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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Probabilistic Mixture Model-Based Spectral Unmixing

Spectral unmixing attempts to decompose a spectral ensemble into the constituent pure spectral signatures (called endmembers) along with the proportion of each endmember. This is essential for techniques like hyperspectral imaging (HSI) used in environment monitoring, geological exploration, etc. Several spectral unmixing approaches have been proposed, many of which are connected to hyperspectral imaging. However, most extant approaches assume highly diverse collections of mixtures and extremely low-loss spectroscopic measurements. Additionally, current non-Bayesian frameworks do not incorporate the uncertainty inherent in unmixing. We propose a probabilistic inference algorithm that explicitly incorporates noise and uncertainty, enabling us to unmix endmembers in collections of mixtures with limited diversity. We use a Bayesian mixture model to jointly extract endmember spectra and mixing parameters while explicitly modeling observation noise and the resulting inference uncertainties. We obtain approximate distributions over endmember coordinates for each set of observed spectra while remaining robust to inference biases from the lack of pure observations and the presence of non-isotropic Gaussian noise. As a direct impact of our methodology, access to reliable uncertainties on the unmixing solutions would enable robust solutions to noise, as well as informed decision-making for HSI applications and other unmixing problems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Electrotransport-induced unmixing and decomposition of ternary oxides

A general expectation is that in a uniform oxygen activity atmosphere, cation electrotransport induces a ternary or higher oxide, e.g., AB{sub 1+ξ}O{sub 3+δ}, to kinetically unmix unless the electrochemical mobilities of, say, A{sup 2+}and B{sup 4+} cations are identically equal, and eventually to decompose into the component oxides AO and BO{sub 2} once the extent of unmixing exceeds the stability range of its nonmolecularity ξ. It has, however, earlier been reported [Yoo et al., Appl. Phys. Lett. 92, 252103 (2008)] that even a massive cation electrotransport induces BaTiO{sub 3} to neither unmix nor decompose even at a voltage far exceeding the so-called decomposition voltage U{sub d}, a measure of the standard formation free energy of the oxide (|ΔG{sub f}{sup o}| = nFU{sub d}). Here, we report that as expected, NiTiO{sub 3} unmixes at any voltage and even decomposes if the voltage applied exceeds seemingly a threshold value larger than U{sub d}. We demonstrate experimentally that the electrochemical mobilities of Ni{sup 2+} and Ti{sup 4+} should be necessarily unequal for unmixing. Also, we show theoretically that equal cation mobilities appear to be a sufficiency for BaTiO{sub 3} only for a thermodynamic reason.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Deep data analysis via physically constrained linear unmixing: universal framework, domain examples, and a community-wide platform

Abstract Many spectral responses in materials science, physics, and chemistry experiments can be characterized as resulting from the superposition of a number of more basic individual spectra. In this context, unmixing is defined as the problem of determining the individual spectra, given measurements of multiple spectra that are spatially resolved across samples, as well as the determination of the corresponding abundance maps indicating the local weighting of each individual spectrum. Matrix factorization is a popular linear unmixing technique that considers that the mixture model between the individual spectra and the spatial maps is linear. Here, we present a tutorial paper targeted at domain scientists to introduce linear unmixing techniques, to facilitate greater understanding of spectroscopic imaging data. We detail a matrix factorization framework that can incorporate different domain information through various parameters of the matrix factorization method. We demonstrate many domain-specific examples to explain the expressivity of the matrix factorization framework and show how the appropriate use of domain-specific constraints such as non-negativity and sum-to-one abundance result in physically meaningful spectral decompositions that are more readily interpretable. Our aim is not only to explain the off-the-shelf available tools, but to add additional constraints when ready-made algorithms are unavailable for the task. All examples use the scalable open source implementation from https://github.com/ramkikannan/nmflibrary that can run from small laptops to supercomputers, creating a user-wide platform for rapid dissemination and adoption across scientific disciplines.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

Direct comparison of Fe-Cr unmixing characterization by atom probe tomography and small angle scattering

The fine microstructure obtained by unmixing of a solid solution either by classical precipitation or spinodal decomposition is often characterized either by small angle scattering or atom probe tomography. This article shows that a common data analysis framework can be used to analyze data obtained from these two techniques. An example of the application of this common analysis is given for characterization of the unmixing of the Fe-Cr matrix of a 15-5 PH stainless steel during long-term ageing at 350 °C and 400 °C. A direct comparison of the Cr composition fluctuations amplitudes and characteristic lengths obtained with both techniques is made showing a quantitative agreement for the fluctuation amplitudes. The origin of the discrepancy remaining for the characteristic lengths is discussed. - Highlights: •Common analysis framework for atom probe tomography and small angle scattering •Comparison of same microstructural characteristics obtained using both techniques •Good correlation of Cr composition fluctuations amplitudes from both techniques •Good correlation of Cr composition fluctuations amplitudes with classic V parameter.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Effect of natural gamma background radiation on portal monitor radioisotope unmixing

It is well known that national security relies on several layers of protection. One of the most important is the traffic control at borders and ports that exploits Radiation Portal Monitors (RPMs) to detect and deter potential smuggling attempts. Most portal monitors rely on plastic scintillators to detect gamma rays. Despite their poor energy resolution, their cost effectiveness and the possibility of growing them in large sizes make them the gamma-ray detector of choice in RPMs. Unmixing algorithms applied to organic scintillator spectra can be used to reliably identify the bare and unshielded radionuclides that triggered an alarm, even with fewer than 1000 detected counts and in the presence of two or three nuclides at the same time. In this work, we experimentally studied the robustness of a state-of-the-art unmixing algorithm to different radiation background spectra, due to varying atmospheric conditions, in the 16 °C to 28 °C temperature range. In the presence of background, the algorithm is able to identify the nuclides present in unknown radionuclide mixtures of three nuclides, when at least 1000 counts from the sources are detected. With fewer counts available, we found larger differences of approximately 35.9% between estimated nuclide fractions and actual ones. In these low count rate regimes, the uncertainty associated by our algorithm with the identified fractions could be an additional valuable tool to determine whether the identification is reliable or a longer measurement to increase the signal-to-noise ratio is needed. Moreover, the algorithm identification performances are consistent throughout different data sets, with negligible differences in the presence of background types of different intensity and spectral shape.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2017

Rotational Spectral Unmixing of Exoplanets: Degeneracies between Surface Colors and Geography

Unmixing the disk-integrated spectra of exoplanets provides hints about heterogeneous surfaces that we cannot directly resolve in the foreseeable future. It is particularly important for terrestrial planets with diverse surface compositions like Earth. Although previous work on unmixing the spectra of Earth from disk-integrated multi-band light curves appeared successful, we point out a mathematical degeneracy between the surface colors and their spatial distributions. Nevertheless, useful constraints on the spectral shape of individual surface types may be obtained from the premise that albedo is everywhere between 0 and 1. We demonstrate the degeneracy and the possible constraints using both mock data based on a toy model of Earth, as well as real observations of Earth. Despite the severe degeneracy, we are still able to recover an approximate albedo spectrum for an ocean. In general, we find that surfaces are easier to identify when they cover a large fraction of the planet and when their spectra approach zero or unity in certain bands.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Robust Spectral Unmixing of Sparse Multispectral Lidar Waveforms using Gamma Markov Random Fields

Here, this paper presents a new Bayesian spectral un-mixing algorithm to analyse remote scenes sensed via sparse multispectral Lidar measurements. To a first approximation, in the presence of a target, each Lidar waveform consists of a main peak, whose position depends on the target distance and whose amplitude depends on the wavelength of the laser source considered (i.e, on the target reflectivity). Besides, these temporal responses are usually assumed to be corrupted by Poisson noise in the low photon count regime. When considering multiple wavelengths, it becomes possible to use spectral information in order to identify and quantify the main materials in the scene, in addition to estimation of the Lidar-based range profiles. Due to its anomaly detection capability, the proposed hierarchical Bayesian model, coupled with an efficient Markov chain Monte Carlo algorithm, allows robust estimation of depth images together with abundance and outlier maps associated with the observed 3D scene. The proposed methodology is illustrated via experiments conducted with real multispectral Lidar data acquired in a controlled environment. The results demonstrate the possibility to unmix spectral responses constructed from extremely sparse photon counts (less than 10 photons per pixel and band).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Unmixing Symmetries

The low-lying spectra of atomic nuclei display diverse behaviors, for example, rotational bands, which can be described phenomenologically by simple symmetry groups such as spatial SU(3). This leads to the idea of dynamical symmetry, where the Hamiltonian commutes with the Casimir operator(s) of a group, and is block diagonal in subspaces defined by the group’s irreducible representations or irreps. Detailed microscopic calculations, however, show these symmetries are in fact often strongly mixed and the wave function fragmented across many irreps. More commonly, the fragmentation across members of a band are similar, which is called a quasidynamical symmetry. In this Letter I explicitly, albeit numerically, construct unitary transformations from a quasidynamical symmetry to a dynamical symmetry, adapting the similarity renormalization group (SRG) in order to transform away the symmetry-mixing parts of the Hamiltonian. In this work, the standard SRG produces unsatisfactory results, forcing the induced dynamical symmetry to be dominated by high-weight irreps irrespective of the original decomposition. Using spectral distribution theory to rederive and diagnose standard SRG, I introduce a new form of SRG. The new SRG transforms a quasidynamical symmetry to a dynamical symmetry, that is, unmixes the mixed symmetries, with intuitively more appealing results.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2015

Non-Intrusive Load Monitoring of HVAC Components using Signal Unmixing

Heating, Ventilating and Air Conditioning units (HVAC) are a major electrical energy consumer in buildings. Monitoring of the operation and energy consumption of HVAC would increase the awareness of building owners and maintenance service providers of the condition and quality of performance of these units, enabling conditioned-based maintenance which would help achieving higher energy efficiency. In this paper, a novel non-intrusive load monitoring method based on group constrained non-negative matrix factorization is proposed for monitoring the different components of HVAC unit by only measuring the whole building aggregated power signal. At the first level of this hierarchical approach, power consumption of the building is decomposed to energy consumption of the HVAC unit and all the other electrical devices operating in the building such as lighting and plug loads. Then, the estimated power signal of the HVAC is used for estimating the power consumption profile of the HVAC major electrical loads such as compressors, condenser fans and indoor blower. Experiments conducted on real data collected from a building testbed maintained at the Oak Ridge National Laboratory (ORNL) demonstrate high accuracy on the disaggregation task.

Flexible Research Platform↗
DOE OSTI2018

Development Of Nutrient And Water Recycling Capabilities In Algae Biofuels Production Systems. Final Summary Report

The objective of this project was to develop and demonstrate methods of recycling of water and nutrients for algal biofuels production. Recycling was accomplished both internal to the system and, in a broader sense, through import and reuse of municipal wastewater. Such an integrated system with wastewater input had not been demonstrated previously, and the performance was unknown, particularly in terms of influence of recycling on algal productivity and the practical extent of nutrient recovery from biomass residuals. Through long-term laboratory and pilot research, the project resulted in the following: 1. Bench-scale pretreatment of algal biomass did not sufficiently increase methane yield of nutrient solubilization during anaerobic digestion to warrant incorporation of pre-treatment into the pilot plant. The trial pretreatments were high-pressure orifice homogenization, sonication, and two types of heat treatment. 2. Solubilization of biomass particulate nutrients by lab anaerobic digesters ranged from 20% to nearly 60% for N and 40-65% for P. Subsequent aerobic degradation of the anaerobically digested biomass simulated raceways receiving whole digestate and resulted in an additional 20-55% N solubilization and additional 20% P solubilization. 3. Comparisons of laboratory and pilot digesters showed that laboratory units were reasonable proxies for pilot-scale. 4. Pilot-scale anaerobic digesters were designed, installed, and operated to digest algal biomass. Nutrient re-solubilization by the digesters was monitored and whole digestate was successfully used as a fertilizer in pilot algae raceways. 5. Unheated, unmixed digesters achieved greater methane yield and nutrient solubilization than heated, mixed digesters, presumably due to longer the solids residence times in unmixed digesters. The unmixed, unheated pilot digesters yielded 0.16 L CH4 /g volatile solids (VS) introduced with 0.15 g VS/L-d organic loading and 16oC average temperature. A conventional heated mixed lab digester yielded 0.22 L CH4 /g VS with 0.25 g VS/L-d and 30oC. The highest yield (0.30 L CH4 /g VS) was achieved by the unmixed lab digesters operated at a constant 20oC. All digesters were operated with a 40-d hydraulic residence time. 6. In general, 50-75% of initial particulate N and P could be solubilized during anaerobic digestion and available for subsequent rounds of algae cultivation. 7. Bench-scale experiments showed the recovery from hydrothermal liquefaction (HTL) wastewater of carbon via anaerobic digestion and of nutrients to grow algae. To satisfy the nitrogen demand of algae cultivation, HTL wastewater would be diluted 400-fold, which was found to eliminate inhibition of algae growth by HTL wastewater. 8. Anaerobic digestion methane yield was lower for algal biomass containing coagulants such as would be used to aid harvesting or dewatering. Depending on doses, starch-based coagulant decreased yield by 10-14% and aluminum chlorohydrate decreased it by 14-26%. The lowest yield was 0.28 L CH 4 /g volatile solids introduced to the digesters. 9. Algae harvested from raceways operated on recycled water had methane yields 13% higher than algae from raceways operated on both recycled water and nutrients provided by algae digestate. The slightly lower yield was expected due to the presence of previously digested biomass from the digestate fertilizer. 10. Defined media was replenished with nutrients and recycled repeatedly in sequential batch growth of Chlorella sorokiniana (DOE 1412). This laboratory study tested for inhibition and accumulation of inhibiting compounds (allelopathic or auto-inhibitory substances), information that would help estimate the blowdown ratio needed for an integrated system. In laboratory experiments in which water was recycled a total of five times, each successive round of reuse resulted in an average 4±3% reduction in log-phase specific growth rates. However, linear-phase growth inhibition was only observed in the final fifth round of reuse. 11. No decline in productivity was detected after 15 rounds of water recycling with nutrients provided by whole digestate in lab cultivation. Lab tests allowed for steady light and temperature, increasing the ability to detect inhibition. 12. In initial pilot inhibition studies, wastewater growth media was reused once while productivity was monitored. Media reuse was accomplished with triplicate sets of 33-m2 raceways operated in series. First-round gross productivity (based on effluent biomass flow) averaged 23 g/m 2 -day annually while second-round gross productivity averaged 19 g/m 2 -day annually. In terms of net productivity (based on raceway effluent biomass minus influent biomass), the first-round productivity averaged 15 g/m2-d and second round averaged 13 g/m 2 -d during June-September operation. The higher productivity in the first-round ponds was likely due to heterotrophic/mixotrophic growth on the wastewater organic matter. 13. In a culminating pilot experiment, coagulant was used to decrease the carry-over of unsettled algae into subsequent rounds of growth. Over nearly 8 months, 93% of the media (the equivalent of 14 rounds of water reuse) was recycled without significant productivity loss compared to controls. Ponds receiving both recycled water and nutrients had net productivities of 14-24 g/m 2 -d during fall and mid-summer, respectively. 14. Techno-economic analysis of the proposed facility found minimum fuel selling price to range from $7.01/gallon gasoline equivalent without revenue other than fuel to $3.85/GGE with revenue from wastewater treatment fees and LCFS and RIN (Low Carbon Fuel Standard and Renewable Identification Numbers) credits. 15. Life cycle assessment indicated GHG emissions of 40.7 g CO 2 /MJ fuel and a net energy ratio (energy required/energy produced) of 0.37.

09 BIOMASS FUELS↗
DOE OSTI2017

Quantum Phases and Collective Excitations of a Spin-Orbit-Coupled Bose–Einstein Condensate in a One-Dimensional Optical Lattice

The ground state of a spin-orbit-coupled Bose gas in a one-dimensional optical lattice is known to exhibit a mixed regime, where the condensate wave function is given by a superposition of multiple Bloch-wave components, and an unmixed one, in which the atoms occupy a single Bloch state. The unmixed regime features two unpolarized Bloch-wave phases, having quasimomentum at the center or at the edge of the first Brillouin zone, and a polarized Bloch-wave phase at intermediate quasimomenta. By calculating the critical values of the Raman coupling and of the lattice strength at the transitions among the various phases, we show the existence of a tricritical point where the mixed, the polarized and the edge-quasimomentum phases meet, and whose appearance is a consequence of the spin-dependent interaction. Furthermore, we evaluate the excitation spectrum in the unmixed regime and we characterize the behavior of the phonon and the roton modes, pointing out the instabilities occurring when a phase transition is approached.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Physical-biopolymer characterization of polyhydroxybutyrate-co-hydroxyvalerate (PHBV) blended with natural rubber latex

A biopolymer of polyhydroxybutyrate-co-hydroxyvalerate (PHBV) is blended with bio-based materials, natural rubber latex, to improve their microstructures. The various ratios between PHBV and natural rubber latex are examined to develop their mechanical properties. In general, physical properties of PHBV are hard, brittle and low flexible while natural rubber (NR) is presented itself as high elastic materials. Concentrations of the PHBV solution are constituted at 1%, 2% and 3% (w/v). The mixtures of their PHBV solutions to natural rubber latex are produced the blended films in three different ratios of 4:6, 5:5 and 6:4, respectively. They are characterized by appearance analyses which are the scanning electron microscope (SEM), universal testing machine (UTM) and differential scanning calorimetry (DSC). The SEM photomicrographs of the blended films and the controlled PHBV can provide the void distribution in the range of 12-14% and 19-21%, respectively. For mechanical properties of the blended films, the various elastic moduli of 1%, 2% and 3% (w/v) PHBV are the average of 773, 956 and 1,007 kPa, respectively. The tensile strengths of the blends increase with the increased concentrations of PHBV, similarly trend to the elastic modulus. The crystallization and melting behavior of unmixed PHBV and the blends are determined by DSC. Melting transition temperatures (T{sub m}) of the unmixed PHBV are stated two melting peak at 154°C and 173°C. Besides, the melting peaks of the blends alter in the range of 152-156°C and 168-171°C, respectively. According to morphology of the blends, the void distribution decreases twice compared to the unmixed PHBV. The results of mechanical properties and thermal analysis indicate that the blended PHBV can be developed their properties by more resilient and wide range of temperature than usual.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Separating Physically Distinct Mechanisms in Complex Infrared Plasmonic Nanostructures via Machine Learning Enhanced Electron Energy Loss Spectroscopy

Electron energy loss spectroscopy (EELS) enables direct exploration of plasmonic phenomena at the nanometer level. To isolate individual plasmon modes, linear unmixing methods can be used to separate different physical mechanisms, but in larger and more complex systems the interpretability of the components becomes uncertain. Here, infrared plasmonic resonances in self-assembled heterogeneous monolayer films of doped-semiconductor nanoparticles are examined beyond linear unmixing techniques, and both supervised and unsupervised machine-learning-based analyses of hyperspectral EELS datasets are demonstrated. Additionally, in the supervised approach, a human operator labels a small number of pixels in the hyperspectral dataset corresponding to features of interest which are then propagated across the entire dataset. In the unsupervised approach, non-linear autoencoders are used to create a highly-reduced latent-space representation of the dataset, within which insight into the relevant physics can be gleaned from straightforward distance metrics that do not depend on operator input and bias. The advantage of these approaches is that the labeling separates physical mechanisms without altering the data, enabling robust analyses of the influence of heterogeneities in mesoscale complex systems.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Jeff=1/2 Mott spin-orbit insulating state close to the cubic limit in Ca4IrO6

The J_eff=1/2 state is manifested in systems with large cubic crystal field splitting and spin-orbit coupling that are comparable to the on-site Coulomb interaction, U. 5d transition metal oxides host parameters in this regime and strong evidence for this state in Sr2IrO4, and additional iridates, has been presented. All the candidates, however, deviate from the cubic crystal field required to provide an unmixed canonical J_eff=1/2 state, impacting the development of a robust model of this novel insulating and magnetic state. We present experimental and theoretical results that not only show Ca4IrO6 hosts the state, but furthermore uniquely resides in the limit required for a canonical unmixed J_eff=1/2 state.

Calder, Stuart A↗
DOE OSTI2016

Conditions for super-adiabatic droplet growth after entrainment mixing

Abstract. Cloud droplet response to entrainment and mixing between a cloud and its environment is considered, accounting for subsequent droplet growth during adiabatic ascent following a mixing event. The vertical profile for liquid water mixing ratio after a mixing event is derived analytically, allowing the reduction to be predicted from the mixing fraction and from the temperature and humidity for both the cloud and environment. It is derived for the limit of homogeneous mixing. The expression leads to a critical height above the mixing level: at the critical height the cloud droplet radius is the same for both mixed and unmixed parcels, and the critical height is independent of the updraft velocity and mixing fraction. Cloud droplets in a mixed parcel are larger than in an unmixed parcel above the critical height, which we refer to as the “super-adiabatic” growth region. Analytical results are confirmed with a bin microphysics cloud model. Using the model, we explore the effects of updraft velocity, aerosol source in the environmental air, and polydisperse cloud droplets. Results show that the mixed parcel is more likely to reach the super-adiabatic growth region when the environmental air is humid and clean. It is also confirmed that the analytical predictions are matched by the volume-mean cloud droplet radius for polydisperse size distributions. The findings have implications for the origin of large cloud droplets that may contribute to onset of collision–coalescence in warm clouds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

High efficiency organic photovoltaic cells employing hybridized mixed-planar heterojunctions

A device is provided, having a first electrode, a second electrode, and a photoactive region disposed between the first electrode and the second electrode. The photoactive region includes a first photoactive organic layer that is a mixture of an organic acceptor material and an organic donor material, wherein the first photoactive organic layer has a thickness not greater than 0.8 characteristic charge transport lengths; a second photoactive organic layer in direct contact with the first organic layer, wherein the second photoactive organic layer is an unmixed layer of the organic acceptor material of the first photoactive organic layer, and the second photoactive organic layer has a thickness not less than about 0.1 optical absorption lengths; and a third photoactive organic layer disposed between the first electrode and the second electrode and in direct contact with the first photoactive organic layer. The third photoactive organic layer is an unmixed layer of the organic donor layer of the first photoactive organic layer and has a thickness not less than about 0.1 optical absorption lengths.

14 SOLAR ENERGY↗
DOE OSTI2016

Phases and interfaces from real space atomically resolved data: Physics-based deep data image analysis

Advances in electron and scanning probe microscopies have led to a wealth of atomically resolved structural and electronic data, often with ~1–10 pm precision. However, knowledge generation from such data requires the development of a physics-based robust framework to link the observed structures to macroscopic chemical and physical descriptors, including single phase regions, order parameter fields, interfaces, and structural and topological defects. Here, we develop an approach based on a synergy of sliding window Fourier transform to capture the local analog of traditional structure factors combined with blind linear unmixing of the resultant 4D data set. This deep data analysis is ideally matched to the underlying physics of the problem and allows reconstruction of the a priori unknown structure factors of individual components and their spatial localization. We demonstrate the principles of this approach using a synthetic data set and further apply it for extracting chemical and physically relevant information from electron and scanning tunneling microscopy data. Furthermore, this method promises to dramatically speed up crystallographic analysis in atomically resolved data, paving the road toward automatic local structure–property determinations in crystalline and quasi-ordered systems, as well as systems with competing structural and electronic order parameters.

36 MATERIALS SCIENCE↗