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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Payload Performance of TDRS KL and Future Services

NASA has accepted two of the 3nd generation Tracking and Data Relay Satellites, TDRS K, L, and M, designed and built by Boeing Defense, Space Security (DSS). TDRS K, L, and M provide S-band Multiple Access (MA) service and S-band, Ku-band and Ka-band Single Access (SA) services to near Earth orbiting satellites. The TDRS KLM satellites offer improved services relative to the 1st generation TDRS spacecraft, such as: an enhanced MA service featuring increased EIRPs and GT; and Ka-band SA capability which provides a 225 and 650 MHz return service (customer-to-TDRS direction) bandwidth and a 50 MHz forward service (TDRS-to-customer direction) bandwidth. MA services are provided through a 15 element forward phased array that forms up to two beams with onboard active beamforming and a 32 element return phased array supported by ground-based beamforming. SA services are provided through two 4.6m tri-band reflector antennas which support program track pointing and autotrack pointing. Prior to NASAs acceptance of the satellites, payload on-orbit testing was performed on each satellite to determine on-orbit compliance with design requirements. Performance parameters evaluated include: EIRP, GT, antenna gain patterns, SA antenna autotrack performance, and radiometric tracking performance. On-orbit antenna calibration and pointing optimization was also performed on the MA and SA antennas including 24 hour duration tests to characterize and calibrate out diurnal effects. Bit-Error-Rate (BER) tests were performed to evaluate the end-to-end link BER performance of service through a TDRS K and L spacecraft. The TDRS M is planned to be launched in August 2017. This paper summarizes the results of the TDRS KL communications payload on-orbit performance verification and end-to-end service characterization and compares the results with the performance of the 2nd generation TDRS J. The paper also provides a high-level overview of an optical communications application that will augment the data rates supported by the Space Network.

Laser↗
NASA NTRS2018

Dynamic Shared Computing Resources for Multi-Robot Mars Exploration

The NASA roadmap for 2020 and beyond includes several key technologies which will have a game-changing impact on planetary exploration. The first of these is High Performance Spaceflight Computing (HPSC), which will provide orders of magnitude increases in processing power for next-generation rovers and orbiters (Doyle et al. 2013). The second is Delay Tolerant Networking, which overlays the Deep Space Network, providing internet-like abstractions and store-forward to route data through intermittent delays in connectivity. The third is a trend toward small, co-dependent robots included in flagship missions (MarCO, PUFFER, and Mars Heli). Taken together, these imply an increasing amount of communication and computing heterogeneity on Mars in coming decades. Motivated by these technological trends, we study the concept of Mars on-site shared analysis, information, and communication (MOSAIC) for Mars exploration. The key algorithmic problem associated with MOSAIC networks is simultaneous scheduling of computation, communication, and caching of data, which we illustrate using the three scenarios. We present models, preliminary solutions, and simulation results for two scenarios, showing how mission efficiency relates to communication bandwidth, processing power, geography of the environment, and optimal scheduling of computation, communication, and data caching. The third scenario illustrates future directions of this work.

Chien, Steve↗
DOE OSTI2024

HGQ: High Granularity Quantization for Real-time Neural Networks on FPGAs

Neural networks with sub-microsecond inference latency are required by many critical applications. Targeting such applications deployed on FPGAs, we present High Granularity Quantization (HGQ), a quantization-aware training framework that optimizes parameter bit-widths through gradient descent. Unlike conventional methods, HGQ determines the optimal bit-width for each parameter independently, making it suitable for hardware platforms supporting heterogeneous arbitrary precision arithmetic. In our experiments, HGQ shows superior performance compared to existing network compression methods, achieving orders of magnitude reduction in resource consumption and latency while maintaining the accuracy on several benchmark tasks. These improvements enable the deployment of complex models previously infeasible due to resource or latency constraints. HGQ is open-source and is used for developing next-generation trigger systems at the CERN ATLAS and CMS experiments for particle physics, enabling the use of advanced machine learning models for real-time data selection with sub-microsecond latency.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Reinforcement learning for real-time process control in high-temperature superconductor manufacturing

With high efficiency and low energy loss, high-temperature superconductors (HTS) have demonstrated their profound applications in various fields, such as medical imaging, transportation, accelerators, microwave devices, and power systems. The high-field applications of HTS tapes have raised the demand for producing cost-effective tapes with long lengths in superconductor manufacturing. However, achieving the uniform and enhanced performance of a long HTS tape is challenging due to the unstable growth conditions in the manufacturing process. Although it is confirmed that the process parameters during the advanced metal organic chemical vapor deposition (A-MOCVD) process influence the uniformity of the produced HTS tapes, the high-dimensional process parameter signals and their complicated interactions make it difficult to develop an effective control policy. In this paper, we propose a local measure for the uniformity of HTS tapes to provide instant feedback for our control policy. Then, we model the manufacturing of HTS tapes as a Markov decision process (MDP) with continuous state and action spaces to assess the instant reward in real time in our feedback control model. As our MDP involves continuous and high-dimensional state and action spaces, a neural fitted Q-iteration (NFQ) algorithm is adopted to solve the MDP with artificial neural network (ANN) function approximation. The collinearity of process parameters can restrict our capability of adjusting the process parameters, which is addressed by the principal component analysis (PCA) in our method. The control policy adjusts the PCA of process parameters using the NFQ algorithm. In conclusion, based on our case studies on real A-MOCVD dataset, the obtained control policy increases the average uniformity of tapes by 5.6% and performs especially well on sample HTS tapes with a low uniformity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

High- Q Nanophotonic Resonators on Diamond Membranes using Templated Atomic Layer Deposition of TiO 2

Integrating solid-state quantum emitters with nanophotonic resonators is essential for efficient spin-photon interfacing and optical networking applications. While diamond color centers have proven to be excellent candidates for emerging quantum technologies, their integration with optical resonators remains challenging. Conventional approaches based on etching resonators into diamond often negatively impact color center performance and offer low device yield. In this work, we developed an integrated photonics platform based on templated atomic layer deposition of TiO 2 on diamond membranes. Our fabrication method yields high-performance nanophotonic devices while avoiding etching wavelength-scale features into diamond. Moreover, this technique generates highly reproducible optical resonances and can be iterated on individual diamond samples, a unique processing advantage. Our approach is suitable for a broad range of both wavelengths and substrates and can enable high-cooperativity interfacing between cavity photons and coherent defects in diamond or silicon carbide, rare earth ions, or other material systems.

42 ENGINEERING↗
DOE OSTI2024

Precision spectroscopy of fast, hot, exotic isotopes using machine-learning-assisted event-by-event Doppler correction

We propose an experimental scheme for performing sensitive, high-precision laser spectroscopy studies on fast exotic isotopes. By inducing a stepwise resonant ionization of the atoms traveling inside an electric field and subsequently detecting the ion and the corresponding electron, time-, and position-sensitive measurements of the resulting particles can be performed. Using a mixture density network, we can leverage this information to predict the initial energy of individual atoms and thus apply a Doppler correction of the observed transition frequencies on an event-by-event basis. We conduct numerical simulations of the proposed experimental scheme and show that kHz-level uncertainties can be achieved for ion beams produced at extreme temperatures ( > 10 8 K), with energy spreads as large as 10 keV and nonuniform velocity distributions. The ability to perform in-flight spectroscopy, directly on highly energetic beams, offers unique opportunities to study short-lived isotopes with lifetimes in the millisecond range and below, produced in low quantities, in hot and highly contaminated environments, without the need for cooling techniques. Such species are of marked interest for nuclear structure, astrophysics, and new physics searches. Published by the American Physical Society 2024

Udrescu, S. M. (ORCID:000000021989576X)↗
NASA NTRS1991

Thermal characterization and toughness of ethynyl containing blends

As part of an effort to develop high performance structural resins with an attractive combination of properties for aerospace applications, a series of ethynyl-terminated polysulfones of different molecular weights were prepared and blended with a low molecular weight ethynyl-terminated coreactant. Upon heating above 200 C, these ethynyl containing materials react to form a chain extended and crosslinked network structure. This reaction renders the materials insoluble in common solvents, but also reduces the toughness as compared to high molecular weight linear polysulfones. The thermal characterization of these blends and the toughness of the resulting cured materials are discussed.

Jensen, Brian J.↗
NASA NTRS2025

Localization of Ad-Hoc Lunar Constellations in Communication Failure Modes for Distributed Spacecraft Autonomy

As Lunar missions increase in complexity, inspired by NASA’s Artemis Program, they will require reliable and sufficient Position, Navigation, and Timing (PNT) capability to support the upcoming Lunar users. The navigation service should also be compatible with the smaller platforms, like CubeSats, being sent by the public and private sectors. A non-dedicated, ad-hoc Lunar navigation constellation can provide PNT services on-demand using the non-dedicated swarm assets. Swarm members cooperatively and autonomously localize themselves with minimal interaction from Earth, freeing up valuable bandwidth and ground segment resources. The autonomous localization of Lunar constellations utilizes neighbor two-way intersatellite link (ISL) measurements in a distributed extended Kalman filter (DEKF) system to minimize operating costs. Because the decentralized Lunar PNT system relies on relay communication amongst the agents, network failures or loss of assets among ad-hoc Lunar constellations may impact localization performance. This study presents an evaluation of localization performance under increasing levels of network degradation. A simulation of an ad-hoc Lunar PNT swarm is augmented to include system faults and the impacts of intermittent and permanent failures on localization performance are evaluated. We investigate three potential causes of network degradation: single spacecraft loss, multiple spacecraft loss, and antenna failure. The numerical assessments from the simulation show that the LPNT system under study, based on an autonomous decentralized concept of operation, is highly robust and resilient to communication failures. Minor faults, such as single spacecraft loss, solar interference, technical malfunctions, message delays, and antenna outages, have minimal impact on state estimation, with only a 4.47% and 3.75% degradation in median position error for assets and a representative ground user, respectively, compared to an ideal communication scenario. However, major faults, such as hardware failures or meteor strikes leading to the loss of multiple spacecrafts, are more concerning. The permanent loss of three spacecraft results in a more severe performance degradation, with median position error increasing by 23.3% for assets and 11.7% for a representative ground user, despite the Lunar PNT system remaining functional.

Yeji Kim↗
DOE OSTI2018

A Method to Identify Seawater Pycnocline Boundaries Based on LSTM Neural Network and Its Application in Underwater Glider Missions

Underwater glider is a kind of buoyancy driven underwater vehicle; it has the features of low operating noise, long endurance and flexible maneuverability. During the glider long-time navigation, there is a high probability to encounter the pycnocline, which has a great influence on underwater glider’s navigation as well as application. In this work, an operation flow of glider hovering movement in the pycnocline was discussed in detail in order to improve the observation performance of glider. We firstly developed an LSTM (Long Short-Term Memory) neural network to identify the pycnocline boundaries. Then the accurate buoyancy adjustment of glider hovering movement was calculated based on the obtained pycnocline information. Finally a hardware in the loop simulation was implemented to verify the feasibility of the method, and the simulation results showed a reasonable performance of glider hovering in the pycnocline.

Song, Dalei↗
DOE OSTI2021

Using Neural Network Force Fields to Ascertain the Quality of Ab Initio Simulations of Liquid Water

Accurately simulating the properties of bulk water, despite the apparent simplicity of the molecule, is still a challenge. In order to fully understand and reproduce its complex phase diagram, it is necessary to perform simulations at the ab initio level, including quantum mechanical effects both for electrons and nuclei. This comes at a high computational cost, given that the structural and dynamical properties tend to require long timescales and large simulation cells. In this work, we evaluate the errors that density functional theory (DFT)-based simulations routinely incur into due time- and size-scale limitations. These errors are evaluated using neural-network-trained force fields that are accurate at the level of DFT methods. We compare different exchange and correlation potentials for properties of bulk water that require large timescales. Here we show that structural properties are less dependent on the system size and that dynamical properties such as the diffusion coefficient have a strong dependence on the simulation size and timescale. Our results facilitate comparisons of DFT-based simulation results with experiments and offer a path to discriminate between model and convergence errors in these simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1990

Extensibility and limitations of FDDI

Recently two standards for Metropolitan Area Networks (MANs), Fiber Distributed Data Interface (FDDI) and Distributed Queue Dual Bus (DQDB), have emerged as the primary competitors for the MAN arena. Great interest exists in building higher speed networks which support large numbers of node and greater distance, and it is not clear what types of protocols are needed for this type of environment. There is some question as to whether or not these MAN standards can be extended to such environments. The extensibility of FDDI to the Gbps range and a long distance environment is investigated. Specification parameters which affect performance are shown and a measure is provided for predicting utilization of FDDI. A comparison of FDDI at 100 Mbps and 1 Gbps is presented. Some specific problems with FDDI are addressed and modifications which improve the viability of FDDI in such high speed networks are investigated.

Game, David↗
DOE OSTI2015

Towards a map of the Populus biomass protein-protein interaction network

Biofuels can be produced from a variety of plant feedstocks. The value of a particular feedstock for biofuels production depends in part on the degree of difficulty associated with the extraction of fermentable sugars from the plant biomass. The wood of trees is potentially a rich source fermentable sugars. However, the sugars in wood exist in a tightly cross-linked matrix of cellulose, hemicellulose, and lignin, making them largely recalcitrant to release and fermentation for biofuels production. Before breeders and genetic engineers can effectively develop plants with reduced recalcitrance to fermentation, it is necessary to gain a better understanding of the fundamental biology of the mechanisms responsible for wood formation. Regulatory, structural, and enzymatic proteins are required for the complicated process of wood formation. To function properly, proteins must interact with other proteins. Yet, very few of the protein-protein interactions necessary for wood formation are known. The main objectives of this project were to 1) identify new protein-protein interactions relevant to wood formation, and 2) perform in-depth characterizations of selected protein-protein interactions. To identify relevant protein-protein interactions, we cloned a set of approximately 400 genes that were highly expressed in the wood-forming tissue (known as secondary xylem) of poplar (Populus trichocarpa). We tested whether the proteins encoded by these biomass genes interacted with each other in a binary matrix design using the yeast two-hybrid (Y2H) method for protein-protein interaction discovery. We also tested a subset of the 400 biomass proteins for interactions with all proteins present in wood-forming tissue of poplar in a biomass library screen design using Y2H. Together, these two Y2H screens yielded over 270 interactions involving over 75 biomass proteins. For the second main objective we selected several interacting pairs or groups of interacting proteins for in-depth characterizations. Characterizations involved both in vivo and in vitro independent methods to confirm protein-protein interactions and the evaluation of novel phenotypes resulting from creation of transgenic poplar and Arabidopsis plants engineered for increased or decreased expression of the selected genes. Transgenic poplar trees were studied in growth chamber, greenhouse, and two separate replicated field trials involving over 25 distinct wood-associated proteins. In-depth characterizations yielding positive results include the following. First, a NAC domain transcription factor (NAC154) that is a promoter of stress response and dormancy in trees was discovered. Increasing expression of NAC154 caused stunted growth and premature senescence, while decreasing expression led to both delayed bud and leaf expansion in spring and delayed leaf drop (i.e., prolonged leaf retention) in fall. Second, we discovered and characterized a new connection between a negative regulator of wood formation, the NAC domain transcription factor XND1, and an important regulator of cell division and cell differentiation, RBR. Third, we identified a new network of interacting wood-associated transcription factors belonging to the MYB and HD families. One of the HD family proteins, WOX13, was used to prepare transgenic poplar for high-level expression, resulting in significantly increased lateral branch growth. Finally, we modeled and performed in vitro analyses of the insect protein rubber resilin and we prepared transgenic Arabidopsis plants for expression of resilin to test the feasibility of using resilin to modify lignin cross-linking in wood and reduce recalcitrance and improve yield of fermentable sugars for biofuels production. Analysis of these and additional transgenics created with this support is continuing.

09 BIOMASS FUELS↗
DOE OSTI2017

A lightweight network anomaly detection technique

While the network anomaly detection is essential in network operations and management, it becomes further challenging to perform the first line of detection against the exponentially increasing volume of network traffic. In this paper, we develop a technique for the first line of online anomaly detection with two important considerations: (i) availability of traffic attributes during the monitoring time, and (ii) computational scalability for streaming data. The presented learning technique is lightweight and highly scalable with the beauty of approximation based on the grid partitioning of the given dimensional space. With the public traffic traces of KDD Cup 1999 and NSL-KDD, we show that our technique yields 98.5% and 83% of detection accuracy, respectively, only with a couple of readily available traffic attributes that can be obtained without the help of post-processing. Finally, the results are at least comparable with the classical learning methods including decision tree and random forest, with approximately two orders of magnitude faster learning performance.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Advances in Autonomous Communications and Operations: Tes-N Series

Advances in nanosat subsystems over the past decade have taken the CubeSat standard from a communication-limited educational tool to a powerful platform enabling space research. The potential for autonomous operations may greatly increase the capability of downlinking even larger data sets. This is enabled through miniaturization of software-defined radio/cognitive communication solutions and a rapidly growing number of ground stations and satellite network crosslinks. The TechEdSat-n orbital flight series is currently demonstrating experiments using cognitive communication concepts including User Initiated Service (UIS) and High-rate Delay Tolerant Networks (HDTN), which show a significant step toward improved capability. At the core of this is the use of the Iridium L-band Short Burst Data (SBD) modems, pioneered by TES-n for space applications. SBD enables unique rapid command, control, and scheduling to initiate the UIS and HDTN protocols. This occurs by performing GPS-assisted on-orbit ephemeris determination, enabling negotiation with high bandwidth ground assets to repeatedly downlink over a specific commercial or government-owned ground station. The technique is RF band-agnostic and may be extended to higher bandwidth stations and SDRs. This may also include free-space optical communication, through both laser and omnidirectional LEDs, which can provide an attractive protocol for downlinking very large datasets over far fewer ground stations. In addition, this may be extended to lunar applications for such future concepts as LunaNet, whereby scheduling and cognitive technologies can assist in greatly improving Earth downlink capabilities with ground stations which will see greater competition for usage. Lastly, the NASA Communication Service Program (CSP), intended to eventually replace the NASA Tracking and Data Relay Satellite System (TDRSS) will also demonstrate the feasibility of commercially-provided satellite communication capabilities. All of these combined advances, including large advances in on-board computation on small platforms, will result in more remarkable data processing capability – yielding even more as of yet unknown discoveries.

Autonomy↗
DOE OSTI2015

Constraint-Based Routing Models for the Transport of Radioactive Materials

The Department of Energy (DOE) has a historic programmatic interest in the safe and secure routing, tracking, and transportation risk analysis of radiological materials in the United States. In order to address these program goals, DOE has funded the development of several tools and related systems designed to provide insight to planners and other professionals handling radioactive materials shipments. These systems include the WebTRAGIS (Transportation Routing Analysis Geographic Information System) platform. WebTRAGIS is a browser-based routing application developed at Oak Ridge National Laboratory (ORNL) focused primarily on the safe transport of spent nuclear fuel from US nuclear reactors via railway, highway, or waterway. It is also used for the transport planning of low-level radiological waste to depositories such as the Waste Isolation Pilot Plant (WIPP) facility. One particular feature of WebTRAGIS is its coupling with high-resolution population data from ORNL s LandScan project. This allows users to obtain highly accurate population count and density information for use in route planning and risk analysis. To perform the routing and risk analysis WebTRAGIS incorporates a basic routing model methodology, with the additional application of various constraints designed to mimic US Department of Transportation (DOT), DOE, and Nuclear Regulatory Commission (NRC) regulations. Aside from the routing models available in WebTRAGIS, the system relies on detailed or specialized modal networks for the route solutions. These include a highly detailed network model of the US railroad system, the inland and coastal waterways, and a specialized highway network that focuses on the US interstate system and the designated hazardous materials and Highway Route Controlled Quantity (HRCQ) -designated roadways. The route constraints in WebTRAGIS rely upon a series of attributes assigned to the various components of the different modal networks. Routes are determined via a constrained shortest-path Dijkstra algorithm that has an assigned impedance factor. The route constraints modify the various impedance weights to bias or prefer particular network characteristics as desired by the user. Both the basic route model and the constrained impedance function calculations are determined by a series of network characteristics and shipment types. The study examines solutions under various constraints modeled by WebTRAGIS including possible routes from select shut-down reactor sites in the US to specific locations in the US. For purposes of illustration, the designated destinations are Oak Ridge National Laboratory in Tennessee and the Savannah River Site in South Carolina. To the degree that routes express sameness or variety under constraints serves to illustrate either a) the determinism of particular transport modes by either configuration or regulatory compliance, and/or b) the variety of constrained routes that are regulation compliant but may not be operationally feasible.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2016

Determination of Ceres Physical Parameters Using Radiometric and Optical Data

The Dawn spacecraft was launched on September 27th, 2007. Its mission is to rendezvous with and observe the two largest bodies in the main asteroid belt, Vesta and Ceres. It has completed over a year’s worth of direct observations of Vesta from early 2011 through late 2012. In the spring of 2015, the Dawn spacecraft entered orbit around the asteroid Ceres for the start of what is expected to be more than a year of science operations. The science data collected from this encounter consist of infrared (IR) images and spectra, visible images through a number of color filters, gamma ray detections and measurements of the Ceres gravity field. These data will be collected during several science phases: an Approach phase (1500000-4860 km from Ceres), a Survey orbit (4860 km radius), a High Altitude Mapping Orbit (HAMO) (1940 km radius) and a Low Altitude Mapping Orbit (LAMO) (855 km radius). The Approach phase included three Rotational Characterization (RC) opportunities. Designing each science orbit and successfully transferring into that orbit requires a sufficiently accurate estimate of Ceres physical parameters (body fixed frame, GM and harmonics). This paper focuses on work performed to estimate Ceres physical parameters using Deep Space Network (DSN) radiometric tracking data and optical measurements derived from science camera imagery. This paper describes planning for the data acquisition, as well as processing techniques and methodology. The trajectories predicted by the gravity field estimations are also compared with the actual as-flown trajectories. Observations of the gravity at high altitudes are found to be sufficient to design precision orbits at lower altitudes. Follow-up analysis after successfully reaching LAMO is included, as is a discussion of lessons learned.

Kennedy, Brian M.↗
DOE OSTI2022

A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks

Physics-informed neural networks (PINNs) have shown to be effective tools for solving both forward and inverse problems of partial differential equations (PDEs). PINNs embed the PDEs into the loss of the neural network using automatic differentiation, and this PDE loss is evaluated at a set of scattered spatio-temporal points (called residual points). The location and distribution of these residual points are highly important to the performance of PINNs. However, in the existing studies on PINNs, only a few simple residual point sampling methods have mainly been used. Here, we present a comprehensive study of two categories of sampling for PINNs: non-adaptive uniform sampling and adaptive nonuniform sampling. We consider six uniform sampling methods, including (1) equispaced uniform grid, (2) uniformly random sampling, (3) Latin hypercube sampling, (4) Halton sequence, (5) Hammersley sequence, and (6) Sobol sequence. We also consider a resampling strategy for uniform sampling. To improve the sampling efficiency and the accuracy of PINNs, we propose two new residual-based adaptive sampling methods: residual-based adaptive distribution (RAD) and residual-based adaptive refinement with distribution (RAR-D), which dynamically improve the distribution of residual points based on the PDE residuals during training. Hence, we have considered a total of 10 different sampling methods, including six non-adaptive uniform sampling, uniform sampling with resampling, two proposed adaptive sampling, and an existing adaptive sampling. We extensively tested the performance of these sampling methods for four forward problems and two inverse problems in many setups. Our numerical results presented in this study are summarized from more than 6000 simulations of PINNs. Here, we show that the proposed adaptive sampling methods of RAD and RAR-D significantly improve the accuracy of PINNs with fewer residual points for both forward and inverse problems. Furthermore, the results obtained in this study can also be used as a practical guideline in choosing sampling methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Al{sub 2}O{sub 3}/GeO{sub x} gate stack on germanium substrate fabricated by in situ cycling ozone oxidation method

Al{sub 2}O{sub 3}/GeO{sub x}/Ge gate stack fabricated by an in situ cycling ozone oxidation (COO) method in the atomic layer deposition (ALD) system at low temperature is systematically investigated. Excellent electrical characteristics such as minimum interface trap density as low as 1.9 × 10{sup 11 }cm{sup −2 }eV{sup −1} have been obtained by COO treatment. The impact of COO treatment against the band alignment of Al{sub 2}O{sub 3} with respect to Ge is studied by x-ray photoelectron spectroscopy (XPS) and spectroscopic ellipsometry (SE). Based on both XPS and SE studies, the origin of gate leakage in the ALD-Al{sub 2}O{sub 3} is attributed to the sub-gap states, which may be correlated to the OH-related groups in Al{sub 2}O{sub 3} network. It is demonstrated that the COO method is effective in repairing the OH-related defects in high-k dielectrics as well as forming superior high-k/Ge interface for high performance Ge MOS devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗