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All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Quantitative photoabsorption and fluorescence spectroscopy of benzene, naphthalene, and some derivatives at 106-295 nm

Photoabsorption and fluorescence cross sections of benzene, (o-, m-, p-) xylenes, naphthalene, 1-methylnaphthalene, and 2-ethylnaphthalene in the gas phase are measured at 106-295 nm using synchrotron radiation as a light source. Fluorescences are observed from the photoexcitation of benzene and xylenes at 230-280 nm and from naphthalene and its derivatives at 190-295 nm. The absolute fluorescence cross section is determined by calibration with respect to the emission intensity of the NO(A-X) system, for which the fluorescence quantum yield is equal to 1. To cross-check the current calibration method, the quantum yield of the SO2(C-X) system at 220-230 nm was measured since it is about equal to 1. The current quantum-yield data are compared with previously published values measured by different methods.

Suto, Masako↗
NASA NTRS1994

Theoretical investigation of wave-vector-dependent analytical and numerical formulations of the interband impact-ionization transition rate for electrons in bulk silicon and GaAs

The electron interband impact-ionization rate for both silicon and gallium arsenide is calculated using an ensemble Monte Carlo simulation with the expressed purpose of comparing different formulations of the interband ionization transition rate. Specifically, three different treatments of the transition rate are examined: the traditional Keldysh formula, a new k-dependent analytical formulation first derived by W. Quade, E. Scholl, and M. Rudan (1993), and a more exact, numerical method of Y. Wang and K. F. Brennan (1994). Although the completely numerical formulation contains no adjustable parameters and as such provides a very reliable result, it is highly computationally intensive. Alternatively, the Keldysh formular, although inherently simple and computationally efficient, fails to include the k dependence as well as the details of the energy band structure. The k-dependent analytical formulation of Quade and co-workers overcomes the limitations of both of these models but at the expense of some new parameterization. It is found that the k-dependent analytical method of Quade and co-workers produces very similar results to those obtained with the completely numerical model for some quantities. Specifically, both models predict that the effective threshold for impact ionization in GaAs and silicon is quite soft, that the majority of ionization events originate from the second conduction band in both materials, and that the transition rate is k dependent. Therefore, it is concluded that the k-dependent analytical model can qualitatively reproduce results similar to those obtained with the numerical model yet with far greater computational efficiency. Nevertheless, there exist some important drawbacks to the k-dependent analytical model of Quade and co-workers: These are that it does not accurately reproduce the quantum yield data for bulk silicon, it requires determination of a new parameter, related physically to the overlap intergrals of the Bloch state which can only be adjusted by comparison to experiment, and fails to account for any wave-vector dependence of the overlap integrals. As such the transition rate may be overestimated at those points for which 'near vertical,' small change in k, transitions occur.

Kolnik, Jan↗
NASA NTRS1994

Theoretical Investigation of Wave-Vector-Dependent Analytical and Numerical Formulations of the Interband Impact-Ionization Transition Rate for Electron in Bulk Silicon and GaAs

The electron interband impact-ionization rate for both silicon and gallium arsenide is calculated using an ensemble Monte Carlo simulation with the expressed purpose of comparing different formulations of the interband ionization transition rate. Specifically, three different treatments of the transition rate are examined: the traditional Keldysh formula, a new k-dependent analytical formulation first derived by W. Quade, E Scholl, and M. Rudan, and a more exact, numerical method of Y. Wang and K. F. Brennan. Although the completely numerical formulation contains no adjustable parameters and as such provides a very reliable result, it is highly computationally intensive. Alternatively, the Keldysh formula, although inherently simple and computationally efficient, fails to include the k dependence as well as the details of the energy band structure. The k-dependent analytical formulation of Quade and co-workers overcomes the limitations of both of these models but at the expense of some new parameterization. It is found that the k-dependent analytical method of Quade and co-workers produces very similar results to those obtained with (he completely numerical model for some quantities. Specifically, both models predict that the effective threshold for impact ionization in GaAs and silicon is quite soft, that the majority of ionization events originate from the second conduction band in both materials, and that the transition rate is k dependent. Therefore, it is concluded that the k-dependent analytical model can qualitatively reproduce results similar to those obtained with the numerical model yet with far greater computational efficiency. Nevertheless, there exist some important drawbacks to the k-dependent analytical model of Quade and co-workers: These are that it does not accurately reproduce the quantum yield data for bulk silicon, it requires determination of a new parameter, related physically to (he overlap integrals of the Bloch state which can only be adjusted by comparison to experiment, and fails to account for any wave-vector dependence of the overlap integrals. As such [he transition rate may be overestimated at those points for which "near vertical," small change in k, transitions occur.

Kolnik, Jan↗
NASA NTRS1997

Optical Characterization and 2,525 micron Lasing of Cr(2+):Cd(0.85)Mn(0.15)Te

Transition metal doped solids are of significant current interest for the development of tunable solid-state lasers for the near and mid-infrared (1-4 pm) spectral region. Applications of these lasers include basic research in atomic, molecular, and solid-state physics, optical communication, medicine, and environmental studies of the atmosphere. In transition metal based laser materials, absorption and emission of light arises from electronic transitions between crystal field split energy levels of 3d transition metal ions. The optical spectra generally exhibit broad bands due to the strong interaction between dopant and host (electron-phonon coupling). Broad emission bands offer the prospect of tunable laser activity over a wide wavelength range, e.g. the tuning range of Ti:Sapphire extends from 700-1100 run. The only current transition metal laser operating in the mid-infrared wavelength region (1.8-2.4 micro-m) is CO(2+):MgF2, but its performance is severely limited due to strong nonradiative decay at room temperature. Based on lifetime data, the quantum efficiency is estimated to be less than 3 deg/0 11,21. In general, the probability for non-radiative decay via multi-phonon relaxation increases with decreasing energy gap between ground and excited state. Therefore, efficient transition metal lasers beyond -1.6 micro-m are rare. Recently, tunable laser activity around 2.3 micro-m was observed from Cr doped ZnS and ZnSe. The new lasing center in these materials was identified as Cr(2+) occupying the tetrahedral Zn site. Tetrahedrally coordinated optical centers are rather unusual among transition metal lasers. Their potential usefulness, however, has been demonstrated by the recent development of near infrared laser materials such as Cr:forsterite and Cr:YAG, which are based on tetrahedrally coordinated Cr(4+) ions. According to the Laporte selection rule, electric-dipole transition within the optically active 3d-electron shells are parity forbidden. However, a static acentric electric crystal field or the coupling of asymmetric phonons can force electric-dipole transitions by the admixture of wave functions with opposite parity. Tetrahedral sites lack inversion symmetry which provides the odd-parity field necessary to relax the parity selection rule. Therefore, high absorption and emission cross sections are observed. An enhanced radiative emission rate is also expected to reduce the detrimental effect of non-radiative decay. Motivated by the initial results on Cr doped ZnS and ZnSe, we have started a comprehensive effort to study Cr(2+) doped II-VI semiconductors for solid-state laser applications. In this paper we present the optical properties and the demonstration of mid-infrared lasing from Cr doped Cd(0.85)Mn(0.15)Te.

Davis, V. R.↗
NASA NTRS2004

4H-SiC UV Photo Detector with Large Area and Very High Specific Detectivity

Pt/4H-SiC Schottky photodiodes have been fabricated with the device areas up to 1 sq cm. The I-V characteristics and photo-response spectra have been measured and analyzed. For a 5 mm x 5 mm area device leakage current of 1 x 10(exp 15)A at zero bias and 1.2 x 10(exp 14)A at -IV have been established. The quantum efficiency is over 30% from 240nm to 320nm. The specific detectivity, D(sup *), has been calculated from the directly measured leakage current and quantum efficiency data and are shown to be higher than 10(exp 15) cmHz(sup 1/2)/W from 210nm to 350nm with a peak D(sup *) of 3.6 x 10(exp 15)cmH(sup 1/2)/W at 300nm.

Yan, Feng↗
NASA NTRSDate not supplied

Modeling Ring-Opening Polymerization with Machine-Learned Committors

Many important industrial and biological processes depend on ring-opening polymerization (ROP), including large-scale production polymers, such as nylon 6, and a variety of biodegradable polymers and high-performance resins. Large-scale simulations (>200K atoms) of ROP were performed using a deep neural network-based method that captured the effect of the local chemical environment of the reactive sites using training data from quantum chemical methods. The utility of this method was demonstrated by modeling the cationic ROP of bis-benzoxazine, a promising resin for use in advanced high-temperature application composites (>200°C). Density functional theory calculations were used to map out the various ring opening and polymerization reaction paths that occur during the thermal processing of bis-benzoxazine. The probabilities of these reactions, as a function of local atomic configurations, were used to construct committor functions using a neural network approach. The learned committor functions were then used to determine when a particular reaction occurred within the REACTER framework for reactive molecular dynamics simulations. The experimentally observed exotherm that occurs during bis-benzoxazine ROP was captured in an effective manner in the simulations by imposing a local heating of the system that corresponds to the enthalpy of reaction for each reaction. The dependence of the final polymer morphology on the ROP reaction temperature was analyzed at the molecular scale. The results presented in this work indicate that machine-learned committor functions are a promising approach for incorporating high-fidelity reactivity criteria that capture the effect of local chemical environments into large-scale polymerization simulations.

machine learning, polymer simulations, molecular d↗
NASA NTRS1990

AlSb/InAs/AlSb quantum wells

Researchers studied the InAs/AlSb system recently, obtaining 12nm wide quantum wells with room temperature mobilities up to 28,000 cm(exp 2)/V center dot S and low-temperature mobilities up to 325,000 cm(exp 2)/V center dot S, both at high electron sheet concentrations in the 10(exp 12)/cm(exp 2) range (corresponding to volume concentrations in the 10(exp 18)/cm(exp 2) range). These wells were not intentionally doped; the combination of high carrier concentrations and high mobilities suggest that the electrons are due to not-intentional modulation doping by an unknown donor in the AlSb barriers, presumably a stoichiometric defect, like an antisite donor. Inasmuch as not intentionally doped bulk AlSb is semi-insulating, the donor must be a deep one, being ionized only by draining into the even deeper InAs quantum well. The excellent transport properties are confirmed by other observations, like excellent quantum Hall effect data, and the successful use of the quantum wells as superconductive weak links between Nb electrodes, with unprecendentedly high critical current densities. The system is promising for future field effect transistors (FETs), but many processing problems must first be solved. Although the researchers have achieved FETs, the results so far have not been competitive with GaAs FETs.

Kroemer, Herbert↗
NASA NTRSDate not supplied

Quantum Hardware-Enabled Molecular Dynamics via Transfer Learning

The ability to perform ab initio molecular dynamics simulations using potential energy surfaces provided by quantum computers would open the door to virtually exact dynamics for a variety of chemical and biochemical systems, with impacts on catalysis and biophysics. Nonetheless, performing molecular dynamics on surfaces produced by quantum hardware has been hampered by the noisy energies typically produced by quantum computers and challenges associated with computing gradients and scaling to large systems interest. A recent set of advances in machine learning, known as transfer learning, provides a new path forward for molecular dynamics simulations on quantum hardware. Transfer learning offers a workaround, where one first trains models on larger, less accurate classical datasets and then refines them on smaller, more accurate quantum datasets. We explore this approach by training machine learning models to predict a molecule's potential energy based on its geometric structure using Behler-Parrinello neural networks. When successfully trained, the model enables energy gradient predictions necessary for dynamic simulations. To reduce the quantum resources needed, the model is initially trained with data derived from classical density functional theory and subsequently refined with a smaller dataset obtained from a variational quantum eigensolver optimization of the unitary coupled cluster ansatz. We show that this approach significantly reduces the size of the needed quantum training dataset while capturing the high accuracies needed within quantum chemistry simulations. The success of this two-step training method opens more opportunities to apply machine learning models on quantum data, a significant stride towards efficient quantum-classical hybrid computational models.

quantum computing↗
NASA NTRS1971

Optimum doping achieves high quantum yields in GaAs photoemitters

Experimental data indicate that optimum doping exists. Measured quantum yield curves indicate optimum overall response is obtained in GaAs emitters with doping in high 10 to the 18th power per cu cm range. Doping for optimum response is not necessarily in this range.

Sonnenberg, H.↗
NASA NTRS2005

NASA Tech Briefs, March 2005

Topics covered include: Scheme for Entering Binary Data Into a Quantum Computer; Encryption for Remote Control via Internet or Intranet; Coupled Receiver/Decoders for Low-Rate Turbo Codes; Processing GPS Occultation Data To Characterize Atmosphere; Displacing Unpredictable Nulls in Antenna Radiation Patterns; Integrated Pointing and Signal Detector for Optical Receiver; Adaptive Thresholding and Parameter Estimation for PPM; Data-Driven Software Framework for Web-Based ISS Telescience; Software for Secondary-School Learning About Robotics; Fuzzy Logic Engine; Telephone-Directory Program; Simulating a Direction-Finder Search for an ELT; Formulating Precursors for Coating Metals and Ceramics; Making Macroscopic Assemblies of Aligned Carbon Nanotubes; Ball Bearings Equipped for In Situ Lubrication on Demand; Synthetic Bursae for Robots; Robot Forearm and Dexterous Hand; Making a Metal-Lined Composite-Overwrapped Pressure Vessel; Ex Vivo Growth of Bioengineered Ligaments and Other Tissues; Stroboscopic Goggles for Reduction of Motion Sickness; Articulating Support for Horizontal Resistive Exercise; Modified Penning-Malmberg Trap for Storing Antiprotons; Tumbleweed Rovers; Two-Photon Fluorescence Microscope for Microgravity Research; Biased Randomized Algorithm for Fast Model-Based Diagnosis; Fast Algorithms for Model-Based Diagnosis; Simulations of Evaporating Multicomponent Fuel Drops; Formation Flying of Tethered and Nontethered Spacecraft; and Two Methods for Efficient Solution of the Hitting- Set Problem.

Source record↗
NASA NTRS1986

EUV astronomical spectroscopy with CCD detectors

The applicability of CCD detectors to astronomical extreme ultraviolet (EUV) spectroscopy (100-1250 A) is discussed. The advantages of CCDs in this spectral region include internal electron yield, the potential for very high quantum efficiency (about 50-90 percent), and broad wavelength response. Visible light suppression is achieved by a combination of low grating scattering, greater than unity electron yield in the EUV, and various filter techniques. For the current generation of CCDs, detection of only a few EUV photons will rapidly overwhelm the read noise; thus, for all practical S/N ratios used in astronomical spectroscopy, read noise will be negligible compared to the poisson statistics of the detected photons. A model based on experimental data for the quantum efficiency and electron yield of CCDs in the EUV is discussed.

Stern, R. A.↗
NASA NTRS1996

Diffusion lengths in irradiated N/P InP-on-Si solar cells

Indium phosphide (InP) solar cells were made on silicon (Si) wafers (InP/Si) by to take advantage of both the radiation-hardness properties of the InP solar cell and the light weight and low cost of Si wafers. The InP/Si cell application is for long duration and/or high radiation orbit space missions. Spire has made N/P InP/Si cells of sizes up to 2 cm by 4 cm with beginning-of-life (BOL) AM0 efficiencies over 13% (one-sun, 28C). These InP/Si cells have higher absolute efficiency and power density after a high radiation dose than gallium arsenide (GaAs) or silicon (Si) solar cells after a fluence of about 2e15 1 MeV electrons/sq. cm. In this work, we investigate the minority carrier (electron) base diffusion lengths in the N/P InP/Si cells. A quantum efficiency model was constructed for a 12% BOL AM0 N/P InP/Si cell which agreed well with the absolutely measured quantum efficiency and the sun-simulator measured AM0 photocurrent (30.1 mA/sq. cm). This model was then used to generate a table of AM0 photocurrents for a range of base diffusion lengths. AM0 photocurrents were then measured for irradiations up to 7.7e16 1 MeV electrons/sq. cm (the 12% BOL cell was 8% after the final irradiation). By comparing the measured photocurrents with the predicted photocurrents, base diffusion lengths were assigned at each fluence level. A damage coefficient K of 4e-8 and a starting (unirradiated) base electron diffusion length of 0.8 microns fits the data well. The quantum efficiency was measured again at the end of the experiment to verify that the photocurrent predicted by the model (25.5 mA/sq. cm) agreed with the simulator-measured photocurrent after irradiation (25.7 mA/sq. cm).

Wojtczuk, Steven↗
NASA NTRS1972

Excitation of Na D-line radiation in collisions of sodium atoms with internally excited H2, D2, and N2

Excitation of D-line radiation in collisions of Na atoms with vibrationally excited N2, H2 and D2 was studied in two modulated crossed beam experiments. In both experiments, the vibrational excitation of the molecules was provided by heating the molecular beam source to temperatures in the range of 2000 to 3000 K, which was assumed to give populations according to the Boltzmann expression. In the first experiment, a total rate coefficient was measured as a function of molecular beam temperature, with absolute calibration of the photon detector being made using the black body radiation from the heated molecular beam source. Since heating affects both the internal energy and the collisional kinetic energy, the first experiment could not determine the relative contributions of internal energy transfer versus collisional excitation. The second experiment achieved partial separation of internal versus kinetic energy transfer effects by using a velocity-selected molecular beam. Using two simple models for the kinetic energy dependence of the transfer cross section for a given change in vibrational quantum number, the data from both experiments were used to determine parameters in the models.

Krause, H. F.↗
NASA NTRS1979

Shallow-homojunction GaAs solar cells

Single-crystal GaAs shallow-homojunction solar cells on GaAs or Ge substrates, without Ga sub 1-x Al sub x As window layers, that have conversion efficiencies exceeding 20% at AM1 (17% at AMO). Using a simple theoretical model, good fits were obtained between computer calculations and experimental data for external quantum efficiency and conversion efficiency of cells with different values of n+ layer thickness. The calculations not only yield values for material properties of the GaAs layers composing the cells but will also permit the optimization of cell designs for space and terrestrial applications. Preliminary measurements indicate that the shallow-homojunction cells are resistant to electron irradiation. In the best test so far, bombardment with 1 x 10 to the 16th power/sq cm fluence of 1 MeV electrons reduced the short-circuit current by only about 6%.

Fan, J. C. C.↗
NASA NTRS1983

GaInAs-AlInAs heterostructures for optical devices grown by MBE

The band gap of Ga(0.47)In(0.53)As corresponds to an emission wavelength of about 1.65 microns. Lasers have been produced with Al(0.48)In(0.52)As as cladding layers operating at room temperature. The peak emission of Ga(0.47)In(0.53)As can be continuously varied from 1.65 to 1.2 microns by the use of the multiquantum well structures. This range of wavelengths covers the minimum loss and dispersion in optical fibers and will be applicable to integrated optics. Double heterostructure broad area lasers have been fabricated using AlInAs as cladding layers to the GaInAs active layer. Room temperature threshold current densities of 4.3 kA/sq cm have been obtained for lasers with a 4500 A active region. The first data on GaInAs/AlInAs quantum well emitters will be presented. Photoluminescence of 4 K from quantum well layers of 100, 150, and 180 A with 150 A AlInAs barrier layers produced emission at 1.27, 1.35, and 1.41 microns, respectively. Ga(0.47)In(0.52)As quantum well LEDs have also been produced which emit at 1.34 microns.

Welch, D. F.↗
NASA NTRS1988

Temperature dependence of the atmospheric photolysis rate coefficient for NO2

Accurate values for the photolysis rate coefficient of NO2 (j1) are required for studies related to the observed imbalance in the photostationary state of O3, NO, and NO2 in the troposphere. Direct measurements of the temperature dependence of j1 at temperatures from -70 to 30 C were made in sunlight for relatively cloudless summer days in Boulder, Colorado. The ratios of j1 (30 C)/j1 (T C) for T = -10 C and -70 C, respectively, were 1.046 + or - 0.040 and 1.070 + or - 0.031. The j1 ratios were independent of solar zenith angle. Theoretical estimates of the temperature-dependent j1 ratios based upon recently reported cross section (sigma) and quantum yield (phi) data are more consistent with these experimental measurements than those based upon the currently accepted sigma and phi data.

Shetter, Richard E.↗
NASA NTRS2005

High-Efficiency Multi-Junction Space Solar Development Utilizing Lattice Grading

Progress towards achieving a high one-sun air mass 0 (AM0) efficiency in a monolithic dual junction solar cell comprised of a 1.62 eV InGaP top cell and a 1.1 eV InGaAs bottom cell grown on buffered GaAs is reported. The performance of stand-alone 1.62 eV InGaP and 1.1 eV InGaAs cells is compared to that of the dual junction cell. Projected AM0 efficiencies of 15.7% and 16.5% are expected for the 1.62 eV InGaP and 1.1 eV InGaAs cells grown on buffered GaAs. The dual junction cell has a projected one-sun AM0 conversion efficiency of 17%. The projected efficiencies are based upon the application of an optimized anti-reflective coating (ARC) to the as-grown cells. Quantum efficiency (QE) data obtained from the dual junction cell indicate that is is bottom cell current limited with the top cell generating 50% more current than the bottom cell. A comparison of the QE data for the stand-alone 1.1 eV InGaAs cell to that of the 1.1 eV InGaAs bottom cell in the tandem configuration indicates a degradation of the bottom cell conversion efficiency in the tandem configuration. The origin of this performance degradation is at present unknown. If the present limitation can be overcome, then a one-sun AM0 efficiency of 26% is achievable with the 1.62 eV/1.1 eV dual junction cell grown lattice-mismatched to GaAs.

Stan, Mark A.↗
NASA NTRSDate not supplied

Image-to-Image Wildfire Detection via Quantum-Compatible Variational Segmentation from Remotely-sensed Data

Over the last decade, the incidence of wildfires has surged, causing widespread destruction globally. To better comprehend and manage these incidents, remote sensing and aerial missions have been implemented in recent efforts. However, this has resulted in an exponential rise in the amount of remote sensing data utilization, leading to a need for intelligent automation of data extraction in wildfire studies. Machine learning provides an accurate automated approach for detecting these natural anomalies and facilitates decision-makers to take prompt actions. To make insightful decisions in wildfire management, it is imperative to move beyond simple detection and explore the potential of probabilistic generative machine learning for creating "what-if" scenarios for various wildfire conditions. Such models offer improved representation of the stochastic nature of wildfire events. However, the optimization of these models can be computationally expensive, especially when using classical computers. Quantum computers have recently emerged as a promising solution to reduce the computational cost of training such models and improve their performance. In this study, we aim to utilize quantum-compatible machine learning techniques to implement our probabilistic generative approach. To that end, we propose a supervised probabilistic variational model consisting of a U-NET-based image-to-image component along with encoder and decoder networks which work as a variational autoencoder (VAE) component. Additionally, we explore the type of latent distribution type in the VAE component and implement different means for modeling the prior distribution. We further investigate the quantum-compatible versions of the model compared to the classical counterpart and benchmark potential benefits of quantum compatibility over the classical model.

quantum machine learning↗