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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 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Large-scale maps of variable infection efficiencies in aquatic Bacteroidetes phage-host model systems: Variable phage-host infection interactions

Microbes drive ecosystem functioning and their viruses modulate these impacts through mortality, gene transfer and metabolic reprogramming. Despite the importance of virus-host interactions and likely variable infection efficiencies of individual phages across hosts, such variability is seldom quantified. In this paper, we quantify infection efficiencies of 38 phages against 19 host strains in aquatic Cellulophaga (Bacteroidetes) phage-host model systems. Binary data revealed that some phages infected only one strain while others infected 17, whereas quantitative data revealed that efficiency of infection could vary 10 orders of magnitude, even among phages within one population. This provides a baseline for understanding and modeling intrapopulation host range variation. Genera specific host ranges were also informative. For example, the Cellulophaga Microviridae, showed a markedly broader intra-species host range than previously observed in Escherichia coli systems. Further, one phage genus, Cba41, was examined to investigate nonheritable changes in plating efficiency and burst size that depended on which host strain it most recently infected. While consistent with host modification of phage DNA, no differences in nucleotide sequence or DNA modifications were detected, leaving the observation repeatable, but the mechanism unresolved. Overall, this study highlights the importance of quantitatively considering replication variations in studies of phage-host interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

An efficient virus–induced gene silencing (VIGS) system for gene functional studies in Miscanthus

Virus-induced gene silencing (VIGS) is a powerful tool for transient gene functional analysis in plants, especially for monocot species (e.g., grasses) that are recalcitrant to transformation. Despite various VIGS systems that have been developed in different plant species, none was previously available for the bioenergy crop Miscanthus. Here, we report the establishment of an efficient and robust VIGS system mediated by Tobacco Rattle Virus (TRV) in Miscanthus. We first investigated the impact of various factors that may affect gene silencing efficiency using the Miscanthus sinensis Phytoene Desaturase (MsPDS) gene as a visual indicator of photobleaching. Then, we optimized the TRV-elicited VIGS procedure using an orthogonal experimental design with four factors (sprout size, Agrobacterium concentration, vacuum infiltration time, and co-incubation time) each at three levels. The following led to the highest silencing efficiency (~76%): inoculation of germinating seedlings (1.0–2.0 mm), Agrobacterium tumefaciens culture grown to optical density at 600 nm (OD 600 ) of 0.4, vacuum infiltration for 90 min, and co-incubation for 5 h. The VIGS system established was applicable for both M. sinensis and M. lutarioriparius, with comparable gene silencing efficiency. We verified the efficacy of the VIGS system via the functional characterization of the role of a MYB transcription factor, MsMYB112, in salt stress tolerance. Expression of MsMYB112 was successfully knocked down using the VIGS system, and this led to compromised salt tolerance in the silenced Miscanthus plants. The TRV-based VIGS system established may, therefore, substantially facilitate functional genomic studies in Miscanthus.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Optimization of multiplexed CRISPR/Cas9 system for highly efficient genome editing in Setaria viridis

Previously, Setaria viridis has been developed as a model plant to better understand the C4 photosynthetic pathway in major crops. With the increasing availability of genomic resources for S. viridis research, highly efficient genome editing technologies are needed to create genetic variation resources for functional genomics. In this paper, we developed a protoplast assay to rapidly optimize the multiplexed CRISPR/Cas9 system in S. viridis. Targeted mutagenesis efficiency was further improved by an average of 1.4-fold with the exonuclease, Trex2. Distinctive mutation profiles were found in the Cas9_Trex2 samples with 94% of deletions larger than 10bp, and less than 1% of mutations being insertions. Further analyses indicated that 52.2% of deletions induced by Cas9_Trex2, as opposed to 3.5% by Cas9 alone, were repaired through microhomology-mediated end joining (MMEJ) rather than the canonical NHEJ DNA repair pathway. Combined with the robust agrobacterium-mediated transformation method with more than 90% efficiency, the multiplex CRISPR/Cas9_Trex2 system was demonstrated to induce targeted mutations in two tightly linked genes, svDrm1a and svDrm1b, at the frequency ranging from 73% to 100% in T0 plants. These mutations were transmitted to at least 60% of the transgene-free T1 plants with 33% of them containing bi-allelic or homozygous mutations in both genes. This highly efficient multiplex CRISPR/Cas9_Trex2 system makes it possible to create a large mutant resource for S. viridis in a rapid and high throughput manner, and has the potential to be widely applicable in achieving more predictable MMEJ-mediated mutations in many plant species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Analyzing the Multiscale Impacts of Implementing Energy-Efficient HVAC Improvements Through Energy Audits and Economic Input–Output Analysis

Abstract Heating, ventilation, and air-conditioning (HVAC) systems are usually an industry’s highest consumer of energy, most of which goes toward space cooling in buildings. Industrial energy-efficiency audits not only benefit manufacturers but also generate significant economic and environmental benefits to localities, states, and the nation. This article analyzes the micro- and macro scale impacts of implementing energy-efficient HVAC systems by integrating the industrial building energy data with the macroeconomic regional economic flow model. Micro-scale data include 10 years of historical energy, cost, and carbon dioxide savings achieved from energy-efficient HVAC implementation offered to manufacturers through industrial energy audits. The data were integrated into the macroeconomic modeling framework to illuminate the cascading regional economic impacts of implementing energy-efficient HVAC recommendations in manufacturing facilities. Results show that if recommendations had been implemented throughout all manufacturers in the region, $656 M energy costs would have been directly saved, 7.8 million metric tons of carbon dioxide emissions would have been avoided, and 4387 jobs could have been created, resulting in a total annual economic impact of $899 M stemming from direct, indirect, and induced impacts. The results offer insight into how industrial energy systems can be designed and provide models for how communities can accomplish a net-zero society.

Energy & Fuels↗
DOE OSTI2021

Impact on Cycle Efficiency of Small Combined Heat and Power Plants from Increasing Firing Temperature Enabled by Additive Manufacturing of Turbine Blades and Vanes

The results of this study show that a 180°F (100°C) increase in firing temperature can increase the gas turbine efficiency by 1 percentage point without improving cooling effectiveness and add 2 additional percentage points in efficiency by using advanced turbine blades with higher internal cooling efficiency. The engine upgrades evaluated in this study show potential for increasing the CHP cycle efficiency by 3 percentage points while increasing the steam generation rate by 8%.

Uysal, Selcuk Can↗
DOE OSTI2023

A Prediction Method for Catchment Efficiency Loss due to Coaxial Nozzle Wear in Powder Fed Directed Energy Deposition Systems

Abstract Powder fed laser directed energy deposition systems show significant promise and their widespread adoption could greatly advance manufacturing technology; however, a significant amount of gas atomized metal powder is wasted during material deposition. As contaminated powder must be collected and disposed of as hazardous waste, this process is often criticized for its low catchment efficiency. This presents potential implementation and scaling issues, as widespread use of this technology would directly increase the amount of contaminated powder in need of safe disposal. A direct contribution to this waste issue was identified in past work as wearing exterior and interior surfaces on a replaceable nozzle component within the additive head of such a system integrated into a hybrid manufacturing machine tool. A computational fluid dynamics simulation is developed specifically for use within the manufacturing process by predicting catchment efficiency losses before a deposition operation is performed. The model is robust enough to calculate a catchment efficiency estimate within a reasonable transition time before deposition and is designed to replace visual estimation of nozzle deterioration by the machine operator. Both of two previously identified wear modes are represented in the simulation. Their effects on powder stream geometry are discussed in detail and the results are compared with in-situ measurements of powder stream geometry and concentrations. The resulting work contributes to the growing understanding of using prediction and prevention methods on catchment efficiency related part defects within these systems.

DeWitte, Lisa↗
DOE OSTI2023

Demonstration of p-side down green light emitting diodes with high external quantum efficiencies

GaN/(In,Ga)N heterostructure based visible Light Emitting Diodes (LED) have enabled a wide range of solid-state lighting applications through excellent efficiency and power output in the shorter wavelengths (≤ 475nm) of violet/blue emission. However, the efficiency of emitters in the longer wavelength range (≥ 500nm) drops drastically due to the need to include higher Indium-content in the InGaN quantum wells. Large average polarization fields for high Indium-content quantum wells for conventional P-up structure, opposes the depletion field leading to large electrostatic barriers for both electrons and holes injection. LEDs fabricated along the N-polar direction with a p-up orientation or Ga-polar direction with p-down orientation lower such electrostatic barriers to carrier injection due to alignment of the polarization dipole field and depletion region field. This can therefore theoretically improve the electrical injection efficiency and reduce the forward voltage of operation. Such a Ga-polar p-down LED requires a bottom buried tunnel junction to avoid current spreading issues for a buried p-GaN layer. In this report, we demonstrate for the first time Ga-polar p-down green emitting LEDs using bottom tunnel junctions and having external quantum efficiencies comparable to those of equivalent p-up LEDs grown by Metal Organic Chemical Vapor Deposition (MOCVD).

36 MATERIALS SCIENCE↗
DOE OSTI2019

Pathways and challenges for efficient solar-thermal desalination

Solar-thermal desalination (STD) is a potentially low-cost, sustainable approach for providing high-quality fresh water in the absence of water and energy infrastructures. Despite recent efforts to advance STD by improving heat-absorbing materials and system designs, the best strategies for maximizing STD performance remain uncertain. To address this problem, we identify three major steps in distillation-based STD: (i) light-to-heat energy conversion, (ii) thermal vapor generation, and (iii) conversion of vapor to water via condensation. Using specific water productivity as a quantitative metric for energy efficiency, we show that efficient recovery of the latent heat of condensation is critical for STD performance enhancement, because solar vapor generation has already been pushed toward its performance limit. We also demonstrate that STD cannot compete with photovoltaic reverse osmosis desalination in energy efficiency. We conclude by emphasizing the importance of factors other than energy efficiency, including cost, ease of maintenance, and applicability to hypersaline waters.

14 SOLAR ENERGY↗
DOE OSTI2021

Efficient light-emitting diodes based on oriented perovskite nanoplatelets

Solution-processed planar perovskite light-emitting diodes (LEDs) promise high-performance and cost-effective electroluminescent devices ideal for large-area display and lighting applications. Exploiting emission layers with high ratios of horizontal transition dipole moments (TDMs) is expected to boost the photon outcoupling of planar LEDs. However, LEDs based on anisotropic perovskite nanoemitters remain to be inefficient (external quantum efficiency, EQE <5%) due to the difficulties of simultaneously controlling the orientations of TDMs, achieving high photoluminescence quantum yields (PLQYs) and realizing charge balance in the films of assembled nanostructures. Here, we demonstrate efficient electroluminescence from an in situ grown perovskite film composed of a monolayer of face-on oriented nanoplatelets. The ratio of horizontal TDMs of the perovskite nanoplatelet film is ~84%, which leads to a light-outcoupling efficiency of ~31%, substantially higher than that of isotropic emitters (~23%). In consequence, LEDs with a peak EQE of 23.6% are achieved, representing highly efficient planar perovskite LEDs.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Investigation of the decolorization efficiency of two pin-to-plate corona discharge plasma system for industrial wastewater treatment

In this article, a dual pin-to-plate high-voltage corona discharge system is introduced to study experimentally the gap distance, the contact time, the effect of pin and plate materials, the thickness of ground plate and the conductivity on the amount of Acid Blue 25 dye color removal efficiency from polluted water. A study for the optimum air gap distance between dual pin and surface of Acid Blue 25 dye solution is carried out using 3D-EM simulator to find maximum electric field intensity at the tip of both pins. The outcomes display that the best gap for corona discharge is approximately 5 mm for 15-kV source. This separation is constant during the study of other factors. In addition, an investigation of the essential reactive species responsible for oxidation of the dye organic compounds (O{sub 3} in air discharge, O{sub 3} in water, and H{sub 2}O{sub 2}) during the experimental time is conducted. Three various materials such as: stainless steel, copper and aluminum are used for pins and plate. The maximum color removal efficiencies of Acid Blue 25 dyes are 99.03, 82.04, and 90.78% after treatment time 15 min for stainless steel, copper, and aluminum, respectively. Measurement results for the impact of thickness of an aluminum ground plate on color removal competence show color removal efficiencies of 86.3, 90.78, and 98.06% after treatment time 15 min for thicknesses of 2, 0.5, and 0.1 mm, respectively. The increasing of the solution conductivity leads to the reduction of decolorization efficiency. A kinetic model is used to define the performance of corona discharge system. The models of pseudo-zero-order, pseudo-first-order, and pseudo-second-order reaction kinetics are utilized to investigate the decolorization of Acid Blue 25 dye. The rate of degradation of Acid Blue 25 dye follows the pseudo-first-order kinetics in the dye concentration.

36 MATERIALS SCIENCE↗
DOE OSTI2018

High-Efficiency AlGaAs/GaAs Photovoltaic Converters with Edge Input of Laser Light

High-efficiency photovoltaic converters (PVCs) have been developed and fabricated by liquidphase epitaxy in the AlGaAs–GaAs system with laser light (λ = 850 nm) introduced through the edge surface in parallel to the plane of the p–n junction of the device structure. To raise the efficiency of light “capture” by the p–n junction, an Al{sub x}Ga{sub 1–x}As waveguide layer is formed, in which the content of aluminum gradually varies from x = 0.55 to 0.15 so that the refractive index gradient is created in this layer and light beams are diverted toward the p–n junction. When a PVC (having no antireflection coating) is exposed to 0.1- to 0.2-W laser light, an efficiency of 41.5% is obtained. Depositing an antireflection coating on the edge surface of a PVC raises its efficiency to 55%.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Calibration of the light-flavour jet mistagging efficiency of the b -tagging algorithms with Z+jets events using 139 $\textrm{fb}^{-1}$ of ATLAS proton–proton collision data at $\sqrt{s} = 13$ TeV

The identification of b -jets, referred to as b -tagging, is an important part of many physics analyses in the ATLAS experiment at the Large Hadron Collider and an accurate calibration of its performance is essential for high-quality physics results. This publication describes the calibration of the light-flavour jet mistagging efficiency in a data sample of proton–proton collision events at $\sqrt{s} = 13$ TeV corresponding to an integrated luminosity of 139 fb -1 . The calibration is performed in a sample of Z bosons produced in association with jets. Due to the low mistagging efficiency for light-flavour jets, a method which uses modified versions of the b-tagging algorithms referred to as flip taggers is used in this work. A fit to the jet-flavour-sensitive secondary-vertex mass is performed to extract a scale factor from data, to correct the light-flavour jet mistagging efficiency in Monte Carlo simulations, while simultaneously correcting the b -jet efficiency. With this procedure, uncertainties coming from the modeling of jets from heavy-flavour hadrons are considerably lower than in previous calibrations of the mistagging scale factors, where they were dominant. The scale factors obtained in this calibration are consistent with unity within uncertainties.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

XploreNAS : Explore Adversarially Robust and Hardware-efficient Neural Architectures for Non-ideal Xbars

Compute In-Memory platforms such as memristive crossbars are gaining focus as they facilitate acceleration of Deep Neural Networks (DNNs) with high area and compute efficiencies. However, the intrinsic non-idealities associated with the analog nature of computing in crossbars limits the performance of the deployed DNNs. Furthermore, DNNs are shown to be vulnerable to adversarial attacks leading to severe security threats in their large-scale deployment. Thus, finding adversarially robust DNN architectures for non-ideal crossbars is critical to the safe and secure deployment of DNNs on the edge. This work proposes a two-phase algorithm-hardware co-optimization approach called XploreNAS that searches for hardware efficient and adversarially robust neural architectures for non-ideal crossbar platforms. We use the one-shot Neural Architecture Search approach to train a large Supernet with crossbar-awareness and sample adversarially robust Subnets therefrom, maintaining competitive hardware efficiency. Our experiments on crossbars with benchmark datasets (SVHN, CIFAR10, CIFAR100) show up to ~8–16% improvement in the adversarial robustness of the searched Subnets against a baseline ResNet-18 model subjected to crossbar-aware adversarial training. We benchmark our robust Subnets for Energy-Delay-Area-Products (EDAPs) using the Neurosim tool and find that with additional hardware efficiency–driven optimizations, the Subnets attain ~1.5–1.6× lower EDAPs than ResNet-18 baseline.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

QProR: An Efficient Framework for Quantity-of-Interest Based Progressive Retrieval with Guaranteed Error Control

Scientific applications generate an unprecedented volume of data, overwhelming the network and file systems’ bandwidth and posing challenges for efficient and scalable data retrieval and analysis. Progressive data compression offers a promising solution by enabling on-demand retrieval at reduced size. However, existing progressive methods either fail to bound the errors in essential quantities of interest (QoIs) derived from raw data or suffer from suboptimal retrieval efficiency. In this work, we propose QProR, an efficient QoI-based progressive framework that optimizes progressive retrieval for target QoIs. Our key contributions include: (1) a systematic framework that integrates error-controlled lossy compressors with bitplane encoding while decoupling the two processes for high flexibility and adaptability; (2) a novel weighted bitplane encoding method which incorperates QoI knowledge into data refactoring to enhance retrieval efficiency; (3) an optimized retrieval strategy that accounts for the varying impacts of different variables on multivariate QoIs; (4) comprehensive evaluations using six real-world datasets from multiple scientific applications and thorough comparisons against state of the arts. Experimental results demonstrate that QProR achieves up to 80.38% reduction in the retrieval size under the same requested QoI error tolerance, when compared with the best-performing existing methods. When transferring 384 GB of scientific data to remote sites, QProR delivers up to 1.68 × speedup in the end-to-end data transfer performance.

Li, Wenbo [University of Kentucky]↗
DOE OSTI2025

Editors’ Choice—Molten Salt Electrolysis in Chloride Melts for Energy-Efficient Iron Metal Production

This study explores chloride molten salt electrolysis (CMSE) as a promising route for energy-efficient iron metal (Fe) production. Moderate temperature (500 °C) LiCl-KCl molten salts offer excellent thermodynamic stability, high ionic conductivity and diffusivity, and high solubility for FeCl 3 , thereby enabling efficient Fe metal extraction at high electrowinning rates. Here, we demonstrate the two essential steps for converting taconite ore into Fe metal. First, Fe 2 O 3 from taconite pellets was selectively leached in HCl yielding a high-purity FeCl 3 aqueous solution, while the gangue components settled at the bottom. Then, anhydrous FeCl 3 was electrolyzed in a LiCl-KCl eutectic molten salt at 500 °C at high current density (1 A cm −2 ) and at high Coulombic efficiency (>85%). Analysis of the electrowon Fe deposits revealed dendritic structures with purity of >99 wt%, which could be further improved to nearly 100 wt% through arc re-melting. CMSE offers low specific energy consumption (3.7 kWhr kg −1 ), competitive with H 2 -DRI and other electrolytic approaches being pursued globally. Our findings underscore the potential of CMSE as an energy-efficient route for electrosynthesis of Fe metal.

36 MATERIALS SCIENCE↗
DOE OSTI2016

A Computational Study of Optically Concentrating, Solar-Fuels Generators from Annual Thermal- and Fuel-Production Efficiency Perspectives

The commercial deployment of wireless photoelectrochemical cells (PECs) may provide a viable means to close the anthropogenic carbon cycle associated with the global transportation sector. The growing body of research on PECs has largely focused on developing and integrating the materials necessary for robust, efficient solar-fuel production on the laboratory benchtop. While these efforts are a prerequisite for the commercialization of PECs, deployed PECs will have to contend with extreme heat, cold, and insolation variations in the outdoor environment. They will also have to operate efficiently throughout their lifetime and in multiple locations. This paper reports a computational framework for estimating the hourly profiles of time-varying temperature and solar-to-hydrogen efficiency that optically concentrating, wireless PECs will attain over the course of a typical year. It is found that annual weighted average solar-to-hydrogen efficiencies in excess of 9 to 11% can be achieved in extremely cloudy and sunny locations, respectively. Additionally, typical PECs will likely incur damage due to overheating or freezing; measures to protect PECs from extreme heat and cold are outlined. Here, the findings also help to bring into focus issues regarding real-world deployment of energy-generation technologies and methodologies towards tackling them.

25 ENERGY STORAGE↗
DOE OSTI2018

Efficient Capacitive Deionization Using Thin Film Sodium Manganese Oxide

Capacitive deionization (CDI) is an emerging electrochemical desalination technology, which could outperform other desalination technologies if new electrode materials are developed with high electrochemical salt sorption capacities. Recent work has demonstrated improved desalination efficiency using redox-active materials in hybrid CDI (hCDI) electrodes. Here, we report new charge-storage behavior in thin-film sodium manganese oxide (NMO) which promises to enable new levels of desalination efficiency. We deposit thin-film MnO via atomic layer deposition (ALD), and electrochemically convert it to NMO in NaCl(aq). NMO coated electrodes exhibit increases in charge storage capacity up to 170 times higher than uncoated electrodes. Electrochemical quartz crystal microbalance (EQCM) measurements reveal that thin-film NMO leads to the electrochemical removal of 2.3 Na+ ions per electron. This super-stoichiometric removal of Na+ is corroborated by ab initio modeling that predicts a new electrochemical phenomenon at the NMO surface, which we term electron-decoupled ion transfer, or “EDIT.” We also describe a new custom low-volume and low-mass-loading hCDI cell which enables the study of the desalination performance of the EDIT mechanism. An hCDI cell comprised of NMO-coated carbon nanotube (CNT) cathode and Ag nanoparticle-decorated CNT anode yields a ~20-fold improvement in charge storage over bare CNT electrodes. The hCDI cell has a reversible charging efficiency (mol NaCl (mol e-)-1) of 123 ± 5% and a coulombic efficiency of 93%, corroborating our EQCM results and the EDIT mechanism. The EDIT mechanism, as well as the hCDI cell design that enabled its study, promise to hasten the development of hCDI devices with unprecendented performance

ab initio modeling↗
DOE OSTI2020

Nested active learning for efficient model contextualization and parameterization: pathway to generating simulated populations using multi-scale computational models

There is increasing interest in the use of mechanism-based multi-scale computational models (such as agent-based models (ABMs)) to generate simulated clinical populations in order to discover and evaluate potential diagnostic and therapeutic modalities. The description of the environment in which a biomedical simulation operates (model context) and parameterization of internal model rules (model content) requires the optimization of a large number of free parameters. In this work, we utilize a nested active learning (AL) workflow to efficiently parameterize and contextualize an ABM of systemic inflammation used to examine sepsis. Contextual parameter space was examined using four parameters external to the model’s rule set. The model’s internal parameterization, which represents gene expression and associated cellular behaviors, was explored through the augmentation or inhibition of signaling pathways for 12 signaling mediators associated with inflammation and wound healing. We have implemented a nested AL approach in which the clinically relevant (CR) model environment space for a given internal model parameterization is mapped using a small Artificial Neural Network (ANN). The outer AL level workflow is a larger ANN that uses AL to efficiently regress the volume and centroid location of the CR space given by a single internal parameterization. We have reduced the number of simulations required to efficiently map the CR parameter space of this model by approximately 99%. In addition, we have shown that more complex models with a larger number of variables may expect further improvements in efficiency.

97 MATHEMATICS AND COMPUTING↗