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At least 325 records · Page 18

Thermodynamics-guided machine learning model for predicting convective boundary layer height and its multi-site applicability

Accurate estimation of convective boundary layer height (CBLH) is vital for weather, climate, and air quality modeling. Machine learning (ML) shows promise in CBLH prediction, but input parameter selection often lacks physical grounding, limiting generalizability. This study introduces a novel ML framework for CBLH prediction, integrating thermodynamic constraints and the diurnal CBLH cycle as an implicit physical guide. Boundary layer growth is modeled as driven by surface heat fluxes and atmospheric heat absorption represented with the low tropospheric stability, using the diurnal cycle as input and output. TPOT and AutoKeras are employed to select optimal models, validated against Doppler lidar-derived CBLH data, achieving an R 2 of 0.84 across untrained years. Comparisons of eddy covariance (ECOR) and energy balance Bowen ratio (EBBR) flux measurements show the same prediction capability. Models trained on the ARM SGP C1 site with ECOR data and tested at E37 and E39 yield R 2 values of 0.79 and 0.81, respectively, demonstrating their adaptability. The ML model trained with all sites' data slightly enhances the performance compared with ML models trained over single-site data. The interquartile range for predicted CBLH is consistently narrower than that for DL-derived CBLH, reflecting lower variability in predicted CBLH compared to DL-derived CBLH, which is influenced by additional factors, which are not well represented with the model inputs. The model's generalizability across multiple sites at the ARM SGP site demonstrates its potential for transfer to greater distances, offering a scalable approach for enhancing boundary layer parameterization in atmospheric models.

Chu, Yufei [Stony Brook Univ., NY (United States)]↗

Physically Based Modeling of PEMFC Cathode Catalyst Layers: Effective Microstructure and Ionomer Structure–Property Relationship Impacts

Abstract This work presents a pseudo-two-dimensional proton exchange membrane fuel cell (PEMFC) model incorporating Nafion ionomer structure–property relationships in the cathode catalyst layer (CL) to capture and explain losses at low Pt loading. Structural data from neutron reflectometry and thin film Nafion conductivity measurements predict variations in the oxygen diffusion coefficient and ionic conductivity with changing CL ionomer thickness and Pt loading. By including these structure–property relationships, predicted polarization curves agree closely with previously published experimental data from cells with Pt loadings between 0.025 and 0.2 mg/cm2. Results demonstrate that structure–property relationships based on physically measurable ionomer and CL properties provide a feasible interpretation of PEMFC CL phenomena for a range of Pt loadings and help explain previously unaccounted-for losses at low Pt. Results also show that simulations must account for surface species coverage variations in order to properly capture the kinetic losses. Finally, results suggest that an increase in ionomer thickness surrounding the C/Pt surfaces may lead to improved cell performance due to improved ionic conductivity.

Electrochemistry↗

A Model with Ellipsoidal Scatterers for Polarimetric Remote Sensing of Anisotropic Layered Media

This paper presents a model with ellipsoidal scatterers for applications to polarimetric remote sensing of anisotropic layered media at microwave frequencies. The physical configuration includes an isotropic layer covering an anisotropic layer above a homogeneous half space. The isotropic layer consists of randomly oriented spheroids. The anisotropic layer contains ellipsoidal scatterers with a preferential vertical alignment and random azimuthal orientations. Effective permittivities of the scattering media are calculated with the strong fluctuation theory extended to account for the nonspherical shapes and the scatterer orientation distributions. On the basis of the analytic wave theory, dyadic Green's functions for layered media are used to derive polarimetric backscattering coefficients under the distorted Born approximation. The ellipsoidal shape of the scatterers gives rise to nonzero cross-polarized returns from the untilted anisotropic medium in the first-order approximation. Effects of rough interfaces are estimated by an incoherent addition method. Theoretical results and experimental data are matched at 9 GHz for thick first-year sea ice with a bare surface and with a snow cover at Point Barrow, Alaska. The model is then used to study the sensitivity of polarimetric backscattering coefficients with respect to correlation lengths representing the geometry of brine inclusions. Polarimetric signatures of bare and snow-covered sea ice are also simulated based on the model to investigate effects of different scattering mechanisms.

Nghiem, S. V.↗

Mesoscale to microscale wind farm flow modeling and evaluation

The increasing size of wind turbines, with rotors already spanning more than 150 m diameter and hub heights above 100 m, requires proper modeling of the atmospheric boundary layer (ABL) from the surface to the free atmosphere. Furthermore, large wind farm arrays create their own boundary layer structure with unique physics. This poses significant challenges to traditional wind engineering models that rely on surface-layer theories and engineering wind farm models to simulate the flow in and around wind farms. However, adopting an ABL approach offers the opportunity to better integrate wind farm design tools and meteorological models. The challenge is how to build the bridge between atmospheric and wind engineering model communities and how to establish a comprehensive evaluation process that identifies relevant physical phenomena for wind energy applications with modeling and experimental requirements. A framework for model verification, validation, and uncertainty quantification is established to guide this process by a systematic evaluation of the modeling system at increasing levels of complexity. In terms of atmospheric physics, ‘building the bridge’ means developing models for the so-called ‘terra incognita,’ a term used to designate the turbulent scales that transition from mesoscale to microscale. This range of scales within atmospheric research deals with the transition from parameterized to resolved turbulence and the improvement of surface boundary-layer parameterizations. The coupling of meteorological and wind engineering flow models and the definition of a formal model evaluation methodology, is a strong area of research for the next generation of wind conditions assessment and wind farm and wind turbine design tools. Some fundamental challenges are identified in order to direct future research in this area.

17 WIND ENERGY↗

Magnetic and electrical control of engineered materials

Methods, systems, and devices are disclosed for controlling the magnetic and electrical properties of materials. In one aspect, a multi-layer structure includes a first layer comprising a ferromagnetic or ferrimagnetic material, and a second layer positioned within the multi-layer structure such that a first surface of the first layer is in direct physical contact with a second surface of the second layer. The second layer includes a material that undergoes structural phase transitions and metal-insulator transitions upon experiencing a change in temperature. One or both of the first and second layers are structured to allow a structural phase change associated with the second layer cause a change magnetic properties of the first layer.

36 MATERIALS SCIENCE↗

Composition and physical properties of the Asian Tropopause Aerosol Layer and the North American Tropospheric Aerosol Layer: Composition of ATAL and NATAL

Recent studies revealed layers of enhanced aerosol scattering in the upper troposphere and lower stratosphere over Asia (Asian Tropopause Aerosol Layer (ATAL)) and North America (North American Tropospheric Aerosol Layer (NATAL)). We use a sectional aerosol model (Community Aerosol and Radiation Model for Atmospheres (CARMA)) coupled with the Community Earth System Model version 1 (CESM1) to explore the composition and optical properties of these aerosol layers. The observed aerosol extinction enhancement is reproduced by CESM1/CARMA. Both model and observations indicate a strong gradient of the sulfur-to-carbon ratio from Europe to the Asia on constant pressure surfaces. We found that the ATAL is mostly composed of sulfates, surface-emitted organics, and secondary organics; the NATAL is mostly composed of sulfates and secondary organics. In conclusion, the model also suggests that emission increases in Asia between 2000 and 2010 led to an increase of aerosol optical depth of the ATAL by 0.002 on average which is consistent with observations.

54 ENVIRONMENTAL SCIENCES↗

Building partnerships for development of sustainable energy systems with atmospheric measurements

Atmospheric dynamics often play a critical role in the sustainability and reliability of diverse forms of energy production. This is especially true for the growing number of renewable energy deployments that harness aspects of the environment for power production. While the University of Memphis has a strong research background in energy systems, we have little experience working with the Earth and Environmental Systems Science Division (EESSD) and their associated User Facilities. Of particular interest to us is the Atmospheric Science Research and the Atmospheric Radiation Measurement (ARM) user facility to address surface-boundary layer interactions and physical phenomena. One of the major challenges for understanding and developing energy systems and management platforms is accurate modeling/forecasting of atmospheric conditions across disparate spatial and temporal scales. These conditions are often required to understand the lowest levels of the atmospheric boundary layer, but are also important to understand higher atmospheric conditions where aerosols affect cloud development. The objective of this work was to develop partnerships with national laboratories for collaboration on environmental science and its intersection with sustainable energy systems, as well as to leverage the ARM user facility data repositories to enhance our research capabilities in energy systems and their inter-dependence on environmental systems for future engagement with EESSD. Specifically, we accomplished these objectives by (1) developing collaborations with Oakridge National Laboratory ARM Data Science and Integration Group which resulted in student internships, (2) employed ARM data to develope modeling of the atmospheric boundary layer optical turbulence, and (3) optimally-sized large-scale renewable energy systems and their associated energy storage systems with ARM repository data.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Convective Instability in Ice I: Application to Callisto and Ganymede

Laboratory experiments measuring ice rheology suggest that it deforms under the influence of several nonNewtonian creep mechanisms, where the viscosity depends on both strain rate and temperature [Goldsby & Kohlstedt, 2001]. Whether or not a fluid with a purely temperature-dependent viscosity convects can be determined by comparing the Rayleigh number of the system to the critical Rayleigh number (Racr), which depends on rheological, thermal, and physical parameters of the fluid layer. However, in a nonNewtonian fluid where viscosity depends on the strain rate (i.e. velocity), convection can only occur if a temperature or velocity perturbation is issued to the system to lower the viscosity and permit fluid motions. Therefore, whether convection occurs in an ice I layer depends on initial conditions, in addition to rheological, thermal, and physical properties of the layer. We show new results for a scaling between the critical Rayleigh number and perturbation amplitude for grain boundary sliding rheology. This scaling can be used to determine the conditions required to initiate convection in the ice I shell of a generic icy satellite. We use this scaling to judge the convective instability of Ganymede and Callisto's ice shells in the absence of tidal dissipation.

Barr, A. C.↗

Electronic structure calculations of twisted multi-layer graphene superlattices

Quantum confinement endows two-dimensional (2D) layered materials with exceptional physics and novel properties compared to their bulk counterparts. Although certain two- and few-layer configurations of graphene have been realized and studied, a systematic investigation of the properties of arbitrarily layered graphene assemblies is still lacking. We introduce theoretical concepts and methods for the processing of materials information, and as a case study, apply them to investigate the electronic structure of multi-layer graphene-based assemblies in a high-throughput fashion. We provide a critical discussion of patterns and trends in tight binding band structures and we identify specific layered assemblies using low-dispersion electronic bands as indicators of potentially interesting physics like strongly correlated behavior. A combination of data-driven models for visualization and prediction is used to intelligently explore the materials space. This work more generally aims to increase confidence in the combined use of physics-based and data-driven modeling for the systematic refinement of knowledge about 2D layered materials, with implications for the development of novel quantum devices.

36 MATERIALS SCIENCE↗

Structure–Capacitance Relationships of Graphene/Ionic Liquid Electrolyte Double Layers

The differential capacitance profile of electrochemical interfaces reflects the physical properties of the double layer. For carbon electrodes and ionic liquid based electrolytes, these capacitance profiles are not fully understood. In this work, we utilize constant voltage molecular dynamics simulations to compute differential capacitance profiles of ionic liquids [BMIm + ][BF 4 - ] and [BMIm + ][TFSI - ] mixed with acetonitrile and 1,2-dichloroethane, at model graphene electrodes. We find that both pure and 10% mole fraction ionic liquid electrolytes exhibit camel shaped capacitance profiles with two peaks on either side of a minimum centered at the potential of zero charge. This profile shape results from electric field induced rearrangement of ion structure within the inner layer closest to the electrode interface. At low potential, the ionic liquid inner layer is concentrated with non-polar tri-fluoromethyl and butyl functional groups of the anions and cations, corresponding to the minimum of the capacitance profiles. With increasing voltage, electrostatic interactions of polar/charged functional groups with the electrode surface compete with these non-polar interactions, leading to ion rearrangement that increases the inner layer charge density and results in higher capacitance. After the ion restructuring is complete, the response saturates and capacitance diminishes. The presence of organic solvent significantly changes the composition of the inner layer. For example, strong non-polar interactions between dichloroethane molecules and the graphene surface substantially block ion/electrode contact at moderate potentials. Overall, our simulations highlight the dynamic nature of the inner region of organic electrolyte double layers, and the sensitive dependence on electrolyte composition and applied voltage.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tailoring physical properties of crystals through synthetic temperature control: A case study for new polymorphic NbFeT e 2 phases

Growth parameters play a significant role in the crystal quality and physical properties of layered materials. Here we present a case study on a van der Waals magnetic NbFeTe 2 material. Two different types of polymorphic NbFeTe 2 phases, synthesized at different temperatures, display significantly different behaviors in crystal symmetry, electronic structure, electrical transport, and magnetism. While the phase synthesized at low temperature showing behavior consistent with previous reports, the new phase synthesized at high temperature, has completely different physical properties, such as metallic resistivity, long-range ferromagnetic order, anomalous Hall effect, negative magnetoresistance, and distinct electronic structures. Neutron diffraction reveals out-of-plane ferromagnetism below 70 K, consistent with the electrical transport and magnetic susceptibility studies. Finally, our work suggests that simply tuning synthetic parameters in a controlled manner could be an effective route to alter the physical properties of existing materials potentially unlocking new states of matter, or even discovering new materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Fuel Thermo-physical Characterization Project: Evaluation of Models to Calculate Thermal Diffusivity of Layered Composites

The Office of Material Management and Minimization Fuel Thermo-physical Characterization Project at Pacific Northwest National Laboratory (PNNL) is tasked with using PNNL facilities and processes to receive irradiated low enriched uranium-molybdenum fuel plate samples and perform analyses in support of the Office of Material Management and Minimization Reactor Conversion Program. This work is in support of the Fuel Development Pillar that is managed by Idaho National Laboratory. A key portion of the scope associated with this project was to measure the thermal properties of fuel segments harvested from plates that were irradiated in the Advanced Test Reactor. Thermal diffusivity of samples prepared from the fuel segments was measured using laser flash analysis. Two models, one developed by PNNL and the other developed by the Technische Universität München (TUM), were evaluated to extract the thermal diffusivity of the uranium-molybdenum alloy from measurements made on the irradiated, layered composites. The experimental data of the “TC” irradiated fuel segment was evaluated using both models considering a three-layer and five-layer system. Both models are in acceptable agreement with one another and indicate that the zirconium diffusion barrier has a minimal impact on the overall thermal diffusivity of the monolithic U-Mo fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Method and apparatus for two-layer copy-on-write

A system, apparatus and method are provided in which a range of virtual memory addresses and a copy of that range are mapped to the same first system address range in a data processing system until an address in the virtual memory address range, or its copy, is written to. The common system address range includes a number of divisions. Responsive to a write request to an address in a division of the common address range, a second system address range is generated. The second system address range is mapped to the same physical addresses as the first system address range, except that the division containing the address to be written to and its corresponding division in the second system address range are mapped to different physical addresses. First layer mapping data may be stored in a range table buffer and updated when the second system address range is generated.

97 MATHEMATICS AND COMPUTING↗

Idealized Large-Eddy Simulations of Stratocumulus Advecting over Cold Water. Part I: Boundary Layer Decoupling

Abstract We explore the decoupling physics of a stratocumulus-topped boundary layer (STBL) moving over cooler water, a situation mimicking warm-air advection (WADV). We simulate an initially well-mixed STBL over a doubly periodic domain with the sea surface temperature decreasing linearly over time using the System for Atmospheric Modeling large-eddy model. Due to the surface cooling, the STBL becomes increasingly stably stratified, manifested as a near-surface temperature inversion topped by a well-mixed cloud-containing layer. Unlike the stably stratified STBL in cold-air advection (CADV) that is characterized by cumulus coupling, the stratocumulus deck in the WADV is unambiguously decoupled from the sea surface, manifested as weakly negative buoyancy flux throughout the subcloud layer. Without the influxes of buoyancy from the surface, the convective circulation in the well-mixed cloud-containing layer is driven by cloud-top radiative cooling. In such a regime, the downdrafts propel the circulation, in contrast to that in CADV regime for which the cumulus updrafts play a more determinant role. Such a contrast in convection regime explains the difference in many aspects of the STBLs including the entrainment rate, cloud homogeneity, vertical exchanges of heat and moisture, and lifetime of the stratocumulus deck, with the last being subject to a more thorough investigation in Part II. Finally, we investigate under what conditions a secondary stratus near the surface (or fog) can form in the WADV. We found that weaker subsidence favors the formation of fog whereas a more rapid surface cooling rate does not. Significant Statement The low-lying blanketlike clouds, called stratocumulus (Sc), reflect much incoming sunlight, substantially modulating Earth’s temperature. While much is known about how the Sc evolves when it moves over warmer water, few studies examine the opposite situation of Sc moving over colder water. We used a high-resolution numerical model to simulate such a case. When moving over cold water, the Sc becomes unambiguously decoupled from the water surface, distinctive from its warm counterpart in which the Sc interacts with the water surface via intermittent cauliflower-like clouds called cumulus clouds. Such decoupling influences many aspects of the Sc–sea surface system, which combine to alter the ability of the Sc to reflect sunlight, thereby influencing the climate. This work laid the foundation for future work that quantifies the contribution of such a decoupled Sc regime to Earth’s radiative budget and climate change.

54 ENVIRONMENTAL SCIENCES↗

Embedding physics domain knowledge into a Bayesian network enables layer-by-layer process innovation for photovoltaics

Process optimization of photovoltaic devices is a time-intensive, trial-and-error endeavor, which lacks full transparency of the underlying physics and relies on user-imposed constraints that may or may not lead to a global optimum. Herein, we demonstrate that embedding physics domain knowledge into a Bayesian network enables an optimization approach for gallium arsenide (GaAs) solar cells that identifies the root cause(s) of underperformance with layer-by-layer resolution and reveals alternative optimal process windows beyond traditional black-box optimization. Our Bayesian network approach links a key GaAs process variable (growth temperature) to material descriptors (bulk and interface properties, e.g., bulk lifetime, doping, and surface recombination) and device performance parameters (e.g., cell efficiency). For this purpose, we combine a Bayesian inference framework with a neural network surrogate device-physics model that is 100× faster than numerical solvers. With the trained surrogate model and only a small number of experimental samples, our approach reduces significantly the time-consuming intervention and characterization required by the experimentalist. As a demonstration of our method, in only five metal organic chemical vapor depositions, we identify a superior growth temperature profile for the window, bulk, and back surface field layer of a GaAs solar cell, without any secondary measurements, and demonstrate a 6.5% relative AM1.5G efficiency improvement above traditional grid search methods.

14 SOLAR ENERGY↗

On the propagation of a light pulse in the “transparency window” of a medium with population inversion

The propagation of a light pulse through a layer of a substance with population inversion and, correspondingly, with an anomalous dispersion in the transparency range is considered. It is shown that, when the wave packet approaches the layer of the substance with a strong anomalous dispersion, two additional wave packets arise at the rear boundary of the layer. One of these packets has a negative energy and moves in the layer from its rear to the front boundary, while the other packet moves away from the rear boundary of the layer into a vacuum. As the initial wave packet comes into contact with the front boundary of the layer of the substance, it meets the packet of the negative energy. As a result, the two packets annihilate one another, after which only one packet remains, which moves away from the layer.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A monitoring campaign for Luhman 16AB. I. Detection of resolved near-infrared spectroscopic variability

We report resolved near-infrared spectroscopic monitoring of the nearby L dwarf/T dwarf binary WISE J104915.57–531906.1AB (Luhman 16AB), as part of a broader campaign to characterize the spectral energy distribution and temporal variability of this system. A continuous 45 minute sequence of low-resolution IRTF/SpeX data spanning 0.8-2.4 μm were obtained, concurrent with combined-light optical photometry with ESO/TRAPPIST. Our spectral observations confirm the flux reversal of this binary, and we detect a wavelength-dependent decline in the relative spectral fluxes of the two components coincident with a decline in the combined-light optical brightness of the system over the course of the observation. These data are successfully modeled as a combination of achromatic (brightness) and chromatic (color) variability in the T0.5 Luhman 16B, consistent with variations in overall cloud opacity; and no significant variability was found in L7.5 Luhman 16A, consistent with recent resolved photometric monitoring. We estimate a peak-to-peak amplitude of 13.5% at 1.25 μm over the full light curve. Using a simple two-spot brightness temperature model for Luhman 16B, we infer an average cold covering fraction of ≈30%-55%, varying by 15%-30% over a rotation period assuming a ≈200-400 K difference between hot and cold regions. We interpret these variations as changes in the covering fraction of a high cloud deck and corresponding 'holes' which expose deeper, hotter cloud layers, although other physical interpretations are possible. A Rhines scale interpretation for the size of the variable features explains an apparent correlation between period and amplitude for Luhman 16B and the variable T dwarfs SIMP 0136+0933 and 2MASS J2139+0220, and predicts relatively fast winds (1-3 km s{sup –1}) for Luhman 16B consistent with light curve evolution on an advective time scale (1-3 rotation periods). The strong variability observed in this flux reversal brown dwarf pair supports the model of a patchy disruption of the mineral cloud layer as a universal feature of the L dwarf/T dwarf transition.

79 ASTRONOMY AND ASTROPHYSICS↗