SEARCH · Search NASA

Results for “engine efficiency”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,657 records · Page 92

All sources NASA NTRS DOE OSTI

DOE OSTI2024

Investigation of Ammonia Carrier Materials for Next Generation Ammonia Dosing System - CRADA 334 (Abstract)

Lean-burn gasoline and diesel engines can offer substantially higher fuel efficiency, good driving performance, and reduced carbon dioxide emission compared to stoichiometric gasoline engines. Various catalyst technologies have been developed to remove the pollutants from these engines. For example, a three-way catalyst (TWC) is used to remove hydrocarbons (HC), carbon monoxide (CO), and nitrogen oxides (NOx) from gasoline engines during the stoichiometric conditions. During the lean-burn conditions, a TWC or a diesel oxidation catalyst (DOC) is used to control HC and CO emissions. NOx is removed by either lean NOx trap catalyst (LNT) that can store NOx under lean conditions and reduce NOx under rich conditions, or selective catalytic reduction catalyst (SCR) that can selectively remove NOx with a reducing agent. Among the NOx reduction catalyst technologies, SCR offers a number of advantages, including excellent NOx reduction efficiency over a wide range of temperatures and overall lower system cost. In fact, the SCR technology using ammonia (NH3) as reductant has been proven effective and used commercially for the removal of NOx emissions from stationary sources since the 1970s. Currently, SCR is being used to meet the NOx emission standards for diesel engines in Europe and North America, and also being considered for meeting the future NOx emission standards for lean-burn gasoline engines. Because of the challenges associated with storage, handling and transportation of ammonia on a vehicle, aqueous urea solution (e.g., Diesel Exhaust Fluid, AdBlue) has been developed as ammonia storage compound for mobile applications. When the aqueous urea solution is sprayed into exhaust gas stream, urea is decomposed to release ammonia, which then reduces NOx over the downstream SCR catalyst. Although aqueous urea solution technology has enabled automakers and engine manufacturers to meet the current NOx emission standards, this process of releasing ammonia requires a hot exhaust gas and sufficient mixing, creating challenges for low temperature NOx emission control and aftertreatment system packaging. For these reasons, alternative technologies have been developed as ammonia sources (e.g., solid urea, ammonium carbamate, metal ammine chloride) during the past few years. These technologies promise more convenient handling and distribution of ammonia sources, and help maximize the low-temperature performance of SCR catalysts and reduce the overall system volume and weight. However, none of these alternative technologies can be successfully implemented without the industry consensus. Therefore, the USCAR SCR work group, which is comprised of representatives from GM, Ford, and Chrysler, has decided to investigate the potential alternative ammonia carriers, define common standard vehicle interfaces, and address personal and environmental safety concerns with part suppliers and chemical companies. Under this CRADA Project, USCAR and Battelle will investigate alternative ammonia carrier materials that are currently under development. Based on the data and information derived under the CRADA project, the USCAR SCR work group plans to build the consensus and make recommendations for the industry.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Investigation of Ammonia Carrier Materials for Next Generation Ammonia Dosing System - CRADA 334 (Abstract)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS1978

Study, optimization, and design of a laser heat engine

Laser heat engine concepts, proposed for satellite applications, are analyzed to determine which engine concept best meets the requirements of high efficiency (50 percent or better), continuous operation in space using near-term technology. The analysis of laser heat engines includes the thermodynamic cycles, engine design, laser power sources, collector/concentrator optics, receiving windows, absorbers, working fluids, electricity generation, and heat rejection. Specific engine concepts, optimized according to thermal efficiency, are rated by their technological availability and scaling to higher powers. A near-term experimental demonstration of the laser heat engine concept appears feasible utilizing an Otto cycle powered by CO2 laser radiation coupled into the engine through a diamond window. Higher cycle temperatures, higher efficiencies, and scalability to larger sizes appear to be achievable from a laser heat engine design based on the Brayton cycle and powered by a CO laser.

Taussig, R. T.↗

DOE OSTI2023

Utilizing data-based modeling with low life cycle GHG emissions algae biofuels for engine optimization

Aquatic microalgae are a highly promising feedstock for the production of biocrude and tailored biofuels, with distinct advantages over traditional terrestrial crops, such as reduced land use and avoidance of food production competition. However, unlocking their full potential requires the development of biofuels with low life cycle greenhouse emissions biofuels, such as algae biofuels, which can significantly reduce the environmental impact of the transportation systems without requiring a complete overhaul of existing engine technology. In this study, we employ cutting-edge data-based AI modeling techniques to optimize the performance of heavy-duty engines, with a focus on transitioning towards biofuels with low life cycle greenhouse emissions biofuels. Our methodology offers significant advantages over traditional sweep testing, enabling efficient and accurate optimization of engine performance with minimal time and resources consumption. Our findings demonstrate the potential of utilizing this approach, with up to 55% NOx emissions reductions and up to 2% reduction in fuel consumption compared to the baseline optimized point. Moving forward, we plan to utilize a 30% blend of algae biofuels with diesel fuel, with the ultimate goal of achieving up to 60% lifecycle GHG emissions. Lastly, we plan to compare the results with 100% renewable biodiesel to add an additional dimension of investigating the impact of fuel chemistry on engine optimization. Overall, this study underscores the vital importance of biofuels for reducing the carbon footprint of the transportation sector and supporting a sustainable future. By harnessing the power of data-based AI modeling with low life cycle greenhouse emissions biofuels, we can accelerate the adoption of more environmentally friendly transportation systems and reduce their impact on the planet. Our findings contribute to this transition and offer insights for developing efficient and effective strategies for addressing global climate change.

09 BIOMASS FUELS↗

DOE OSTI2018

Ultrathin Lutetium Oxide Film as an Epitaxial Hole-Blocking Layer for Crystalline Bismuth Vanadate Water Splitting Photoanodes

Here a novel ultrathin lutetium oxide (Lu 2 O 3 ) interlayer is integrated with crystalline bismuth vanadate (BiVO4) thin film photoanodes to facilitate carrier transport through atomic-scale interface control. The epitaxial Lu 2 O 3 2 O 3</sub interlayer modulates the electronic conduction pathways along structural grain boundaries and determines the overall device performance. This study provides more information on the nature of interface-engineered carrier transport for efficient photoelectrode heterostructure design.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Multifunction Hydrophobic Ligand Engineered Cd(S, Se)/ZnS Quantum Dots for Stabilizing Highly Efficient Carbon‐Based Perovskite Solar Cells

The long-term operational stability of perovskite solar cells (PSCs) remains a key challenge impeding their commercialization, particularly due to ambient environments (e.g., moisture, oxygen, heat)-induced degradation. Carbon electrode-based PSCs have emerged as cost-effective and relatively stable alternatives to metal electrode-based devices due to carbon materials' hydrophobic behavior, yet they still lag in both long-term durability and power conversion efficiency (PCE). In this work, an ultrathin hydrophobic ligand-modified core–shell Cd(S,Se)/ZnS quantum dots (QDs) capping layer is introduced as a multifunctional interfacial modifier for carbon-electrode-based PSCs. This oleic acid ligand-modified QDs capping layer exhibits inherent hydrophobicity, effectively serving as a moisture barrier to retard perovskite degradation under ambient conditions. Furthermore, the strong interfacial bonding between the QDs and perovskite halide surfaces leads to efficient trap state passivation, reducing trap density and creating a more uniform electrical contact. The modified QDs/perovskite interface also features an elevated conduction band edge, promoting improved charge extraction. As a result, devices incorporating this quantum dot capping layer retain 98% of their initial PCE after 450 h of ambient aging and achieve a champion efficiency of 20.74%. As a result, this strategy highlights the potential of hydrophobic ligand-modified chalcogenide QDs as surface modifiers to enhance both the stability and performance of carbon-based PSCs, offering a promising route toward scalable fabrication of durable perovskite solar modules.

14 SOLAR ENERGY↗

DOE OSTI2017

Triplet Harvesting from Intramolecular Singlet Fission in Polytetracene

Abstract Singlet fission (SF), a promising mechanism of multiple exciton generation, has only recently been engineered as a fast, efficient, intramolecular process (iSF). The challenge now lies in designing and optimizing iSF materials that can be practically applied in high‐performance optoelectronic devices. However, most of the reported iSF systems, such as those based on donor–acceptor polymers or pentacene, have low triplet energies, which limits their applications. Tetracene‐based materials can overcome significant challenges, as the tetracene triplet state is practically useful, ≈1.2 eV. Here, the synthesis and excited state dynamics of a conjugated tetracene homopolymer are studied. This polymer undergoes ultrafast iSF in solution, generating high‐energy triplets on a sub‐picosecond time scale. Magnetic‐field‐dependent photocurrent measurements of polytetracene‐based devices demonstrate the first example of iSF‐generated triplet extraction in devices, exhibiting the potential of iSF materials for use in next‐generation devices.

Pun, Andrew B.↗

DOE OSTI2016

Rapid Solidification and Phase Transformations in Additive Manufactured Materials

Within the past few years, additive manufacturing (AM) has emerged as a promising manufacturing technique to enable the production of complex engineering structures with high efficiency and accuracy. Among the important factors establishing AM as a sustainable manufacturing process is the ability to control the microstructures and properties of AM products. In most AM processes, such as laser sintering (LS), laser melting (LM), and laser metal deposition (LMD), rapid solidification and high-temperature phase transformations play primary roles in determining nano- and microstructures, and consequently the mechanical and other properties of AM products. This topic of JOM is dedicated to summarizing the current research efforts in the area of rapid solidification and phase transformations in additively manufactured materials. Finally, a brief summary follows below of 10 journal articles in this topic.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Scheduling and Performance of Asynchronous Tasks in Fortran 2018 with FEATS

Most parallel scientific programs contain compiler directives (pragmas) such as those from OpenMP (Hermanns in Parallel programming in Fortran 95 using openMP, 2002. School of Aeronautical Engineering, Universidad Politécnica de Madrid, España, 2011), explicit calls to runtime library procedures such as those implementing the Message Passing Interface (MPI) (in A message-passing interface standard version 4.0, 2021. https://www.mpi-forum.org/docs/mpi-4.0/mpi40-report.pdf), or compiler-specific language extensions such as those provided by CUDA (Ruetsch and Fatica in CUDA Fortran for scientists and engineers: best practices for efficient CUDA Fortran programming, Elsevier, 2013). By contrast, the recent Fortran standards empower developers to express parallel algorithms without directly referencing lower-level parallel programming models (Numrich in Parallel programming with co-arrays, CRC Press, 2018, and Curcic in Modern Fortran: building efficient parallel applications, Manning Publications, 2020). Fortran’s parallel features place the language within the Partitioned Global Address Space (PGAS) class of programming models. When writing programs that exploit data parallelism, application developers often find it straightforward to develop custom parallel algorithms. Problems involving complex, heterogeneous, staged calculations, however, pose much greater challenges. Such applications require careful coordination of tasks in a manner that respects dependencies prescribed by a directed acyclic graph. When rolling one’s own solution proves difficult, extending a customizable framework becomes attractive. Further, the paper presents the design, implementation, and use of the Framework for Extensible Asynchronous Task Scheduling (FEATS), which we believe to be the first task scheduling tool written in modern Fortran. We describe the benefits and compromises associated with choosing Fortran as the implementation language, and we propose ways in which future Fortran standards can best support the use case in this paper.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Theory and numerics of subspace approximation of eigenvalue problems

Large-scale eigenvalue problems arise in various fields of science and engineering and demand computationally efficient solutions. In this study, we investigate the subspace approximation for parametric linear eigenvalue problems, aiming to mitigate the computational burden associated with high-fidelity systems. Furthermore, we provide general error estimates under non-simple eigenvalue conditions, establishing some theoretical foundations for understanding the convergence behavior of subspace approximations. Numerical examples, including problems with one-dimensional to three-dimensional spatial domain and one-dimensional to two-dimensional parameter domain, are presented to demonstrate the efficacy of reduced basis method in handling parametric variations in boundary conditions and coefficient fields to achieve significant computational savings while maintaining high accuracy, making them promising tools for practical applications in large-scale eigenvalue computations.

Eigenvalue problems↗

DOE OSTI2019

Tailor-made trees: engineering lignin for ease of processing and tomorrow’s bioeconomy

Lignocellulosic biomass represents an abundant source of cellulosic fibres and fermentable sugars. Yet, lignin, a polyphenolic constituent of secondary-thickened plant cell walls significantly contributes to biomass recalcitrance during industrial processing. Efforts to reduce plant total lignin content through genetic engineering have improved processing efficiency, but often incur an agronomic penalty. Alternatively, modifications that alter the composition of lignin and/or its interaction with other cell wall polymers display improved processing efficiency without compromising biomass yield. We propose that future efforts to improve woody feedstocks should focus on altering lignin composition and cell wall ultrastructure. Here, we describe potential future modifications to lignin and/or other cell wall characteristics that may serve as strategic targets in the production of trees that are tailor-made for specific pretreatments and end-product applications.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Capillary-Enhanced Two-Phase Micro-Cooler Using Copper-Inverse-Opal Wick with Silicon Microchannel Manifold for High-Heat-Flux Cooling Application

In this work, we demonstrate a two-phase capillary-fed boiling micro-cooler that consists of a ~ 25-..mu..m-thick copper inverse opal (CIO) porous wicking structure for high-heat-flux boiling and a silicon 3D-manifold for distributed liquid delivery and vapor extraction across a 0.5 cm x 0.5 cm heated area. At low inlet water mass flow rates of 1.5 to 1.9 g(min)-1, the micro-cooler displays nearly two-phase boiling with exit vapor quality ~ 1 and a high critical heat flux (CHF) of 253 to 320 W cm-2 with low superheat of ~ 10 degrees C resulting in a thermal resistance of boiling ~ 0.025 cm2 degrees C W-1 or heat transfer coefficient of 0.4 MW m-2 degrees C-1. For higher flow rates of 5, 10, and 15 g(min)-1, the micro-cooler exhibits a hybrid single-phase and two-phase cooling regime where the contribution of the sensible heat (single-phase) cooling is linearly added to that of the two-phase cooling. For the highest flow rate of 15 g(min)-1, the CHF is increased to ~ 500 W cm-2 resulting in an overall thermal resistance of ~ 0.18 cm2 degrees C W-1. However, the two-phase heat transfer effectiveness, which estimates the utilization level of the inlet mass flow rate for two-phase boiling, is reduced to ~ 0.11. To achieve the best cooling system performances, the micro-cooler must operate entirely within the two-phase boiling regime (exit vapor quality or two-phase heat transfer effectiveness ~ 1). Ideally, the "coolant" should be delivered near its saturation temperature (~ 100 degrees C for water), which provides significant advantages for the energy-efficient operation of data centers and power electronics. We present detailed analysis with Infrared and high speed camera images at various inlet flow rates and heat fluxes to understand complex heat transfer in the micro-cooler. Furthermore, a conjugate thermofluidic simulation model, which incorporates the physics of capillary-fed boiling in a porous copper layer, agrees well with the experimental data.

capillary-enhanced boiling↗

DOE OSTI2016

Polynomial meta-models with canonical low-rank approximations: Numerical insights and comparison to sparse polynomial chaos expansions

The growing need for uncertainty analysis of complex computational models has led to an expanding use of meta-models across engineering and sciences. The efficiency of meta-modeling techniques relies on their ability to provide statistically-equivalent analytical representations based on relatively few evaluations of the original model. Polynomial chaos expansions (PCE) have proven a powerful tool for developing meta-models in a wide range of applications; the key idea thereof is to expand the model response onto a basis made of multivariate polynomials obtained as tensor products of appropriate univariate polynomials. The classical PCE approach nevertheless faces the “curse of dimensionality”, namely the exponential increase of the basis size with increasing input dimension. To address this limitation, the sparse PCE technique has been proposed, in which the expansion is carried out on only a few relevant basis terms that are automatically selected by a suitable algorithm. An alternative for developing meta-models with polynomial functions in high-dimensional problems is offered by the newly emerged low-rank approximations (LRA) approach. By exploiting the tensor–product structure of the multivariate basis, LRA can provide polynomial representations in highly compressed formats. Through extensive numerical investigations, we herein first shed light on issues relating to the construction of canonical LRA with a particular greedy algorithm involving a sequential updating of the polynomial coefficients along separate dimensions. Specifically, we examine the selection of optimal rank, stopping criteria in the updating of the polynomial coefficients and error estimation. In the sequel, we confront canonical LRA to sparse PCE in structural-mechanics and heat-conduction applications based on finite-element solutions. Canonical LRA exhibit smaller errors than sparse PCE in cases when the number of available model evaluations is small with respect to the input dimension, a situation that is often encountered in real-life problems. By introducing the conditional generalization error, we further demonstrate that canonical LRA tend to outperform sparse PCE in the prediction of extreme model responses, which is critical in reliability analysis.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2018

Record-Low and Anisotropic Thermal Conductivity of a Quasi-One-Dimensional Bulk ZrTe 5 Single Crystal

Zirconium pentatelluride (ZrTe 5 ) has recently attracted renewed interest owing to many of its newly discovered extraordinary physical properties, such as 2D and 3D topological-insulator behavior, pressure-induced superconductivity, Weyl semimetal behavior, Zeeman splitting, and resistivity anomaly. The quasi-one-dimensional structure of single-crystal ZrTe 5 also promises large anisotropy in its thermal properties, which have not yet been studied. In this work, via time-domain thermoreflectance measurements, ZrTe 5 single crystals are discovered to possess a record-low thermal conductivity along the b-axis (through-plane), as small as 0.33 ± 0.03 W m –1 K –1 at room temperature. This ultralow b-axis thermal conductivity is 12 times smaller than its a-axis thermal conductivity (4 ± 1 W m –1 K –1 ) owing to the material’s asymmetrical crystalline structure. First-principles calculations are further conducted to reveal the physical origins of the ultralow b-axis thermal conductivity, which can be attributed to: (1) the resonant bonding and strong lattice anharmonicity induced by electron lone pairs, (2) the weak interlayer van der Waals interactions, and (3) the heavy mass of Te atoms, which results in low phonon group velocity. This work sheds light on the design and engineering of high-efficiency thermal insulators for applications such as thermal barrier coatings, thermoelectrics, thermal energy storage, and thermal management.

36 MATERIALS SCIENCE↗

DOE OSTI2017

CRISPR-Cpf1 mediates efficient homology-directed repair and temperature-controlled genome editing

Cpf1 is a novel class of CRISPR-Cas DNA endonucleases, with a wide range of activity across different eukaryotic systems. Yet, the underlying determinants of this variability are poorly understood. Here, we demonstrate that LbCpf1, but not AsCpf1, ribonucleoprotein complexes allow efficient mutagenesis in zebrafish and Xenopus. We show that temperature modulates Cpf1 activity by controlling its ability to access genomic DNA. This effect is stronger on AsCpf1, explaining its lower efficiency in ectothermic organisms. We capitalize on this property to show that temporal control of the temperature allows post-translational modulation of Cpf1-mediated genome editing. Finally, we determine that LbCpf1 significantly increases homology-directed repair in zebrafish, improving current approaches for targeted DNA integration in the genome. Together, we provide a molecular understanding of Cpf1 activity in vivo and establish Cpf1 as an efficient and inducible genome engineering tool across ectothermic species.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Reconfigurable training and reservoir computing in an artificial spin-vortex ice via spin-wave fingerprinting

Strongly interacting artificial spin systems are moving beyond mimicking naturally occurring materials to emerge as versatile functional platforms, from reconfigurable magnonics to neuromorphic computing. Typically, artificial spin systems comprise nanomagnets with a single magnetization texture: collinear macrospins or chiral vortices. Here, by tuning nanoarray dimensions we have achieved macrospin–vortex bistability and demonstrated a four-state metamaterial spin system, the ‘artificial spin-vortex ice’ (ASVI). ASVI can host Ising-like macrospins with strong ice-like vertex interactions and weakly coupled vortices with low stray dipolar field. Vortices and macrospins exhibit starkly differing spin-wave spectra with analogue mode amplitude control and mode frequency shifts of Δf = 3.8 GHz. The enhanced bitextural microstate space gives rise to emergent physical memory phenomena, with ratchet-like vortex injection and history-dependent non-linear fading memory when driven through global magnetic field cycles. We employed spin-wave microstate fingerprinting for rapid, scalable readout of vortex and macrospin populations, and leveraged this for spin-wave reservoir computation. ASVI performs non-linear mapping transformations of diverse input and target signals in addition to chaotic time-series forecasting.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Bioinspiration in light harvesting and catalysis

Capturing and converting solar energy into fuels and feedstocks is a global challenge that spans numerous disciplines and fields of research. Billions of years of evolution have allowed natural organisms to hone strategies for harvesting light from the sun and storing energy in the form of carbon–carbon and carbon–hydrogen bonds. Photosynthetic antenna proteins capture solar photons and funnel photoexcitations to reaction centres with high yields, and enzymes catalyze multi-electron reactions, facilitating chemical transformations not yet efficiently implemented using artificially engineered catalysts. Researchers in renewable energy often look to nature to understand the mechanisms at work and, if possible, to explore their translation into artificial systems. Here, we review advances in bioinspiration across the fields of biological light harvesting and chemical energy conversion. We examine how multi-photon and multi-electron reactions in biology can inspire new methods in photoredox chemistry to achieve novel, selective and complex organic transformations; how carbonic-dehydrogenase-inspired design principles enable catalytic reactions such as the conversion of CO 2 into useful products such as fuels; and how concepts from photosynthetic antenna complexes and reaction centres can benefit artificial light-harvesting materials. We then consider areas in which bioinspiration could enable advances in the rational design of molecules and materials, the expansion of the synthetic capabilities of catalysts and the valorization of molecular building blocks. Here, we highlight the challenges that must be overcome to realize these advances and propose new directions that may use bioinspiration to achieve them.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Methane utilization in Methylomicrobium alcaliphilum 20Z R : a systems approach

Biological methane utilization, one of the main sinks of the greenhouse gas in nature, represents an attractive platform for production of fuels and value-added chemicals. Despite the progress made in our understanding of the individual parts of methane utilization, our knowledge of how the whole-cell metabolic network is organized and coordinated is limited. Attractive growth and methane-conversion rates, a complete and expert-annotated genome sequence, as well as large enzymatic, 13 C-labeling, and transcriptomic datasets make Methylomicrobium alcaliphilum 20Z R an exceptional model system for investigating methane utilization networks. Here we present a comprehensive metabolic framework of methane and methanol utilization in M. alcaliphilum 20Z R . A set of novel metabolic reactions governing carbon distribution across central pathways in methanotrophic bacteria was predicted by in-silico simulations and confirmed by global non-targeted metabolomics and enzymatic evidences. Our data highlight the importance of substitution of ATP-linked steps with PPi-dependent reactions and support the presence of a carbon shunt from acetyl-CoA to the pentose-phosphate pathway and highly branched TCA cycle. The diverged TCA reactions promote balance between anabolic reactions and redox demands. As a result, the computational framework of C 1 -metabolism in methanotrophic bacteria can represent an efficient tool for metabolic engineering or ecosystem modeling.

09 BIOMASS FUELS↗