STT-MRAM characterization and its test implications

Spin torque transfer (STT)-magnetoresistive random-access memory (MRAM) has come a long way in research to meet the speed and power consumption requirements for future memory applications. The state-of-the-art STT-MRAM bit-cells employ magnetic tunnel junction (MTJ) with perpendicular magnetic anisotropy (PMA). The process repeatabil- ity and yield stability for wafer fabrication are some of the critical issues encountered in STT-MRAM mass production. Some of the yield improvement techniques to combat the e ect of process variations have been previously explored. However, little research has been done on defect oriented testing of STT-MRAM arrays. In this thesis, the author investi- gates the parameter deviation and non-idealities encountered during the development of a novel MTJ stack con guration. The characterization result provides motivation for the development of the design for testability (DFT) scheme that can help test and characterize STT-MRAM bit-cells and the CMOS peripheral circuitry e ciently. The primary factors for wafer yield degradation are the device parameter variation and its non-uniformity across the wafer due to the fabrication process non-idealities. There- fore, e ective in-process testing strategies for exploring and verifying the impact of the parameter variation on the wafer yield will be needed to achieve fabrication process opti- mization. While yield depends on the CMOS process variability, quality of the deposited MTJ lm, and other process non-idealities, test platform can enable parametric optimiza- tion and veri cation using the CMOS-based DFT circuits. In this work, we develop a DFT algorithm and implement a DFT circuit for parametric testing and prequali cation of the critical circuits in the CMOS wafer. The DFT circuit successfully replicates the electrical characteristics of MTJ devices and captures their spatial variation across the wafer with an error of less than 4%. We estimate the yield of the read sensing path by implement- ing the DFT circuit, which can replicate the resistance-area product variation up to 50% from its nominal value. The yield data from the read sensing path at di erent wafer loca- tions are analyzed, and a usable wafer radius has been estimated. Our DFT scheme can provide quantitative feedback based on in-die measurement, enabling fabrication process optimization through iterative estimation and veri cation of the calibrated parameters. Another concern that prevents mass production of STT-MRAM arrays is the defect formation in MTJ devices due to aging. Identifying manufacturing defects in the magnetic tunnel junction (MTJ) device is crucial for the yield and reliability of spin-torque-transfer (STT) magnetic random-access memory (MRAM) arrays. Several of the MTJ defects result in parametric deviations of the device that deteriorate over time. We extend our work on the DFT scheme by monitoring the electrical parameter deviations occurring due to the defect formation over time. A programmable DFT scheme was implemented for a sub-arrayin 65 nm CMOS technology to evaluate the feasibility of the test scheme. The scheme utilizes the read sense path to compare the bit-cell electrical parameters against known DFT cells characteristics. Built-in-self-test (BIST) methodology is utilized to trigger the onset of the fault once the device parameter crosses a threshold value. We demonstrate the operation and evaluate the accuracy of detection with the proposed scheme. The DFT scheme can be exploited for monitoring aging defects, modeling their behavior and optimization of the fabrication process. DFT scheme could potentially nd numerous applications for parametric characteriza- tion and fault monitoring of STT-MRAM bit-cell arrays during mass production. Some of the applications include a) Fabrication process feedback to improve wafer turnaround time, b) STT-MRAM bit-cell health monitoring, c) Decoupled characterization of the CMOS pe- ripheral circuitry such as read-sensing path and sense ampli er characterization within the STT-MRAM array. Additionally, the DFT scheme has potential applications for detec- tion of fault formation that could be utilized for deploying redundancy schemes, providing a graceful degradation in MTJ-based bit-cell array due to aging of the device, and also providing feedback to improve the fabrication process and yield learning

Flight Avionics Hardware Roadmap

As part of NASA's Avionics Steering Committee's stated goal to advance the avionics discipline ahead of program and project needs, the committee initiated a multi-Center technology roadmapping activity to create a comprehensive avionics roadmap. The roadmap is intended to strategically guide avionics technology development to effectively meet future NASA missions needs. The scope of the roadmap aligns with the twelve avionics elements defined in the ASC charter, but is subdivided into the following five areas: Foundational Technology (including devices and components), Command and Data Handling, Spaceflight Instrumentation, Communication and Tracking, and Human Interfaces

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

The Architecture of a Reusable Built-In Self-Test for Link Training, IO and Memory Defect Detection and Auto Repair on 14nm Intel SOC

The complexity of designing and testing today's system on chip (SOC) is increasing due to greater integrated circuit (IC) density and higher IO and memory frequencies. SOCs for the mobile phone and tablet market have the unique challenge of short product development windows, at times less than six months, and low cost board and platform that limits physical access to test access ports (TAP). This dissertation presents the architecture of a reusable built-in self-test (BIST) engine called converged pattern generator and checker (CPGC) that was developed to address the above challenges. It is used in the critical path of millions of x86 SOC for DDR3, DDR4, LP-DDR3, LP-DDR4 IO initialization and link training. The CPGC is also an essential BIST engine for IO and memory defect detection, and in some cases, the automatic repair of detected memory defects. The software and hardware infrastructure that leverages CPU L2/L3 cache to enable cache based testing (CBT) and the parallel execution of the CPGC Intel BIST engine is shown to improve test time 60x to 170x over conventional TAP based testing. In addition, silicon results are presented showing that CPGC enables easy debug of inter symbol interference (ISI) and crosstalk issues in silicon and boards, enables fast IO link training, improves validation time by 3x, and in some instances, reduces SOC and platform power by 5% to 11% through closed loop IO circuit power optimization. This CPGC BIST engine has been developed into a reusable IP solution, which has been successfully designed into at least 11 Intel CPUs and SOCs (32nm-14nm), with seven of these successfully debugged, tested, and launched into the market place. Ultimately has led to over 100 million CPUs being shipped within one quarter using this architecture

Grazing Incidence X-ray Scattering from Magnetic Thin Films and Nanostructures

Grazing incidence scattering of synchrotron x-rays has been used to characterize the structure of magnetic thin films and periodic nanostructures. The combined metal and metal oxide films have been chosen to clarify the effects of growth processing techniques in technologically important magnetic and magnetoresistive thin film materials, and have particular relevance to the magnetic tunnel junction (MTJ) class of magnetic sensor. Co/Al2O3 thin films and Co/MgO multilayer thin films have been characterized using x-ray reflectivity and diffuse scatter analysis to explain how preparatory oxidation of the lower ferromagnet in an MTJ can reduce Néel interlayer coupling and improve the consistency of magnetoresistance. Measurements reveal differing effects for Al2O3 and MgO tunnel barrier materials. In Co/Al2O3 systems, preoxidation is found to reduce significantly chemical interdiffusion at the interface between the two layers, implying a more uniform oxidation of the barrier layer. In Co/MgO multilayers, an increased in-plane correlation length of the inherited interface roughness is seen after preoxidation. This implies that preoxidation suppresses the short wavelength undulations on both sides of the tunnel barrier that cause Néel coupling. Grazing incidence in-plane diffraction measurements on epitaxial Fe/MgO/Fe [001] and Fe/Au/MgO/Fe [001] films during annealing to 600 K have shown that, in both cases, the MgO lattice is initially strained towards being commensurate with the iron and gold layers, but relaxes after annealing towards a typical bulk MgO lattice. The iron and gold layers display linear thermal expansion at rates consistent with the bulk material. These in-plane lattice measurements demonstrate how the strain and strain dispersion in an epitaxial MgO barrier layer can be relieved under controlled annealing conditions. Finally, patterned thin film surfaces with submicron periodic symmetries have been studied by grazing incidence x-ray scattering. A novel semi-kinematical theory has been developed into a numerical algorithm capable of simulating the scatter from a wide range of arbitrary and disordered nanoscale arrays. This has allowed key structural parameters including array periodicity, symmetry and array coherence lengths to be extracted from experimental data

Mn3Pt反強磁性体の磁気特性と非従来型スピン軌道トルクとの相関に関する研究

Tohoku University大兼幹彦課

2020 NASA Technology Taxonomy

This document is an update (new photos used) of the PDF version of the 2020 NASA Technology Taxonomy that will be available to download on the OCT Public Website. The updated 2020 NASA Technology Taxonomy, or "technology dictionary", uses a technology discipline based approach that realigns like-technologies independent of their application within the NASA mission portfolio. This tool is meant to serve as a common technology discipline-based communication tool across the agency and with its partners in other government agencies, academia, industry, and across the world

Potential and Challenges of Analog Reconfigurable Computation in Modern and Future CMOS

In this work, the feasibility of the floating-gate technology in analog computing platforms in a scaled down general-purpose CMOS technology is considered. When the technology is scaled down the performance of analog circuits tends to get worse because the process parameters are optimized for digital transistors and the scaling involves the reduction of supply voltages. Generally, the challenge in analog circuit design is that all salient design metrics such as power, area, bandwidth and accuracy are interrelated. Furthermore, poor flexibility, i.e. lack of reconfigurability, the reuse of IP etc., can be considered the most severe weakness of analog hardware. On this account, digital calibration schemes are often required for improved performance or yield enhancement, whereas high flexibility/reconfigurability can not be easily achieved. Here, it is discussed whether it is possible to work around these obstacles by using floating-gate transistors (FGTs), and analyze problems associated with the practical implementation. FGT technology is attractive because it is electrically programmable and also features a charge-based built-in non-volatile memory. Apart from being ideal for canceling the circuit non-idealities due to process variations, the FGTs can also be used as computational or adaptive elements in analog circuits. The nominal gate oxide thickness in the deep sub-micron (DSM) processes is too thin to support robust charge retention and consequently the FGT becomes leaky. In principle, non-leaky FGTs can be implemented in a scaled down process without any special masks by using “double”-oxide transistors intended for providing devices that operate with higher supply voltages than general purpose devices. However, in practice the technology scaling poses several challenges which are addressed in this thesis. To provide a sufficiently wide-ranging survey, six prototype chips with varying complexity were implemented in four different DSM process nodes and investigated from this perspective. The focus is on non-leaky FGTs, but the presented autozeroing floating-gate amplifier (AFGA) demonstrates that leaky FGTs may also find a use. The simplest test structures contain only a few transistors, whereas the most complex experimental chip is an implementation of a spiking neural network (SNN) which comprises thousands of active and passive devices. More precisely, it is a fully connected (256 FGT synapses) two-layer spiking neural network (SNN), where the adaptive properties of FGT are taken advantage of. A compact realization of Spike Timing Dependent Plasticity (STDP) within the SNN is one of the key contributions of this thesis. Finally, the considerations in this thesis extend beyond CMOS to emerging nanodevices. To this end, one promising emerging nanoscale circuit element - memristor - is reviewed and its applicability for analog processing is considered. Furthermore, it is discussed how the FGT technology can be used to prototype computation paradigms compatible with these emerging two-terminal nanoscale devices in a mature and widely available CMOS technology.Siirretty Doriast

Study of magnetic nanostructures fabricated by nanosphere lithography

Ph.DDOCTOR OF PHILOSOPH