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At least 1,009 records · Page 56

Diffraction by a finite strip

A new approach is presented to diffraction problems involving plane strip barriers or slit apertures. These are problems that display the effects of multiple interacting edges. The approach taken here provides exact, compact solutions. The theory is introduced through a series of examples that are, in fact, the 'standard' problems of the subject, diffraction of a plane oblique wave by a slit, for example. In each case, the solutions are found to depend explicitly on a single 'special' function and its Fourier transform. These fundamental functions are described, with the emphasis placed on practical computational methods. The example problems are all couched in the language of acoustics.

Williams, M. H.↗

A Model Predictive Control Approach for In-Flight Acoustic Constraint Compliance

Vehicle noise remains one of the major barriers to public acceptance of Urban Air Mobility-class aircraft. This work focuses on motion planning for aircraft in noise-sensitive areas. A nonlinear Model Predictive Path Integral~(MPPI) control law is used to generate a finite-horizon trajectory that satisfies acoustic level constraints at a set of observer locations. The MPPI framework places no restrictions on the class of state-dependent cost functionals that can be employed, making it well-suited for use with sophisticated acoustic models and metrics, in addition to dynamic and mission-relevant constraints. The proposed control law is also suitable for implementation in a real-time application. A simulation example demonstrates the ability of the controller to modify the flight trajectory in order to satisfy acoustic constraints at multiple measurement locations.

Aircraft motion planning↗

Defect characterization and charge transport measurements in high-resolution Ni/n-4H-SiC Schottky barrier radiation detectors fabricated on 250 μ m epitaxial layers

Advances in the growth processes of 4H-SiC epitaxial layers have led to the continued expansion of epilayer thickness, allowing for the detection of more penetrative radioactive particles. In this work, we report the fabrication and characterization of high-resolution Schottky barrier radiation detectors on 250 μm thick n-type 4H-SiC epitaxial layers, the highest reported thickness to date. Several 8 × 8 mm 2 detectors were fabricated from a diced 100 mm diameter 4H-SiC epitaxial wafer grown on a conductive 4H-SiC substrate with a mean micropipe density of 0.11 cm -2 From the Mott–Schottky plots, the effective doping concentration was found to be in the range (0.95–1.85) × 10 14 cm -3 , implying that full depletion could be achieved at ~5.7 kV (0.5 MV/cm at the interface). The current-voltage characteristics demonstrated consistently low leakage current densities of 1–3 nA/cm 2 at a reverse bias of -800 V. This resulted in the pulse-height spectra generated using a 241Am alpha source (5486 keV) manifesting an energy resolution of less than 0.5% full width at half maximum (FWHM) for all the detectors at -200 V. The charge collection efficiencies (CCEs) were measured to be 98–99% with no discernable correlation to the energy resolution. A drift-diffusion model fit to the variation of CCE as a function of bias voltage, revealed a minority carrier diffusion length of ~10 μm. Deep level transient spectroscopy measurements on the best resolution detector revealed that the excellent performance was the result of having ultralow concentrations of the order of 1011 cm-3 lifetime limiting defects—Z 1/2 and EH 6/7 .

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Developing Standards for AI/ML Systems in Civil Aviation: Challenges and Barriers

The inability to establish appropriate assurance methods for AI/ML components in safety critical systems leaves us unable to effectively manage the risks and benefits of such systems. It drives cost of development for systems with AI/ML components uneconomically high, it delays the adoption of systems with AI/ML components at scale, and it can result in catastrophic consequences in terms of the safety of systems with AI/ML components. In this presentation we will explore what constitutes sufficient scientific-based evidence to substantiate a safety claim related to an AI/ML component performing a safety-critical function.

AI/ML Standards↗

Adsorption and Surface Diffusion of Metals on α-Al2O3 for Advanced Manufacturing Applications

Abstract The adsorption and diffusion of Mo and Nb adatoms on the $$\alpha$$ α -Al 2 O 3 (0001) surface were explored using density functional theory-based methods. Adsorption energies of Mo and Nb adatoms at minima sites on the surface were determined. Mo and Nb adatoms prefer to adsorb to the same locations on the surface, and larger adsorption energies calculated for Nb compared to Mo indicate that Nb adatom-surface interactions are stronger than Mo. Using minima adsorption sites as initial and final locations for surface diffusion, energy barriers for diffusion were calculated using the nudged elastic band method. Overall, Mo and Nb follow roughly the same diffusion paths. The diffusion pre-factors for Mo and Nb are similar; however, Mo diffusion has a lower energy barrier and thus a larger diffusion coefficient compared with Nb. These results provide insight into the role of surface diffusion of Mo and Nb adatoms during advanced manufacturing processes.

Biaggne, Austin (ORCID:0000000328074960)↗

Plasmon-Induced CO 2 Conversion on Al@Cu 2 O: A DFT Study

In plasmonic catalysis, localized surface plasmon was leveraged to drive chemical reactions. This approach is promising for catalyzing many challenging reactions at relatively low temperatures and pressures. We apply density functional calculations to provide the insight for the mechanism of plasmon-induced direct CO 2 dissociation on an Al@Cu 2 O core-shell structure, which was observed in a previous experimental study. We show that the interaction of Cu 2 O with CO 2 results in the accessible antibonding states of the adsorbed CO 2 in the range of visible light. Though the intrinsic activation barrier for direct CO 2 dissociation is as high as 3.6 eV, we find that an effective reaction barrier of CO 2 dissociation under photon excitation could be reduced by 2 eV. We also show that the charge transfer is more pronounced in the final state of the dissociation due to the strong hybridization of the dissociated species with Cu 2 O. These results thus provide an explanation for the visible-light-induced direct CO 2 dissociation at relatively low temperature and under ambient pressure. This finding also shows the promising impact of plasmonic catalysis in mitigating carbon emission.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Assessing the Activity of Ni Clusters Supported on TiC(001) toward CO 2 and H 2 Dissociation

Small Ni particles supported on TiC(001) were shown to display a very high activity for the catalytic hydrogenation of CO 2 but the underlying chemistry is, to a large extent, unknown. Here, by means of periodic density functional theory (DFT) calculations with the BEEF–vdW functional, we explore the adsorption and subsequent dissociation of CO 2 and H 2 on several Ni n clusters ( n = 4, 9, 13, and 16) supported on TiC(001) and compare the results to those obtained for the bare Ni(111) and TiC(001) surfaces using exactly the same computational approach. The calculations reveal that the Ni n /TiC system exhibits stronger adsorption energies and lower dissociation energy barriers for CO 2 and H 2 than the bare Ni(111) and TiC(001) surfaces. Furthermore, this is in line with the experimental finding evidencing that the Ni/TiC system has a catalytic activity higher than that of the separated Ni and TiC constituents. In addition, the calculated results show that two-dimensional (2D) supported clusters adsorb CO 2 and H 2 stronger than the three-dimensional (3D) supported clusters and also the 2D clusters exhibit lower energy barriers for CO 2 dissociation. Within the 2D supported clusters, larger particles feature slightly stronger adsorption energies and lower CO 2 dissociation energy barriers. Finally, H 2 dissociation proceeds with a very low energy barrier on all of the studied models, which makes these novel systems potential good candidates for hydrogenation reactions.

36 MATERIALS SCIENCE↗

Single-hole couplings in GaAs/AlGaAs double dots probed with transport and EDSR spectroscopy

Here, we report a detailed study of the tunnel barriers within a single-hole GaAs/AlGaAs double quantum dot device (DQD). For quantum information applications as well as fundamental studies, careful tuning and reliable measurements of the barriers are important requirements. In order to tune a DQD device adequately into the single-hole electric dipole spin resonance regime, one has to employ a variety of techniques to cover the extended range of tunnel couplings. In this work, we demonstrate four separate techniques, based upon charge sensing, quantum transport, time-resolved pulsing, and electron dipole spin resonance spectroscopy to determine the couplings as a function of relevant gate voltages and magnetic field. Measurements were performed under conditions of both symmetric and asymmetric tunnel couplings to the leads. Good agreement was observed between different techniques when measured under the same conditions. The results indicate that even in this relatively simple circuit, the requirement to tune multiple gates and the consequences of real potential profiles result in non-intuitive dependencies of the couplings as a function of the plunger gate voltage and the magnetic field.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Analyzing and Exploring Training Recipes for Large-Scale Transformer-Based Weather Prediction

Abstract The rapid rise of deep learning (DL) in numerical weather prediction (NWP) has led to a proliferation of models which forecast atmospheric variables with comparable or superior skill than traditional physics-based NWP. However, among these leading DL models, there is a wide variance in both the training settings and architecture used. Further, the lack of thorough ablation studies makes it hard to discern which components are most critical to success. In this work, we show that it is possible to attain high forecast skill even with relatively off-the-shelf architectures, simple training procedures, and moderate compute budgets. Specifically, we train a minimally modified Swin Transformer V2 (SwinV2) on ERA5 data and find that it attains superior skill in terms of mean-square errors of deterministic forecasts when compared against the European Centre for Medium-Range Weather Forecasts’ Integrated Forecasting System (IFS). Almost all DL–NWP systems share a core set of hyperparameters and design decisions. To aid and expedite future DL–NWP research, we present an in-depth, systematic exploration of different loss functions, model sizes and depths, patch sizes, and multistep training objectives. We also examine the model performance with metrics beyond the typical accuracy (ACC) and RMSE and investigate how the performance scales with model size. Through our open-source code, scoring pipelines, and models, we share our findings on key aspects of the training pipeline. These ablations reduce the necessity for expensive hyperparameter tuning and lower the barrier to entry for future DL–NWP research. Significance Statement This study investigates the potential of using large-scale transformer-based models for weather prediction, showing that it is possible to achieve high forecast accuracy with simpler, off-the-shelf architectures. By training a minimally modified SwinV2 transformer on ERA5 data, we show that the model achieves competitive forecast skill in terms of mean-square error for key variables, outperforming the European Centre for Medium-Range Weather Forecasts’ Integrated Forecasting System (IFS) at all lead times. Our findings suggest that effective training strategies, such as multistep fine-tuning and channel-weighted losses, significantly enhance the model’s performance. However, we also highlight that these improvements come with trade-offs in other areas, such as ensemble spread and high-frequency spatial detail. This work highlights the promise of deep learning in improving weather forecasts, which could lead to better preparedness and response to weather events, ultimately benefiting society by providing more reliable weather predictions.

Willard, Jared D. [Lawrence Berkeley National Labo↗

Wood Decomposition: Understanding Processes Regulating Carbon Transfer to Soil Carbon Pools Using FACE Wood at Multiple Scales

Dead wood comprises approximately 20% of forest biomass. While it is widely recognized for its role in ecosystem functions relative to habitat and nutrient cycling, there are considerable uncertainties associated with its role in the forest carbon (C) cycle. The principal uncertainty is whether dead wood contributes to the soil C pool. With little supporting evidence, the presumption is that C in wood is respired back to the atmosphere through decomposition processes. The inability to attribute forest soil C to its source components has been a barrier to addressing this important forest carbon cycle question. The U.S. Dept. of Energy’s Free Air CO 2 Enrichment (FACE) experiment produced wood that has a distinct δ 13 C signature that can be used to trace its fate through organic matter decomposition processes. Using two hardwood species (aspen, birch) from the Rhinelander FACE site and pine from the Duke FACE site, the FACE Wood Decomposition Experiment (FWDE) was established in 2011 to provide the foundation for addressing wood decomposition and its associated processes at the continental scale. Plots were installed on nine experimental forests representing a range in bioclimatic forest conditions within the continental U.S. Each identical plot has logs of the three species incubating on the soil surface and pine logs suspended in the air, representing standing dead wood. Abiotic conditions are monitored continuously, and soil and forest conditions characterized. Logs on the sites have been measured every two years to assess decay. This project was initiated in 2016 with specific objectives to: (a) determine whether dead wood C contributes to the soil C pool, (b) assess the fungal community composition mediating the decay, (c) assess the interactions of termites with microbial decay, and (d) develop a mechanistic model to simulate wood decomposition. The principal field sampling was conducted in 2017; correspondingly, the results reported here represent six years of decomposition. Wood decomposition varied from 13 to 75 % loss across the bioclimatic gradient. Sites in the southeastern U.S. coastal plain and piedmont had fastest decomposition rates for each of the species. In contrast sites in the Rocky Mountains had the slowest decay rates, which were associated with cold temperatures. Standing deadwood decomposes at a much slower rate than logs on the soil surface; a response due to differences in wood moisture content. Wood carbon was measured in the mineral soil across each of the sites; accordingly, this is the first study to affirm that a portion of the wood C does become part of the soil C pool. Averaged across the FWDE sites, approximately 1.4% of the soil C in the upper 10 cm of the mineral soil directly beneath the log was derived from the deadwood; within 50 cm of the log, wood C accounted for an average of 2.1%. These results demonstrate that the contribution of deadwood to the soil C pool is a soil volume surrounding the log; and it’s likely a larger volume than what we sampled. We also hypothesized that there would be more wood C in the mineral soil when termites were present. However, that hypothesis wasn’t supported by measurements on the Santee Experimental Forest termite exclusion (SEF-TX) plots under FACE logs that incubated for 6 years. Across all the sites, the majority of the wood C was transferred to the atmosphere. Approximately 7,000 fungal species were sequenced. The fungal communities were different among each of the sites suggesting local colonization; interestingly, within sites the three species also exhibited differences in fungal community composition. White rot was the dominant fungal form in pine and hardwood, which yields less lignin in the wood residue. Brown rot occurred in approximately 20% of the pine and aspen logs, and it did not occur in birch logs. The occurrence of brown rot was only weakly correlated to site factors. We conducted two additional experiments to assess the effects of termites on wood decomposition and the associated interactions with the fungal community. Pine and birch logs were incubated on the Santee Experimental Forest termite exclusion plots in upland and riparian settings. There was no difference in decay between areas where termites were able colonize and plots where they had been excluded. Highly variable foraging by termites was a primary contributor the result. Correspondingly, fungal communities did not vary on logs incubated among the two treatments, but they did reflect site and species differences. The second experiment was conducted on each of the nine FWDE sites where pine and birch wood blocks were incubated for two years with and without a wrapping designed to exclude termites and other arthropods. The effects of termites on wood decomposition could be confirmed on two of the four sites known to have subterranean termites. On the two southeastern sites, termites contributed approximately 8% to mass loss in pine blocks over two years. A major factor clouding the role of termites in wood decomposition is the inability to assess the time, duration, and intensity of the foraging with the logs. Another uncertainty is related to whether a piece of wood will be foraged. A process-based wood decomposition model was developed representing biological processes mediated by fungi, bacteria, termites, beetles, as well as physical and chemical processes. The Coarse Wood Decomposition Model (CWDM) was parameterized based on a thorough review of the literature and it was validated using data from the FWDE. In the initial setup, the model considers softwoods and hardwoods groups, as opposed to individual species. Sensitivity analyses incorporating climate data from 89 locations in North America demonstrated that CWDM was stable from the tropics to the boreal zone. Model calibration and validation showed it to perform very well. The CWDM is poised for additional testing with subsequent FWDE data as well as other data sets, and it is available for incorporation into forest biogeochemical models or DOEs Earth System Modeling framework.

54 ENVIRONMENTAL SCIENCES↗

A Model Predictive Control Approach for In-Flight Acoustic Constraint Compliance

Vehicle noise remains one of the major barriers to public acceptance of Urban Air Mobility class aircraft. This work focuses on motion planning for aircraft in noise-sensitive areas. A nonlinear Model Predictive Path Integral (MPPI) control law is used to generate a finite horizon trajectory that satisfies acoustic level constraints at a set of (three-dimensional) observer locations. The MPPI framework places no restrictions on the class of state-dependent cost functionals that can be employed, making it well-suited for use with sophisticated acoustic models and metrics, in addition to dynamic and mission-relevant constraints. The model predictive control architecture is also suitable for implementation in a real-time application. A simulation example demonstrates the ability of the controller to modify the flight trajectory in order to satisfy acoustic constraints at multiple measurement locations.

acoustically-aware vehicle↗

Multistability of isolated and hydrogenated Ga–O divacancies in β–Ga 2 O 3

This work systematically explores 19 unique configurations of the close-associate Ga–O divacancies (V Ga V O ) in β–Ga 2 O 3 , including their complexes with H impurities, using hybrid functional calculations. Interestingly, most configurations are found to retain the negative-U behavior of V O , as they exhibit a thermodynamic (–/3–) charge-state transition level energetically located in the upper part of the band gap, where the 3– charge state is associated with the formation of a Ga–Ga dimer. The energy positions of the thermodynamic (–/3–) charge-state transition levels divide the divacancy configurations into three different groups, which can be understood from the three possible Ga–Ga dimerizations resulting from the tetrahedral and octahedral Ga sites. The relative formation energies of the different divacancy configurations, and hence the electrical activity of the divacancies, is found to depend on the Fermi-level position, and the energy barriers for transformation between different divacancy configurations are explored from nudged elastic band calculations. Hydrogenation of the divacancies is found to either passivate their negative-U charge-state transition levels or shift them down in Fermi level position, depending on whether the H resides at V O or forms an O–H bond at V Ga , respectively. Finally, the divacancy is discussed as a potential origin of the so-called E$^{*}_{2}$ center previously observed by deep-level transient spectroscopy.

36 MATERIALS SCIENCE↗

Hydrogen trapping energetics at BCC iron-helium interfaces

Density functional theory (DFT) calculations have been performed to assess the trapping and segregation strength of hydrogen (H) to helium (He) interfaces in BCC (Fe) as a function of He density and surface orientation. The He density ranges from 0 to 2 He/V which corresponds to equilibrium bubbles that are expected to form in the structural components in a fusion reactor environment. The DFT calculations consist of a slab of BCC metal and an initial lattice of FCC He. Here, the report on the binding energy of H to these interfaces as well as the migration barriers into and away from the surface, which together provide information on the de-trapping energy for H at He bubbles. It was found that the binding energy of H to He-Fe interfaces decreases with increasing He density. Migration barriers are also modified due to the He density, which are sensitive to the surface orientation as well as the diffusion pathway. These results provide valuable first-principles energetics that are necessary for higher-order, mesoscale models, and provide insight into the extent to which He bubbles may trap tritium in fusion structural materials.

42 ENGINEERING↗

Computational Study of an Iron(II) Polypyridine Electrocatalyst for CO 2 Reduction: Key Roles for Intramolecular Interactions in CO 2 Binding and Proton Transfer

A solar-driven conversion of CO 2 into fuels by artificial photosynthesis would not only mitigate the greenhouse effect but also provide an alternative to obtain fuels in a renewable fashion. To this end, the new iron polypyridine catalyst [Fe(bpy NHEt PY2Me)L 2 ] 2+ (L = H 2 O, CH 3 CN) was recently developed for the electrochemical reduction of CO 2 to CO. Here, we performed density functional theory (DFT) electronic structure calculations to shed light on a possible pathway for CO 2 reduction and the origin of the selectivity between CO 2 reduction versus the hydrogen evolution reaction. The metal center remains Lewis acidic throughout the reduction process due to ligand loss and mainly ligand-based reduction stabilized by antiferromagnetic coupling to a high-spin Fe(II) center. This results in a high barrier for hydride formation but a facile addition and activation of CO 2 via an η 2 coordination and stabilizing hydrogen bonding by the amine group. The second unoccupied equatorial coordination site opens up the possibility for an intramolecular protonation with a coordinated water ligand. This facilitates protonation because not only CO 2 but also the proton source H 2 O is activated and properly aligned for a proton transfer due to the Fe-OH 2 bond; consequently, both protonation steps are facile. The moderate ligand field allows a rapid ligand exchange for a second intramolecular protonation step and facilitates an exergonic CO release. The lower selectivity of the related [Fe(bpy OH PY2Me)L 2 ] 2+ complex can be related to its more acidic second coordination sphere, which enables an intramolecular proton transfer that is kinetically competitive with CO 2 addition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The role of native defects and their diffusivity in CdTe

CdTe is a leading thin-film technology for solar-cell applications. Basic features such as the optimum band gap of 1.5 eV and simple manufacturing process have been driving the research on improving the current record efficiency of 22% for CdTe solar cells toward the theoretical limit of 32%. Low p-type doping and short carrier lifetimes in the CdTe absorber have been suggested as the main limiting factors and attributed to defect compensation and carrier recombination. Understanding the role of point defects and impurities in CdTe is crucial to solving these problems. Despite many years of research, the sources of compensation and the microscopic recombination mechanisms are still unclear. By using hybrid density functional calculations with spin-orbit coupling and large supercells, we investigate the electronic properties, the formation energies, and the diffusivities of the native defects in CdTe. As possible sources of compensation for p-type conductivity, we discuss the structural and electronic properties of Cd interstitial, Te vacancies, and TeCd antisites. The stability of each defect is discussed in terms of both the defect formation energy and the migration barrier. We also address possible mechanisms that lead to non-radiative recombination.

14 SOLAR ENERGY↗

Seal with Integrated Shroud for Androgynous Docking and Berthing

A specially configured seal system (see figure) has been developed and produced that provides a barrier to gas leakage between a pressurized module and its external environment. The seal system includes a shroud covering that both protects the sealing surface from its environment when not in use and retracts to expose the sealing surface when engaged. The seal system is constructed and arranged to mate with a replicate seal system or with a flat surface. When mated with a replicate seal system, the seal system functions when the two sealing surfaces are aligned or misaligned. The seal system can operate over a wide range of temperatures, limited only by the glass transition and melt temperatures of the material from which the sealing surface is manufactured.

Daniels, Christopher C.↗

Modulation Transfer Function of Infrared Focal Plane Arrays

Modulation transfer function (MTF) is the ability of an imaging system to faithfully image a given object. The MTF of an imaging system quantifies the ability of the system to resolve or transfer spatial frequencies. In this presentation we will discuss the detail MTF measurements of 1024x1024 pixels mid -wavelength and long- wavelength quantum well infrared photodetector, and 320x256 pixels long- wavelength InAs/GaSb superlattice infrared focal plane arrays (FPAs). Long wavelength Complementary Barrier Infrared Detector (CBIRD) based on InAs/GaSb superlattice material is hybridized to recently designed and fabricated 320x256 pixel format ROIC. The n-type CBIRD was characterized in terms of performance and thermal stability. The experimentally measured NE delta T of the 8.8 micron cutoff n-CBIRD FPA was 18.6 mK with 300 K background and f/2 cold stop at 78K FPA operating temperature. The horizontal and vertical MTFs of this pixel fully delineated CBIRD FPA at Nyquist frequency are 49% and 52%, respectively.

long-wave infrared↗

A Model Predictive Control Approach for In-Flight Acoustic Constraint Compliance

Vehicle noise remains one of the major barriers to public acceptance of Urban Air Mobility-class aircraft. This work focuses on motion planning for aircraft in noise-sensitive areas. A nonlinear Model Predictive Path Integral (MPPI) control law is used to generate a finite-horizon trajectory that satisfies acoustic level constraints at a set of (three-dimensional) observer locations. The MPPI framework places no restrictions on the class of state-dependent cost functionals that can be employed, making it well-suited for use with sophisticated acoustic models and metrics, in addition to dynamic and mission-relevant constraints. The model predictive control architecture is also suitable for implementation in a real-time application. A simulation example demonstrates the ability of the controller to modify the flight trajectory in order to satisfy acoustic constraints at multiple measurement locations.

acoustically-aware vehicle↗