76 research outputs found
Endurance characterization and improvement of floating gate semiconductor memory devices:
No full textLow power consumption, virtually zero latency, extremely fast boot-up for OS and applications, fast data access, portability, and high shock resistance are some of many reasons that make Flash memory devices an ideal choice for a vast variety of consumer electronics. Flash memory is a specific type of non-volatile EEPROM. A typical Flash memory cell looks similar to a MOSFET, except that it has a dual-gate structure. Flash memory cells use the principle of threshold voltage modulation to alter the channel current (Ids) when a reference read voltage (Vread) is applied to the control gate. Different levels of Ids are, in turn, interpreted as unique logic states. Fowler-Nordheim tunneling is used to achieve threshold voltage modulation in NAND Flash memory cells.
Despite its high performance potential, NAND Flash memory suffers from the drawback of limited program/erase endurance. High field/current stress caused by Fowler-Nordheim tunneling (during program/erase cycling) leads to tunnel oxide degradation, which eventually limits the endurance characteristics of NAND Flash memory cells. One of the most significant tunnel oxide degradation mechanisms is charge trapping. This work is devoted to the study of charge trapping and its effects on the endurance characteristics and reliability of NAND Flash memory devices. Cell threshold voltage shift and memory window narrowing, a direct consequence of tunnel oxide degradation caused by charge trapping, are typical failure modes in NAND Flash memory cells.
In this work, endurance characterization of NAND Flash memory devices and a detailed analysis has been conducted reconfirming the issue of limited program/erase endurance. Subsequently, a novel NAND Flash memory cell design has been proposed which eliminates tunnel oxide degradation caused by Fowler-Nordheim tunneling. Device simulations (using the Sentaurus TCAD tool suite by Synopsys®, Inc.) and corresponding analysis show that, as compared to conventional cells, the proposed cell design offers a 10 times reduction in intrinsic threshold voltage shift. That, according to the measured endurance characteristics of cells fabricated in this work, translates to an improvement of over 200 times in program/erase endurance. In a nutshell, the proposed cell design offers superior reliability and endurance as compared to conventional NAND Flash memory cells.M.S.Includes bibliographical references (p. 113-116)by Faraz Kha
Failure mechanisms of dielectric materials for electric motors
No full textSubmission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2023-12-01The student, Faraz Arastu, accepted the attached license on 2021-10-22 at 14:40.The student, Faraz Arastu, submitted this Thesis for approval on 2021-10-22 at 14:43.This Thesis was approved for publication on 2021-10-28 at 13:03.DSpace SAF Submission Ingestion Package generated from Vireo submission #17170 on 2022-04-29 at 16:09:09Made available in DSpace on 2022-04-29T21:58:17Z (GMT). No. of bitstreams: 2
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Previous issue date: 2021-10-28Embargo set by: Seth Robbins for item 123415
Lift date: 2024-04-29T21:58:46Z
Reason: Author requested closed access (OA after 2yrs) in Vireo ETD systemAuthor requested closed access (OA after 2yrs) in Vireo ETD systemLimitedRecent trends in electrification have increased demand for advanced sensors and actuators in the transportation and power systems industries. Complex thermomechanical systems used in geothermal energy, industrial gas turbines, aircraft propulsion systems, and spacecraft power systems require high power density devices that generate large amounts of heat in a smaller form factor. The community has looked to high critical flux cooling technology as well as higher-temperature materials development to address these needs. However, the development of high-temperature actuators, like electric motors, has lagged behind the development of high-temperature sensors and circuitry. This study explores the thermal operating limits of electric motor insulation to develop design and downselection criteria for developing high-temperature insulation materials that will meet the demands for high power density in industrial applications. A preceramic resin, polymethylsilsesquioxane, is first used to demonstrate that motor insulation can operate up to 660◦C with a dielectric strength of 162 VRMS, outperforming the stateof-the-art ML240 insulation commonly used in commercial motors. Then, insulation materials spanning a range of chemical structure motifs are used to build electric motor prototypes to determine the excitation current, force, and temperature windows in which each material can operate at the device level. Surprisingly, devices made with ML240 insulation - which has a 663◦C lower intrinsic thermal stability than ceramawire insulation - outperform ceramawire devices by nearly 60◦C. An investigation of the underlying failure mechanisms of the insulation was conducted to explain this result, revealing that thermal expansion-induced mechanical stresses dominate over intrinsic thermal stability in determining the critical failure temperature of a device.
To account for these stresses in the development of new, high-temperature insulation materials, a thermal expansion model is developed to downselect materials based on their thermomechanical properties and predict their device-level performance without building experimental device prototypes. This model can be used by both materials scientists and motor engineers to tailor the operating temperature window of film-insulation materials and meet the thermal requirements of a given application
Structure-Property Relationship of Thermoset Nanocomposites
No full textIn this thesis we report the synthesis, characterization and thermo-mechanical properties of a high-temperature resistant themoset nanocomposite system based on an aero-space-grade Bismaleimide resin. Various processing techniques with various fillers are used. The emphasis is on establishing the relationship between the structure and mechanical properties of nanocomposite systems. We characterized the nanocomposite systems experimentally using rheology, X-ray diffraction, Thermo-mechanical and microscopic techniques. The mechanical properties e.g. viscoelastic properties are interpreted in terms of the microstructure and explained by using micromechanical and viscoelastic models. In order to get insight into the structure of clay particles in the form of suspension we studied the rheology of organoclay dispersions before curing. We investigated the development of organoclay dispersions over time with the help of rheometry by applying small amplitude oscillatory deformation. Dispersions evolve over time with distinct stages into a percolating network. In most of the cases with various clay concentrations the behavior of dispersions was elastic solids-like. There is a critical threshold concentration of clay particles at which the dispersions initially behave as elastic solids and below which they form viscous fluids. This critical threshold seems to coincide with overlap concentration of the bodies of revolution of the particles, which is at a low clay concentration (of the order of 0.5% w/w). This overlapping of the bodies of revolution of particles may also limit the degree of exfoliation. Complete exfoliation is hardly ever achieved, as usually the concentration of particles used is much larger than the critical threshold concentration. Moreover, surprisingly, the frequency dependency of the mechanical moduli of the dispersions resemble that of a critical gel (a system just at the cross over between a visco-elastic solid and a visco-elastic fluid), normally reported for cross-linking polymers. This aspect has not been highlighted yet for clay dispersions. Interestingly the critical gel-like behavior of the dispersions persisted throughout the evolution over time. Thermo-mechanical properties of nanocomposite systems prepared with both carbon nanofiber and organoclay were investigated. The matrix itself and the nanocomposite system show excellent thermal properties and reasonable mechanical properties, better than the normal engineering polymers. The use of carbon nanofiber did not produce significant improvement in mechanical properties due to the poor adhesion of the fiber with the matrix. However, the use of organo clays shows systematic increase in mechanical properties and heat deflection temperature with the concentration of clay particles. The evaporation of solvent during curing leads to alignment of clay particles, which may also be beneficial for the properties of the nanocomposite. The stiffness of the nanocomposite was modeled by the Halpin-Tsai model. The model reproduces the data reasonably well. XRD results and the apparent aspect ratio obtained by Halpin-Tsai fitting indicate that the nanocomposite system is not completely exfoliated, and that the degree of exfoliation decreases with increasing particle concentration. We also investigated creep behavior of the nanocomposite system. The matrix shows very good creep stability and the use of nanofiller further enhances it. Application of the Findley power law and the Burgers model, which are widely used to describe the creep behavior of polymers, is critically evaluated. Their limitations to describe the creep behavior of thermoset matrices are discussed. We used a modified form of Burgers’ model which we named the ‘stretched Burgers model’ (SB) to describe the creep behavior of thermoset matrix and the nanocomposite. The stretched Burgers model reproduces the time-dependent creep compliance remarkably well. We made assumptions in fitting the data that retardation time scale distribution should be independent of filler concentration. The very good fitting of data supports the assumption. This means that the dynamics of the nanocomposite system is mainly governed by the dynamics of the matrix. This is an interesting assumption in our study and never highlighted in creep studies of nanocomposites. We believe that this finding is helpful for developing a better understanding of the mechanics of nanocomposites and of the role of filler on the dynamics of the matrix, which is greatly debated. The stretched Burgers model appears to be very suitable for describing the creep behavior of thermoset systems both from a physical point of view and concerning the quality of the fits.Chemical EngineeringApplied Science
Electrothermal simulation of superconducting nanowire avalanche photodetectors
No full textWe developed an electrothermal model of NbN superconducting nanowire avalanche photodetectors (SNAPs) on sapphire substrates. SNAPs are single-photon detectors consisting of the parallel connection of N superconducting nanowires. We extrapolated the physical constants of the model from experimental data and we simulated the time evolution of the device resistance, temperature and current by solving two coupled electrical and thermal differential equations describing the nanowires. The predictions of the model were in good quantitative agreement with the experimental results.United States. Dept. of Energy. Center for Excitonics (Award DE-SC0001088
Yellow Dravite from Tanzania
No full textDuring the 2016 Tucson gem shows, Todd Wacks (Tucson Todd’s Gems, Tucson, Arizona, USA) showed author BML a yellow 11.13 ct tourmaline that he faceted from a piece of rough recently obtained on a buying trip to Tanzania by Sir-Faraz Ahmad (Farooq) Hashmi (Intimate Gems, Glen Cove, New York, USA). The rough material was reportedly found in October–November 2015 in the Landanai region of north-eastern Tanzania, in an area that is known for producing green
‘chrome’ tourmaline. The rough consisted of a round ‘nodule’ that showed a few crystal faces. In faceting the gemsone, Wacks cut a small table and a deep pavilion to maximize the colour appearance
Spatial and Temporal Analysis of Road Deformation based on Remote Sensing and Subsurface Exploration
No full textIn the western part of the Netherlands, the soil contains mainly sand, peat, and clay which are known as soft soil layers. The buildings and infrastructures, such as roads, constructed on these soil layers are usually associated with substantial construction measures during the execution of the project and might suffer from damages induced by the post-construction deformations. In practice, one of the primary stages of road construction involves geotechnical in-situ investigations for determining the soil properties based on which the settlement is predicted through empirical models. There are several techniques for monitoring the post-construction deformation on roads, among which the most time and cost-efficient technique is advanced Differential InSAR (D-InSAR). Since no research has been dedicated to establishing a direct link between the geotechnical in situ measurements and deformation measurements, in this research, the main focus is to develop a fully data-driven methodology to model road deformation based on loading/unloading conditions and soil properties. The study area is the newly constructed part of the A4 highway (Delft-Schiedam) in the Netherlands.The proposed methodology in this research consists of three steps. In the first step of the methodology, the measurements that represent soil properties, loading/unloading and deformation measurements should be determined and gathered. Cone Penetration Testing (CPT) measurements and boreholes are two freely available data sets that represent soil properties. Another important soil property is the variations in soil water content can be characterized by temperature and precipitation. The latest stage of loading/unloading history can be determined by comparing the elevation of the study area before and after the construction. Deformation time series produced by D-InSAR techniques are suitable measurements for investigating spatiotemporal deformations on roads. After determining pre-processing steps for each of the raw data sets, the relevant parameters from each data source are extracted. In the next step, the correlations and similarities between the soil properties, loading/unloading condition, and deformation are investigated. The last step deals with extracting suitable features from CPT profiles in order to use machine learning to model the relationship between soil properties, loading/unloading conditions, and deformation. To this end, the CPT profiles are segmented, then qualitative (soil types) or quantitative descriptors of the segments are used as features. To determine the soil classes, Support Vector Machines (SVM) classifier is used. The relationship between soil properties, loading/unloading and the linear rate of deformation is modeled through two tree-based algorithms, i.e. Random Forests and Gradient tree-boosting. The Pearson correlation and the coefficient of determination between soil properties, loading/unloading and the linear rate of deformation are 0.6 and 0.4, respectively. The correlation of deformation time series and temperature and precipitation is quite low and no consistent pattern could be found between the time delays. The soil classification by SVM classifier is more accurate compared to empirical charts. For the deformation modeling, the best performance metrics are obtained through the Gradient Boosting algorithm with quantitative descriptors as features, (Mean Absolute Error (MAE) is 1.1 mm/year, Root Mean Squared Error (RMSE) is 1.5 mm/year and the coefficient of determination is 0.5). In conclusion, the resulting models with different algorithms and different sets of features are of moderate accuracy. The uncertainty of the models is due to three main reasons: 1. The complexity of the study area in terms of construction history 2. Lack of other necessary data 3. The uncertainties caused by the proposed methodology.Geomatic
Building antifragile manufacturing systems through strategic technology integration
No full textPurpose – This study develops and validates, through expert consensus, a framework for achieving antifragilityin manufacturing by strategically integrating modern digital technologies with capabilities that enableorganizations to grow stronger through disruption. It moves beyond traditional resilience-focused approaches byemphasizing continuous adaptability, sustained growth and competitive advantage in an environmentcharacterized by volatility and rapid technological change. Design/methodology/approach – Grounded in the dynamic capability perspective, the study synthesizesinsights from an extensive literature review with the results of a Delphi study involving a panel of 14 industryand academic experts. The process identified and refined a set of critical supporting capabilities, including cross-functional governance, interoperability assessment and risk-responsive integration, that enable the alignment ofdigital transformation initiatives with antifragile objectives. Findings – Antifragility is positioned as a higher-order dynamic capability that transforms volatility into a driverof innovation and strategic renewal. The resulting expert-based framework maps emerging technologies such asartificial intelligence, the Internet of Things and big data analytics to specific sensing, seizing and transformingcapabilities, providing a structured pathway for operationalizing antifragility in manufacturing contexts. Practical implications – The framework offers manufacturers a structured approach for aligning technology investments with antifragile objectives, ensuring that digital transformation enhances rather than undermines adaptability and growth. It encourages a phased, resource-aware implementation strategy that leverages disruptions as strategic assets, fostering both business continuity and long-term competitiveness. Originality/value – This research conceptualizes antifragility as a distinct and advanced capability in manufacturing and demonstrates how it can be purposefully developed through strategic technology integration. By combining theoretical grounding with expert validation, it bridges the gap between digital transformation and antifragility, offering a practical roadmap for turning uncertainty and variability into sources of competitive advantage.CC BY 4.0© Morteza Ghobakhloo, Behzad Foroughi, Masood Fathi, Mostafa Al-Emran, Mohammed A. Al-Sharafiand Muhammad Faraz Mubarak.Corresponding author Morteza Ghobakhloo can be contacted at: [email protected]</p
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