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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Influence of growth temperature and temperature ramps on deep level defect incorporation in m-plane GaN

The dependence of deep level defect incorporation in m-plane GaN films grown by metal-organic chemical vapor deposition on bulk m-plane GaN substrates as a function of growth temperature (T{sub g}) and T{sub g} ramping method was investigated using deep level optical spectroscopy. Understanding the influence of T{sub g} on GaN deep level incorporation is important for InGaN/GaN multi-quantum well (MQW) light emitting diodes (LEDs) and laser diodes (LDs) because GaN quantum barrier (QB) layers are grown much colder than thin film GaN to accommodate InGaN QW growth. Deep level spectra of low T{sub g} (800 °C) GaN films grown under QB conditions were compared to deep level spectra of high T{sub g} (1150 °C) GaN. Reducing T{sub g}, increased the defect density significantly (>50×) through introduction of emergent deep level defects at 2.09 eV and 2.9 eV below the conduction band minimum. However, optimizing growth conditions during the temperature ramp when transitioning from high to low T{sub g} substantially reduced the density of these emergent deep levels by approximately 40%. The results suggest that it is important to consider the potential for non-radiative recombination in QBs of LED or LD active regions, and tailoring the transition from high T{sub g} GaN growth to active layer growth can mitigate such non-radiative channels.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Defect properties of Sb- and Bi-doped CuInSe{sub 2}: The effect of the deep lone-pair s states

Bi or Sb doping has been used to make better material properties of polycrystalline Cu{sub 2}(In,Ga)Se{sub 2} as solar cell absorbers, including the experimentally observed improved electrical properties. However, the mechanism is still not clear. Using first-principles method, we investigate the stability and electronic structure of Bi- and Sb-related defects in CuInSe{sub 2} and study their effects on the doping efficiency. Contrary to previous thinking that Bi or Sb substituted on the anion site, we find that under anion-rich conditions, the impurities can substitute on cation sites and are isovalent to In because of the formation of the impurity lone pair s states. When the impurities substitute for Cu, the defects act as shallow double donors and help remove the deep In{sub Cu} level, thus resulting in the improved carrier life time. On the other hand, under anion-poor conditions, impurities at the Se site create amphoteric deep levels that are detrimental to the device performance.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Deep Point Cloud Building Envelope Segmentation (DeeP-CuBES) using Deep Learning

Building Information Modeling (BIM) plays an important role in building design and construction, particularly for achieving energy-efficient retrofits. Building envelope retrofits using panelized prefabricated system, such as those popularized by the Energiesprong program, need accurate as-built dimensions of facade features (windows, doors, etc.) to achieve the desired thermal and air tightness. Traditionally, building surveying is done manually, resulting in a time-consuming and labor-intensive process. Recently, 3D point clouds from terrestrial LiDAR have been used to automate the generation of as-built dimensions of existing buildings. However, automated BIM using LiDAR relies on solving the point cloud semantic segmentation (PCSS) problem. In this work, we propose a robust pipeline for solving the PCSS problem using deep neural networks, focusing on overcoming challenges posed by imbalanced datasets and complex architectural features. We introduce the first high-density, labeled, and validated building envelope point cloud dataset derived from multiple building scans, specifically curated to tackle challenges in facade-level segmentation. Results from the trained neural networks show that advanced attention-based architectures and incorporating radiometry (light intensity and RGB) features significantly boost segmentation accuracy for windows and doors.

Selvakumar, Balaji [ORNL]↗
DOE OSTI2015

Growth temperature dependence of Si doping efficiency and compensating deep level defect incorporation in Al{sub 0.7}Ga{sub 0.3}N

The growth temperature dependence of Si doping efficiency and deep level defect formation was investigated for n-type Al{sub 0.7}Ga{sub 0.3}N. It was observed that dopant compensation was greatly reduced with reduced growth temperature. Deep level optical spectroscopy and lighted capacitance-voltage were used to understand the role of acceptor-like deep level defects on doping efficiency. Deep level defects were observed at 2.34 eV, 3.56 eV, and 4.74 eV below the conduction band minimum. The latter two deep levels were identified as the major compensators because the reduction in their concentrations at reduced growth temperature correlated closely with the concomitant increase in free electron concentration. Possible mechanisms for the strong growth temperature dependence of deep level formation are considered, including thermodynamically driven compensating defect formation that can arise for a semiconductor with very large band gap energy, such as Al{sub 0.7}Ga{sub 0.3}N.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Parameterizing deep convection using the assumed probability density function method

Due to their coarse horizontal resolution, present-day climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization. The PDF parameterization predicts the PDF of subgrid variability of turbulence, clouds, and hydrometeors. That variability is interfaced to a prognostic microphysics scheme using a Monte Carlo sampling method.The PDF parameterization is used to simulate tropical deep convection, the transition from shallow to deep convection over land, and mid-latitude deep convection.These parameterized single-column simulations are compared with 3-D reference simulations. The agreement is satisfactory except when the convective forcing is weak. The same PDF parameterization is also used to simulate shallow cumulus and stratocumulus layers. The PDF method is sufficiently general to adequately simulate these five deep, shallow, and stratiform cloud cases with a single equation set. This raises hopes that it may be possible in the future, with further refinements at coarse time step and grid spacing, to parameterize all cloud types in a large-scale model in a unified way.

Storer, R. L.↗
DOE OSTI2026

Are Deep Energy Retrofits in Commercial Buildings Including Window Upgrades?

U.S. Commercial buildings account for about 20% of total U.S. energy consumption. Because the thermal performance of windows significantly affects building energy efficiency and HVAC system performance, best practice guidance often includes window and envelope improvements in conjunction with HVAC upgrades to optimize energy use and improve occupant comfort. It is an open question, however, regarding how often these best practices are implemented in the field. This paper aims to address that gap by conducting a literature review and a series of interviews with commercial building auditing and management professionals to explore the factors that drive window retrofits in commercial buildings. The paper explores a range of case studies from deep energy retrofits across the globe, comparing projects with and without window retrofits. The primary goals of this review are to: (1) provide data from real-world case studies illustrating the role of windows in deep energy renovations and HVAC upgrades, (2) conduct retrofit cost analyses for windows and high-performance HVAC systems and (3) offer insights into how window upgrade decisions are made and when they are implemented as part of deep energy retrofits. Most of the retrofit studies focused exclusively on high performance HVAC upgrades without considering how window upgrades might further enhance the overall energy efficiency of commercial buildings. Interviews with building industry experts shed light on the key factors influencing deep energy retrofit decisions and what factors tip the scales in favor of including window measures with more comprehensive retrofit projects.

Cort, Katherine↗
DOE OSTI2015

S-CANDELS: The Spitzer-cosmic assembly near-infrared deep extragalactic survey. Survey design, photometry, and deep IRAC source counts

The Spitzer-Cosmic Assembly Deep Near-infrared Extragalactic Legacy Survey (S-CANDELS; PI G.Fazio) is a Cycle 8 Exploration Program designed to detect galaxies at very high redshifts (z>5). To mitigate the effects of cosmic variance and also to take advantage of deep coextensive coverage in multiple bands by the Hubble Space Telescope (HST) Multi-cycle Treasury Program CANDELS, S-CANDELS was carried out within five widely separated extragalactic fields: the UKIDSS Ultra-deep Survey, the Extended Chandra Deep Field South, COSMOS, the HST Deep Field North, and the Extended Groth Strip. S-CANDELS builds upon the existing coverage of these fields from the Spitzer Extended Deep Survey (SEDS), a Cycle 6 Exploration Program, by increasing the integration time from SEDS’ 12 hr to a total of 50 hr but within a smaller area, 0.16 deg{sup 2}. The additional depth significantly increases the survey completeness at faint magnitudes. This paper describes the S-CANDELS survey design, processing, and publicly available data products. We present Infrared Array Camera (IRAC) dual-band 3.6+4.5 μm catalogs reaching to a depth of 26.5 AB mag. Deep IRAC counts for the roughly 135,000 galaxies detected by S-CANDELS are consistent with models based on known galaxy populations. The increase in depth beyond earlier Spitzer/IRAC surveys does not reveal a significant additional contribution from discrete sources to the diffuse Cosmic Infrared Background (CIB). Thus it remains true that only roughly half of the estimated CIB flux from COBE/DIRBE is resolved.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Hydrogeologic Lessons Learned from Deep Drilling Projects Applied to Deep Borehole Disposal of Radioactive Wastes - 16133

Hydrogeological results from the Kola SG-3, Gravberg-1, Cajon Pass, and KTB-VB and KTB-HB boreholes are applied to the US deep borehole disposal concept to assess whether old, saline, and reducing deep groundwater, in low bulk permeability crystalline basement rocks, could be found in a DOE proposed deep borehole field test. Each of the drilling projects faced characterization challenges, including obtaining sufficient information to characterize key parameters and their uncertainty, equipment limitations and failures, and obtaining samples that are representative of in situ conditions while maintaining sample integrity. Despite these characterization challenges, each project obtained sufficient data to directly measure or infer, for redox state, conditions at the 3 to 5 km (1.9 - 3.1 miles) target disposal depth of the US deep borehole disposal concept. The hydrogeologic data suggest that old, saline, and reducing deep groundwater could be found at a test site located in geologically stable crystalline basement. Although the DOE deep borehole testing program has not defined the magnitude of an acceptably low bulk permeability, bulk permeability results indicate that values used in current US deep borehole modeling efforts may be too low by an order of magnitude or more, as compared with in situ conditions. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

Advection, moistening, and shallow‐to‐deep convection transitions during the initiation and propagation of M adden‐ J ulian O scillation

Abstract Using observations from the 2011 AMIE/DYNAMO field campaign over the Indian Ocean and a high‐resolution regional model simulation, the processes that lead to the rapid shallow‐to‐deep convection transitions associated with the initiation and eastward propagation of the Madden‐Julian Oscillation (MJO) are examined. By tracking the evolution of the depth of several thousand individual model simulated precipitation features, the role of and the processes that control the observed midtropospheric moisture buildup ahead of the detection of deep convection are quantified at large and convection scales. The frequency of shallow‐to‐deep convection transitions is found to be sensitive to this midlevel moisture and large‐scale uplift. This uplift along with the decline of large‐scale drying by equator‐ward advection causes the moisture buildup leading to the initiation of the MJO. Convection scale moisture variability and uplift, and large‐scale zonal advection play secondary roles.

Hagos, Samson↗
DOE OSTI2014

Disproportionation of (Mg,Fe)SiO 3 perovskite in Earth's deep lower mantle

The mineralogical constitution of the Earth's mantle dictates the geophysical and geochemical properties of this region. Previous models of a perovskite-dominant lower mantle have been built on the assumption that the entire lower mantle down to the top of the D" layer contains ferromagnesian silicate [(Mg,Fe)SiO 3 ] with nominally 10 mole percent Fe. On the basis of experiments in laser-heated diamond anvil cells, at pressures of 95 to 101 gigapascals and temperatures of 2200 to 2400 kelvin, we found that such perovskite is unstable; it loses its Fe and disproportionates to a nearly Fe-free MgSiO 3 perovskite phase and an Fe-rich phase with a hexagonal structure. This observation has implications for enigmatic seismic features beyond ~2000 kilometers depth and suggests that the lower mantle may contain previously unidentified major phases.

Zhang, L.↗