 종래의 평판 구조체 저항변화메모리에 비해 안정적인 저항 변화 거동과 향상된 장치 성능을 보여주었다. 저항 변화 층 내의 전기장을 향상시키기 위한 또 다른 접근법으로, 자기조립 (self-assembled)된 블록공중합체 (block copolymer)/금속 복합체 미셀 (micelle)을 이용하여 구형의 나노구조체를 소자의 중간층으로 도입하였다. 블록공중합체 및 금속전구체를 복합체 미셀로 사용하기 위해 선택적 용매에 용해시켰다. 해당 미셀을 메모리 소자의 상보적 저항 변화 (complementary resistive switch) 층으로 사용하였으며, 상보적 저항 변화 거동의 메커니즘을 조사하였다. 구형의 금속 나노구조체는 전기장을 향상시켜 전기화학적 금속화 (electrochemical metallization)에 기반한 저항 변화 메커니즘을 촉진시킬 수 있었다. 그 결과 상보적 저항 변화 메모리는 사이클 및 셀간 반복 시험 모두에서 4개의 임계 전압으로 안정적인 저항 변화 동작을 나타내었다. 또한 전류-전압 자료 플롯 (plot) 분석과 저항의 온도 계수 결정을 통해 장치의 전도 및 저항 변화 메커니즘을 실험적으로 입증하였다. 전반적으로 본 논문에서는 장치 내 전기장을 증폭시킬 수 있는 금속 나노구조체의 효율적인 엔지니어링을 통해 메모리 장치의 성능과 신뢰성 향상을 추구하였다. 지속적인 관심과 연구를 통해 저항변화메모리의 모든 과제를 극복한 후, 상용화된 저항변화메모리가 가까운 미래에 대중화될 것임을 믿어 의심치 않는다. 우리는 이 결과가 저항변화메모리를 포함한 모든 전자 장치의 획기적인 발전에 기여할 뿐만 아니라 전자 장치 분야의 연구 활동을 촉진하는 데에도 도움이 될 것이라고 믿는다.Chapter 1. Introduction 1 1.1. Background 1 1.1.1. Necessity of new memory devices 1 1.1.2. Resistive random access memory 2 1.2. Motivation 4 1.3. Dissertation Overview 6 1.4. References 9 Chapter 2. Tip-Enhanced Electric Field-Driven Efficient Charge Injection and Transport in Organic Material-Based Resistive Memories 19 2.1. Introduction 21 2.2. Experimental 24 2.3. Results and Discussion 27 2.4. Conclusions 37 2.5. References 38 Chapter 3. Facilitation of the Thermochemical Mechanism in NiO-Based Resistive Switching Memories via Tip-Enhanced Electric Fields 52 3.1. Introduction 54 3.2. Experimental 57 3.3. Results and Discussion 60 3.4. Conclusions 66 3.5. References 67 Chapter 4. Facile Achievement of Complementary Resistive Switching Behaviors via Self-Assembled Block Copolymer Micelles 82 4.1. Introduction 83 4.2. Experimental 86 4.3. Results and Discussion 89 4.4. Conclusions 96 4.5. References 97 Chapter 5. Conclusion 109 Abstract in Korean 112박

Cerium oxide based resistive random access memory devices

Resistive Random Access Memory (RRAM) is an emerging technology of non-volatile memory (NVM). Although the observation of metal oxide that can undergo an abrupt insulator-metal transition into a conductive state has been known for over 40 years, researchers started investigating those materials for memory applications in late 1990s. It has been considered as the next generation memory technology to replace current flash memory because RRAM has demonstrated feasible switching characteristics and potential to build high density arrays and also RRAM is also compatible with contemporary CMOS processes, which means RRAM can be integrated into current CMOS chips. While the structure of RRAM is a simple metal-insulator-metal (MIM) device, there are numerous materials that exhibit resistive switching. The switching behavior is not only dependent on the switching layer materials but also dependent on the choice of metal electrodes and their interfacial properties. Many metal oxides such as hafnium oxide, titanium oxide, aluminum oxide, nickel oxide (NiO), tantalum oxide and etc. have been studied in details; however, some materials are unexplored such as cerium oxide. In addition to nonvolatile storage applications, RRAM is considered as one of essential elements for advancing neuromorphic computing because of its analog switching and retention characteristics. This thesis investigated CeO[subscript x]-based RRAMs, from its fundamental device characteristics to neuromorphic applications.Electrical and Computer Engineerin

Spiking Neural Networks for Inference and Learning: A Memristor-based Design Perspective

On metrics of density and power efficiency, neuromorphic technologies have the potential to surpass mainstream computing technologies in tasks where real-time functionality, adaptability, and autonomy are essential. While algorithmic advances in neuromorphic computing are proceeding successfully, the potential of memristors to improve neuromorphic computing have not yet born fruit, primarily because they are often used as a drop-in replacement to conventional memory. However, interdisciplinary approaches anchored in machine learning theory suggest that multifactor plasticity rules matching neural and synaptic dynamics to the device capabilities can take better advantage of memristor dynamics and its stochasticity. Furthermore, such plasticity rules generally show much higher performance than that of classical Spike Time Dependent Plasticity (STDP) rules. This chapter reviews the recent development in learning with spiking neural network models and their possible implementation with memristor-based hardware

MEMSORN: Self-organization of an inhomogeneous memristive hardware for sequence learning

Learning is a fundamental component for creating intelligent machines. Biological intelligence orchestrates synaptic and neuronal learning at multiple time-scales to self-organize populations of neurons for solving complex tasks. Inspired by this, we design and experimentally demonstrate an adaptive hardware architecture Memristive Self-organizing Spiking Recurrent Neural Network (MEMSORN). MEMSORN incorporates resistive memory (RRAM) in its synapses and neurons which configure their state based on Hebbian and Homeostatic plasticity respectively. For the first time, we derive these plasticity rules directly from the statistical measurements of our fabricated RRAM-based neurons and synapses. These “technologically plausible” learning rules exploit the intrinsic variability of the devices and improve the accuracy of the network on a sequence learning task by 30%. Finally, we compare the performance of MEMSORN to a fully-randomly set-up recurrent network on the same task, showing that self-organization improves the accuracy by more than 15%. This work demonstrates the importance of the device-circuit-algorithm co-design approach for implementing brain-inspired computing hardware

Fabrication and characterization of memory devices based on nanoparticles

Tese de doutoramento, Engenharia Electrónica e Telecomunicações, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2013The objective of this study is to understand the electrical properties of non-volatile memories based on metal oxide nanoparticles embedded into an insulating polymer matrix. These memories are classified as resistive random access memories (RRAM), as they undergo resistive switching between well-defined conductance states when submitted to a voltage pulse. A number of memory devices were fabricated and studied using electrical techniques. Current-voltage characteristics were studied as a function of the ambient atmosphere and temperature. The dynamic electrical behaviour was probed using triangular voltage profiles with different scan rates, transient techniques and electrical noise techniques. Electrical measurements were complemented with morphological characterization. Important outcomes of this thesis are the following: It was shown that adsorbed moisture on the surface of the devices causes resistive switching. This type of resistive switching can lead to very high on/off ratios, and therefore it is not reliable. Silver oxide nanoparticles undergo an electroforming process similar to a soft-breakdown mechanism as reported for binary oxides. A model that explains the basic features of the electroforming mechanism was proposed. After the electroforming, the devices show resistance switching properties with a high on/off ratio (> 104), good retention time, and programming endurance. A resistive switching mechanism was proposed. The model assumes that during electroforming a percolation network of micro conducting paths (filaments) is established between the electrodes. The creation and rupture of these micro-paths is responsible for the changes in conductance. Results from this study indicate that nanostructured thin films made of silver oxide nanoparticles embedded in an insulating polymer show an electrical behaviour like the bulk oxide based memory structures. The planar structures present the advantage of being programmed in multi-resistance levels suggesting a very interesting finding that may pave the way to achieve a multi-bit memory deviceO objetivo desta tese foi estudar as propriedades elétricas de componentes electrónicos fabricados com nanopartículas de metálicas. Este tipo de memoria é designado por memorias resistivas porque mudam a sua resistência elétrica através da aplicação de um tensão elétrica. Este componente é conhecido por “memristor”. Um conjunto de memorias resistivas foi fabricado e caracterizado. Nomeadamente foram realizadas um conjunto de medidas elétricas em diferentes ambientes (vácuo e atmosfera ambiente) e em função da temperatura para obter informação sobre os mecanismos de transporte electrónico e sobre a comutação elétrica da resistência. As memorias fabricadas tem um elevado hiato entre os estados resistivos (> 104), são não-voláteis e robustas, tendo sido testadas com mais de mil ciclos de programação entre os estados resistivos. Esta tese propõe um modelo para explicar as variações de resistência elétrica. O modelo assume que as partículas de prata oxidam e formam um óxido de prata. Durante o processo de formação da memoria, o elevado campo elétrico aplicado leva a ruptura dielétrica controlada do óxido e forma defeitos eletricamente ativos. Esta rede de defeitos gera micro-caminhos para a condução elétrica ou filamentos. As mudanças de resistência elétrica são causadas pela criação/ruptura deste filamentos. Os resultados desta tese indicam que as mudanças de resistência elétrica em filmes nanoestruturados com nanopartículas metálicas são semelhantes as observadas em estruturas resistivas com base em filmes finos óxidos como o dióxido de titânio (TiO2) e o óxido de alumínio (Al2O3) entre outros. Os “memristors” fabricadas neste tese são estruturas planares. O objectivo inicial foi ter um instrumento de caracterização mais simples que a estrutura convencional em sanduiche. No entanto a estrutura planar permite também obter vários níveis de resistência elétrica sugerindo que pode funcionar como memorias “multi-bit”

Resistive-RAM for Data Storage Applications.

Mainstream non-volatile memory technology, dominated by the floating gate transistor, has historically improved in density, performance and cost primarily by means of process scaling. This simple geometrical scaling now faces significant challenges due to constraints of electrostatics and reliability. Thus, novel non-transistor based memory paradigms are being widely explored. Among the various contenders for next generation storage technology, RRAM devices have got immense attention due to their high-speed, multilevel capability, scalability, simple structure, low voltage operation and high endurance. In this thesis, electrical and material characterization is carried out on a MIM device system and formation / annihilation of nanoscale filaments is shown to be the reason behind the resistance switching. The MIM system is optimized to include an in-cell resistor which is shown to improve device endurance and reduce stuck-at-one faults. For highest density, the devices were arranged in a crossbar geometry and vertically integrated on CMOS decoders to demonstrate the feasibility of practical data storage applications. Next, we show that these binary RRAM devices exhibit native stochastic nature of resistive switching. Even for a fixed voltage on the same device, the wait time associated with programming is not fixed and is random and broadly distributed. However, the probability of switching can be predicted and controlled by the programming pulse. These binary devices have been used to generate random bit-streams with predicable bias ratios in time and space domains. The ability to produce random bit-streams using binary resistive switching devices based on the native stochastic switching principle may potentially lead to novel non-von-Neumann computing paradigms. Further, sub-1nA operating current devices have been developed. This ultra-low current provides energy savings by minimizing programming, erase and read currents. Despite having such low currents, excellent retention, on/off ratio and endurance have been demonstrated. Finally a scalable approach to simple 3D stacking is discussed. By implementation of a vertical sidewall-based architecture, the number of critical lithography steps can be reduced. A vertical device structure based on a W / WOx / Pd material system is developed. This scalable architecture is well suited for development of analog memory and neuromorphic systems.PhDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/110461/1/sidgaba_1.pd

Perovskite Materials, Devices and Integration

Perovskites have attracted great attention in the fields of energy storage, pollutant degradation as well as optoelectronic devices due to their excellent properties. This kind of material can be divided into two categories; inorganic perovskite represented by perovskite oxide and organic-inorganic hybrid perovskite, which have described the recent advancement separately in terms of catalysis and photoelectron applications. This book systematically illustrates the crystal structures, physic-chemical properties, fabrication process, and perovskite-related devices. In a word, perovskite has broad application prospects. However, the current challenges cannot be ignored, such as toxicity and stability