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At least 1,297 records · Page 72

Suboxide/subnitride formation on Ta masks during magnetic material etching by reactive plasmas

Etching characteristics of tantalum (Ta) masks used in magnetoresistive random-access memory etching processes by carbon monoxide and ammonium (CO/NH{sub 3}) or methanol (CH{sub 3}OH) plasmas have been examined by mass-selected ion beam experiments with in-situ surface analyses. It has been suggested in earlier studies that etching of magnetic materials, i.e., Fe, Ni, Co, and their alloys, by such plasmas is mostly due to physical sputtering and etch selectivity of the process arises from etch resistance (i.e., low-sputtering yield) of the hard mask materials such as Ta. In this study, it is shown that, during Ta etching by energetic CO{sup +} or N{sup +} ions, suboxides or subnitrides are formed on the Ta surface, which reduces the apparent sputtering yield of Ta. It is also shown that the sputtering yield of Ta by energetic CO{sup +} or N{sup +} ions has a strong dependence on the angle of ion incidence, which suggests a correlation between the sputtering yield and the oxidation states of Ta in the suboxide or subnitride; the higher the oxidation state of Ta, the lower is the sputtering yield. These data account for the observed etch selectivity by CO/NH{sub 3} and CH{sub 3}OH plasmas.

36 MATERIALS SCIENCE↗

The impact of cine EPID image acquisition frame rate on markerless soft-tissue tracking

Purpose: Although reduction of the cine electronic portal imaging device (EPID) acquisition frame rate through multiple frame averaging may reduce hardware memory burden and decrease image noise, it can hinder the continuity of soft-tissue motion leading to poor autotracking results. The impact of motion blurring and image noise on the tracking performance was investigated. Methods: Phantom and patient images were acquired at a frame rate of 12.87 Hz with an amorphous silicon portal imager (AS1000, Varian Medical Systems, Palo Alto, CA). The maximum frame rate of 12.87 Hz is imposed by the EPID. Low frame rate images were obtained by continuous frame averaging. A previously validated tracking algorithm was employed for autotracking. The difference between the programmed and autotracked positions of a Las Vegas phantom moving in the superior-inferior direction defined the tracking error (δ). Motion blurring was assessed by measuring the area change of the circle with the greatest depth. Additionally, lung tumors on 1747 frames acquired at 11 field angles from four radiotherapy patients are manually and automatically tracked with varying frame averaging. δ was defined by the position difference of the two tracking methods. Image noise was defined as the standard deviation of the background intensity. Motion blurring and image noise are correlated with δ using Pearson correlation coefficient (R). Results: For both phantom and patient studies, the autotracking errors increased at frame rates lower than 4.29 Hz. Above 4.29 Hz, changes in errors were negligible withδ < 1.60 mm. Motion blurring and image noise were observed to increase and decrease with frame averaging, respectively. Motion blurring and tracking errors were significantly correlated for the phantom (R = 0.94) and patient studies (R = 0.72). Moderate to poor correlation was found between image noise and tracking error with R −0.58 and −0.19 for both studies, respectively. Conclusions: Cine EPID image acquisition at the frame rate of at least 4.29 Hz is recommended. Motion blurring in the images with frame rates below 4.29 Hz can significantly reduce the accuracy of autotracking.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Development of Gamma Background Radiation Digital Twin with Machine Learning Algorithms: Application of Unsupervised Machine Learning to Detection of Anomalies and Nuisances in Gamma Background Radiation Environmental Screening Data

Environmental screening of gamma radiation consists of detecting weak nuisance and anomaly signal in the presence of strong and highly varying background. In a typical scenario, a mobile detector-spectrometer continuously measures gamma radiation spectra in short, e.g., one-second, signal acquisition intervals. The measurement data is a 2D matrix, where one dimension is gamma ray energy, and the other dimension is the number of measurements or total time. In principle, gamma radiation sources can be detected and identified from the measured data by their unique spectral lines. Detecting sources from data measured in a search scenario is difficult due to the highly varying background because of naturally occurring radioactive material (NORM), and low signal-to-noise ratio (S/N) of spectral signal measured during one-second acquisition intervals. The objective of this work is to explore unsupervised machine learning (ML) algorithms for development of a digital twin of gamma radiation background, and for detection and identification of weak nuisances and anomalies events in the presence of highly fluctuating background. In one segment of work, we developed a gamma background estimation model using a Longshort term memory (LSTM) network for one-step CPS time series prediction. The LSTM model was validated with two data sets of measurements from two independent NaI detectors positioned on a mobile platform. The data sets contained background radiation only and no orphan isotope sources. The LSTM model was constructed and tested using data from one of the detectors. Performance of the LSTM model was validate through one-step prediction of CPS time series of another NaI detector without re-training. This approach allows to create a digital twin for nuclear background estimation. Using LSTM, it could be possible to detect a source through subtraction of the estimated counts from the measured background. In another segment of work, we investigated detection of gamma emitting sources in the presence of complex background using unsupervised machine learning. Spectral lines of isotopes are difficult to observe in one-second measurements. Averaging over the entire measurement campaign data set reveals spectral lines of most common background isotopes. Spectral lines of orphan sources, which might appear only in a few measurements during the campaign, will be washed out if averaging is performed over the entire measurement data set. The approach we have explored consists of extracting one-second measurements containing weak spectral features through data clustering. Averaging one-second spectra in a cluster should reveal the presence of anomaly sources. We created two ML models using K-means clustering and Neural Network Self-organizing Map (SOM). Performance of these ML models was benchmarked using search data. One data set contained 137 Cs source, and another dataset contained 131 I source.

54 ENVIRONMENTAL SCIENCES↗

Direct Solve of Electrically Large Integral Equations for Problem Sizes to 1M Unknowns

Matrix methods for solving integral equations via direct solve LU factorization are presently limited to weeks to months of very expensive supercomputer time for problems sizes of several hundred thousand unknowns. This report presents matrix LU factor solutions for electromagnetic scattering problems for problem sizes to one million unknowns with thousands of right hand sides that run in mere days on PC level hardware. This EM solution is accomplished by utilizing the numerical low rank nature of spatially blocked unknowns using the Adaptive Cross Approximation for compressing the rank deficient blocks of the system Z matrix, the L and U factors, the right hand side forcing function and the final current solution. This compressed matrix solution is applied to a frequency domain EM solution of Maxwell's equations using standard Method of Moments approach. Compressed matrix storage and operations count leads to orders of magnitude reduction in memory and run time.

Shaeffer, John↗

NASA Tech Briefs, January 2006

Topics covered include: Semiautonomous Avionics-and-Sensors System for a UAV; Biomimetic/Optical Sensors for Detecting Bacterial Species; System Would Detect Foreign-Object Damage in Turbofan Engine; Detection of Water Hazards for Autonomous Robotic Vehicles; Fuel Cells Utilizing Oxygen From Air at Low Pressures; Hybrid Ion-Detector/Data-Acquisition System for a TOF-MS; Spontaneous-Desorption Ionizer for a TOF-MS; Equipment for On-Wafer Testing From 220 to 325 GHz; Computing Isentropic Flow Properties of Air/R-134a Mixtures; Java Mission Evaluation Workstation System; Using a Quadtree Algorithm To Assess Line of Sight; Software for Automated Generation of Cartesian Meshes; Optics Program Modified for Multithreaded Parallel Computing; Programs for Testing Processor-in-Memory Computing Systems; PVM Enhancement for Beowulf Multiple-Processor Nodes; Ion-Exclusion Chromatography for Analyzing Organics in Water; Selective Plasma Deposition of Fluorocarbon Films on SAMs; Water-Based Pressure-Sensitive Paints; System Finds Horizontal Location of Center of Gravity; Predicting Tail Buffet Loads of a Fighter Airplane; Water Containment Systems for Testing High-Speed Flywheels; Vapor-Compression Heat Pumps for Operation Aboard Spacecraft; Multistage Electrophoretic Separators; Recovering Residual Xenon Propellant for an Ion Propulsion System; Automated Solvent Seaming of Large Polyimide Membranes; Manufacturing Precise, Lightweight Paraboloidal Mirrors; Analysis of Membrane Lipids of Airborne Micro-Organisms; Noninvasive Diagnosis of Coronary Artery Disease Using 12-Lead High-Frequency Electrocardiograms; Dual-Laser-Pulse Ignition; Enhanced-Contrast Viewing of White-Hot Objects in Furnaces; Electrically Tunable Terahertz Quantum-Cascade Lasers; Few-Mode Whispering-Gallery-Mode Resonators; Conflict-Aware Scheduling Algorithm; and Real-Time Diagnosis of Faults Using a Bank of Kalman Filters.

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Localised nanoscale resistive switching in GaP thin films with low power consumption

Nanoscale localisation of the electroforming-free resistive switching (RS) behaviour in polycrystalline GaP thin films has been observed for the first time. A combination of conductive atomic force microscopy and first-order reversal curve current–voltage measurements indicated that the grain boundaries are the preferred sites for the formation of the conductive switching filaments. It is proposed, based on TEM and XPS results, that local electrochemical migration of Ga ions along the grain boundaries plays a critical role in the switching mechanism. In the low-resistance (ON) state, the conduction mechanism was found to be the space-charge-limited current mechanism, while the high-resistance (OFF) state was governed by the Frenkel–Poole mechanism. Here, a high OFF/ON resistance ratio (~10 4 ) and lower power consumption than current RS devices, in addition to the easy integration of GaP with silicon substrates, make these GaP films promising for future applications in future non-volatile resistive random access memory (RRAM).

36 MATERIALS SCIENCE↗

BMS symmetry, soft particles and memory

Here, in this work, we revisit unitary irreducible representations of the Bondi–Metzner–Sachs (BMS) group discovered by McCarthy. Representations are labelled by an infinite number of supermomenta in addition to 4-momentum. Tensor products of these irreducible representations lead to particle-like states dressed by soft gravitational modes. Conservation of 4-momentum and supermomentum in the scattering of such states leads to a memory effect encoded in the outgoing soft modes. We note there exist irreducible representations corresponding to soft states with strictly vanishing 4-momentum, which may nevertheless be produced by scattering of particle-like states. This fact has interesting implications for the S-matrix in gravitational theories.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Simple, low-cost and accurate data-driven geophysical forecasting with learned kernels

Modelling geophysical processes as low-dimensional dynamical systems and regressing their vector field from data is a promising approach for learning emulators of such systems. We show that when the kernel of these emulators is also learned from data (using kernel flows, a variant of cross-validation), then the resulting data-driven models are not only faster than equation-based models but are easier to train than neural networks such as the long short-term memory neural network. In addition, they are also more accurate and predictive than the latter. When trained on geophysical observational data, for example the weekly averaged global sea-surface temperature, considerable gains are also observed by the proposed technique in comparison with classical partial differential equation-based models in terms of forecast computational cost and accuracy. When trained on publicly available re-analysis data for the daily temperature of the North American continent, we observe significant improvements over classical baselines such as climatology and persistence-based forecast techniques. Although our experiments concern specific examples, the proposed approach is general, and our results support the viability of kernel methods (with learned kernels) for interpretable and computationally efficient geophysical forecasting for a large diversity of processes.

58 GEOSCIENCES↗

Artificial Neural Network as the FPGA Trigger in the Cyclone V based Front-End for a Detection of Neutrino-Origin Showers

Neutrinos play a fundamental role in the understanding of the origin of ultra-high-energy cosmic rays. They interact through charged and neutral currents in the atmosphere generating extensive air showers. However, their a very low rate of events potentially generated by neutrinos is a significant challenge for a detection technique and requires both sophisticated algorithms and high-resolution hardware. A trigger based on a artificial neural network was implemented into the Cyclone{sup R} V E FPGA 5CEFA9F31I7 - the heart of the prototype Front-End boards developed for tests of new algorithms in the Pierre Auger surface detectors. Showers for muon and tau neutrino initiating particles on various altitudes, angles and energies were simulated in CORSICA and Offline platforms giving pattern of ADC traces in Auger water Cherenkov detectors. The 3-layer 12-8-1 neural network was taught in MATLAB by simulated ADC traces according the Levenberg-Marquardt algorithm. Results show that a probability of a ADC traces generation is very low due to a small neutrino cross-section. Nevertheless, ADC traces, if occur, for 1-10 EeV showers are relatively short and can be analyzed by 16-point input algorithm. We optimized the coefficients from MATLAB to get a maximal range of potentially registered events and for fixed-point FPGA processing to minimize calculation errors. New sophisticated triggers implemented in Cyclone{sup R} V E FPGAs with large amount of DSP blocks, embedded memory running with 120 - 160 MHz sampling may support a discovery of neutrino events in the Pierre Auger Observatory. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Data and Thread Placement in NUMA Architectures: A Statistical Learning Approach

Nowadays, NUMA architectures are common in compute-intensive systems. Achieving high performance for multi-threaded application requires both a careful placement of threads on computing units and a thorough allocation of data in memory. Finding such a placement is a hard problem to solve, because performance depends on complex interactions in several layers of the memory hierarchy. In this paper we propose a black-box approach to decide if an application execution time can be impacted by the placement of its threads and data, and in such a case, to choose the best placement strategy to adopt. We show that it is possible to reach near-optimal placement policy selection. Furthermore, solutions work across several recent processor architectures and decisions can be taken with a single run of low overhead profiling.

data↗

High-performance, flexible, deployable array development for space applications

Flexible, deployable arrays are an attractive alternative to conventional solar arrays for near-term and future space power applications, particularly due to their potential for high specific power and low storage volume. Combined with low-cost flexible thin-film photovoltaics, these arrays have the potential to become an enabling or an enhancing technology for many missions. In order to expedite the acceptance of thin-film photovoltaics for space applications, however, parallel development of flexible photovoltaics and the corresponding deployable structure is essential. Many innovative technologies must be incorporated in these arrays to ensure a significant performance increase over conventional technologies. For example, innovative mechanisms which employ shape memory alloys for storage latches, deployment mechanisms, and array positioning gimbals can be incorporated into flexible array design with significant improvement in the areas of cost, weight, and reliability. This paper discusses recent activities at Martin Marietta regarding the development of flexible, deployable solar array technology. Particular emphasis is placed on the novel use of shape memory alloys for lightweight deployment elements to improve the overall specific power of the array. Array performance projections with flexible thin-film copper-indium-diselenide (CIS) are presented, and government-sponsored solar array programs recently initiated at Martin Marietta through NASA and Air Force Phillips Laboratory are discussed.

Gehling, Russell N.↗

NASA Tech Briefs, November 2008

Topics covered include: Digital Phase Meter for a Laser Heterodyne Interferometer; Vision System Measures Motions of Robot and External Objects; Advanced Precipitation Radar Antenna to Measure Rainfall From Space; Wide-Band Radar for Measuring Thickness of Sea Ice; Vertical Isolation for Photodiodes in CMOS Imagers; Wide-Band Microwave Receivers Using Photonic Processing; L-Band Transmit/Receive Module for Phase-Stable Array Antennas; Microwave Power Combiner/Switch Utilizing a Faraday Rotator; Compact Low-Loss Planar Magic-T; Using Pipelined XNOR Logic to Reduce SEU Risks in State Machines; Quasi-Optical Transmission Line for 94-GHz Radar; Next Generation Flight Controller Trainer System; Converting from DDOR SASF to APF; Converting from CVF to AAF; Documenting AUTOGEN and APGEN Model Files; Sequence History Update Tool; Extraction and Analysis of Display Data; MRO DKF Post-Processing Tool; Rig Diagnostic Tools; MRO Sequence Checking Tool; Science Activity Planner for the MER Mission; UAVSAR Flight-Planning System; Templates for Deposition of Microscopic Pointed Structures; Adjustable Membrane Mirrors Incorporating G-Elastomers; Hall-Effect Thruster Utilizing Bismuth as Propellant; High-Temperature Crystal-Growth Cartridge Tubes Made by VPS; Quench Crucibles Reinforced with Metal; Deep-Sea Hydrothermal-Vent Sampler; Mars Rocket Propulsion System; Two-Stage Passive Vibration Isolator; Improved Thermal Design of a Compression Mold; Enhanced Pseudo-Waypoint Guidance for Spacecraft Maneuvers; Altimetry Using GPS-Reflection/Occultation Interferometry; Thermally Driven Josephson Effect; Perturbation Effects on a Supercritical C7H16/N2 Mixing Layer; Gold Nanoparticle Labels Amplify Ellipsometric Signals; Phase Matching of Diverse Modes in a WGM Resonator; WGM Resonators for Terahertz-to-Optical Frequency Conversion; Determining Concentration of Nanoparticles from Ellipsometry; Microwave-to-Optical Conversion in WGM Resonators; Four-Pass Coupler for Laser-Diode-Pumped Solid-State Laser; Low-Resolution Raman-Spectroscopy Combustion Thermometry; Temperature Sensors Based on WGM Optical Resonators; Varying the Divergence of Multiple Parallel Laser Beams; Efficient Algorithm for Rectangular Spiral Search; Algorithm-Based Fault Tolerance Integrated with Replication; Targeting and Localization for Mars Rover Operations; Terrain-Adaptive Navigation Architecture; Self-Adjusting Hash Tables for Embedded Flight Applications; Schema for Spacecraft-Command Dictionary; Combined GMSK Communications and PN Ranging; System-Level Integration of Mass Memory; Network-Attached Solid-State Recorder Architecture; Method of Cross-Linking Aerogels Using a One-Pot Reaction Scheme; An Efficient Reachability Analysis Algorithm.

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NASA Tech Briefs, June 2009

Topics covered include: Device for Measuring Low Flow Speed in a Duct, Measuring Thermal Conductivity of a Small Insulation Sample, Alignment Jig for the Precise Measurement of THz Radiation, Autoignition Chamber for Remote Testing of Pyrotechnic Devices, Microwave Power Combiners for Signals of Arbitrary Amplitude, Synthetic Foveal Imaging Technology, Airborne Antenna System for Minimum-Cycle-Slip GPS Reception, Improved Starting Materials for Back-Illuminated Imagers, Multi-Modulator for Bandwidth-Efficient Communication, Some Improvements in Utilization of Flash Memory Devices, GPS/MEMS IMU/Microprocessor Board for Navigation, T/R Multi-Chip MMIC Modules for 150 GHz, Pneumatic Haptic Interfaces, Device Acquires and Retains Rock or Ice Samples, Cryogenic Feedthrough Test Rig, Improved Assembly for Gas Shielding During Welding or Brazing, Two-Step Plasma Process for Cleaning Indium Bonding Bumps, Tool for Crimping Flexible Circuit Leads, Yb14MnSb11 as a High-Efficiency Thermoelectric Material, Polyimide-Foam/Aerogel Composites for Thermal Insulation, Converting CSV Files to RKSML Files, Service Management Database for DSN Equipment, Chemochromic Hydrogen Leak Detectors, Compatibility of Segments of Thermoelectric Generators, Complementary Barrier Infrared Detector, JPL Greenland Moulin Exploration Probe, Ultra-Lightweight Self-Deployable Nanocomposite Structure for Habitat Applications, and Room-Temperature Ionic Liquids for Electrochemical Capacitors.

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Pattern-Recognition Processor Using Holographic Photopolymer

proposed joint-transform optical correlator (JTOC) would be capable of operating as a real-time pattern-recognition processor. The key correlation-filter reading/writing medium of this JTOC would be an updateable holographic photopolymer. The high-resolution, high-speed characteristics of this photopolymer would enable pattern-recognition processing to occur at a speed three orders of magnitude greater than that of state-of-the-art digital pattern-recognition processors. There are many potential applications in biometric personal identification (e.g., using images of fingerprints and faces) and nondestructive industrial inspection. In order to appreciate the advantages of the proposed JTOC, it is necessary to understand the principle of operation of a conventional JTOC. In a conventional JTOC (shown in the upper part of the figure), a collimated laser beam passes through two side-by-side spatial light modulators (SLMs). One SLM displays a real-time input image to be recognized. The other SLM displays a reference image from a digital memory. A Fourier-transform lens is placed at its focal distance from the SLM plane, and a charge-coupled device (CCD) image detector is placed at the back focal plane of the lens for use as a square-law recorder. Processing takes place in two stages. In the first stage, the CCD records the interference pattern between the Fourier transforms of the input and reference images, and the pattern is then digitized and saved in a buffer memory. In the second stage, the reference SLM is turned off and the interference pattern is fed back to the input SLM. The interference pattern thus becomes Fourier-transformed, yielding at the CCD an image representing the joint-transform correlation between the input and reference images. This image contains a sharp correlation peak when the input and reference images are matched. The drawbacks of a conventional JTOC are the following: The CCD has low spatial resolution and is not an ideal square-law detector for the purpose of holographic recording of interference fringes. A typical state-of-the-art CCD has a pixel-pitch limited resolution of about 100 lines/mm. In contrast, the holographic photopolymer to be used in the proposed JTOC offers a resolution > 2,000 lines/mm. In addition to being disadvantageous in itself, the low resolution of the CCD causes overlap of a DC term and the desired correlation term in the output image. This overlap severely limits the correlation signal-to-noise ratio. The two-stage nature of the process limits the achievable throughput rate. A further limit is imposed by the low frame rate (typical video rates) of low- and medium-cost commercial CCDs.

Chao, Tien-Hsin↗

Adult Rhabdomyosarcoma Survival Improved With Treatment on Multimodality Protocols

Purpose: Rhabdomyosarcoma (RMS) is a pediatric sarcoma rarely occurring in adults. For unknown reasons, adults with RMS have worse outcomes than do children. Methods and Materials: We analyzed data from all patients who presented to Memorial Sloan-Kettering Cancer Center between 1990 and 2011 with RMS diagnosed at age 16 or older. One hundred forty-eight patients met the study criteria. Ten were excluded for lack of adequate data. Results: The median age was 28 years. The histologic diagnoses were as follows: embryonal 54%, alveolar 33%, pleomorphic 12%, and not otherwise specified 2%. The tumor site was unfavorable in 67% of patients. Thirty-three patients (24%) were at low risk, 61 (44%) at intermediate risk, and 44 (32%) at high risk. Forty-six percent were treated on or according to a prospective RMS protocol. The 5-year rate of overall survival (OS) was 45% for patients with nonmetastatic disease. The failure rates at 5 years for patients with nonmetastatic disease were 34% for local failure and 42% for distant failure. Among patients with nonmetastatic disease (n=94), significant factors associated with OS were histologic diagnosis, site, risk group, age, and protocol treatment. On multivariate analysis, risk group and protocol treatment were significant after adjustment for age. The 5-year OS was 54% for protocol patients versus 36% for nonprotocol patients. Conclusions: Survival in adult patients with nonmetastatic disease was significantly improved for those treated on RMS protocols, most of which are now open to adults.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Scalable focused ion beam creation of nearly lifetime-limited single quantum emitters in diamond nanostructures

The controlled creation of defect centre—nanocavity systems is one of the outstanding challenges for efficiently interfacing spin quantum memories with photons for photon-based entanglement operations in a quantum network. Here we demonstrate direct, maskless creation of atom-like single silicon vacancy (SiV) centres in diamond nanostructures via focused ion beam implantation with ~32 nm lateral precision and <50 nm positioning accuracy relative to a nanocavity. We determine the Si+ ion to SiV centre conversion yield to be ~2.5% and observe a 10-fold conversion yield increase by additional electron irradiation. Low-temperature spectroscopy reveals inhomogeneously broadened ensemble emission linewidths of ~51 GHz and close to lifetime-limited single-emitter transition linewidths down to 126±13 MHz corresponding to ~1.4 times the natural linewidth. Furthermore, this method for the targeted generation of nearly transform-limited quantum emitters should facilitate the development of scalable solid-state quantum information processors.

36 MATERIALS SCIENCE↗

Ambipolar nonvolatile memory based on a quantum-dot transistor with a nanoscale floating gate

Using only solution processing methods, we developed ambipolar quantum-dot (QD) transistor floating-gate memory (FGM) that uses Au nanoparticles as a floating gate. Because of the bipolarity of the active channel of PbSe QDs, the memory could easily trap holes or electrons in the floating gate by programming/erasing (P/E) operations, which could shift the threshold voltage both up and down. As a result, the memory exhibited good programmable memory characteristics: a large memory window (ΔV{sub th} ∼ 15 V) and a long retention time (>10{sup 5 }s). The magnitude of ΔV{sub th} depended on both P/E voltages and the bias voltage (V{sub DS}): ΔV{sub th} was a cubic function to V{sub P/E} and linearly depended on V{sub DS}. Therefore, this FGM based on a QD transistor is a promising alternative to its inorganic counterparts owing to its advantages of bipolarity, high mobility, low cost, and large-area production.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Epitaxial growth of high quality SrFeO 3 films on (001) oriented (LaAlO 3 ) 0.3 (Sr 2 TaAlO 6 ) 0.7

Growth of strontium ferrite SrFeO 3 films with stoichiometry of (1:1:3) is challenging as the unstable Fe 4+ oxidation state favors the formation of O vacancies. Here, we report layer by layer growth of SrFeO 3 on (001) oriented (LaAlO 3 ) 0.3 (Sr 2 TaAlO 6 ) 0.7 using ozone assisted molecular beam epitaxy. Upon cooling from room temperature, the film’s resistivity decreased from 750 μΩ cm to 150 μΩ cm, as low as the best single crystals, with two identifiable transition points near 110 K and 60 K in resistivity measurements, being hysteretic between cooling and warming through the 60 K transition. During various annealing steps, the low temperature resistivity changes by orders of magnitude, accompanied by an increase in the c-axis lattice parameter. The hysteresis near 60 K persists for a wide range of annealing conditions. We have identified conditions under which changes due to annealing can be reversed. Here, we attribute changes in resistivity and out of plane lattice parameter to the reversible movement of oxygen ions in the lattice. SrFeO 3 may be a promising material for resistive memory applications based upon the control of oxygen vacancies.

36 MATERIALS SCIENCE↗