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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4

Biomass-Derived Carbon and Their Composites for Supercapacitor Applications: Sources, Functions, and Mechanisms

Biomass-derived carbons are eco-friendly and sustainable materials, making them ideal for supercapacitors due to their high surface area, excellent conductivity, cost-effectiveness, and environmental benefits. This review provides valuable insights into biomass-derived carbon and modified carbon for supercapacitors, integrating both experimental results and theoretical calculations. This review begins by discussing the origins of biomass-derived carbon in supercapacitors, including plant-based, food waste-derived, animal-origin, and microorganism-generated sources. Then, this review presents strategies to improve the performance of biomass-derived carbon in supercapacitors, including heteroatom doping, surface functionalization, and hybrid composite construction. Furthermore, this review analyzes the functions of biomass-derived carbon in supercapacitors both in its pure form and as modified materials. The review also explores composites derived from biomass-based carbon, including carbon/MXenes, carbon/MOFs, carbon/graphene, carbon/conductive polymers, carbon/transition metal oxides, and carbon/hydroxides, providing a thorough investigation. Most importantly, this review offers an innovative summary and analysis of the role of biomass-derived carbon in supercapacitors through theoretical calculations, concentrating on four key aspects: energy band structure, density of states, electron cloud density, and adsorption energy. Finally, the review concludes the future research directions for biomass carbon-based supercapacitors, including the discovery of novel biomass materials, tailoring surface functional groups, fabricating high-performance composite materials, exploring ion transfer mechanisms, and enhancing practical applications. In summary, this review offers a thorough exploration of the sources, functions, and mechanisms of biomass-derived carbon in supercapacitors, providing valuable insights for future research.

biomass-derived carbon↗

Inverse Mapping of the Collision Kernel and Wall Flux Scaling in a Tall Convection‐Cloud Chamber Using Local Sensors and Knowledge‐Informed Deep Learning

Droplet collision–coalescence is a crucial process in cloud physics, but accurately representing this process under different dynamical conditions remains challenging. A proposed future convective‐cloud chamber aims to investigate this key process, but the method for observing it remains unclear, even though it is theoretically established that collision‐coalescence will occur. This study serves as a proof‐of‐concept demonstration of how knowledge‐informed deep learning, combined with measurement data from local sensors in the chamber, can be used to estimate the collision kernels, which determine how the droplet size distribution evolves during collision‐coalescence. In addition to estimating the collision kernel, we also address wall fluxes, another uncertain but important process that acts as a source of heat and moisture in the chamber. Ensemble runs of large‐eddy simulations are conducted by scaling the wall fluxes and the collision kernel, while the measured flow and cloud properties are used as inputs for a neural network. Results indicate that this approach successfully maps the scaling of wall fluxes and the collision kernel with biases of approximately 1% or less relative to the range of the target data. This proof‐of‐concept lays the groundwork for future applications; when the real measurements are available, real sensor data combined with the trained model presented in this work will enable estimation of the actual wall fluxes and collision kernel.

cloud chamber↗

Steady-State Solution of a Solar Wind-Generated Electron Cloud in a Lunar Crater

We formulate an analytic description of a steady-state electron cloud and affiliated surface charge, formed in the plasma wake generated as the solar wind flows horizontally over a lunar crater. The solution is complementary to the well-known self-similar plasma expansion formulation, which breaksdown at the plasma wake front and thus fails to capture a substantial region of the crater interior. The present model establishes a theoretical basis for existing simulation results, which suggest that the cavity formed below the wake front is populated mainly by electrons, resulting in a substantial negative surface charge. The electrostatic potential throughout this subwake region is determined by solving Poisson'sequation for a Maxwellian electron cloud, bounded above by the self-similar plasma expansion front and below by the electrostatically charged surface.

Rhodes, Dov J.↗

Climatology of Cloud‐Land‐Surface Coupling Across Different ARM Sites

Land-atmosphere interactions play a critical role in the evolution and formation of low-level clouds. The different states of coupling between low-level clouds and the surface are uncertain, primarily over continental regions, where complex thermodynamics complicates their investigation. This study uses observations from the Atmospheric Radiation Measurement User Facility to explore cloud-surface coupling and perform a climatological analysis of this interaction in five countries across three continents. The results reveal consistent coupling thresholds and average percentages across the five sites, with coupled clouds accounting for 66% of the cases and decoupled clouds for 34%. Thermodynamic and dynamic evaluations show distinct differences between coupled and decoupled clouds. Coupled clouds are characterized by humid environments, in which vertical motions connect the surface and lower atmosphere to the cloud base, conditions that favor the formation of boundary layer clouds. Decoupled clouds prefer to occur in a drier and colder environment with vertical motions inside the boundary layer being detached from the cloud base, under which boundary layer clouds are hard to form. Coupled clouds peak during warmer hours and seasons, and vice versa for decoupled clouds. This study underscores the complexity of cloud-land-surface interactions and paves the way for further investigations into cloud formation and evolution under different atmospheric environments.

54 ENVIRONMENTAL SCIENCES↗

Estimating Ice Water Content for Winter Storms from Millimeter-Wavelength Radar Measurements Using a Synthesis of Polarimetric and Dual-Frequency Radar Observations

The potential of millimeter-wavelength radar-based ice water content (IWC) estimation is demonstrated using a Ka-band Scanning Polarimetric Radar (KASPR) for the U.S. northeast coast winter storms. Two IWC relations for Ka-band polarimetric radar measurements are proposed: one that uses a combination of the radar reflectivity Z and the estimated total number concentration of snow particles N t and the other based on the joint use of Z, specific differential phase K DP , and the degree of riming f rim . A key element of the algorithms is to obtain the “Rayleigh-equivalent” value of Z measured at the Ka band, i.e., the corresponding Z at a longer radar wavelength for which Rayleigh scattering takes place. This is achieved via polarimetric retrieval of the mean volume diameter D m and incorporating the relationship between the dual-wavelength ratio DWR S/Ka and D m . Those techniques allow for retrievals from single millimeter-wavelength radar measurements and do not necessarily require the dual-wavelength ratio (DWR) measurements, if the DWR–D m relation and Rayleigh assumption for Ka-band K DP are valid. Comparison between the quasivertical profile product obtained from KASPR and the columnar vertical profile product generated from the nearby WSR-88D S-band radar measurements demonstrates that the DWR S/Ka can be estimated from the two close radars without the need for collocated radar beams and synchronized antenna scanning and can be used for determining the Rayleigh-equivalent value of Z. As a result, the performance of the suggested techniques is evaluated for seven winter storms using surface disdrometer and snow accumulation measurements.

Cloud retrieval↗

Remote sensing of ocean currents

The author has identified the following significant results. Fourteen field experiments in support of the NOAA investigation of ocean color boundary determination using ERTS-1 data have been conducted since June 1972. The boundary between coastal waters and the Loop Current has been detected by ERTS-1 as a result of sea state changes as well as color differences. Computer enchancement of MSS data are revealing many features not shown in the NDPF product. Analysis of the 24 channel MSS data shows that a thermal IR channel is required on an ERTS MSS to distinguish between atmospheric and sea state effects. Cloud cover analysis suggests the need for daily coverage of this type sensor for routinely useful oceanographic applications.

Maul, G. A.↗

The carbon monoxide abundance in interstellar clouds

The steady-state abundance of carbon monoxide in interstellar clouds is calculated as a function of optical depth, density, and temperature. The molecular reactions which lead to CO can be initiated by the following ion-molecule reactions: H(+) + O yields O(+) + H, C(+) + H2 yields CH2(+) + a photon, and H3(+) + C and O. As the ultraviolet radiation field is attenuated, C(+) is transformed primarily into CO and C I. There are characteristic column densities for the transition to CO corresponding to the optical depths for attenuating this field at different wavelengths. For thick, low-temperature clouds the attenuation of the fields which ionize carbon, sulfur, and heavy metals is important for CO production initiated by H3(+). Complete conversion to CO does not necessarily occur, and considerable neutral carbon may be expected even in optically thick clouds. Comparison of integrated column densities of CO with extinction are in reasonable agreement with observations.

Langer, W.↗

Solar wind-plasma interaction: The AMPTE solar wind plasma releases

In situ measurements during AMPTE solar wind ion releases are described. The creation of a diamagnetic cavity, compression and draping of magnetic field lines, recoil of the entire artificial comet, and ion beam and tail formation are discussed. The wave measurements were used to determine the time variation of the plasma density from the measurement of the electron plasma frequency and to determine the state of cloud expansion and cavity formation. Features found include absence of strong turbulence and anomalous diffusion in the cavity boundary, and the appearance of very intense shock-like emission in front of the plasma clouds. The first effect suggests partially unknowm processes leading to magnetic field penetration into the region of the clouds. The direct observation of the interaction processes between the fast streaming solar wind plasma and the expanding cloud plasma of the Li and artificial comet releases may have relevance to astrophysical situations as, for instance, encountered in solar flares, interstellar clouds, or during accretion of matter onto compact objects.

Source record↗

Scientific goals of the Cooperative Multiscale Experiment (CME)

Mesoscale Convective Systems (MCS) form the focus of CME. Recent developments in global climate models, the urgent need to improve the representation of the physics of convection, radiation, the boundary layer, and orography, and the surge of interest in coupling hydrologic, chemistry, and atmospheric models of various scales, have emphasized the need for a broad interdisciplinary and multi-scale approach to understanding and predicting MCS's and their interactions with processes at other scales. The role of mesoscale systems in the large-scale atmospheric circulation, the representation of organized convection and other mesoscale flux sources in terms of bulk properties, and the mutually consistent treatment of water vapor, clouds, radiation, and precipitation, are all key scientific issues concerning which CME will seek to increase understanding. The manner in which convective, mesoscale, and larger scale processes interact to produce and organize MCS's, the moisture cycling properties of MCS's, and the use of coupled cloud/mesoscale models to better understand these processes, are also major objectives of CME. Particular emphasis will be placed on the multi-scale role of MCS's in the hydrological cycle and in the production and transport of chemical trace constituents. The scientific goals of the CME consist of the following: understand how the large and small scales of motion influence the location, structure, intensity, and life cycles of MCS's; understand processes and conditions that determine the relative roles of balanced (slow manifold) and unbalanced (fast manifold) circulations in the dynamics of MCS's throughout their life cycles; assess the predictability of MCS's and improve the quantitative forecasting of precipitation and severe weather events; quantify the upscale feedback of MCS's to the large-scale environment and determine interrelationships between MCS occurrence and variations in the large-scale flow and surface forcing; provide a data base for initialization and verification of coupled regional, mesoscale/hydrologic, mesoscale/chemistry, and prototype mesoscale/cloud-resolving models for prediction of severe weather, ceilings, and visibility; provide a data base for initialization and validation of cloud-resolving models, and for assisting in the fabrication, calibration, and testing of cloud and MCS parameterization schemes; and provide a data base for validation of four dimensional data assimilation schemes and algorithms for retrieving cloud and state parameters from remote sensing instrumentation.

Cotton, William↗

On the Retrieval and Analysis of Multilevel Clouds

An accurate satellite retrieval of cloud properties depends upon the detection and analysis of multilayered, overlapping cloud systems that surface observations show to be common. Multiple cloud layers are often found, for instance, in frontal situations, where cirrus overlays boundary layer convective cloud or low-to mid-level stratus cloud. Surface observers (Hahan et al., 1982) indicate that over ocean in the Northern Hemisphere between 30 deg. N and 60 deg. N, 51 percent of observations are of multilevel clouds. A satellite analysis by Coakley (1983) over the Pacific Ocean finds that more than 50 percent of 500 (250 sq km) frames exhibit evidence of multilayered cloud systems. The questions addressed in this study are the following: What error is introduced when inferring the cloud pressure from a Field-Of-View (FOV) that contains some arbitrary amount of transparent cloud overlaying a lower-level black cloud, such as stratus, by making the assumption that there is only a single cloud layer in the FOV, and what may be done to improve the cloud retrieval? The CO2 slicing methods (e.g. McCleese and Wilson, 1976; Smith and Platt, 1978; Chahine, 1974) have been shown to provide accurate means of inferring cirrus cloud altitude from passive infrared radiance measurements. The CO2 techniques have been applied to radiometric data from several instruments, notably the High Resolution Infrared Radiometric Sounder (HIRS/2, hereafter referred to as HIRS), the VISSR Atmospheric Sounder (VAS) (e.g., Menzel et al., 1983; Wylie and Menzel, 1989), and most recently to the High Resolution Interferometer Sounder (HIS) (Smith and Frey, 1990). The methods take advantage of the fact that infrared CO2 sounding channels spaced closely in wavenumber each have varying opacity to CO2, thereby causing each channel to be sensitive to a different level in the atmosphere. The techniques have been shown to be effective for single-layered, nonblack, mid- to high-level clouds such as cirrus, but are generally applied operationally to any given cloud occurrence. The CO2 slicing algorithms are most accurate for clouds than occur in a single, well-defined layer, or for multi-layered cloud cases in which the uppermost cloud layer is nearly black. Significant cloud height retrieval errors may ensue if the HIRS Field-Of-View (FOV) is cotaminated with low cloud. McCleese and Wilson (1976) have shown that the retrieved cloud height for the case of multiple cloud layers is a weighted average of the cloud heights actually present. The weight is approximately proportional to the product of the cloud heigt and the effective cloud amount. The effect of their result is that the uppermost cloud layer dominates the cloud pressure retrieval. Beyond stating that the higher cloud dominates the cloud pressure retrieval, there is no quantitative information to provide a way of estimating the errors in cloud pressure retrieval one should expect for certain common multilevel cloud situations or any suggestions on how to reduce the errors. In this paper we estimate the magnitude of the errors and use a simple algorithm to reduce the errors in optically thin cloud height retrival.

Baum, Bryan A.↗

Random Matrix Approach to Quantum Adiabatic Evolution Algorithms

We analyze the power of quantum adiabatic evolution algorithms (Q-QA) for solving random NP-hard optimization problems within a theoretical framework based on the random matrix theory (RMT). We present two types of the driven RMT models. In the first model, the driving Hamiltonian is represented by Brownian motion in the matrix space. We use the Brownian motion model to obtain a description of multiple avoided crossing phenomena. We show that the failure mechanism of the QAA is due to the interaction of the ground state with the "cloud" formed by all the excited states, confirming that in the driven RMT models. the Landau-Zener mechanism of dissipation is not important. We show that the QAEA has a finite probability of success in a certain range of parameters. implying the polynomial complexity of the algorithm. The second model corresponds to the standard QAEA with the problem Hamiltonian taken from the Gaussian Unitary RMT ensemble (GUE). We show that the level dynamics in this model can be mapped onto the dynamics in the Brownian motion model. However, the driven RMT model always leads to the exponential complexity of the algorithm due to the presence of the long-range intertemporal correlations of the eigenvalues. Our results indicate that the weakness of effective transitions is the leading effect that can make the Markovian type QAEA successful.

Boulatov, Alexei↗

Assessing Alternatives in the Systems Engineering Process: Case Study of an Earth Observing Satellite Concept

Defining design alternatives constitutes one of the critical initial steps of the systems engineering process. Once these design alternatives have been identified, assessing which alternatives best satisfy the project’s objectives can prove to be challenging when dealing with complex decision frameworks. Complex systems often involve the participation of different interest groups, who have different value systems and are focused on distinct aspects of the project. For example, design alternatives might be assessed predominantly for their technical merit by one group of stakeholders, while a different group might be more inclined to assess the design alternatives primarily based on programmatic values. MESCAL (Monitoring the Evolving State of Clouds and Aerosol Layers) is an ongoing NASA / CNES (Centre National d’Etudes Spatiales) joint study for an active remote sensing Earth observing satellite. Several design alternatives have been identified and the assessment of these alternatives requires consideration of a variety of factors. This paper presents the approach that was used to support a global assessment of the MESCAL design alternatives. A mapping of the interactions between mission, instrument, and science requirements was modeled to support the assessment of the trade space. In addition, a set of metrics was developed to structure the assessment that was conducted. Finally, this paper also discusses the general applicability of these metrics to other science mission concepts in the formulation phase.

Ivanco, Marie L.↗

A Deep Learning Approach to Fast Radiative Transfer

Due to the sheer volume of data, leveraging satellite instrument observations effectively in a data assimilation context for numerical weather prediction or for remote sensing requires a radiative transfer model as an observation operator that is both fast and accurate at the same time. Physics-based line-by-line radiative transfer (RT) models fulfil the requirement for accuracy, but are too slow and too costly in computational terms for operational applications. Therefore, fast methods were developed to be able to perform fast RT calculations using techniques such as spectral sampling or pre-computed look-up tables. The operational fast models currently calculate the absorption and scattering coefficients from the pre-computed regression coefficients and atmospheric state and cloud profiles. As a novel solution to this problem, this work investigates a deep learning approach to replace the regression coefficients in the fast RT models. A selection of hidden-layer neural network configurations is trained against atmospheric transmittance profile data computed by an accurate line-by-line model and their performance is evaluated and their advantages and disadvantages are discussed.

Machine learning↗

Stratus: An interactive steady state mixed layer model for personal computers

A steady-state, horizontally homogeneous, cloud-topped marine boundary layer model based primarily on the work of Lilly (1968) and Schubert et al., (1979) is presented. The conservative thermodynamic variables are equivalent potential temperature, theta(sub e), and total water mixing ratio, q + l. Some of the differences between this and Lilly's (1968) model are: radiation is allowed to penetrate into the boundary layer; cloud top values of longwave radiation, equivalent potential temperature, and water vapor mixing ratio are linear functions of height derived from climatological data at California coastal stations; and the closure assumption assumes a weighted average of Lilly's (1968) maximum and minimum entrainment theories. This model was programmed in FORTRAN and will run interactively on an IBM-compatible personal computer. The program allows the user to specify the geographical location, the wind speed, the sea-surface temperature, the large scale horizontal divergence, and the initial guess for cloud top height. Output includes the steady state values of cloud top and cloud base height, mixed layer equivalent potential temperature and total water mixing ratio, and the associated convective and radiative fluxes.

Guinn, Thomas A.↗

Boundary Conditions of the Heliosphere

As described in the Revised Task Statement for this grant (submitted following the award at a reduced budget), my role in these investigations is to focus on the theoretical calculations relevant to the ionization state and dust content of the Local Cloud that surrounds the Solar System. An important motivation for our investigations is to aid in the interpretation of pick-up ion (PUI) and anomalous cosmic ray (ACR) observations which depends on knowledge of the flux of neutral atoms of various elements into the heliosphere. This flux depends on the ionization and elemental abundances of the gas of the Local Cloud. We have made substantial progress in our program to understand the ionization of the Local Cloud. Our steady state photoionization models are remarkably successful in accounting for the ionization observed both by line of sight (column density) observations towards nearby stars and in situ measurements. By lifting some of the simplifying assumptions in our earlier modeling we hope to make further progress in this understanding. In future work on this project we will continue our exploration of photoionization models, focusing on making sense of the differences between the LIC and the BC. In addition we will explore the effects of altered abundances in the hot gas on the ionization and thermal balance in the LIC.

Frisch, Priscilla C.↗

The Impact of Sampling Strategy on the Cloud Droplet Number Concentration Estimated From Satellite Data

Cloud droplet number concentration (Nd) is of central importance to observation-based estimates of aerosol indirect effects, being used to quantify both the cloud sensitivity to aerosol and the base state of the cloud. However, the derivation of Nd from satellite data depends on a number of assumptions about the cloud and the accuracy of the retrievals of the cloud properties from which it is derived, making it prone to systematic biases. A number of sampling strategies have been proposed to address these biases by selecting the most accurate Nd retrievals in the satellite data. This work compares the impact of these strategies on the accuracy of the satellite retrieved Nd, using a selection of in situ measurements. In stratocumulus regions, the MODIS Nd retrieval is able to achieve a high precision (r2 of 0.5–0.8). This is lower in other cloud regimes but can be increased by appropriate sampling choices. Although the Nd sampling can have significant effects on the Nd climatology, it produces only a 20 % variation in the implied radiative forcing from aerosol–cloud interactions, with the choice of aerosol proxy driving the overall uncertainty. The results are summarised into recommendations for using MODIS Nd products and appropriate sampling.

Edward Gryspeerdt↗