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At least 1,135 records · Page 63

Moisture-temperature degradation in module encapsulants: The general problem of moisture in photovoltaic encapsulants

A general research approach was outlined toward understanding water-module interactions and the influence of temperature involving the need to: quantify module performance loss versus level of accumulated degradation, establish the dependence of the degradation reaction rate on module moisture and temperature levels, and determine module moisture and temperature levels in field environments. These elements were illustrated with examples drawn from studies of the now relatively well understood module electrochemical degradation process. Research data presented include temperature and humidity-dependent equilibrium leakage current values for multiparameter module material and design configurations. The contributions of surface, volume, and interfacial conductivities was demonstrated. Research directions were suggested to more fully understand the contributions to overall module conductivity of surface, volume, and interfacial conductivities over ranges of temperature and relative humidity characteristic of field environments.

Mon, G. R.↗

Evaluation of the Benefits of High Temperature Electronics for Lunar Power Systems

A comparative evaluation is conducted of several approaches to the cooling of a lunar power system's power electronics, in view of the 400 K temperature of the 354-hour lunar day and lunar dust accumulation, which can contaminate power components and radiator surfaces. It is noted that, by raising the power electronics' baseplate temperature to 480 K, no thermal control system is required; the surface of the baseplate acts as its own, waste-heat-rejecting radiator, but the baseplate must be kept clean of lunar dust contamination.

Fay, Edgar H.↗

The relaxation behavior of supercooled and glassy imidacloprid

Employing dielectric spectroscopy, oscillatory shear rheology, and calorimetry, the present work explores the molecular dynamics of the widely used insecticide imidacloprid above and below its glass transition temperature. In its supercooled liquid regime, the applied techniques yield good agreement regarding the characteristic structural (alpha) relaxation times of this material. In addition, the generalized Gemant–DiMarzio–Bishop model provides a good conversion between the frequency-dependent dielectric and shear mechanical responses in its viscous state, allowing for an assessment of imidacloprid’s molecular hydrodynamic radius. In order to characterize the molecular dynamics in its glassy regime, we employ several approaches. These include the application of frequency–temperature superposition (FTS) to its isostructural dielectric and rheological responses as well as use of dielectric and calorimetric physical aging and the Adam–Gibbs–Vogel model. While the latter approach and dielectric FTS provide relaxation times that are close to each other, the other methods predict notably longer times that are closer to those reflecting a complete recovery of ergodicity. In conclusion, this seemingly conflicting dissimilarity demonstrates that the molecular dynamics of glassy imidacloprid strongly depends on its thermal history, with high relevance for the use of this insecticide as an active ingredient in technological applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Merging flux-variance with surface renewal methods in the roughness sublayer and the atmospheric surface layer

In this article, Two micrometeorological methods utilizing high-frequency sampled air temperature were tested against eddy covariance (EC) sensible heat flux (𝐻) measurements at three sites representing agricultural, agro-forestry, and forestry systems. The two methods cover conventional and newly proposed forms of the flux-variance (FV) and surface renewal (SR) schemes of differing complexities. The sites represent measurements in surface, roughness, and roughness to surface transitional layers. Regression analyzes against EC show that the most reliable FV and SR forms estimate 𝐻 with slopes within ±10% from unity and coefficient of determination 𝑅2 > 0.9 across all the three sites. The best performance of both FV and SR was found at the agricultural site with measurements well within the surface layer, while the worst was found for the tall forest with measurements within the roughness sublayer where its thickness needed to be additionally estimated. The main variable driving 𝐻 in FV is the temperature variance, whereas in SR, it is the geometry of ramp-like structures. Since these structures are also responsible for most of the temperature variance, a novel FV-SR approach emerging from combining the methods is proposed and evaluated against EC measurements and conventional FV and SR schemes. The proposed FV-SR approach requiring only a single fast response thermocouple is potentially independent of calibration and ameliorates some of the theoretical objections that arise when combining ramp statistics with similarity arguments. The combination of methods also provides new insights into the contribution of coherent structures to the temperature variance and its dependence on atmospheric stratification. Other potential utility of the new method is to include it in multi-tool assessments of surface energy fluxes, since a convergence or divergence of the results has a high diagnostic value.

54 ENVIRONMENTAL SCIENCES↗

High-temperature stability and thermal expansion behavior of equi-atomic refractory multi-principal element alloys based on MoNbTi system for Gen IV reactor applications

The present study investigates the thermal stability and thermal expansion behavior of seven equi-atomic refractory multi-principal element alloys (MPEAs) based on the MoNbTi ternary system composed of low neutron absorption cross section elements. Through an integrated approach utilizing in-situ high-temperature X-ray diffraction (HT-XRD) in conjunction with differential scanning calorimetry (DSC), dilatometry and ageing heat treatment, the thermal stability of the MPEAs was comprehensively analyzed. In-situ HT-XRD experiment confirmed the stability of the room temperature phases up to 1000 °C with no peaks observed corresponding to additional phases in the HT-XRD patterns at 500, 800 and 1100 °C. DSC thermograms showed the absence of peaks up to 1000 °C, while peaks and valleys corresponding to exothermic and endothermic events were observed above 1000 °C. Coefficient of thermal expansion (CTE) derived from second order polynomial fitting of linear thermal expansion data from the dilatometry experiment showed linear increment up to 1000 °C for all the alloys except those containing Zr. The Cr containing alloys exhibited notably higher CTE values, particularly the Al containing alloy exhibited the highest value. Ageing heat treatment at 800 and 1000 °C for 96 h and subsequent microstructural analysis revealed significant precipitation of secondary phases in MoNbTiZr, MoNbTiZrV and MoNbTiCrAl. In conclusion, a substantial increase in hardness was observed in MoNbTiZr and MoNbTiCrAl due to secondary phase precipitation, while the other alloys maintained hardness values comparable to their as-cast and homogenized states.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Room temperature sodium diffusion in sodium iron phosphate investigated with neutron scattering

Sodium iron phosphate, Na x FePO 4 , is currently one of the most promising cathode materials for sodium ion batteries. Here we employ a systematic approach using three neutron scattering techniques to investigate temperature dependent properties with a focus on the charge transfer processes. Two distinct Na + diffusive motions are observed with quasielastic neutron scattering, including room temperature motion. These processes correspond to rapid double jumps through extrinsic vacancy sites of ∼6 Å along with the more fundamental nearest neighbor jumps of 3.1 Å. Experimental observations of room temperature ionic diffusion are highly desirable, as the diffusion pathways are naturally well suited for efficient transport. Inelastic neutron scattering was used to probe the vibrational density of states that assist in the ionic and electronic (polaronic) transport processes, which are further supported with density functional theory. Neutron diffraction examines the disordering of the sodium sublattice upon transition to the solid-solution phase, which is believed to enhance the overall kinetics during sodium insertion/extraction. Finally, 57 Fe Mössbauer spectroscopy measurements probes polaron hopping and the local structural evolution that modifies the electron density surrounding the redox active iron sites. This study sheds light on the temperature induced atomic scale dynamics that occur in olivine Na x FePO 4 .

Novak, Eric [Swarthmore College, Swarthmore, PA (U↗

Slow Electron Spin Relaxation at Ambient Temperatures with Copper Coordinated by a Rigid Macrocyclic Ligand

Paramagnetic transition metal complexes can serve as quantum bits, storing phase information through unpaired electrons. Despite their promise, these systems often require low temperatures and tend to rapidly decohere. Recent efforts have sought to improve longitudinal relaxation (T 1 ), which provides an upper limit for phase coherence (T m ), by investigating existing literature compounds with reduced vibrational coupling and orbital angular momentum. However, synthetic strategies for improving T 1 through novel ligand design have remained scant. Here, we disclose the synthesis of a new modular macrocyclic ligand framework with four nitrogen donors (N 4 ) derived from phenanthroline that supports room-temperature coherent Cu(II) spin centers. The optimized complex more than doubles the T 1 over the next best Cu(II)-N 4 compound and exhibits a room temperature coherence time (T m ) of 0.28 μs, close to previously reported values. This performance enhancement arises from a tight binding site with short Cu–N distances, resulting in a stronger ligand field and reduced thermal accessibility of symmetric vibrational modes. This work demonstrates a practical approach to enabling spin coherence at room temperature, a factor critical to accessing relevant quantum bits and biological sensors, through a designer macrocyclic ligand platform.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Process-based Model with Temperature, Water, and Lab-derived Data Improves Predictions of Daily Culex pipiens/restuans Mosquito Density

While the number of human cases of mosquito-borne diseases has increased in North America in the last decade, accurate modeling of mosquito population density has remained a challenge. Longitudinal mosquito trap data over the many years needed for model calibration, and validation is relatively rare. In particular, capturing the relative changes in mosquito abundance across seasons is necessary for predicting the risk of disease spread as it varies from year to year. We developed a discrete, semi-stochastic, mechanistic process-based mosquito population model that captures life-cycle egg, larva, pupa, adult stages, and diapause for Culex pipiens (Diptera, Culicidae) and Culex restuans (Diptera, Culicidae) mosquito populations. This model combines known models for development and survival into a fully connected age-structured model that can reproduce mosquito population dynamics. Mosquito development through these stages is a function of time, temperature, daylight hours, and aquatic habitat availability. The time-dependent parameters are informed by both laboratory studies and mosquito trap data from the Greater Toronto Area. The model incorporates city-wide water-body gauge and precipitation data as a proxy for aquatic habitat. This approach accounts for the nonlinear interaction of temperature and aquatic habitat variability on the mosquito life stages. We demonstrate that the full model predicts the yearly variations in mosquito populations better than a statistical model using the same data sources. This improvement in modeling mosquito abundance can help guide interventions for reducing mosquito abundance in mitigating mosquito-borne diseases like West Nile virus.

59 BASIC BIOLOGICAL SCIENCES↗

Multiphase computational fluid dynamics modeling of reacting flows in absorption columns for carbon capture

First-principles derived computational fluid dynamics (CFD) simulations have been proposed as a fundamental tool for investigating solvent-based CO 2 absorption in packed columns due to their ability to accurately represent the underlying nonlinear, multiscale dynamics. Numerous studies have previously utilized such CFD simulations to investigate hydrodynamics of columns with structured and random packings by assessing the key hydrodynamic metrics such as the interfacial and wetted areas. While mapping such metrics for different conditions is essential to the optimization of absorption columns, it is not sufficient, as the CO 2 capture rate depends also on the coupled, nonlinear dynamics from the underlying chemical reaction kinetics, thermodynamics, and heat-transfer rates. In this work, we present detailed CFD simulation results augmented by incorporating the effects of interfacial physical mass transfer of CO 2 , heat release from chemical reaction kinetics, and thermophysical property variations from resulting temperature gradients. We demonstrate the applicability of the proposed approach in numerically assessing the performance of packed columns by evaluating key hydrodynamic quantities, CO 2 absorption rates, and temperature rise in a reference column with packings that are structurally similar to the Sulzer Mellapak™ 250.Y packing, for different solvent inflow velocities and temperatures. Predictions from simulation results are found to be consistent with the trends in experimental observations from the literature, suggesting that the predictive capabilities of the simulation framework can be leveraged to guide the future development of absorber-column designs and optimized process flowsheets.

Absorption columns↗

Constraining the Low-Temperature Oxidation Mechanism of n -Hexanol through the Detection and Identification of C 6 Elusive Intermediates

Alcohol-based fuels are currently considered to be viable energy carriers for the transportation sector. Consequently, a comprehensive mechanistic understanding of the low-temperature oxidation of alcohols is essential for application in advanced low-temperature compression engines. Here, in this work, a multidimensional approach involving experimental investigations, kinetic modeling, and theoretical calculations was used to provide new insights into the low-temperature oxidation mechanism of a C 6 alcohol, n -hexanol (CH 3 (CH 2 ) 5 OH), through the detection and identification of elusive C 6 intermediates. The oxidation of n-hexanol was investigated in a jet-stirred reactor under stoichiometric conditions (ϕ = 1.0), an initial fuel concentration of 2%, a residence time of 2 s, a temperature range between 500 and 660 K, and a pressure of 700 Torr. The reactants, intermediates, and final products were detected and identified by means of molecular-beam mass spectrometry coupled with single-photon ionization employing tunable synchrotron-generated vacuum ultraviolet radiation. Chemical kinetic simulations were performed using a previously published kinetic model (Togbé et al., Energy Fuels 2010, 11, 5859−5875) to predict the reactivity of n-hexanol and elucidate the predominant formation pathways of the observed low-temperature species. Experimental photoionization efficiency curves in conjunction with ab initio calculations, enabled the identification of important low-temperature species, such as C 6 unsaturated alcohols, C 6 olefinic hydroperoxides, C 6 cyclic ethers, C 6 diones, and C 6 ketohydroperoxides. The results of this study provide valuable insight into the mechanism of the low-temperature oxidation chemistry of n -hexanol, contributing to the development of kinetic models for the low-temperature oxidation of n-hexanol and other long-chain linear alcohols.

alcohols↗

Instrumentation and experimental procedures for robust collection of X-ray diffraction data from protein crystals across physiological temperatures

Traditional X-ray diffraction data collected at cryo-temperatures have delivered invaluable insights into the three-dimensional structures of proteins, providing the backbone of structure–function studies. While cryo-cooling mitigates radiation damage, cryo-temperatures can alter protein conformational ensembles and solvent structure. Furthermore, conformational ensembles underlie protein function and energetics, and recent advances in room-temperature X-ray crystallography have delivered conformational heterogeneity information that can be directly related to biological function. Given this capability, the next challenge is to develop a robust and broadly applicable method to collect single-crystal X-ray diffraction data at and above room temperature. This challenge is addressed herein. The approach described provides complete diffraction data sets with total collection times as short as ~5 s from single protein crystals, dramatically increasing the quantity of data that can be collected within allocated synchrotron beam time. Its applicability was demonstrated by collecting 1.09–1.54 Å resolution data over a temperature range of 293–363 K for proteinase K, thaumatin and lysozyme crystals at BL14-1 at the Stanford Synchrotron Radiation Lightsource. Here, the analyses presented here indicate that the diffraction data are of high quality and do not suffer from excessive dehydration or radiation damage.

36 MATERIALS SCIENCE↗

Development of an Improved RELAP5-3D Model for the High Temperature Test Facility

High-temperature gas-cooled reactors (HTGRs) are rapidly approaching deployment. Confidence in transient analysis of these systems requires modeling and simulation tools that have been validated against data relevant to HTGR conditions. The High Temperature Test Facility (HTTF) is an integral effects thermal hydraulics test facility for prismatic HTGRs. In spring and summer of 2019, HTTF was used for a series of experiments that now serve as the basis for the Organization of Economic Cooperation and Development / Nuclear Energy Agency Thermal Hydraulic Code Validation Benchmark for High Temperature Gas-Cooled Reactors using HTTF Data (HTGR T/H Benchmark). Previous analyses as part of the HTGR T/H benchmark used a RELAP5-3D model developed at Idaho National Laboratory (INL) and demonstrated an ability to reproduce trends in the measured data but difficulties reproducing experimental values within their uncertainty. These difficulties were largely attributed to assumptions made during the development of the initial RELAP5-3D model, which predated the HTTF experiments. A significant cause of difficulty reproducing the measured temperatures may be the radial nodalization of the previous RELAP5-3D model. In this paper, we present a new RELAP5-3D model of HTTF with finer radial nodalization built to assess the impact of radial heat transfer. We describe the new model and compare it against the old one at full-power steady state and for the pressurized conduction cooldown (PCC) transient. These analyses are based on the code-to-code comparison exercise for the PCC problem of the HTGR T/H benchmark. We compare maximum block temperature as the primary figure of merit and include discussion on intracore natural circulation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Study of Unsteady Flows with Concave Wall Effect

This paper presents computational fluid dynamic studies of the inlet turbulence and wall curvature effects on the flow steadiness at near wall surface locations in boundary layer flows. The time-stepping RANS numerical solver of the NASA Glenn-HT RANS code and a one-equation turbulence model, with a uniform inlet turbulence modeling level of the order of 10 percent of molecular viscosity, were used to perform the numerical computations. The approach was first calibrated for its predictabilities of friction factor, velocity, and temperature at near surface locations within a transitional boundary layer over concave wall. The approach was then used to predict the velocity and friction factor variations in a boundary layer recovering from concave curvature. As time iteration proceeded in the computations, the computed friction factors converged to their values from existing experiments. The computed friction factors, velocity, and static temperatures at near wall surface locations oscillated periodically in terms of time iteration steps and physical locations along the span-wise direction. At the upstream stations, the relationship among the normal and tangential velocities showed vortices effects on the velocity variations. Coherent vortices effect on the velocity components broke down at downstream stations. The computations also predicted the vortices effects on the velocity variations within a boundary layer flow developed along a concave wall surface with a downstream recovery flat wall surface. It was concluded that the computational approach might have the potential to analyze the flow steadiness in a turbine blade flow.

Wang, Chi R.↗

Heat transfer of phase-change materials in two-dimensional cylindrical coordinates

Two-dimensional phase-change problem is numerically solved in cylindrical coordinates (r and z) by utilizing two Taylor series expansions for the temperature distributions in the neighborhood of the interface location. These two expansions form two polynomials in r and z directions. For the regions sufficiently away from the interface the temperature field equations are numerically solved in the usual way and the results are coupled with the polynomials. The main advantages of this efficient approach include ability to accept arbitrarily time dependent boundary conditions of all types and arbitrarily specified initial temperature distributions. A modified approach using a single Taylor series expansion in two variables is also suggested.

Labdon, M. B.↗

Retrieval of Vegetation Water Content Using Brightness Temperatures from the Soil Moisture Active Passive (SMAP) Mission

In this paper, we explore a time series approach to using the tau-omega (τ-ω) model to retrieve vegetation water content (kg/m2) with minimal use of ancillary data. Analytically, this approach calls for nonlinear optimization in two steps. First, multiple days of co-located brightness temperature observations are used to retrieve the effective vegetation opacity, which incorporates the combined radiometric and polarization effects of surface roughness and vegetation opacity. The resulting effective vegetation opacity is then used to retrieve vegetation water content to within a gain factor α and an offset factor β. By using a climatological vegetation water content ancillary database as the one adopted in the development of the SMAP standard and enhanced soil moisture products, α and β can be determined globally using the annual minimum and annual maximum of vegetation water content. The resulting values of α and β can then be used to reconstruct the retrieved vegetation water content. Formulation, assumptions, and limitations of this approach are presented alongside the preliminary global retrieval of vegetation water content using one year (2016) ofSMAP brightness temperature observations.

radiative transfer↗

Passive optical and infrared meteorology

Applications of passive visible and infrared techniques to the study of meteorological parameters are presented. For the remote sensing of temperature and humidity profiles, infrared sounder improvements have proceeded with the narrow band-pass channels approach, and the partially scanned interferogram approach. Current and planned infrared and microwave sea-surface temperature sounders have an expected accuracy of approximately 2 K, and this can be improved by using three super window channels from the 3.7 micron window region, with narrow band passes away from principal water vapor absorption lines. Cloud data remote sensing is currently performed from satellites, and these visible and infrared images have been used to track weather patterns. In addition, a passive infrared correlation-spectroscopy technique has been proposed for wind measurements. Finally, these techniques have also been applied to monitor such parameters as the Solar Constant, aerosols, and minor gas constituents.

Chahine, M. T.↗

Laser-induced annealing of aged PuO 2

Plutonium dioxide (PuO 2 ) is an important compound used in nuclear fuel, irradiation targets, and heat sources. As such, improved understanding of its structural and spectroscopic properties has numerous applications. Alpha particle-induced damage of a PuO 2 crystal lattice modifies several properties of its Raman spectrum, including band intensities, positions, and widths. The decay also induces growth of new bands and creates electron-trapped defects with luminescent properties. Herein, we show for the first time that laser-induced heating can reverse damage to an aged and damaged PuO 2 lattice. Using automated instrumentation to heat a single 6–10 μm spot to temperatures above 1,300°C, we show that laser-induced annealing of aged PuO 2 results in restoration of T2g band intensity with a concomitant decrease in defect band intensity, a result that indicates laser annealing can be used to reverse age-damage in PuO 2 . This laser annealing approach permitted in situ observation of temperature-dependent Raman spectral changes, thereby providing insight into the thermodynamics of structural alterations in a radiolytically damaged PuO 2 .

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Data-driven modeling of dislocation mobility from atomistics using physics-informed machine learning

Dislocation mobility, which dictates the response of dislocations to an applied stress, is a fundamental property of crystalline materials that governs the evolution of plastic deformation. Traditional approaches for deriving mobility laws rely on phenomenological models of the underlying physics, whose free parameters are in turn fitted to a small number of intuition-driven atomic scale simulations under varying conditions of temperature and stress. This tedious and time-consuming approach becomes particularly cumbersome for materials with complex dependencies on stress, temperature, and local environment, such as body-centered cubic crystals (BCC) metals and alloys. In this paper, we present a novel, uncertainty quantification-driven active learning paradigm for learning dislocation mobility laws from automated high-throughput large-scale molecular dynamics simulations, using Graph Neural Networks (GNN) with a physics-informed architecture. We demonstrate that this Physics-informed Graph Neural Network (PI-GNN) framework captures the underlying physics more accurately compared to existing phenomenological mobility laws in BCC metals.

36 MATERIALS SCIENCE↗