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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Simulation of the Multi-Wake Evolution of Two Sandia National Labs/National Rotor Testbed Turbines Operating in a Tandem Layout

The future of wind power systems deployment is in the form of wind farms comprised of scores of such large turbines, most likely at offshore locations. Individual turbines have grown in span from a few tens of meters to today’s large turbines with rotor diameters that dwarf even the largest commercial aircraft. These massive dynamical systems present unique challenges at scales unparalleled in prior applications of wind science research. Fundamental to this effort is the understanding of the wind turbine wake and its evolution. Furthermore, the optimization of the entire wind farm depends on the evolution of the wakes of different turbines and their interactions within the wind farm. In this article, we use the capabilities of the Common ODE Framework (CODEF) model for the analysis of the effects of wake–rotor and wake-to-wake interactions between two turbines situated in a tandem layout fully and partially aligned with the incoming wind. These experiments were conducted in the context of a research project supported by the National Rotor Testbed (NRT) program of Sandia National Labs (SNL). Results are presented for a layout which emulates the turbine interspace and relative turbine emplacement found at SNL’s Scaled Wind Technologies Facility (SWiFT), located in Lubbock, Texas. The evolution of the twin-wake interaction generates a very rich series of secondary transitions in the vortex structure of the combined wake. These ultimately affect the wake’s axial velocity patterns, altering the position, number, intensity, and shape of localized velocity-deficit zones in the wake’s cross-section. This complex distribution of axial velocity patterns has the capacity to substantially affect the power output, peak loads, fatigue damage, and aeroelastic stability of turbines located in subsequent rows downstream on the farm.

Baruah, Apurva (ORCID:0000000252354068)↗
DOE OSTI2020

From Atom to Engine: Understanding Fundamental Effects of Structure on Combustion Using Tandem Experiment and Computation

The ability to tie structural features to a fuel candidate’s ignition properties provides a path for rational design of advantaged fuels that facilitate higher-efficiency, lower-emitting combustion in engines. The time evolution of a fuel’s radical population directly correlates with global combustion parameters, and because the generated radicals depend on the initial structure and reaction pathways of the fuel molecule, it follows that the molecular structure of a fuel has a direct impact on this cascade, and therefore salient ignition-tied fuel properties. This work aims to understand the impact of structural features in the context of global combustion properties for direct application to emerging engine technologies. Specifically, we highlight the ability to identify potential fuel blendstocks for specific engine strategies by examining and elucidating the radical cascade tied to ignition. A representative subset of alcohols possessing a variety of structural features (e.g. branching, chain length) was selected for study using a robust combination of experimental and computational methods. The approach begins with identifying short-lived radicals and likely abstraction sites upon pyrolysis in a microreactor coupled with photoionization mass spectrometry for direct detection of product species. In tandem, electronic structure calculations were performed to calculate the relevant potential energy surfaces for fuel pyrolysis as well as the subsequent O2 addition-isomerization reactions, which govern ignition behavior. Furthermore, the theoretical energetic and ro-vibrational data are used to calculate rate constants for direct ignition modeling to explore how structural effects impact NTC behavior. The microreactor data combined with electronic structure theory calculations provide a well-informed picture of the reactions relevant to ignition for each fuel in this study, as well as the most likely radicals generated under engine conditions. This thorough fundamental picture of fuel decomposition and ignition chemistry is used to correlate the observed ignition behavior to molecular structural effects.

advanced biofuels↗
DOE OSTI2021

32.9% Efficient Tandem Solar Cell with Strain-Balanced GaInAs/GaAsP Quantum Wells: Preprint

We demonstrate single and dual junction solar cells with up to 80 strain-balanced GaInAs/GaAsP quantum wells (QWs), in order to extend the range of photon absorption. The net average stress in the quantum well layers is =12 MPa, despite coherent stresses in the individual layers that are 35-70 times greater. The GaAs-QW cell has a certified efficiency of (27.2 ± 0.2)% at one-sun; the GaInP/GaAs-QW tandem has a certified record one-sun efficiency of (32.9 ± 0.5)%. We will discuss the architecture of the devices, the physics behind the high performance, and pathways to further improvement.

GaAsP↗
DOE OSTI2025

Tandem Predictions for HPC Jobs: Preprint

At the core of the predictive analytics applied to High Performance Computing (HPC), the most prominent tasks are the prediction of job runtimes and the prediction of job queue times, both of which have the potential for informing HPC users during their every-day decision making. Accurate runtime predictions can help users better choose so-called wallclock times at job submission, decreasing the odds of their jobs waiting in queues longer than necessary. The accurate and timely queue time predictions offered for the available partitions can inform the favorable selection of partitions for running jobs. This potential is well understood as we see in the abundance of research studies that propose solutions for these tasks, including the work published in the last several years. These tasks are seemingly receptive to the Machine Learning (ML) solutions, considering that there is no shortage of training data where HPC centers over time run millions and millions of jobs. However, we study the existing research literature, as well as look for examples in the toolchains supported on the exemplar HPC facilities, and, surprisingly, do not find any practical solutions that are ready to be adopted. We interpret this as a manifestation of the shortage of UX/UI efforts that support HPC analytics and also as a sign that the research has not come to the consensus on solving these tasks. In this study, we aim to shed new light on the long-running task of job queue time prediction by exploring the utility of runtime predictions in improving prediction accuracy and, actually, predicting these two metrics together, in tandem. In other words, we show how runtime predictions become valuable input in the queue time modeling. We challenge the existing approaches to feature engineering for the queue time prediction and describe promising results we obtained for a large dataset of HPC jobs from a supercomputer at the National Renewable Energy Laboratory.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Advances and Challenges in Low‐Temperature Upcycling of Waste Polyolefins via Tandem Catalysis

Abstract Polyolefin waste is the largest polymer waste stream that could potentially serve as an advantageous hydrocarbon feedstock. Upcycling polyolefins poses significant challenges due to their inherent kinetic and thermodynamic stability. Traditional methods, such as thermal and catalytic cracking, are straightforward but require temperatures exceeding 400 °C for complete conversion because of thermodynamic constraints. We summarize and critically compare recent advances in upgrading spent polyolefins and model reactants via kinetic (and thermodynamic) coupling of the endothermic C─C bond cleavage of polyolefins with exothermic reactions including hydrogenation, hydrogenolysis, metathesis, cyclization, oxidation, and alkylation. These approaches enable complete conversion to desired products at low temperatures (<300 °C). The goal is to identify challenges and possible pathways for catalytic conversions that minimize energy and carbon footprints.

C-C cleavage↗
DOE OSTI2020

Facile Fabrication of Hierarchical MOF–Metal Nanoparticle Tandem Catalysts for the Synthesis of Bioactive Molecules

Multifunctional metal–organic frameworks (MOFs) that possess permanent porosity are promising catalysts in organic transformation. Herein, we report the construction of a hierarchical MOF functionalized with basic aliphatic amine groups and polyvinylpyrrolidone-capped platinum nanoparticles (Pt NPs). The postsynthetic covalent modification of organic ligands increases basic site density in the MOF and simultaneously introduces mesopores to create a hierarchically porous structure. The multifunctional MOF is capable of catalyzing a sequential Knoevenagel condensation–hydrogenation–intramolecular cyclization reaction. The unique selective reduction of the nitro group to intermediate hydroxylamine by Pt NPs supported on MOF followed by intramolecular cyclization with a cyano group affords an excellent yield (up to 92%) to the uncommon quinoline N-oxides over quinolines. The hierarchical MOF and polyvinylpyrrolidone capping agent on Pt NPs synergistically facilitate the enrichment of substrates and thus lead to high activity in the reduction–intramolecular cyclization reaction. The bioactivity assay indicates that the synthesized quinoline N-oxides evidently inhibit the proliferation of lung cancer cells. Finally, our findings demonstrate the feasibility of MOF-catalyzed direct synthesis of bioactive molecules from readily available compounds under mild conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Optically thick GaInAs/GaAsP strain-balanced quantum-well tandem solar cells with 29.2% efficiency under the AM0 space spectrum

GaAs is often used as a multijunction subcell due to its high material quality on GaAs substrates, despite having a non-optimal bandgap. The bandgap can be beneficially reduced using many layers of thin, strain-balanced GaInAs in a superlattice or quantum well device, but achieving excellent carrier collection without increased recombination has proven challenging. Here, we develop and demonstrate high performance, optically thick GaInAs/GaAsP strain-balanced solar cells. Excellent material quality is achieved in thick superlattices by using growth conditions that limit progressive thickness and composition fluctuations. Bandgap-voltage offsets as low as 0.31V are shown in superlattice cells using thin, highly strained GaP barriers. Optically thick superlattice cells with over 2500 nm of total GaInAs in the depletion region are developed, enabling 3.8 mA/cm 2 of extra photocurrent beyond the GaAs band edge under the AM0 space spectrum. Optimized superlattice solar cells are incorporated into two-junction devices that achieve 29.2% efficiency under the AM0 space spectrum due to their improved bandgap combination and high subcell voltages.

14 SOLAR ENERGY↗
DOE OSTI2021

Lamination of transparent conductive adhesives for tandem solar cell applications

A transparent conductive adhesive (TCA) interlayer for mechanically stacked multijunction solar cells provides adhesive strength and electrical connection between sub-cells when stacked. The fabrication of TCA sheets from an ethyl-vinyl acetate (EVA) matrix and silver coated compliant conductive microspheres, similar to industry-standard EVA encapsulant sheets, compatible with a standard lamination process was developed. Blade coating TCA sheets using 3D printed blades and testing of vertical conduction through the interlayer with a TCA conductivity jig allowed for reproducible measurements and low-cost fabrication. The supplemental information provides design files to enable other researchers to produce their own blades and testing jigs. We identified 0.5 mm as an optimal blade height for producing lab-scale TCA sheets and 120 °C at 3 psi for 10 min as the optimal vacuum lamination process to minimize resistance and possible damage to samples. For TCA sheets with coverages between 0.75% and 9%, the series resistance was approximately 0.2 O cm2 which should result in minimal losses for one-sun photovoltaic applications.

14 SOLAR ENERGY↗
DOE OSTI2021

Dopant Diffusion Control for Improved Tandem Cells Grown by D-HVPE

GaInP top cell current-density presently limits the performance of HVPE-grown two-junction devices, in large part due to unwanted dopant diffusion. Here, we institute mitigation strategies to lower the diffusion of dopants from both the front contact and back surface field. Successful application of these strategies resulted in a short-circuit current density of 12.1 mA/cm 2 in a GaInP/GaAs cell, an improvement of 0.9 mA/cm2 over our previous best cell. The reduced Se diffusion results in a thinner unpassivated emitter, which can lead to higher series resistance. Despite the increased resistance we obtained an efficiency increase from 23.7% to 24.8%.

42 ENGINEERING↗
DOE OSTI2022

Mixed Plastics Waste Valorization through Tandem Chemical Oxidation and Biological Funneling

Mixed plastics waste represents an abundant and largely untapped feedstock for the production of valuable products. The chemical diversity and complexity of these materials, however, present major barriers to realizing this opportunity. In this work, we show that metal-catalyzed autoxidation depolymerizes comingled polymers into a mixture of oxygenated small molecules that are advantaged substrates for biological conversion. We engineer a robust soil bacterium, Pseudomonas putida, to funnel these oxygenated compounds into a single exemplary chemical product, either ..beta..-ketoadipate or polyhydroxyalkanoates. This hybrid process establishes a strategy for the selective conversion of mixed plastics waste into useful chemical products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗