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At least 289 records · Page 16

Simulation App for Time-Resolved Photoluminescence in Thin-Film Solar Cells

We develop a COMSOL Multiphysics-based model and application, or "app", for time-resolved photoluminescence (TRPL) measurements in thin-film solar cells. TRPL is commonly used to measure recombination in thin-film solar cells. However, simulations show that decay times extracted from TRPL data are not, in general, equal to the Shockley-Read-Hall lifetime parameter set in the model. Here, we present a model and app, using graded CdSe y Te 1-y solar cells as an example, that can be used to study impacts of a range of potentially important material and measurement parameters on TRPL results.

minority-carrier lifetime↗

Interplay between microstructure, defect states, and mobile charge generation in transition metal dichalcogenide heterojunctions

Two-dimensional transition metal dichalcogenides (2D-TMDCs) have gained attention for their promise in next-generation energy-harvesting and quantum computing technologies, but realizing these technologies requires a greater understanding of TMDC properties that influence their photophysics. To this end, we discuss here the interplay between TMDC microstructure and defects with the charge generation yield, lifetime, and mobility. As a model system, we compare monolayer-only and monolayer-rich MoS 2 grown by chemical vapor deposition, and we employ the TMDCs in Type-II charge-separating heterojunctions with semiconducting single-walled carbon nanotubes (s-SWCNTs). Our results suggest longer lifetimes and higher yields of mobile carriers in samples containing a small fraction of defect-rich multilayer islands on predominately monolayer MoS 2 . Compared to the monolayer-only heterojunctions, the carrier lifetimes increase from 0.73 μs to 4.71 μs, the hole transfer yield increases from 23% to 34%, and the electron transfer yield increases from 39% to 59%. We reach these conclusions using a unique combination of microwave photoconductivity (which probes only mobile carriers) along with transient absorption spectroscopy (which identifies spectral signatures unique to each material and type of photoexcited quasiparticle, but does not probe mobility). Overall, our results highlight the substantial changes in photophysics that can occur from small changes in TMDC microstructure and defect density, where the presence of defects does not necessarily preclude improvements in charge generation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Predicting the oxidative lifetime of beta NiAl-Zr alloys

Nickel aluminides containing 40 to 50 at. pct Al and 0.1 at. pct Zr were studied following cyclic oxidation at 1400 C. The selective oxidation of Al resulted in the formation of protective Al2O3 scales on each alloy composition. However, repeated cycling eventually resulted in the gradual formation of less-protective NiAl2O4, first appearing on the 40Al alloys followed at longer times on the 45Al alloys. The appearance of the NiAl2O4, signaling the end of the protective scale-forming capability of the alloy, was related to the presence of gamma-prime (Ni3Al) which formed as a result of the loss of Al from the sample. A diffusion model, based on finite-difference techniques, was developed to predict the protective life of beta Ni-Al alloys. This model predicts Ni and Al concentration profiles after various oxidation exposures. The model can predict the oxidative lifetime due to Al depletion when the Al concentration decreases to a critical concentration. Measured Al concentration profiles on two alloys after various oxidation exposures are compared to those predicted by the diffusion model. The time to the appearance of the NiAl2O4 and that predicted by the diffusion model are compared and discussed.

Nesbitt, J. A.↗

Using Machine Learning to Estimate Surface-Level SO2 Concentrations from Satellite-Based Measurements

Sulfur dioxide (SO2) is a criteria air pollutant due to its contributions to aerosol formation, rainfall acidification, and harm to human health. The placement of air quality monitoring sites is typically biased towards urban areas, leaving large areas with very limited monitoring data. The Ozone Monitoring Instrument (OMI) has been used to provide estimates of SO2 vertical column densities (VCDs) globally at spatial resolution of 10s of kms once per day. OMI SO2 VCDs have been previously used to estimate surface SO2 concentrations using chemical transport model (CTM) simulations. The CTMs use estimated emissions and assimilated meteorological data, and simulate the chemical and physical processes that determine the vertical profile of SO2, which can be used to derive a ratio between the surface concentrations and VCDs. These models are complex, computationally expensive, and have large uncertainties in the simulated surface-to-VCD ratio due to biases in emissions and relatively coarse resolution. Machine learning techniques are comparatively easier to use, much less computationally expensive to use after training, and can produce more accurate estimations of surface concentrations than the CTM-based method. The interpretation of machine learning models often poses challenges, and in some cases, non-physical variables unrelated to SO2 are used as predictors. In this work, we create an artificial neural network (ANN) to relate OMI retrievals and archived GEOS-FP boundary layer heights to surface SO2 concentrations from the ChinaHighAirPollutants ChinaHighSO2 dataset (CHAP; Wei et al., 2023) on a seasonal average timescale from 2013-2018. Our model only utilizes five variables that are directly relevant to the satellite retrieval, lifetime, and spatial distribution of SO2. The model was trained on 16 seasons (four of each) with independent validation (one of each season) and testing datasets (one of each season) to avoid overfitting. Our ANN generates surface SO2 concentrations that are sensitive (slope = 0.51) and consistent (r = 0.74) with the CHAP data, but are underpredicted by an average of 1.2 ppbv with a mean absolute error of 2.2 ppbv. These results are better than recent studies utilizing the CTM method. To our knowledge, this is the best performing machine learning model that only uses physical variables to predict surface SO2. Our work demonstrates that a carefully constructed, simple ML model can accurately estimate surface-based SO2 concentrations from satellite VCD measurements, and this technique has future promise to expend to newer, higher resolution satellites and other air pollutants.

SO2, air quality, OMI, machine learning↗

An in-situ measurement of particulates from solid rocket motors fired in space

Current models exist that predict the damage caused by the impact of aluminum oxide exhaust particles as well as their lifetime in useable space. In these models, two necessary inputs are the size and flux of the particles. An experiment, referred to as the Plume Witness Plate, was designed for the Remote Manipulator System of the space shuttle orbiter to measure in-situ the flux and material effects of a solid rocket motor (SRM) firing in space. Five different types of samples were used to provide a broad range of substances: (1) fused quartz glass (representative of orbiter windows); (2) germanium micrometeroid capture cells; (3) orbiter HRTS tiles from the thermal protection system; (4) Kapton foil; and (5) metallic disks of aluminum, copper, titanium, graphite epoxy, and gold. The analyses of the data show excellent agreement with ground-based SRM firings in terms of particle size distribution and mass distribution. The Particle Impact Damage Integrator computer model used to calculate potential damage of orbiter surfaces by SRM exhaust plumes agrees favorable with the results in terms of particle size and velocity distributions though it may be conservative by as much as 20%.

Alred, J. W.↗

Added value of site load measurements in probabilistic lifetime extension: a Lillgrund case study

Site-specific fatigue estimation is an essential part of wind turbine lifetime extension, with various methods depending on data availability. The present study compares probabilistic lifetime extension assessment results for rotor blades with and without load measurements. It also addresses two key questions in such assessments: the applicability of the Frandsen model for estimating waked turbulence under complex and mixed wake conditions and the extrapolation of mid-term data over longer time periods. The case study wind turbine is SWT-2.3-93, located at the edge of the Lillgrund wind farm, situated in the Øresund Strait between Denmark and Sweden. The turbine is extensively instrumented, with 5 years of data available from its supervisory control and data acquisition (SCADA) system. Although the Frandsen turbulence estimates deviate in a different manner from measurements at below- and above-rated mean wind speeds, the model remains a conservative approach for fatigue load prediction and reliability. In the current case study, the site-specific assessment using strain gauge measurements yields a 33 % higher annual fatigue reliability index after 35 years compared to a scenario based on the Frandsen estimation combined with ambient environmental data and a generic aeroelastic model. The results also demonstrate that the sensitivity of fatigue reliability to load uncertainty is negligible when load measurements are used directly but relatively high when relying on the Frandsen model in combination with a generic aeroelastic model. Overall, the high variability of the lifetime extension in different scenarios of data availability and accuracy shows the importance and added value of high-quality measurements combined with wind-farm-level SCADA and a model updated in real time (digital twins).

17 WIND ENERGY↗

Excited state dynamics of thulium ions in yttrium aluminum garnets

The processes that take place in the excited states of a trivalent Thulium (Tm) ion in an Yttrium Aluminum Garnet (YAG) crystal, being relevant to the use of this system for laser applications, have been the object of several studies. We have reexamined this system focusing our attention on the dynamics of Tm following its excitation in the H-3(sub 4) level. Under these conditions the system relaxes through a cross-relaxation process. H-3(sub 4) yields F-3(sub 4), H-3(sub 6) yields F-3(sub 4), whose rate depends upon both the concentration of the Tm ion and the temperature of the crystal. The excitation spectrum obtained by monitoring the 1.8 micron emission of Tm (due to the F-3(sub 4) yields H-3(sub 6) transition) indicates an increase in the contribution to this emission from the H-3(sub 4) level relative to the H-3(sub 5) level as the Tm concentration increases; this shows the increased role played by the H-3(sub 4) level in pumping the infrared emission. Correspondingly, the duration of the luminescence originating in the H-3(sub 4) level is shortened as the concentration of Tm increases. The concentration quenching of this lifetime can be fit to a model which assumes that the cross-relaxation is due to a dipole-dipole interaction; from this fit, the intrinsic Tm lifetime in the absence of cross relaxation can be derived. We have used this lifetime to calculate the rate of the cross-relaxation process. We have evaluated this rate as a function of the temperature and found it to be fastest at 77 K. We have also calculated the microscopic interaction parameters for the cross-relaxation process by using two independent experimental features: (1) the time evolution of the emission from the H-3(sub 4) level; and (2) the spectral overlap between the H-3(sub 4) yields F-3(sub 4) emission and the H-3(sub 6) yields F-3(sub 4) absorption. We have also considered the migration of excitation among the Tm ions in the F-3(sub 4) level and calculated the relevant microparameter by the use of the relevant spectral overlap. The data are consistent with the model in which the Tm ions, once excited into the H-3(sub 4) level decay by cross-relaxation to the F-3(sub 4), and then transfer rapidly their energy to other Tm ions.

Armagan, G.↗

Lifetime predictions for the Solar Maximum Mission (SMM) and San Marco spacecraft

Lifetime prediction techniques developed by the Goddard Space Flight Center (GSFC) Flight Dynamics Division (FDD) are described. These techniques were developed to predict the Solar Maximum Mission (SMM) spacecraft orbit, which is decaying due to atmospheric drag, with reentry predicted to occur before the end of 1989. Lifetime predictions were also performed for the Long Duration Exposure Facility (LDEF), which was deployed on the 1984 SMM repair mission and is scheduled for retrieval on another Space Transportation System (STS) mission later this year. Concepts used in the lifetime predictions were tested on the San Marco spacecraft, which reentered the Earth's atmosphere on December 6, 1988. Ephemerides predicting the orbit evolution of the San Marco spacecraft until reentry were generated over the final 90 days of the mission when the altitude was less than 380 kilometers. The errors in the predicted ephemerides are due to errors in the prediction of atmospheric density variations over the lifetime of the satellite. To model the time dependence of the atmospheric densities, predictions of the solar flux at the 10.7-centimeter wavelength were used in conjunction with Harris-Priester (HP) atmospheric density tables. Orbital state vectors, together with the spacecraft mass and area, are used as input to the Goddard Trajectory Determination System (GTDS). Propagations proceed in monthly segments, with the nominal atmospheric drag model scaled for each month according to the predicted monthly average value of F10.7. Calibration propagations are performed over a period of known orbital decay to obtain the effective ballistic coefficient. Progagations using plus or minus 2 sigma solar flux predictions are also generated to estimate the despersion in expected reentry dates. Definitive orbits are compared with these predictions as time expases. As updated vectors are received, these are also propagated to reentryto continually update the lifetime predictions.

Smith, E. A.↗

Search for long-lived particles decaying into muon pairs in proton-proton collisions at $\sqrt{s}$ = 13 TeV collected with a dedicated high-rate data stream

A search for long-lived particles decaying into muon pairs is performed using proton-proton collisions at a center-of-mass energy of 13 TeV, collected by the CMS experiment at the LHC in 2017 and 2018, corresponding to an integrated luminosity of 101 fb -1 . The data sets used in this search were collected with a dedicated dimuon trigger stream with low transverse momentum thresholds, recorded at high rate by retaining a reduced amount of information, in order to explore otherwise inaccessible phase space at low dimuon mass and nonzero displacement from the primary interaction vertex. No significant excess of events beyond the standard model expectation is found. Upper limits on branching fractions at 95% confidence level are set on a wide range of mass and lifetime hypotheses in beyond the standard model frameworks with the Higgs boson decaying into a pair of long-lived dark photons, or with a long-lived scalar resonance arising from a decay of a b hadron. The limits are the most stringent to date for substantial regions of the parameter space. These results can be also used to constrain models of displaced dimuons that are not explicitly considered in this paper.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

30-cm mercury ion thruster technology

The LeRC/Hughes 30-cm mercury ion thruster has been developed to a state of maturity such that is has become meaningful to formulate models for describing the performance characteristics of the major subassemblies. The thruster hollow cathode and the ion optics subassemblies have been investigated with this objective and conceptual, semiquantitative models have been formulated for relating lifetime and performance capabilities to design and operating parameters. This paper summarizes the investigations, discusses the factors considered for inclusion in the models, and describes the status of the models.

Poeschel, R. L.↗

GEN3D Experimental and Numerical Development of GEN3 Durability Models

Understanding of the high temperature durability of particles and the materials that contain them is critical to next generation of concentrating solar power (CSP) technology. Here we studied the durability of particles and their containment materials under extreme UV cycling, thermal cycling, and in low-speed high temperature mechanical wear situations. The optical stability of seven candidate particles has been determined following exposure to the high temperature conditions present in a generation 3 particle-based CSP technology. Particle solar weighted absorptance and emittance measured periodically during 10,000 high solar irradiance exposure cycles and up to 400 hours of isothermal aging has been documented. The particle aging due to repeated exposure to concentrated solar flux represented the 30-year lifetime of a power plant. Models were fit to the absorptivity and emissivity data following the isothermal aging provides the projected optical degradation of the particles as a function of temperature. Mechanical wear was studied through the use of custom developed wear testing facilities for measuring high temperature impact wear, abrasion wear, and particle attrition. Additionally, a novel technique for measuring the high temperature mechanical properties of single particles was developed. Through these tests it was observed that high nickel alloys generally showed lower wear than comparable iron based steels, particularly at elevated temperatures of 800°C. Mechanical wear at these temperatures is a highly complex phenomenon combining both mechanical wear and oxidation. Additionally, the containment materials wear rates are influenced by the particles (both hardness and roundness), making the wear mechanisms complex. The initial wear test conducted in the abrasion test rig revealed a substantial amount of oxide materials in the particle bed after testing (in relative to later tests), and substantially more wear, likely indicating a need for concern in startup operation of particle facilities to not incur high wear from the presence of oxides. Particle attrition experiments have only been conducted for a single material but increase size distribution, reduction in circularity, and particle diameter is observed. Efforts to develop predictive models was limited due to a testing campaign that prioritized testing materials for particle pathway developers over building a comprehensive design of experiments. The results discussed in this report inform future CSP developers and researchers further de risking the technology and assisting in its future development. ParticleBased CSP development provides a path to dispatchable solar power generation with storage at a price competitive in the current energy market. Lowering the cost of CSP technology provides a carbon free power generation solution that can assist in the transition from fossil fuels to renewable sources of electricity.

14 SOLAR ENERGY↗

Tropospheric OH and the lifetimes of hydrochlorofluorocarbons

Hydrochlorofluorocarbons (HCFCs) may be used as alternatives for the chlorofluorocarbons (CFCs). Lifetimes for the HCFCs are predicted here in two ways: integrating their loss with a global model and scaling to another compound with a better known lifetime. Both approaches are shown to yield similar results. Three-dimensional fields of modeled tropospheric OH concentrations are used to calculate lifetimes against destruction by OH for the HCFCs and other hydrogenated halocarbons. The lifetimes of various hydro-halocarbons are shown to be insensitive to possible spatial variations and seasonal cycles. It is possible to scale the HCFC lifetimes to that of methyl chloroform or methane by using a ratio of the rate coefficients for reaction with OH at an appropriate temperature, about 277 K.

Prather, Michael↗

Low-Earth Orbit Trajectory Optimization in the Presence of Atmospheric Uncertainty

The previous 20 to 25 years have seen a tremendous increase in space exploration, and with that an increase in the level of logistics planning needed to ensure mission success. For spacecraft that are designed to be periodically re-supplied, a key logistics consumable is propellant, as it constitutes the greatest up-mass on re-supply vehicles. A trajectory design strategy is therefore desired that minimizes propellant usage in order to ease the demand for propellant re-supply missions. This thesis develops such a strategy in three stages, and uses the International Space Station (ISS) as its testbed, as no other LEO spacecraft is more challenging from a space logistics standpoint. First, the ISS trajectory planning problem is formulated as a constrained burn optimization problem assuming a deterministic atmosphere. The cost function is total ∆v, with constraints imposed on longitude of ascending viii node (LAN) and semi-major axis (SMA) altitude. Analytic derivatives are constructed for both the cost and constraints, which are necessary given the 6-week to 2-year time frames being considered. A gradient-based optimizer is then utilized to find locally-optimal solutions to real-world ISS trajectory planning problems. Second, atmospheric uncertainty is addressed by constructing a probabilistic model of space weather data using Gaussian Processes (GPs). Bayesian inference is performed using the GP model to generate mean and covariance estimates for space weather predictions, whose pedigree is assessed against test data. The predictions are then mapped into atmospheric density via the analytic Jacchia-Roberts density model, and the effect of space weather uncertainty on orbital lifetime is examined. Third, an ISS burn execution uncertainty model is developed. This model, along with the space weather uncertainty model, are deployed in a linear covariance analysis to ascertain their combined effect on LAN and SMA altitude dispersions. The deterministic constraints from the original problem are re-formulated as stochastic constraints, where now the constraint uncertainty interval is required to fall within specified bounds. An updated optimization framework is constructed using the original ∆v cost function along with the stochastic constraints to solve the trajectory optimization problem under atmospheric uncertainty. Finally, the complete architecture is summarized for deployment in an operational setting.

Trajectory Optimization↗

A Wrf-Chem Flash Rate Parameterization Scheme and LNO(x) Analysis of the 29-30 May 2012 Convective Event in Oklahoma During DC3

The Deep Convective Clouds and Chemistry (DC3) field campaign in 2012 provided a plethora of aircraft and ground-based observations (e.g., trace gases, lightning and radar) to study deep convective storms, their convective transport of trace gases, and associated lightning occurrence and production of nitrogen oxides (NOx). Based on the measurements taken of the 29-30 May 2012 Oklahoma thunderstorm, an analysis against a Weather Research and Forecasting Chemistry (WRF-Chem) model simulation of the same event at 3-km horizontal resolution was performed. One of the main objectives was to include various flash rate parameterization schemes (FRPSs) in the model and identify which scheme(s) best captured the flash rates observed by the National Lightning Detection Network (NLDN) and Oklahoma Lightning Mapping Array (LMA). The comparison indicates how well the schemes predicted the timing, location, and number of lightning flashes. The FRPSs implemented in the model were based on the simulated thunderstorms physical features, such as maximum vertical velocity, cloud top height, and updraft volume. Adjustment factors were added to each FRPS to best capture the observed flash trend and a sensitivity study was performed to compare the range in model-simulated lightning-generated nitrogen oxides (LNOx) generated by each FRPS over the storms lifetime. Based on the best FRPS, model-simulated LNOx was compared against aircraft measured NOx. The trace gas analysis, along with the increased detail in the model specification of the vertical distribution of lightning flashes as suggested by the LMA data, provide guidance in determining the scenario of NO production per intracloud and cloud-to-ground flash that best matches the NOx mixing ratios observed by the aircraft.

Cloud physics↗

A WRF-Chem Flash Rate Parameterization Scheme and LNOx Analysis of the 29-30 May 2012 Convective Event in Oklahoma During DC3

The Deep Convective Clouds and Chemistry (DC3) field campaign in 2012 provided a plethora of aircraft and ground-based observations (e.g., trace gases, lightning and radar) to study deep convective storms, their convective transport of trace gases, and associated lightning occurrence and production of nitrogen oxides (NOx). Based on the measurements taken of the 29-30 May 2012 Oklahoma thunderstorm, an analysis against a Weather Research and Forecasting Chemistry (WRF-Chem) model simulation of the same event at 3-km horizontal resolution was performed. One of the main objectives was to include various flash rate parameterization schemes (FRPSs) in the model and identify which scheme(s) best captured the flash rates observed by the National Lightning Detection Network (NLDN) and Oklahoma Lightning Mapping Array (LMA). The comparison indicates how well the schemes predicted the timing, location, and number of lightning flashes. The FRPSs implemented in the model were based on the simulated thunderstorms physical features, such as maximum vertical velocity, cloud top height, and updraft volume. Adjustment factors were applied to each FRPS to best capture the observed flash trend and a sensitivity study was performed to compare the range in model-simulated lightning-generated nitrogen oxides (LNOx) generated by each FRPS over the storms lifetime. Based on the best FRPS, model-simulated LNOx was compared against aircraft measured NOx. The trace gas analysis, along with the increased detail in the model specification of the vertical distribution of lightning flashes as suggested by the LMA data, provide guidance in determining the scenario of NO production per intracloud and cloud-to-ground flash that best matches the NOx mixing ratios observed by the aircraft.

Atmospheric chemistry↗

Modeling in High Temperature Corrosion: A Review and Outlook

Realizing higher operating temperatures to increase efficiency of future applications for energy conversion and storage while minimizing cost is a challenge for development of high-temperature materials. Simultaneous optimization of mechanical properties and corrosion resistance continues to be a difficult task but is essential due to the need to significantly accelerate the transition between technology readiness levels in the future. Furthermore, oxidation-induced degradation will be a critical life-limiting mechanism at increased operating temperatures. Suitable high-temperature materials cannot be solely identified by time-consuming experiments and reliable computational methods incorporating the relevant physics of processes must be considered to complement the experimental efforts. In the present work, a review of the methods employed to model oxidation-induced material degradation described in literature will be discussed. Furthermore, their capability to predict lifetime and aid in material selection will be evaluated.

36 MATERIALS SCIENCE↗