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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Characterization of electrically-active defects in ultraviolet light-emitting diodes with laser-based failure analysis techniques

Laser-based failure analysis techniques demonstrate the ability to quickly and non-intrusively screen deep ultraviolet light-emitting diodes (LEDs) for electrically-active defects. In particular, two laser-based techniques, light-induced voltage alteration and thermally-induced voltage alteration, generate applied voltage maps (AVMs) that provide information on electrically-active defect behavior including turn-on bias, density, and spatial location. Here, multiple commercial LEDs were examined and found to have dark defect signals in the AVM indicating a site of reduced resistance or leakage through the diode. The existence of the dark defect signals in the AVM correlates strongly with an increased forward-bias leakage current. This increased leakage is not present in devices without AVM signals. Transmission electron microscopy analysis of a dark defect signal site revealed a dislocation cluster through the pn junction. The cluster included an open core dislocation. Even though LEDs with few dark AVM defect signals did not correlate strongly with power loss, direct association between increased open core dislocation densities and reduced LED device performance has been presented elsewhere [M. W. Moseley et al., J. Appl. Phys. 117, 095301 (2015)].

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

A Many-Body Perturbation Theory Approach to Energy Band Alignment at the Crystalline Tetracene–Silicon Interface

Hybrid inorganic–organic semiconductor (HIOS) interfaces are of interest for new photovoltaic devices operating above the Shockley–Queisser limit. Predicting energy band alignment at the interfaces is crucial for their design, but represents a challenging problem due to the large scales of the system, the energy precision required and a wide range of physical phenomena that occur at the interface. To tackle this problem, many-body perturbation theory in the non-self-consistent GW approximation, orbital relaxation corrections for organic semiconductors, and line-up potential method for inorganic semiconductors which allows for tractable and accurate computing of energy band alignment in crystalline van-der-Waals hybrid inorganic–organic semiconductor interfaces are used. In this work, crystalline tetracene physisorbed on the clean hydrogen-passivated 1 × 2 reconstructed (100) silicon surface is studied. Using this computational approach, it is found that the energy band alignment is determined by an interplay of the mutual dynamic dielectric screening of two materials and the formation of a dipole layer due to a weak hybridization of atomic/molecular orbitals at the interface. The significant role of the exchange-correlation effects in predicting band offsets for the hybrid inorganic–organic semiconductor interfaces is also emphasized.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2016

Insights into cellulase-lignin non-specific binding revealed by computational redesign of the surface of green fluorescent protein

Biological-mediated conversion of pretreated lignocellulosic biomass to biofuels and biochemicals is a promising avenue towards energy sustainability. However, a critical impediment to the commercialization of cellulosic biofuel production is the high cost of cellulase enzymes needed to deconstruct biomass into fermentable sugars. One major factor driving cost is cellulase adsorption and inactivation in the presence of lignin, yet we currently have a poor understanding of the protein structure-function relationships driving this adsorption. In this work, we have systematically investigated the role of protein surface potential on lignin adsorption using a model monomeric fluorescent protein. We have designed and experimentally characterized 16 model protein variants spanning the physiological range of net charge (-24 to +16 total charges) and total charge density (0.28 to 0.40 charges per sequence length) typical for natural proteins. Protein designs were expressed, purified, and subjected to in silico and in vitro biophysical measurements to evaluate the relationship between protein surface potential and lignin adsorption properties. The designs were comparable to model fluorescent protein in terms of thermostability and heterologous expression yield, although the majority of the designs unexpectedly formed homodimers. Protein adsorption to lignin was studied at two different temperatures using Quartz Crystal Microbalance with Dissipation Monitoring and a subtractive mass balance assay. We found a weak correlation between protein net charge and protein-binding capacity to lignin. No other single characteristic, including apparent melting temperature and 2nd virial coefficient, showed correlation with lignin binding. Analysis of an unrelated cellulase dataset with mutations localized to a family I carbohydrate-binding module showed a similar correlation between net charge and lignin binding capacity. Altogether, our study provides strategies to identify highly active, low lignin-binding cellulases by either rational design or by computational screening genomic databases.

09 BIOMASS FUELS↗
DOE OSTI2018

Characterizing the Quantum-Confined Stark Effect in Semiconductor Quantum Dots and Nanorods for Single-Molecule Electrophysiology

We optimized the performance of quantum-confined Stark effect (QCSE)-based voltage nanosensors. A high-throughput approach for single-particle QCSE characterization was developed and utilized to screen a library of such nanosensors. Type-II ZnSe/CdS-seeded nanorods were found to have the best performance among the different nanosensors evaluated in this work. The degree of correlation between intensity changes and spectral changes of the exciton's emission under an applied field was characterized. An upper limit for the temporal response of individual ZnSe/CdS nanorods to voltage modulation was characterized by high-throughput, high temporal resolution intensity measurements using a novel photon-counting camera. The measured 3.5 μs response time is limited by the voltage modulation electronics and represents ~30 times higher bandwidth than needed for recording an action potential in a neuron.

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

Structure–function relationships in single molecule rectification by N -phenylbenzamide derivatives

Here, we examine structure–function relationships in a series of N -phenylbenzamide (NPBA) derivatives by using computational modeling to identify molecular structures that exhibit both rectification and good conductance together with experimental studies of bias-dependent single molecule conductance and rectification behavior using the scanning tunneling microscopy break-junction technique. From a large number of computationally screened molecular diode structures, we have identified NPBA as a promising candidate, relative to the other structures that were screened. We demonstrate experimentally that conductance and rectification are both enhanced by functionalization of the NPBA 4-carboxamido-aniline moiety with electron donating methoxy groups, and are strongly correlated with the energy of the conducting frontier orbital relative to the Fermi level of the gold leads used in break-junction experiments.

36 MATERIALS SCIENCE↗
NASA NTRS1980

Capillary device refilling

An analytical and experimental study was conducted dealing with refilling start baskets (capillary devices) with settled fluid. A computer program was written to include dynamic pressure, screen wicking, multiple-screen barriers, standpipe screens, variable vehicle mass for computing vehicle acceleration, and calculation of tank outflow rate and vapor pullthrough height. An experimental apparatus was fabricated and tested to provide data for correlation with the analytical model; the test program was conducted in normal gravity using a scale-model capillary device and ethanol as the test fluid. The test data correlated with the analytical model; the model is a versatile and apparently accurate tool for predicting start basket refilling under actual mission conditions.

Blatt, M. H.↗
DOE OSTI2014

Evaluation of High Throughput Screening Methods in Picking up Differences between Cultivars of Lignocellulosic Biomass for Ethanol Production

Here, we present a unique evaluation of three advanced high throughput pretreatment and enzymatic hydrolysis systems (HTPH-systems) for screening of lignocellulosic biomass for enzymatic saccharification. Straw from 20 cultivars of winter wheat from two sites in Denmark was hydrothermally pretreated and enzymatically processed in each of the separately engineered HTPH-systems at 1) University of California, Riverside, 2) National Renewable Energy Laboratory (NREL), Colorado, and 3) University of Copenhagen (CPH). All three systems were able to detect significant differences between the cultivars in the release of fermentable sugars, with average cellulose conversions of 57%, 64%, and 71% from Riverside, NREL and CPH, respectively. We found the best correlation of glucose yields between the Riverside and NREL systems (R2 = 0.2139), and the best correlation for xylose yields was found between Riverside and CPH (R2 = 0.4269). The three systems identified Flair as the highest yielding cultivar and Dinosor, Glasgow, and Robigus as low yielding cultivars. Despite different conditions in the three HTPH-systems, the approach of microscale screening for phenotypically less recalcitrant feedstock seems sufficiently robust to be used as a generic analytical platform.

09 BIOMASS FUELS↗
DOE OSTI2018

Functional analysis of juxta- and intra-membrane domains of murine APP by genome editing in Neuro2a cells

Highlights: • Mutations of iuxta-/intra-membrane domains of murine APP were screened by genome editing using neuro2a cell. • Identified mutations influences APP metabolisms and neurite outgrowth. • Juxta-/intra membrane domains may have unknown regulatory functions. Amyloid-β precursor protein (APP) correlates with the pathogenesis of certain brain diseases, such as Alzheimer disease (AD). APP is cleaved by several enzymes to produce APP metabolites, including the amyloid beta peptide (Aβ), which accumulates in the brain of AD patients. However, the exact functions of APP metabolites remain elusive. In this study, using genome editing technology, we mutated juxta- and intra-membrane domains of murine APP in the mouse neuroblastoma cell line, Neuro2a. We identified several clones that expressed characteristic patterns of APP metabolites. Mutations in juxta- (deletion 673A), and intra-membrane (deletion 705-6LM) domains of APP, decreased overall levels of APP metabolites or decreased the level of α-secretase-cleaved carboxy-terminal fragment (αCTF), respectively. APP is known to influence neuronal differentiation; therefore, we used theses clones to dissect the function of APP metabolites during neuronal differentiation. One clone (CA), which expressed reduced levels of both FL-APP and αCTF, showed increased expression of the neuronal marker, β3-tubulin, and enhanced retinoic acid (RA)-induced neurite outgrowth. In contrast, a clone that expressed FL-APP, but was devoid of αCTF (CE), showed comparable expression of β3-tubulin and neurite outgrowth compared with normal Neuro2a cells. These data indicate that FL-APP is a suppressor of neurite outgrowth. Our data suggest a novel regulatory function of juxta- and intra-membrane domains on the metabolism and function of APP.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Intersections of Disadvantaged Communities and Renewable Energy Potential: Data Set and Analysis to Inform Equitable Investment Prioritization in the United States

Renewable energy development can bolster local economies through job creation, local tax revenues, and reduced energy costs; however, communities most in need of economic development and employment opportunities often see lower levels of renewable energy deployment. We sought to identify areas where disadvantaged community indicators and high generation potential from cost-effective renewable energy opportunities intersect and deployment could lead to economic development and job creation. This presentation will highlight several of our findings. This research and the associated county-level data set are intended to inform national- and state-level energy-related assistance programs, economic development efforts, and infrastructure programs seeking to prioritize investments in disadvantaged communities.

community energy planning↗
DOE OSTI2020

In vitro prototyping and rapid optimization of biosynthetic enzymes for cell design

The design and optimization of biosynthetic pathways for industrially relevant, non-model organisms is challenging due to transformation idiosyncrasies, reduced numbers of validated genetic parts and a lack of high-throughput workflows. Here we describe a platform for in vitro prototyping and rapid optimization of biosynthetic enzymes (iPROBE) to accelerate this process. In iPROBE, cell lysates are enriched with biosynthetic enzymes by cell-free protein synthesis and then metabolic pathways are assembled in a mix-and-match fashion to assess pathway performance. We demonstrate iPROBE by screening 54 different cell-free pathways for 3-hydroxybutyrate production and optimizing a six-step butanol pathway across 205 permutations using data-driven design. Observing a strong correlation (r = 0.79) between cell-free and cellular performance, we then scaled up our highest-performing pathway, which improved in vivo 3-HB production in Clostridium by 20-fold to 14.63 ± 0.48 g l -1 . Finally, we expect iPROBE to accelerate design–build–test cycles for industrial biotechnology.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Thermal ionization induced metal-semiconductor transition and room temperature ferromagnetism in trivalent doped ZnO codoped with lithium

Thermal ionization induced metallic to semiconductor (MST) transition occurring at 460 K for Zn{sub 0.97}Al{sub 0.03}O, 463 K for Zn{sub 0.94}Al{sub 0.03}Li{sub 0.03}O, and 503 K for Zn{sub 0.91}Al{sub 0.03}Li{sub 0.03}Mn{sub 0.03}O has been found in the sol-gel synthesized (using hexamethylenetetramine), trivalent doped (Al, Mn) ZnO codoped with lithium. Increase in the thermally ionized carrier concentration due to Al doping is responsible for near band edge (NBE) peak shift causing Fermi level to move into conduction band making it metallic consistent with resistivity results. Free carrier (thermally activated) neutralization with ionized donor is responsible for semiconducting nature, which is supported from the free carrier screening produced energy shift in the NBE of photoluminescence peak. Furthermore, independently band gap shrinkage is also obtained from UV-Visible studies confirming localization induced MST. An anti-correlation is found between defect density (DLE) and room temperature ferromagnetism (RTFM) indicating intrinsic defects are not directly responsible for RTFM.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

First-principles calculation of gate-tunable ferromagnetism in magic-angle twisted bilayer graphene under pressure

Magic-angle twisted bilayer graphene (MATBG) is notable as a highly tunable platform for investigating strongly correlated phenomena such as unconventional superconductivity and quantum spin liquids, due to easy control of doping level through gating and sensitive dependence of the magic angle on hydrostatic pressure. Experimental observations of correlated insulating states, unconventional superconductivity and ferromagnetism in MATBG indicate that this system exhibits rich exotic phases. In this work, using density functional theory calculations in conjunction with the effective screening medium method, we find the MATBG under pressure at a twisting angle of 2.88 °and simulate how its electronic states evolve when doping level and electric field perpendicular to plane are tuned by gating. Our calculations show that, at doping levels between two electrons and four holes per moiré unit cell, a ferromagnetic (FM) solution with spin density localized at AA stacking sites is lower in energy than the nonmagnetic solution. The magnetic moment of this FM state decreases with both electron and hole doping and vanishes at four electrons/holes doped per moiré unit cell. Hybridization between the flat bands at the Fermi level and the surrounding dispersive bands can take place at finite doping. On increasing the out-of-plane electric field at zero doping, a transition from the FM state to the nonmagnetic one is seen. An investigation of impurity effects shows that both absorption of O 2 molecules and occurrence of Stone–Wales impurities suppress the FM state, and the mechanisms are understood from our calculations. We also analyze the interlayer bonding character due to flat bands via Wannier functions. Finally, we report trivial band topology of the flat bands in the FM state at a certain doping level.

Physics↗
DOE OSTI2022

Measurements of the Five-Dimensional Phase Space Distribution of an Intense Ion Beam

No simulation of intense beam transport has accurately reproduced measurements at the level of beam halo. One potential explanation of this discrepancy is a lack of knowledge of the initial distribution of particles in six-dimensional (6D) phase space. A direct 6D measurement of an ion beam was recently performed at the Spallation Neutron Source (SNS) Beam Test Facility (BTF), revealing nonlinear transverse-longitudinal correlations in the beam core that affect downstream evolution. Unfortunately, direct 6D measurements are limited in resolution and dynamic range; here, we discuss the use of three slits and one screen to measure a 5D projection of the 6D phase space distribution, overcoming these limitations at the cost of one dimension. We examine the measured 5D distribution before and after transport through the BTF and compare to particle-in-cell simulations. We also discuss the possibility of reconstructing the 6D distribution from 5D and 4D projections.

Hoover, Austin↗
DOE OSTI2020

Interference of electrical double layers: Confinement effects on structure, dynamics, and screening of ionic liquids

Ionic liquids are widely used as electrolytes in electronic devices in which they are subject to nanoconfinement within nanopores or nanofilms. Because the intrinsic width of an electrical double layer is on the order of several nanometers, nanoconfinement is expected to fundamentally alter the double layer properties. Furthermore, in confined systems, a large portion of the ions are interfacial, e.g., at the electrode interface, leading to significant deviations of electrostatic screening and ion dynamics as compared to bulk properties. In this article, we systematically investigate the interference between electrical double layers for nanoconfined ionic liquids and the resulting influence on the structure, dynamics, and screening behavior. We perform molecular dynamics simulations for the ionic liquids [BMIm + ][BF$^-_4$] and [BMIm + ][PF$^-_6$] confined between two flat electrodes at systematic separation distances between 1.5 nm and 4.5 nm for both conducting and insulating boundary conditions. We find that while ion dynamics is expectedly slower than in the bulk (by ~2 orders of magnitude), there is an unexpected non-linear trend with the confinement length that leads to a local maximum in dynamic rates at ~3.5–4.5 nm confinement. We show that this nonlinear trend is due to the ion correlation that arises from the interference between opposite double layers. We further evaluate confinement effects on the ion structure and capacitance and investigate the influence of electronic polarization of the ionic liquid on the resulting properties. This systematic evaluation of the connection between electrostatic screening and structure and dynamics of ionic liquids in confined systems is important for the fundamental understanding of electrochemical supercapacitors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Prediction of O and OH Adsorption on Transition Metal Oxide Surfaces from Bulk Descriptors

In the search for stable and active catalysts, density functional theory and machine learning (ML) based models can accelerate the screening of materials. While stability is conveniently addressed on the bulk level of computation, the modelling of catalytic activity requires expensive surface simulations. Here, in this work, we develop models for the surface adsorption energy of O and OH intermediates across a consistent and extensive dataset of pure transition metal oxide surfaces. We show that adsorption energies across metal oxidation states of +2 to +6 are well captured from the metal-oxygen bond strength extracted from the bulk level calculation. Specifically, we calculate the integrated crystal orbital Hamiltonian population (ICOHP) of the metal-oxygen bond in the bulk oxide and employ a simple normalization scheme to obtain a strong correlation with adsorption energetics. By combining our ICOHP descriptor with non DFT features in a Gaussian Process regression (GPR) model, we achieve high model accuracy with mean absolute errors of 0.166 and 0.219 eV for OH and O adsorption, respectively. By targeting the O-OH adsorption energy difference with our GPR model, we predict the the oxygen evolution reaction (OER) activity from bulk descriptors only. Furthermore, we utilize the strong correlation between the COHP and metal oxygen bond lengths to rapidly predict adsorption energetics and catalytic activity from the optimized bulk geometry. Our approach can enable an efficient search for active catalysts by eliminating the need for surface calculations in the initial screening phase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Rapid screening of secondary aromatic metabolites in Populus trichocarpa leaves

Abstract Background High-throughput metabolomics analytical methodology is needed for population-scale studies of bioenergy-relevant feedstocks such as poplar ( Populus sp.). Here, the authors report the relative abundance of extractable aromatic metabolites in Populus trichocarpa leaves rapidly estimated using pyrolysis-molecular beam mass spectrometry (py-MBMS). Poplar leaves were analyzed in conjunction with and validated by GC/MS analysis of extracts to determine key spectral features used to build PLS models to predict the relative composition of extractable aromatic metabolites in whole poplar leaves. Results The Pearson correlation coefficient for the relative abundance of extractable aromatic metabolites based on ranking between GC/MS analysis and py-MBMS analysis of the Boardman leaf set was 0.86 with R 2 = 0.76 using a simplified prediction approach from select ions in MBMS spectra. Metabolites most influential to py-MBMS spectral features in the Clatskanie set included the following compounds: catechol, salicortin, salicyloyl-coumaroyl-glucoside conjugates, α-salicyloylsalicin, tremulacin, as well as other salicylates, trichocarpin, salicylic acid, and various tremuloidin conjugates. Ions in py-MBMS spectra with the highest correlation to the abundance of extractable aromatic metabolites as determined by GC/MS analysis of extracts, included m/z 68, 71, 77, 91, 94, 105, 107, 108, and 122, and were used to develop the simplified prediction approach without PLS models or a priori measurements. Conclusions The simplified py-MBMS method is capable of rapidly screening leaf tissue for relative abundance of extractable aromatic secondary metabolites to enable prioritization of samples in large populations requiring comprehensive metabolomics that will ultimately inform plant systems biology models and advance the development of optimized biomass feedstocks for renewable fuels and chemicals.

09 BIOMASS FUELS↗
DOE OSTI2022

Dynamics of superconducting qubit relaxation times

Superconducting qubits are a leading candidate for quantum computing but display temporal fluctuations in their energy relaxation times T 1 . This introduces instabilities in multi-qubit device performance. Furthermore, autocorrelation in these time fluctuations introduces challenges for obtaining representative measures of T 1 for process optimization and device screening. These T 1 fluctuations are often attributed to time varying coupling of the qubit to defects, putative two level systems (TLSs). In this work, we develop a technique to probe the spectral and temporal dynamics of T 1 in single junction transmons by repeated T 1 measurements in the frequency vicinity of the bare qubit transition, via the AC-Stark effect. Across 10 qubits, we observe strong correlations between the mean T 1 averaged over approximately nine months and a snapshot of an equally weighted T 1 average over the Stark shifted frequency range. These observations are suggestive of an ergodic-like spectral diffusion of TLSs dominating T 1 , and offer a promising path to more rapid T 1 characterization for device screening and process optimization.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗