Search NASA⌕ Search

SEARCH · Search NASA

Results for “Substrate Phonons”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

26 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Fabrication of Feedhorn-Coupled Transition Edge Sensor Arrays for Measurement of the Cosmic Microwave Background Polarization

Characterization of the minute cosmic microwave background (CMB) polarization signature requires multi-frequency high-throughput precision instrument systems. We have previously described the detector fabrication of a 40 gigahertz focal plane and now describe the fabrication of a 37-element dual-polarization detector module for measurement of the CMB at 90 gigahertz. The 72-TES (Transition Edge Sensor)-based bolometers in each module are coupled to a niobium-based planar orthomode transducer with integrated band defining filters implemented in microstrip transmission line. A single crystal silicon dielectric substrate serves as microstrip dielectric and as a thermal link between the membrane isolated MoAu TES operating at 150 millikelvins and the heat bath. A short silicon leg between the heat bath and the TES bolometer is designed for ballistic phonon transport and provides improved process control and uniformity of thermal conductance in the presence of phonon scattering on roughened surfaces. Micro-machined structures are used to realize the orthomode transducer backshort, provide out of band signal rejection, and a silicon photonic choke for feedhorn coupling are described. The backshort, choke wafer, and detector wafer are indium bump-bonded to create a single 37-element dual-polarization detector module. Fourteen such hexagonally shaped modules each 80 millimeters in size comprise two focal planes. These, along with the recently delivered 40 gigahertz focal plane, will survey a large fraction of the sky as part of the Johns Hopkins University-led ground-based CLASS (Cosmology Large Angular Scale Surveyor) telescope.

Detectors↗
NASA NTRS2013

Athermal Energy Loss from X-rays Deposited in Thin Superconducting Films on Solid Substrates

When energy is deposited in a thin-film cryogenic detector, such as from the absorption of an X-ray, an important feature that determines the energy resolution is the amount of athermal energy that can be lost to the heat bath prior to the elementary excitation systems coming into thermal equilibrium. This form of energy loss will be position-dependent and therefore can limit the detector energy resolution. An understanding of the physical processes that occur when elementary excitations are generated in metal films on dielectric substrates is important for the design and optimization of a number of different types of low temperature detector. We have measured the total energy loss in one relatively simple geometry that allows us to study these processes and compare measurements with calculation based upon a model for the various di.erent processes. We have modeled the athermal phonon energy loss in this device by finding an evolving phonon distribution function that solves the system of kinetic equations for the interacting system of electrons and phonons. Using measurements of device parameters such as the Debye energy and the thermal di.usivity we have calculated the expected energy loss from this detector geometry, and also the position-dependent variation of this loss. We have also calculated the predicted impact on measured spectral line-shapes, and shown that they agree well with measurements. In addition, we have tested this model by using it to predict the performance of a number of other types of detector with di.erent geometries, where good agreement is also found.

Kozorezov, Alexander G.↗
NASA NTRS1995

An electron tunneling study of superconductivity in amorphous Sn(sub 1-x)Cu(sub x) thin films

The amorphous phase of Sn would have a superconducting transition temperature near 8 K, much higher than that of crystalline Sn with T(sub c) = 3.5 K. To obtain the amorphous phase, however, it is necessary to use a Sn alloy, usually Cu, and quench condense the alloy films onto a liquid He temperature substrate. Alloying with Cu reduces the superconducting transition temperature almost linearly with Cu concentration with an extrapolation of T(sub c) to zero for x = 0.85. Analysis of the tunneling characteristics between a normal metal electrode with an insulating barrier and superconducting amorphous Sn-Cu films provides detailed information on the changes in the electron-phonon coupling which determines T(sub c) in these alloys. The change from very strong electron-phonon coupling to weak-coupling with the increase in Cu content of amorphous Sn-Cu alloys for the range 0.08 is less than or equal to x is less than or equal to 0.41 is presented and discussed in terms of theories of electron-phonon coupling in disordered metals.

Naugle, D. G.↗
NASA NTRS2012

Rhombohedral cubic semiconductor materials on trigonal substrate with single crystal properties and devices based on such materials

Growth conditions are developed, based on a temperature-dependent alignment model, to enable formation of cubic group IV, group II-V and group II-VI crystals in the [111] orientation on the basal (0001) plane of trigonal crystal substrates, controlled such that the volume percentage of primary twin crystal is reduced from about 40% to about 0.3%, compared to the majority single crystal. The control of stacking faults in this and other embodiments can yield single crystalline semiconductors based on these materials that are substantially without defects, or improved thermoelectric materials with twinned crystals for phonon scattering while maintaining electrical integrity. These methods can selectively yield a cubic-on-trigonal epitaxial semiconductor material in which the cubic layer is substantially either directly aligned, or 60 degrees-rotated from, the underlying trigonal material.

Park, Yeonjoon↗
NASA NTRS1995

Superradiance of J-Aggregated 2,2'-Cyanine Absorbed onto a Vesicle Surface

Phospholipid vesicles are used as substrates to form adsorbed aggregates of 2,2'-cyanine, also referred to as pseudoisocyanine (PIC). In this paper, we report photophysical parameters of two putative adsorbed aggregates species (cis- and trans-aggregates, relating to their makeup from mono-cis and all-transstereoisomers, respectively). Phase modulation picosecond fluorescence decay measurements reveal that superradiance and energy transfer are dominant features controlling photophysical processes. Superradiance, coherence size, energy transfer and exciton-phonon coupling are discussed for the two types of aggregates; as regards photophysical parameters, the fluorescence lifetimes, fluorescence quantum yields, and nonradiative rate constants are determined. It is suggested that structure plays the crucial role in excited state dynamics.

Akins, Daniel L.↗
NASA NTRS2005

Temperature-dependent optical properties of Cd(1-x),Zn(x),Te substitute material

In this study, we report cryogenic optical properties of Cd(l-x), Zn(x), Te wafers that are used as substrate seed layers in the manufacturing of HgCdTe focal-plane array detectors. These studies are motivated by the fact that the substrate optical properties influence the overall detector performance. The studies consist of measuring the substrate frequency dependent transmittance T(W) and reflectance R(W) above and below the optical band-gap in the UV/Visible and infrared frequency ranges, and with temperature variation of the sample from 5 to 300 K. Determination of the optical absorption from these measurements show that the optical absorption energy gap near 1.6 eV shows a substantial increase as the temperature is reduced from 300 to 5 K. Furthermore, we observe the presence of infrared-active optical phonons whose peak frequency shifts as the temperature of the sample is varied over the measured temperature range. The theoretical frequency dependent optical conductivity, with allowance for redistribution of spectral weight among the interband transition charge carriers, will be discussed.

Quijada, Manuel A.↗
NASA NTRS1992

A multilayered approach to superconducting tunnel junction x ray detectors

'First generation' superconducting tunnel junction X-ray detectors (characterized by a single tunnel junction in direct contact with its substrate, with totally external amplification) remain more than an order of magnitude away from their theoretical energy resolutions which are in the order of eV's. The difficulties that first generation devices are encountering are being attacked by a 'second generation' of superconducting X-ray detector designs including quasiparticle trapping configurations and Josephson junction arrays. A second generation design concept, the multilayered superconducting tunnel junction X-ray detector, consisting of tens to hundreds of tunnel junctions stacked on top of one another (a superlattice), is presented. Some of the possibilities of this engineered materials approach include the tuning of phonon transmission characteristics of the material, suppression of parasitic quasiparticle trapping and intrinsic amplification.

Rippert, E. D.↗
NASA NTRSDate not supplied

Machine Learning Approaches for Rare-Earth Silicate Environmental Barrier Coating Thermochemical and Thermomechanical Property Predictions

Environmental barrier coatings (EBCs) are a necessary enabling technology for the transition from superalloys to silicon carbide (SiC) ceramic matrix composites (CMCs) in gas turbine engines for increased efficiency and decreased fuel costs. SiC-based CMCs are prone to oxidation-based degradation in the engine hot section, and rare-earth (RE) silicates are promising candidates for EBCs due to their close thermal expansion match to the composite substrate and oxidation resistance. However, the design of EBCs is hindered by the large chemical space of candidate materials and the difficulty in obtaining material properties for engineering optimization. This is especially difficult as research continues into mixed-cation or “high-entropy” RE silicates. First-principles computational methods such as density functional theory (DFT) are highly effective at calculating material properties to guide coating design but are limited by their computational cost. Atomistic simulations have the potential to both accelerate property calculations and expand the properties able to be calculated due to their lower computational compared to DFT. However, they require interatomic potentials (IAPs) specific to the material system of interest, and, to our knowledge, there are no suitable IAPs for RE silicates. Machine learning (ML) is a promising technique to accelerate material property predictions indirectly by generating IAPs for atomistic simulations or via direct prediction. In this work, we present two ML approaches to accelerate the calculation of RE silicate properties relevant to EBC design: 1) a ML-derived interatomic potential (IAP) for atomistic simulations of yttrium disilicate (Y2Si2O7) from DFT training data, and 2) a neural network (NN) model to directly predict thermochemical properties of RE silicates and oxides directly from easily obtainable unit cell parameters. Classical MD simulations using the IAP yield lattice properties and bond lengths in good agreement with both DFT and experimental results from x-ray diffraction. Thermodynamic properties calculated using the finite-displacement phonon method and quasi-harmonic approximation were orders of magnitude faster than DFT with good agreement to the DFT results. The IAP was also used to calculate properties such as coefficient of thermal expansion (CTE) that require large simulation supercells and are therefore difficult with DFT. The IAP correctly predicted the anisotropic nature of the CTE in three different phases of Y2Si2O7. The NN model predicts constant pressure heat capacity, Cp, orders of magnitude faster than DFT calculations, which can enable its use as a surrogate model for multiscale simulations. The two methods presented in this work demonstrate the utility of ML for accelerating the prediction of RE silicate properties, which can in turn accelerate EBC design and optimization.

machine learning↗