Multiple-valued content-addressable memory using metal-ferroelectric-semiconductor FETs

科研費報告書収録論文(課題番号:09558027・基盤研究(B)(2)・H9～H12/研究代表者:羽生, 貴弘/1トランジスタセル多値連想メモリの試作とその応用

Multiple-valued logic-in-memory VLSI based on ferroelectric capacitor storage and charge addition

科研費報告書収録論文(課題番号:13558026・基盤研究(B)(2)・13～16/研究代表者:羽生, 貴弘/転送ボトルネックフリー多値ロジックインメモリVLSIの開発と応用

Challenge of a multiple-valued technology in recent deep-submicron VLSI

科研費報告書収録論文(課題番号:13558026・基盤研究(B)(2)・13～16/研究代表者:羽生, 貴弘/転送ボトルネックフリー多値ロジックインメモリVLSIの開発と応用

Quantum and spin-based tunneling devices for memory systems

Rapid developments in information technology, such as internet, portable computing, and wireless communication, create a huge demand for fast and reliable ways to store and process information. Thus far, this need has been paralleled with the revolution in solid-state memory technologies. Memory devices, such as SRAM, DRAM, and flash, have been widely used in most electronic products. The primary strategy to keep up the trend is miniaturization. CMOS devices have been scaled down beyond sub-45 nm, the size of only a few atomic layers. Scaling, however, will soon reach the physical limitation of the material and cease to yield the desired enhancement in device performance. In this thesis, an alternative method to scaling is proposed and successfully realized. The proposed scheme integrates quantum devices, Si/SiGe resonant interband tunnel diodes (RITD), with classical CMOS devices forming a microsystem of disparate devices to achieve higher performance as well as higher density. The device/circuit designs, layouts and masks involving 12 levels were fabricated utilizing a process that incorporates nearly a hundred processing steps. Utilizing unique characteristics of each component, a low-power tunneling-based static random access memory (TSRAM) has been demonstrated. The TSRAM cells exhibit bistability operation with a power supply voltage as low as 0.37 V. Various TSRAM cells were also constructed and their latching mechanisms have been extensively investigated. In addition, the operation margins of TSRAM cells are evaluated based on different device structures and temperature variation from room temperature up to 200oC. The versatility of TSRAM is extended beyond the binary system. Using multi-peak Si/SiGe RITD, various multi-valued TSRAM (MV-TSRAM) configurations that can store more than two logic levels per cell are demonstrated. By this virtue, memory density can be substantially increased. Using two novel methods via ambipolar operation and utilization of enable/disable transistors, a six-valued MV-TSRAM cell are demonstrated. A revolutionary novel concept of integrating of Si/SiGe RITD with spin tunnel devices, magnetic tunnel junctions (MTJ), has been developed. This hybrid approach adds non-volatility and multi-valued memory potential as demonstrated by theoretical predictions and simulations. The challenges of physically fabricating these devices have been identified. These include process compatibility and device design. A test bed approach of fabricating RITD-MTJ structures has been developed. In conclusion, this body of work has created a sound foundation for new research frontiers in four different major areas: integrated TSRAM system, MV-TSRAM system, MTJ/RITD-based nonvolatile MRAM, and RITD/CMOS logic circuits

AI/ML Algorithms and Applications in VLSI Design and Technology

An evident challenge ahead for the integrated circuit (IC) industry in the nanometer regime is the investigation and development of methods that can reduce the design complexity ensuing from growing process variations and curtail the turnaround time of chip manufacturing. Conventional methodologies employed for such tasks are largely manual; thus, time-consuming and resource-intensive. In contrast, the unique learning strategies of artificial intelligence (AI) provide numerous exciting automated approaches for handling complex and data-intensive tasks in very-large-scale integration (VLSI) design and testing. Employing AI and machine learning (ML) algorithms in VLSI design and manufacturing reduces the time and effort for understanding and processing the data within and across different abstraction levels via automated learning algorithms. It, in turn, improves the IC yield and reduces the manufacturing turnaround time. This paper thoroughly reviews the AI/ML automated approaches introduced in the past towards VLSI design and manufacturing. Moreover, we discuss the scope of AI/ML applications in the future at various abstraction levels to revolutionize the field of VLSI design, aiming for high-speed, highly intelligent, and efficient implementations

Inorganic micro/nanostructures-based high-performance flexible electronics for electronic skin application

Electronics in the future will be printed on diverse substrates, benefiting several emerging applications such as electronic skin (e-skin) for robotics/prosthetics, flexible displays, flexible/conformable biosensors, large area electronics, and implantable devices. For such applications, electronics based on inorganic micro/nanostructures (IMNSs) from high mobility materials such as single crystal silicon and compound semiconductors in the form of ultrathin chips, membranes, nanoribbons (NRs), nanowires (NWs) etc., offer promising high-performance solutions compared to conventional organic materials. This thesis presents an investigation of the various forms of IMNSs for high-performance electronics. Active components (from Silicon) and sensor components (from indium tin oxide (ITO), vanadium pentaoxide (V2O5), and zinc oxide (ZnO)) were realised based on the IMNS for application in artificial tactile skin for prosthetics/robotics. Inspired by human tactile sensing, a capacitive-piezoelectric tandem architecture was realised with indium tin oxide (ITO) on a flexible polymer sheet for achieving static (upto 0.25 kPa-1 sensitivity) and dynamic (2.28 kPa-1 sensitivity) tactile sensing. These passive tactile sensors were interfaced in extended gate mode with flexible high-performance metal oxide semiconductor field effect transistors (MOSFETs) fabricated through a scalable process. The developed process enabled wafer scale transfer of ultrathin chips (UTCs) of silicon with various devices (ultrathin chip resistive samples, metal oxide semiconductor (MOS) capacitors and n‐channel MOSFETs) on flexible substrates up to 4″ diameter. The devices were capable of bending upto 1.437 mm radius of curvature and exhibited surface mobility above 330 cm2/V-s, on-to-off current ratios above 4.32 decades, and a subthreshold slope above 0.98 V/decade, under various bending conditions. While UTCs are useful for realizing high-density high-performance micro-electronics on small areas, high-performance electronics on large area flexible substrates along with low-cost fabrication techniques are also important for realizing e-skin. In this regard, two other IMNS forms are investigated in this thesis, namely, NWs and NRs. The controlled selective source/drain doping needed to obtain transistors from such structure remains a bottleneck during post transfer printing. An attractive solution to address this challenge based on junctionless FETs (JLFETs), is investigated in this thesis via technology computer-aided design (TCAD) simulation and practical fabrication. The TCAD optimization implies a current of 3.36 mA for a 15 μm channel length, 40 μm channel width with an on-to-off ratio of 4.02x 107. Similar to the NRs, NWs are also suitable for realizing high performance e-skin. NWs of various sizes, distribution and length have been fabricated using various nano-patterning methods followed by metal assisted chemical etching (MACE). Synthesis of Si NWs of diameter as low as 10 nm and of aspect ratio more than 200:1 was achieved. Apart from Si NWs, V2O5 and ZnO NWs were also explored for sensor applications. Two approaches were investigated for printing NWs on flexible substrates namely (i) contact printing and (ii) large-area dielectrophoresis (DEP) assisted transfer printing. Both approaches were used to realize electronic layers with high NW density. The former approach resulted in 7 NWs/μm for bottom-up ZnO and 3 NWs/μm for top-down Si NWs while the latter approach resulted in 7 NWs/μm with simultaneous assembly on 30x30 electrode patterns in a 3 cm x 3 cm area. The contact-printing system was used to fabricate ZnO and Si NW-based ultraviolet (UV) photodetectors (PDs) with a Wheatstone bridge (WB) configuration. The assembled V2O5 NWs were used to realize temperature sensors with sensitivity of 0.03% /K. The sensor arrays are suitable for tactile e-skin application. While the above focuses on realizing conventional sensing and addressing elements for e-skin, processing of a large amount of data from e-skin has remained a challenge, especially in the case of large area skin. A Neural NW Field Effect Transistors (υ-NWFETs) based hardware-implementable neural network (HNN) approach for tactile data processing in e-skin is presented in the final part of this thesis. The concept is evaluated by interfacing with a fabricated kirigami-inspired e-skin. Apart from e-skin for prosthetics and robotics, the presented research will also be useful for obtaining high performance flexible circuits needed in many futuristic flexible electronics applications such as smart surgical tools, biosensors, implantable electronics/electroceuticals and flexible mobile phones

Low Power Memory/Memristor Devices and Systems

This reprint focusses on achieving low-power computation using memristive devices. The topic was designed as a convenient reference point: it contains a mix of techniques starting from the fundamental manufacturing of memristive devices all the way to applications such as physically unclonable functions, and also covers perspectives on, e.g., in-memory computing, which is inextricably linked with emerging memory devices such as memristors. Finally, the reprint contains a few articles representing how other communities (from typical CMOS design to photonics) are fighting on their own fronts in the quest towards low-power computation, as a comparison with the memristor literature. We hope that readers will enjoy discovering the articles within