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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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Temperature Effects on the Equation of State and Symmetry Energy at Low and High Densities

Thermal properties of symmetric nuclear matter and pure neutron matter are studied in a selfconsistent Green’s function and Brueckner–Hartree–Fock approaches with the inclusion of the contact interaction using CDBONN potential. Also we investigate the temperature dependence of the symmetry energy. The symmetry energy at fixed density is found to generally decrease with temperature. The temperature effects on the nuclear matter symmetry energy are found to be stronger at lower densities while become much weaker at higher densities. The results of several microscopic approaches are compared. Also the results are compared with recent experimental data. There is good agreement between the experimental symmetry energy and those calculated in the Brueckner–Hartree–Fock approach.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Microgrid energy scheduling under uncertain extreme weather: Adaptation from parallelized reinforcement learning agents

Microgrids are useful solutions for integrating renewable energy resources and providing seamless green electricity to minimize carbon footprint. In recent years, extreme weather events happened often worldwide and caused significant economic and societal losses. Such events bring uncertainties to the microgrid energy scheduling problems and increase the challenges of microgrid operation. Traditional optimization approaches suffer from the inaccuracy of the uncertain microgrid model and the unseen events. Existing reinforcement learning (RL) - based approaches are also hampered by the limited generalization and the increasing computational burden when stochastic formulations are required to accommodate the uncertainties. This paper proposes a new parallelized reinforcement learning (PRL) method based on the probabilistic events to handle the microgrid energy uncertainties. Specifically, several local learning agents are employed to interact with pertinent microgrid environments in a distributed manner and report outcomes to the global agent, which will optimize microgrid energy resources online during extreme events. The stochastic microgrid energy optimization problem is reformulated to include all possible scenarios with probabilities. The advantage estimate functions of learning agents are designed with a backward sweep to transfer the outcomes to the value function updating process. Two simulation studies, stochastic optimization and online testing, are performed to compare with several existing RL approaches. Results substantiate that the proposed PRL method can achieve up to 20% optimization performance improvement with 4 and 28 times less computation cost than Q-learning with experience replay and multi-agent Q-learning approaches, respectively.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Polaron mobility obtained by a variational approach for lattice Fröhlich models

Charge carrier mobility for a class of lattice models with long-range electron–phonon interaction was investigated. The approach for mobility calculation is based on a suitably chosen unitary transformation of the model Hamiltonian which transforms it into the form where the remaining interaction part can be treated as a perturbation. Relevant spectral functions were then obtained using Matsubara Green’s functions technique and charge carrier mobility was evaluated using Kubo’s linear response formula. Numerical results were presented for a wide range of electron–phonon interaction strengths and temperatures in the case of one-dimensional version of the model. The results indicate that the mobility decreases with increasing temperature for all electron–phonon interaction strengths in the investigated range, while longer interaction range leads to more mobile carriers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

New approaches for metabolomics by mass spectrometry

Small molecules constitute a large part of the world around us, including fossil and some renewable energy sources. Solar energy harvested by plants and bacteria is converted into energy rich small molecules on a massive scale. Some of the worst contaminants of the environment and compounds of interest for national security also fall in the category of small molecules. The development of large scale metabolomic analysis methods lags behind the state of the art established for genomics and proteomics. This is commonly attributed to the diversity of molecular classes included in a metabolome. Unlike nucleic acids and proteins, metabolites do not have standard building blocks, and, as a result, their molecular properties exhibit a wide spectrum. This impedes the development of dedicated separation and spectroscopic methods. Mass spectrometry (MS) is a strong contender in the quest for a quantitative analytical tool with extensive metabolite coverage. Although various MS-based techniques are emerging for metabolomics, many of these approaches include extensive sample preparation that make large scale studies resource intensive and slow. New ionization methods are redefining the range of analytical problems that can be solved using MS. This project developed new approaches for the direct analysis of small molecules in unprocessed samples, as well as pushed the limits of ultratrace analysis in volume limited complex samples. The projects resulted in techniques that enabled metabolomics investigations with enhanced molecular coverage, as well as the study of cellular response to stimuli on a single cell level. Effectively individual cells became reaction vessels, where we followed the response of a complex biological system to external perturbation. We established two new analytical platforms for the direct study of metabolic changes in cells and tissues following external perturbation. For this purpose we developed a novel technique, laser ablation electrospray ionization (LAESI), for metabolite profiling of functioning cells and tissues. The technique was based on microscopic sampling of biological specimens by mid-infrared laser ablation followed by electrospray ionization of the plume and MS analysis. The two main shortcomings of this technique had been limited specificity due to the lack of a separation step, and limited molecular coverage, especially for nonpolar chemical species. To improve specificity and the coverage of the metabolome, we implemented the LAESI ion source on a mass spectrometer with ion mobility separation (IMS). In this system, the gas phase ions produced by the LAESI source were first sorted according to their collisional cross sections in a mobility cell. These separated ion packets were then subjected to MS analysis. By combining the atmospheric pressure ionization with IMS, we improved the metabolite coverage. Further enhancement of the non-polar metabolite coverage resulted from the combination of laser ablation with vacuum UV irradiation of the ablation plume. Our results indicated that this new ionization modality provided improved detection for neutral and non-polar compounds. Based on rapid progress in photonics, we had introduced another novel ion source that utilized the interaction of a laser pulse with silicon nanopost arrays (NAPA). In these nanophotonic ion sources, the structural features were commensurate with the wavelength of the laser light. The enhanced interaction resulted in high ion yields. This ultrasensitive analytical platform enabled the MS analysis of single yeast cells. We extended these NAPA studies from yeast to other microorganisms, including green algae (Chlamydomonas reinhardtii) that captured energy from sunlight on a massive scale. Combining cellular perturbations, e.g., through environmental changes, with the newly developed single cell analysis methods enabled us to follow dynamic changes induced in the cells. In effect, we were able to use individual cells as a “laboratory,” and approached the long-standing goal of establishing a “lab-in-a-cell.” Model systems for these studies included cells of cyanobacteria (Anabaena), yeast (Saccharomyces cerevisiae), green algae (C. reinhardtii) and Arabidopsis thaliana.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

A DYNAMIC DENSITY FUNCTIONAL THEORY APPROACH TO DIFFUSION IN WHITE DWARFS AND NEUTRON STAR ENVELOPES

We develop a multicomponent hydrodynamic model based on moments of the Born–Bogolyubov–Green–Kirkwood–Yvon hierarchy equations for physical conditions relevant to astrophysical plasmas. These equations incorporate strong correlations through a density functional theory closure, while transport enters through a relaxation approximation. This approach enables the introduction of Coulomb coupling correction terms into the standard Burgers equations. The diffusive currents for these strongly coupled plasmas is self-consistently derived. The settling of impurities and its impact on cooling can be greatly affected by strong Coulomb coupling, which we show can be quantified using the direct correlation function.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Predicting Reduction Rates of Energetic Nitroaromatic Compounds Using Calculated One-Electron Reduction Potentials

The evaluation of new energetic nitroaromatic compounds (NACs) for use in green munitions formulations requires models that can predict their environmental fate. The susceptibility of energetic NACs to nitro reduction might be predicted from correlations between rate constants (k) for this reaction and one-electron reduction potentials (E1NAC) / 0.059 V, but the mechanistic implications of such correlations are inconsistent with evidence from other methods. To address this inconsistency, we have reevaluated existing kinetic data using a (non-linear) free-energy relationship (FER) based on the Marcus theory of outer-sphere electron transfer. For most reductants, the results are inconsistent with rate limitation by an initial, outer-sphere electron transfer, suggesting that the strong correlation between k and E1NAC is justified only as an empirical model. This empirical correlation was used to calibrate a new quantitative structure-activity relationship (QSAR) using previously reported values of k for non-energetic NAC reduction by Fe(II) porphyrin and newly reported values of E1NAC determined using density functional theory at the B3LYP/6-311++G(2d,2p) level with the COSMO solvation model. The QSAR was then validated for energetic NACs using newly measured kinetic data for 2,4,6-trinitrotoluene (TNT), 2,4-dinitrotoluene (2,4-DNT), and 2,4-dinitroanisole (DNAN). The data show close agreement with the QSAR, supporting its applicability to energetic NACs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

FY21 Progress Report: SRNL Analysis of ICCWR LCM and WAMS data for Corrosion and Cracking

The development of algorithms for machine learning and data analysis for the 3013 Surveillance Program is a collaborative effort by the Savannah River National Laboratory (SRNL) and the University of South Carolina (USC). For corrosion detection, Laser Confocal Microscope (LCM) or Wide Area 3D Measurement System (WAMS) data is extracted from large binary files, with software written to convert the data to physical attributes (e.g., height, color and grayscale values; all as functions of a location in a plane projection). A user-friendly Matlab Graphical User Interface (GUI) that reads data from either LCM or WAMS files was developed to integrate input data with software developed for processing and evaluation. The GUI can selectively download binary data, interrogate data attributes, label data, flag significant features, execute Machine Learning (ML) algorithms, output parameters for trained ML algorithms, report ML model accuracy with respect to labeled data, and generate graphical representations for various analyses. Features can be called out by user-specified thresholds, manual labeling or machine learning algorithms when they have been completed. The ability to rapidly label data is important because of the volume of data required for training machine learning algorithms. The GUI has the flexibility to allow addition of improved ML algorithms, methods for data visualization, and statistical computations. Statistical analyses via the GUI include areas of pits within a defined range of pit depths, correlations between Red-Green-Blue (RGB) or grayscale intensity and relative surface height, covariances between values associated with features, and feature histograms. The development of supervised machine learning algorithms, however, has been hindered by a lack of training data. The machine learning algorithms for crack identification are being refined but require improvements to the true positive rate for crack detection. This shortcoming is an artifact of the limited training data currently available, perhaps more so than the structure of the neural networks. At present, the best results are had from a consensus over an ensemble of randomly generated Deep Neural Network (DNN) or Convolutional Neural Network (CNN) algorithms. Although the consensus accuracy method has yielded optimum true positive and true negative rates in excess of 80%, additional validation testing is necessary. In addition to the suite of LCM data that was initially used, and which represents the majority of the work presented in this report, WAMS image data was also reviewed at a preliminary level. The review included a comparison between image resolution and dynamic range for each method. WAMS (ZON file) image data was found to have a pixel pitch of 3.69μm compared to 1 μm for the LCM (vk4 file) data, which implies a lower resolution for the WAMS images. Conversely, the ratio of dynamic range of the WAMS data to the LCM data was approximately 41:20 for height data, suggesting that information from WAMS should more accurately determine the depth of pits. At present, the significance of the greater dynamic range of the WAMS data relative to the LCM data has not yet been evaluated.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Innovation and Winemaking By-Product Valorization: An Ohmic Heating Approach

The by-products of the winemaking process can represent chances for the development of new products. This study focused on the “zero waste” strategy development for by-products generated within winemaking from white and red grape varieties cultivated in the north of Portugal. The phytochemical properties of by-products were identified and characterized. Ohmic heating (OH) as a green extraction method was also applied to grape pomace due to their unknown effects on centesimal and phytochemical compositions. Both protein and carbohydrates were shown to be higher in grape bagasse than in stems. Additionally, red bagasse is richer in bioactive compounds (BC) than white bagasse. The sugar content was 21.91 and 11.01 g/100 g of DW in red and white grape bagasse, respectively. The amount of protein was 12.46 g/100 g of DW for red grape bagasse and 13.18 g/100 g of DW for white. Regarding the extraction methods, two fractions were obtained, a liquid fraction and solid (the remainder after the methodology application). OH presented a higher antioxidant capacity than a conventional (CONV) method. In addition, both extracts presented similar contents of anthocyanins, e.g., delphinidin-3-O-glucoside, petunidin-3-O-glucoside, and peonidin-3-O-glucoside. The solid fraction presented higher amounts of protein and phenols bound to fiber than CONV, which allows its use as a functional ingredient. In conclusion, OH can be an alternative extraction method compared with CONV methods, avoiding non-food grade solvents, thus contributing to circular economy implementation.

Coelho, Marta C. (ORCID:000000026542175X)↗
NASA NTRS1986

Evaluation of the infrared test method for the olympus thermal balance tests

The performance of the infrared (IR) rig used for the thermal balance testing of the Olympus S/C thermal model is discussed. Included in this evaluation are the rig effects themselves, the IRFLUX computer code used to predict the radiation inputs, the Monitored Background Radiometers (MBR's) developed to measure the absorbed radiation flux intensity, the Uniform Temperature Reference (UTR) based temperature measurement system and the data acquisition system. A preliminary set of verification tests were performed on a 1 m x 1 m zone to assess the performance of the IR lamps, calrods, MBR's and aluminized baffles. The results were used, in part, to obtain some empirical data required for the IRFLUX code. This data included lamp and calrod characteristics, the absorptance function for various surface types, and the baffle reflectivities.

Donato, M.↗
DOE OSTI2015

Rhenium-phthalocyanine molecular nanojunction with high magnetic anisotropy and high spin filtering efficiency

Using the density functional and non-equilibrium Green's function approaches, we studied the magnetic anisotropy and spin-filtering properties of various transition metal-Phthalocyanine molecular junctions across two Au electrodes. Our important finding is that the Au-RePc-Au junction has both large spin filtering efficiency (>80%) and large magnetic anisotropy energy, which makes it suitable for device applications. To provide insights for the further experimental work, we discussed the correlation between the transport property, magnetic anisotropy, and wave function features of the RePc molecule, and we also illustrated the possibility of controlling its magnetic state.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Virtual Design Studio (VDS) - Development of an Integrated Computer Simulation Environment for Performance Based Design of Very-Low Energy and High IEQ Buildings

Executive Summary The objective of this study was to develop a “Virtual Design Studio (VDS)”: a software platform for integrated, coordinated and optimized design of green building systems with low energy consumption, high indoor environmental quality (IEQ), and high level of sustainability. This VDS is intended to assist collaborating architects, engineers and project management team members throughout from the early phases to the detailed building design stages. It can be used to plan design tasks and workflow, and evaluate the potential impacts of various green building strategies on the building performance by using the state of the art simulation tools as well as industrial/professional standards and guidelines for green building system design. Engaged in the development of VDS was a multi-disciplinary research team that included architects, engineers, and software developers. Based on the review and analysis of how existing professional practices in building systems design operate, particularly those used in the U.S., Germany and UK, a generic process for performance-based building design, construction and operation was proposed. It distinguishes the whole process into five distinct stages: Assess, Define, Design, Apply, and Monitoring (ADDAM). The current VDS is focused on the first three stages. The VDS considers building design as a multi-dimensional process, involving multiple design teams, design factors, and design stages. The intersection among these three dimensions defines a specific design task in terms of “who”, “what” and “when”. It also considers building design as a multi-objective process that aims to enhance the five aspects of performance for green building systems: site sustainability, materials and resource efficiency, water utilization efficiency, energy efficiency and impacts to the atmospheric environment, and IEQ. The current VDS development has been limited to energy efficiency and IEQ performance, with particular focus on evaluating thermal performance, air quality and lighting environmental quality because of their strong interaction with the energy performance of buildings. The VDS software framework contains four major functions: 1) Design coordination: It enables users to define tasks using the Input-Process-Output flow approach, which specifies the anticipated activities (i.e., the process), required input and output information, and anticipated interactions with other tasks. It also allows task scheduling to define the work flow, and sharing of the design data and information via the internet. 2) Modeling and simulation: It enables users to perform building simulations to predict the energy consumption and IEQ conditions at any of the design stages by using EnergyPlus and a combined heat, air, moisture and pollutant simulation (CHAMPS) model. A method for co-simulation was developed to allow the use of both models at the same time step for the combined energy and indoor air quality analysis. 3) Results visualization: It enables users to display a 3-D geometric design of the building by reading BIM (building information model) file generated by design software such as SketchUp, and the predicted results of heat, air, moisture, pollutant and light distributions in the building. 4) Performance evaluation: It enables the users to compare the performance of a proposed building design against a reference building that is defined for the same type of buildings under the same climate condition, and predicts the percent of improvements over the minimum requirements specified in ASHRAE Standard 55-2010, 62.1-2010 and 90.1-2010. An approach was developed to estimate the potential impact of a design factor on the whole building performance, and hence can assist the user to identify areas that have most pay back for investment. The VDS software was developed by using C++ with the conventional Model, View and Control (MVC) software architecture. The software has been verified by using a simple 3-zone case building. The application of the VDS concepts and framework for building design and performance analysis has been illustrated by using a medium-sized, five story office building that received LEED Platinum Certification from USGBC.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Engineering Anti-Microbial Peptide Production in Fungi and Bioprocess Development (CRADA 502)

Crop Protection, specifically controlling agricultural diseases and pests, is essential for crop production at every agricultural scale. Biologics hold enormous potential in this equation to decrease use of more toxic pesticides. Currently, the widespread use of biologics in crop protection is severely hampered by the lack of available tools for their mass production. To ensure biologics are regulated under EPA Biopesticide regulations, the following must be true: The biopesticide is a naturally occurring substance or structurally similar and functionally identical to a naturally occurring substance with a history of exposure to humans and the environment demonstrating minimal toxicity. Since this pertains to the marketed product it is also essential that fermentation hosts have a history of exposure and safe use by humans This research focuses on developing a novel platform for the production and delivery of the cghSAMP peptide using the filamentous fungus Aspergillus niger. A. niger is a well-established industrial microorganism, widely recognized for its strong protein secretion capabilities, high-yield production of enzymes, and classification as a generally recognized as safe (GRAS) organism. By genetically modifying A. niger to express the cghSAMP peptide transgene, we aim to leverage the fungus's robust fermentation system to produce a high volume of the antimicrobial agent. This engineered system represents a potential breakthrough in sustainable disease management, offering an environmentally friendly method for localized application or large-scale production of a biopesticide designed to mitigate the effects of citrus greening disease. The main objectives of this project were: 1. Developing a high-yield and cost-efficient bioprocess to produce an AMP in a current ABF host or readily onboarded hosts. 2. Scale up the process in stirred tank reactors and produce at least 100 grams of AMP at 1- 5g/L

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Comparison of classical and quantal calculations of helium three-body recombination

A general method to study classical scattering in n-dimension is developed. Through classical trajectory calculations, the three-body recombination is computed as a function of the collision energy for helium atoms, as an example. Quantum calculations are also performed for the J{sup Π} = 0{sup +} symmetry of the three-body recombination rate in order to compare with the classical results, yielding good agreement for E ≳ 1 K. The classical threshold law is derived and numerically confirmed for the Newtonian three-body recombination rate. Finally, a relationship is found between the quantum and classical three-body hard hypersphere elastic cross sections which is analogous to the well-known shadow scattering in two-body collisions.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Designing Catalysts for Dehydrogenation of Methane for Reducing Greenhouse Gas during Natural Gas Extraction

Catalytic conversion of methane (CH 4 ) into useful products is critical for maximizing the utility of natural gas output and for reducing green house gas release associated with flaring (burning off CH 4 at natural gas extraction sites). One particular useful technique is methane dry reforming (DRM), which involves the chemical reaction of CH 4 with carbon dioxide (CO 2 ) to generate carbon monoxide (CO), hydrogen gas (H 2 ), and subsequently other useful products. New and improved catalysts are required to facilitate efficient dry methane reforming. In this report, we apply the Density Functional Theory (DFT) computational technique to investigate a catalyst consisting of small nickel clusters (Ni n , n < 10) on ceria (Ce0 2 (111) surfaces) support. One main thrust of this project is to study the initial CH 4 and CO 2 reactions with the catalyst. We find that CH 4 exhibits barrierless reactive adsorption on to the catalyst. In order words, this step is likely not the rate-determining step. A second thrust is to perform detailed studies of the catalyst itself and examine the role of oxygen vacancies. Using a specific DFT method and a hypothesis about the absence of the Ce(III) redox state, we obtain predictions about oxygen vacancies in good agreement with experimental observations.

03 NATURAL GAS↗
NASA NTRS2021

Synthesis and Characterization of Fe(III)-Fe(II)- Mg- Al Smectite Solid Solutions and Implications for Planetary Science

This study demonstrates the synergies and limits of multiple measurement types for the detection of smectite chemistry and oxidation state on planetary surfaces to infer past geochemical conditions. Smectite clay minerals are common products of water-rock interactions throughout the solar system, and their detection and characterization provides important clues about geochemical conditions and past environments if sufficient information about their composition can be discerned. Here, we synthesize and report on the spectroscopic properties of a suite of smectite samples that span the intermediate compositional range between Fe(II), Fe(III), Mg, and Al end-member species using bulk chemical analyses, X-ray diffraction, Vis/IR reflectance spectroscopy, UV and green-laser Raman spectroscopy, and Mössbauer spectroscopy. Our data show that smectite composition and the oxidation state of octahedral Fe can be reliably identified in the near infrared on the basis of combination and fundamental metal-OH stretching modes between 2.1–2.9 μm, which vary systematically with chemistry. Smectites dominated by Mg or Fe(III) have spectrally distinct fundamental and combination stretches, whereas Al-rich and Fe(II)-rich smectites have similar fundamental minima near 2.76 μm, but have distinct combination M-OH features between 2.24 and 2.36 μm. We show that with expanded spectral libraries that include intermediate composition smectites and both Fe(III) and Fe(II) oxidation states, more refined characterization of smectites from MIR data is now possible, as the position of the 450 cm–1 absorption shifts systematically with octahedral Fe content, although detailed analysis is best accomplished in concert with other characterization methods. Our data also provide the first Raman spectral libraries of smectite clays as a function of chemistry, and we demonstrate that Raman spectroscopy at multiple excitation wavelengths can qualitatively distinguish smectite clays of different structures and can enhance interpretation by other types of analyses. Our sample set demonstrates how X-ray diffraction can distinguish between dioctahedral and trioctahedral smectites using either the (02,11) or (06,33) peaks, but auxiliary information about chemistry and oxidation state aids in specific identifications. Finally, the temperature-dependent isomer shift and quadrupole splitting in Mössbauer data are insensitive to changes in Fe content but reliability differentiates Fe within the smectite mineral structure.

Valerie K Fox↗
NASA NTRS1986

An example of scaling MST Doppler spectra using median spectra, spectral smoothing, and velocity tracing

Although automatic, computer scaling methods appeared at the start of the MST (mesosphere stratosphere troposphere) radar technique, there is a continuing need for scaling algorithms that perform editing functions and increase the sensitivity of radar by post processing. The scaling method presented is an adaptation of the method of scaling MST Doppler spectra presented by Rastogi (1984). A brief overview of this method is as follows: a median spectrum is calculated from several sequential spectra; the median noise value is subtracted from this derived spectrum; the median spectrum is smoothed; the detection/nondetection decision is made by comparing the smoothed spectrum to the variance of the smoothed noise; and if a signal is detected, then the half-power points of the smoothed echo spectrum are used to place limits on the evaluation of the first two moments of the unsmoothed median spectrum. In all of the above steps, the algorithm is guided by tracing the expected velocity range upward from the lowest range as far as possible. The method is discussed in more detail.

Green, J. L.↗
DOE OSTI2015

A systematic benchmark of the ab initio Bethe-Salpeter equation approach for low-lying optical excitations of small organic molecules

The predictive power of the ab initio Bethe-Salpeter equation (BSE) approach, rigorously based on many-body Green’s function theory but incorporating information from density functional theory, has already been demonstrated for the optical gaps and spectra of solid-state systems. Interest in photoactive hybrid organic/inorganic systems has recently increased and so has the use of the BSE for computing neutral excitations of organic molecules. However, no systematic benchmarks of the BSE for neutral electronic excitations of organic molecules exist. Here, we study the performance of the BSE for the 28 small molecules in Thiel’s widely used time-dependent density functional theory benchmark set [Schreiber et al., J. Chem. Phys. 128, 134110 (2008)]. We observe that the BSE produces results that depend critically on the mean-field starting point employed in the perturbative approach. We find that this starting point dependence is mainly introduced through the quasiparticle energies obtained at the intermediate GW step and that with a judicious choice of starting mean-field, singlet excitation energies obtained from BSE are in excellent quantitative agreement with higher-level wavefunction methods. The quality of the triplet excitations is slightly less satisfactory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Effect of Er{sup 3+} ions on the phase formation and properties of In{sub 2}O{sub 3}nanostructures crystallized upon microwave heating

Regular sized nanostructures of indium oxide (In{sub 2}O{sub 3}) were homogeneously grown using a facile route, i.e. a microwave-hydrothermal method combined with rapid thermal treatment in a microwave oven. The presence of Er{sup 3+} doping plays an important role in controlling the formation of cubic (bcc) and rhombohedral (rh) In{sub 2}O{sub 3} phases. The samples presented broad photoluminescent emission bands in the green-orange region, which were attributed to the recombination of electrons at oxygen vacancies. The photocatalytic activities of pure bcc-In{sub 2}O{sub 3} and a bcc-rh-In{sub 2}O{sub 3} mixture towards the UVA degradation of methylene blue (MB) were also evaluated. The results showed that Er{sup +3} doped In{sub 2}O{sub 3} exhibited the highest photocatalytic activity with a photonic efficiency three times higher than the pure oxide. The improved performance was attributed to the higher surface area, the greater concentration of electron traps due the presence of the dopant and the possible formation of heterojunctions between the cubic and rhombohedral phases. - Graphical abstract: Photodegradation curves as a function of irradiation time of the samples obtained upon rapid microwave heating. - Highlights: • Efficient and rapid microwave heating to obtain Er{sup 3+} doped In{sub 2}O{sub 3} nanostructures. • Er{sup 3+} ions doping is fundamental to stabilizing the crystalline rhombohedral phase. • Symmetry breaking induced by vacancies in the lattice leads to photoluminescence. • Surface area of doped sample was two times higher than the surface of pure oxide. • The presence of defects in the lattice structure favors photocatalytic activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗