Silver-functionalized silica aerogel for iodine capture: Adsorbent aging by NO[subscript 2] in spent
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Shen, Ziheng↗
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Emergent flat band electronic structure in a VSe 2 /Bi 2 Se 3 heterostructure
Flat band electronic states are proposed to be a fundamental tool to achieve various quantum states of matter at higher temperatures due to the enhanced electronic correlations. However, materials with such peculiar electronic states are rare and often rely on subtle properties of the band structures. Here, by using angle-resolved photoemission spectroscopy, we show the emergent flat band in a VSe 2 / Bi 2 Se 3 heterostructure. Our photoemission study demonstrates that the flat band covers the entire Brillouin zone and exhibits 2D nature with a complex circular dichroism. In addition, the Dirac cone of Bi 2 Se 3 is not reshaped by the flat band even though they overlap in proximity of the Dirac point. These features make this flat band distinguishable from the ones previously found. Thereby, the observation of a flat band in the VSe 2 / Bi 2 Se 3 heterostructure opens a promising pathway to realize strongly correlated quantum effects in topological materials.
36 MATERIALS SCIENCE↗
Finite-difference time-domain methods
The finite-difference time-domain (FDTD) method is a widespread numerical tool for full-wave analysis of electromagnetic fields in complex media and for detailed geometries. Applications of the FDTD method cover a range of time and spatial scales, extending from subatomic to galactic lengths and from classical to quantum physics. Technology areas that benefit from the FDTD method include biomedicine — bioimaging, biophotonics, bioelectronics and biosensors; geophysics — remote sensing, communications, space weather hazards and geolocation; metamaterials — sub-wavelength focusing lenses, electromagnetic cloaks and continuously scanning leaky-wave antennas; optics — diffractive optical elements, photonic bandgap structures, photonic crystal waveguides and ring-resonator devices; plasmonics — plasmonic waveguides and antennas; and quantum applications — quantum devices and quantum radar. This Primer summarizes the main features of the FDTD method, along with key extensions that enable accurate solutions to be obtained for different research questions. Additionally, hardware considerations are discussed, plus examples of how to extract magnitude and phase data, Brillouin diagrams and scattering parameters from the output of an FDTD model. Furthermore, the Primer ends with a discussion of ongoing challenges and opportunities to further enhance the FDTD method for current and future applications.
42 ENGINEERING↗
Updated Thermofluid Performance of the Simplified Flat Variant of the HEMJ
Our group has recently developed and studied “finger”-type divertors that are a simplified version of the helium-cooled modular divertor with multiple jets (HEMJ) using coupled computational fluid dynamics and thermal stress simulations. Such a simplified geometry could reduce complexity and cost given the large number of fingers required to cover the total divertor target area. Previous experimental studies for this simplified flat design reported lower heat transfer coefficients and higher pressure drops than the HEMJ, contrary to numerical predictions. Subsequent measurements determined that the original test section had significant dimensional variations in the jet exit holes. A new test section was therefore manufactured and tested in the Georgia Tech (GT) helium loop. The experimental results presented here for this test section at maximum heat flux of 7.1 MW/m 2 are in good agreement with numerical predictions. Correlations developed from these experimental data are extrapolated to predict the maximum heat flux that can be accommodated by the flat design and the coolant pumping power requirements under prototypical conditions. Lastly, numerical simulations are used to estimate the sensitivity of the flat design to geometric variations typical of manufacturing tolerances and variations in the gap width.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Stress-Induced Changes in Alternative Splicing Landscape in Rice: Functional Significance of Splice Isoforms in Stress Tolerance
Improvements in yield and quality of rice are crucial for global food security. However, global rice production is substantially hindered by various biotic and abiotic stresses. Making further improvements in rice yield is a major challenge to the rice research community, which can be accomplished through developing abiotic stress-resilient rice varieties and engineering durable agrochemical-independent pathogen resistance in high-yielding elite rice varieties. This, in turn, needs increased understanding of the mechanisms by which stresses affect rice growth and development. Alternative splicing (AS), a post-transcriptional gene regulatory mechanism, allows rapid changes in the transcriptome and can generate novel regulatory mechanisms to confer plasticity to plant growth and development. Mounting evidence indicates that AS has a prominent role in regulating rice growth and development under stress conditions. Several regulatory and structural genes and splicing factors of rice undergo different types of stress-induced AS events, and the functional significance of some of them in stress tolerance has been defined. Both rice and its pathogens use this complex regulatory mechanism to devise strategies against each other. This review covers the current understanding and evidence for the involvement of AS in biotic and abiotic stress-responsive genes, and its relevance to rice growth and development. Furthermore, we discuss implications of AS for the virulence of different rice pathogens and highlight the areas of further research and potential future avenues to develop climate-smart and disease-resistant rice varieties.
59 BASIC BIOLOGICAL SCIENCES↗
Spectrometry of Pasture Condition and Biogeochemistry in the Central Amazon
Regional analyses of Amazon cattle pasture biogeochemistry are difficult due to the complexity of human, edaphic, biotic and climatic factors and persistent cloud cover in satellite observations. We developed a method to estimate key biophysical properties of Amazon pastures using hyperspectral reflectance data and photon transport inverse modeling. Remote estimates of live and senescent biomass were strongly correlated with plant-available forms of soil phosphorus and calcium. These results provide a basis for monitoring pasture condition and biogeochemistry in the Amazon Basin using spaceborne hyperspectral sensors.
Asner, Gregory P.↗
European Service Module - Structural Test Article (E-STA) Building Block Test Approach and Model Correlation Observations
The Orion European Service Module - Structural Test Article (E-STA) underwent sine vibration testing in 2016 using the Mechanical Vibration Facility (MVF) multi-axis shaker system at NASA Glenn Research Center’s (GRC) Plum Brook Station (PBS) Space Power Facility (SPF). The main objective was to verify the structural integrity of the European Service Module (ESM) under sine sweep dynamic qualification vibration testing. A secondary objective was to perform a fixed-base modal survey, while E-STA was still mounted to MVF, in order to achieve a test correlate the finite element model (FEM). To facilitate the E-STA system level correlation effort, a building block test approach was implemented. Modal tests were performed on two major subassemblies, the crew module/launch abort structure (CM/LAS) and the crew module adapter (CMA) mass simulators. These subassembly FEMs were individually correlated and then integrated into the E-STA FEM prior to the start of the E-STA sine vibration test. This paper summarizes the modal testing and model correlation efforts of both of these subassemblies and how the building block approach assisted in the overall correlation of the E-STA FEM. This paper will also cover modeling practices that should be avoided, recommended instrumentation positioning on complex structures, and the importance of the FEM geometrically matching CAD in sufficient detail in order to adequately replicate internal load paths. The goal of this paper is to inform the reader of the hard earned lessons learned and pitfalls to avoid when applying a building block test approach.
Winkel, James P.↗
ACS3 - Flight Dynamics for A Solar Sail Technology Demonstration Mission
The NASA's Advanced Composite Solar Sail System (ACS3) mission consist of a spacecraft that will deploy an 80 m 2 solar sail in a 1000 km sun-synchronous orbit. The main objective of the mission is to demonstrate that the solar wind can impulse the spacecraft to change the semimajor-axis and obtain a different orbit altitude. The sail will be composed of a combination of composite materials with distinct properties, and it will be deployed with lightweight booms from a 12U CubeSat bus, developed by Nanoavionics. The spacecraft will be launched aboard an Electron launch vehicle from Rocket LAB Launch Complex in New Zealand no earlier than July 2023. This paper covers the orbital mechanics and navigation developments to support the mission, from the solar sail trajectory model to the actual flight dynamics system to provide the orbit determination analysis prior to flight. First, we introduce a description of our high-fidelity propagation that accounts for the solar radiation pressure to produce predictive ephemeris of the solar sail performance with several spacecraft attitude modes. As part of our results, we present plots of the expected altitudes achieved by the spacecraft once the solar sail is deployed under various assumptions of the solar weather. In addition to that, we present a full description of our orbit determination process which relies in GPS state vectors to accurately estimate the position and velocity uncertainties at a frequent cadence during the mission. The outcome of this process will be critical to achieving the objective of determining effective altitude change produced by the solar sail.
Solar Sail↗
The State of NOS3
The NASA Operational Simulator for Small Satellites (NOS3) showcases some of the Jon McBride Software Testing and Research (JSTAR) laboratories technologies on an open-source platform. NOS3 is a software digital twin providing a virtualized platform inside which you have your traditional flight software, ground software, environmental simulators, and middleware to keep all pieces in sync. NOS3 leverages the core Flight System (cFS), OpenC3 COSMOS, and NASA GSFC’s 42 software as the baseline to which additional research technologies can be developed. Current technologies to be demonstrated include NOS3 Igniter, constellation support, NASA JPL’s SYNOPSIS integration, and NASA GSFC’s OnAir. NOS3 Igniter is a GUI in which you can configure, build, and run your simulation. This along with improvements to the documentation and training available open source aims to reduce the ramp up time with new users and improve accessibility. As constellations introduce another level of complexity, it is important to ensure the baseline design reference mission covers all the basics required and allows users to experiment, understand, and test at all levels of the system. The Science Yield improvement via Onboard Prioritization and Summary of Information Systems (SYNOPSIS) is an open-source tool developed by NASA JPL to enable data prioritization and planning. GSFC’s Onboard Artificial Intelligence Research (OnAIR) enables custom algorithm development written in python to interface with the flight software allowing scientists to develop what they need for the next generation of missions and easily interface back to the traditional flight software. During the presentation, a review and demonstration of the above technologies is planned along with a roadmap.
NOS3↗
Improved silicon carbide for advanced heat engines
This is the second annual technical report entitled, Improved Silicon Carbide for Advanced Heat Engines, and includes work performed during the period February 16, 1986 to February 15, 1987. The program is conducted for NASA under contract NAS3-24384. The objective is the development of high strength, high reliability silicon carbide parts with complex shapes suitable for use in advanced heat engines. The fabrication methods used are to be adaptable for mass production of such parts on an economically sound basis. Injection molding is the forming method selected. This objective is to be accomplished in a two-phase program: (1) to achieve a 20 percent improvement in strength and a 100 percent increase in Weibull modulus of the baseline material; and (2) to produce a complex shaped part, a gas turbine rotor, for example, with the improved mechanical properties attained in the first phase. Eight tasks are included in the first phase covering the characterization of the properties of a baseline material, the improvement of those properties and the fabrication of complex shaped parts. Activities during the first contract year concentrated on two of these areas: fabrication and characterization of the baseline material (Task 1) and improvement of material and processes (Task 7). Activities during the second contract year included an MOR bar matrix study to improve mechanical properties (Task 2), materials and process improvements (Task 7), and a Ford-funded task to mold a turbocharger rotor with an improved material (Task 8).
Whalen, Thomas J.↗
Research in Quantum Field Theory, Cosmology, and String Theory
This project covered research in theoretical high energy physics at Brandeis University by PI Albion Lawrence and Co-PIs Matthew Headrick and Howard Schnitzer. The work of Albion Lawrence covered quantum field theoretic models of cosmic inflation and of quintessence-type dark energy, consistent with constraints on quantum gravity; the dynamics of open quantum systems, with an eye towards applications to holography; and the application of quantum information theory – particularly measures of quantum entanglement – to quantum field theories and quantum gravity. The work of Matthew Headrick covered the intersection of quantum information theory and quantum gravity, with a focus on the holographic encoding of quantum information theoretic concepts such as entanglement and computational complexity in field theory. Headrick also achieved significant technical results in closed string field theory. The work of Howard Schnitzer covered the computation of quantum information theoretic quantities in quantum field theories.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Improving energy yield in photovoltaic modules with photonic structures
When installed outdoors, Si solar cells typically operate 20 – 30 K above ambient conditions. These elevated operating temperatures lead to diminished performance, reducing efficiency by ~0.4%/K for crystalline Si cells and decreasing module lifetime. Since much of the elevated temperature of the modules derives from parasitic absorption of sub-bandgap sunlight by the contacts, encapsulants, or other materials, reflectors that remove the sub-bandgap radiation from the module before it is absorbed promise to reduce the operating temperature. However, there are many competing strategies to reject this light: selective reflectors could be integrated into the outer module glass, at the textured Si-encapsulant interface, or on the rear. Furthermore, many of these approaches are complex and expensive to fabricate. The issue of heating can be even more critical in bifacial modules: high fractions of rear irradiance can lead to higher operating temperatures. Prior to this project, relatively little was known about the optical strategies for temperature reduction in bifacial modules. The goal of this project was to quantitatively assess optical strategies for improving the energy yield via a combination of improved anti-reflection and sub-bandgap light rejection. We studied two complementary concepts: the performance of ideal structures to determine the upper limits to performance, and low-complexity structures made from standard materials as cost-effective implementations. We also studied the performance of these reflectors in different types of modules, including Al BSF, PERC, and bifacial. Here we build from our prior accomplishments in developing mirror optimization techniques, and make use of simulation methods that accurately capture the optical properties of the modules throughout the visible and near-infrared spectrum. We connect these optical properties to energy yield under realistic, outdoor conditions. We also experimentally fabricated mirrors, incorporated them into mini-modules, and performed outdoor testing of performance at NREL. We found definitively that spectrally-selective mirrors on the outside of the module cover glass offer the best performance, both under ideal conditions and for realistic, low- complexity mirrors. Mirrors at the Si cell/encapsulant interface are limited by the multiple reflections needed to remove sub-bandgap light. Mirrors at the cell surface and mirrors on the rear also cannot remove all the sub-bandgap light, since parasitic absorption also occurs in the cover glass, encapsulant, and front contacts, depending on the module configuration. Also, cell texturing places higher demands on any cell-surface mirror because multiple interactions with the mirror are required to reject sub bandgap light which compounds losses. For bifacial modules, mirrors on the back do provide additional cooling and energy yield improvements, and the mirrors can have the same structure. In the monofacial case up to 3.3K of cooling is possible for mirrors on the front, compared to 2.2K at the cell surface and 1.2K at the rear. For bifacial modules, up to 2.4K of cooling is possible when mirrors are included at both the front and back. Our realistic designs utilize 4 – 6 layers of common photovoltaic materials such as SiO 2 , TiO 2 , and SiN x , making them more cost effective. Finally, we used our models to study thermal management in bifacial modules with different back lamination materials, finding that glass-glass laminated modules operated hotter than equivalent glass-polymer backsheet modules, due solely to the increased absorption of light incident from the rear of the module. Improving the energy yield by 2%, which is achievable with these realistic designs, would lead to LCOE reductions of $0.03/kWh by 2030. These benefits make photovoltaic panels more accessible to the public and may reduce associated maintenance costs.
14 SOLAR ENERGY↗
Delay of Turbulent Boundary Layer Detachment by Mechanical Excitation: Application to Rearward-facing Ramp
A vane oscillating about a fixed point at the inlet to a two-dimensional 20 deg rearward-facing ramp proved effective in delaying the detachment of a turbulent boundary layer. Flow-field, surface static pressure, and smoke-wire flow visualization measurements were made. Surface pressure coefficient distributions revealed that two different effects occurred with axial distance along the ramp surface. The surface pressure coefficient varied as a complex function of the vane oscillation frequency and its trailing edge displacement amplitude; that is, it varied as a function of the vane oscillation frequency throughout the entire range of frequencies covered during the test, but it varied over only a limited range of the trailing edge displacement amplitudes covered.The complexity of these findings prompted a detailed investigation, the results of which revealed a combination of phenomena that explain qualitatively how the mechanically generated, periodic, sinusoidal perturbing signal produced by the oscillating vane reacts with the fluid flow to delay the detachment of a turbulent boundary layer experiencing transitory detachment.
McKinzie, Daniel J., Jr.↗
Deep Learning Based Frequency Stability Assessment in Power Grid with High Renewables
Frequency stability assessment is one critical aspect of power system security assessment. Traditional N-1 screening method is based on the simulations of a few typical daily and seasonal operation scenarios. However, the increasing integration of inverter-based renewables and the retirement of conventional synchronous generators result in decreasing system inertia and growing complexity of system operating conditions. Selecting a few typical operation scenarios cannot cover all operating conditions, and the time-domain simulation of all operation conditions requires tremendous time. This paper proposes a more efficient frequency stability assessment method based on deep learning. The affinity propagation clustering algorithm is used to divide the dataset into different clusters, so the selected dataset for training can cover the diversified operating conditions as much as possible. Also, feature normalization is applied to both the training dataset and testing dataset in order to remove any unnecessary bias. Especially, trained model based on full dataset normalization has bounded error in the prediction. The case study on the reduced 240-bus WECC system demonstrates that the proposed method can predict accurate frequency nadir with limited training dataset. The deep learning model using the revised feature normalization can predict more accurate frequency nadir than that using the traditional feature normalization and has very small maximum prediction error.
affinity propagation↗
Optimisation of root traits to provide enhanced ecosystem services in agricultural systems: A focus on cover crops
Roots are the interface between the plant and the soil and play a central role in multiple ecosystem processes. With intensification of agricultural practices, rhizosphere processes are being disrupted and are causing degradation of the physical, chemical and biotic properties of soil. However, cover crops, a group of plants that provide ecosystem services, can be utilised during fallow periods or used as an intercrop to restore soil health. The effectiveness of ecosystem services provided by cover crops varies widely as very little breeding has occurred in these species. Improvement of ecosystem service performance is rarely considered as a breeding trait due to the complexities and challenges of belowground evaluation. Advancements in root phenotyping and genetic tools are critical in accelerating ecosystem service improvement in cover crops. In this study, we provide an overview of the range of belowground ecosystem services provided by cover crop roots: (1) soil structural remediation, (2) capture of soil resources and (3) maintenance of the rhizosphere and building of organic matter content. Based on the ecosystem services described, we outline current and promising phenotyping technologies and breeding strategies in cover crops that can enhance agricultural sustainability through improvement of root traits.
54 ENVIRONMENTAL SCIENCES↗
A HPC Theory-Guided Machine Learning Cyberinfrastructure for Communicating Hydrometeorological Data Across Scales
High-resolution predictions of hydrometeorological variables are critical for supporting hydropower generation decisions and flood control at hydroelectric power plants. Traditional climate and hydrologic models rely on the numerical simulation of detailed physical processes. Therefore, running these simulations is time-, labor-, and computation-intensive. Improving the spatial and temporal resolution in these modeling outputs could lead to cubic increases in both the simulation time and computational demands, rendering high-resolution hydrometeorological predictions expensive and impractical. Many past studies apply the super resolution (SR) technique to downscale climate models using deep learners. However, deep learners are deemed “black-boxes,” as their derivation processes from low-resolution outputs to high-resolution outputs are often hidden. Their results are difficult for domain scientists to interpret and validate. Thus, there is a need for an exploratory machine learning approach that can partially integrate domain-specific theory and knowledge into the data-driven mapping process between simulation outputs of different spatial scales. The domain-specific theory and knowledge can be incorporated into the data model through an inductive approach in which process-related environmental variables are used and analyzed as key drivers (i.e., environmental surrogates) to reflect the complex physical processes. Many of these variables, such as land use land cover, soil types, topography, digital elevation, air temperature, and various watershed characteristics, can be directly measured through sensors or remote sensing techniques. Additionally, SR applications that can downscale hydrological and hydrodynamics models to efficiently produce high-resolution (1 m) flood depth grids are still rare. Since the flood depth grid can be used to support critical decisions for flood control operation at hydroelectric power plants, it is crucial to enable an SR-based capability for interpolating high-resolution flood inundation maps.
13 HYDRO ENERGY↗
Navigating Options for Transportation Electrification and Solar Charging: Steps and Lessons Learned in Montana Communities
This document is intended to assist communities who are considering investing in electric transportation. It can assist communities engage stakeholders, prioritize community goals, assess electric transportation options, and navigate complex decisions about deploying zero emission electric transportation in their community. It covers technological, economic and environmental aspects of the transition to electric vehicles (EV), and highlights the specific considerations related to the deployment of renewable energy technologies (e.g., distributed solar) in combination with EV supply equipment (EVSE, e.g., charging stations). There are many important decisions to make and questions for communities to ask themselves as they consider electric vehicle types, charging infrastructure, and electricity generation options. This guide will help communities assess: (1) Which stage in the decision-making process they are in with respect to EV deployment; (2) Questions they can explore to guide their decisions about EV deployment; (3) How to engage key stakeholders on EV deployment options; (4) Tradeoffs and benefits of various electric transportation options and; (5) Synergies of pairing electric vehicle charging and renewable energy generation technologies. The analysis and lessons learned presented in this roadmap are intended to serve as a template and guide for similarly situated communities across the country who want to prepare for and play a role in the electrified transportation future.
14 SOLAR ENERGY↗
Application of remote sensing to the geological study of the alkaline complex region of Itatiaia
The methodology of remote sensing applied to geological study in a complex area was evaluated. Itatiaia was selected as a test area, which covers the alkaline massives and its precambrian basement. LANDSAT-MSS and radar mosaic of the RADAMBRASIL Project were used for photointerpretation. Previous geological works were consulted and many discrepancies in the distribution of stratigraphic units were found. Moreover, structural lineaments and talus deposits were clearly delineated.
Dejesusparada, N.↗