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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 361 records · Page 20

X-ray photoelectron spectroscopy and rotating disk electrode measurements of smooth sputtered Fe-N-C films

Electrocatalysts for the oxygen reduction reaction (ORR) based on complexes of iron and nitrogen in a carbon matrix (Fe-N-C) are a promising alternative to platinum group metal (PGM) based catalysts in polymer electrolyte membrane (PEM) fuel cells. Further improvements of Fe-N-C catalysts would benefit from model thin film studies of activity and stability of catalytic sites, but synthesis of Fe-N-C model thin films is challenging. Here we report on synthesis and characterization of Fe-N-C thin films produced by co-sputtering iron and carbon in a reactive nitrogen atmosphere onto removable glassy carbon rotating disk electrode (RDE) tips. Scanning electron microscopy (SEM) measurements indicate that the Fe-N-C films deposited at high temperature are smoother than the films annealed at high temperature. Electrocatalytic activity measured on the thin Fe-N-C films is greater for both high-temperature samples than for the room-temperature sample. From the analysis of X-ray photoelectron spectroscopy (XPS) data, exposure of the films to high temperatures results in increased graphitization of the carbon with the Fe-N-C films, and increased relative amount of graphitic and hydrogenated nitrogen species. Overall the results of this study demonstrate the feasibility of a thin film model system approach for studying active sites in PGM-free catalysts.

14 SOLAR ENERGY↗

Novel Strategy To Analyze Fourier Transform Ion Cyclotron Resonance Mass Spectrometry Data of Biomass Pyrolysis Oil for Oligomeric Structure Assignment

Among the most prominent challenges for the analysis of biomass pyrolysis products is the characterization of the abundant oligomer fraction of bio-oil. This fraction is principally made up of pyrolytic lignins and dehydrated, highly modified sugar oligomers, called humins, in liquid phase. An emerging technique for analysis of this oligomer fraction is high-resolution Fourier transform-ion cyclotron resonance mass spectrometry (FT-ICR MS), which allows for accurate determination of C x H y O z formulae for detected oligomers. Additionally, using simple dehydration and fragmentation reaction schemes, similar formulae can be developed from cellulose-, hemicellulose- and lignin-derived oligomers, which are primary depolymerization products. In this paper, FT-ICR MS analysis is coupled with combinatoric dehydration and fragmentation modeling in order to match experimentally detected bio-oil oligomers with hypothetical pathways for their formation during pyrolysis. In this way, we present a novel strategy by which oligomeric structures can be proposed for bio-oils. Using this approach, it becomes possible to advance the understanding of both the molecular structures comprising the bio-oil oligomer fraction and the pathways by which these structures form during biomass pyrolysis reactions.

09 BIOMASS FUELS↗

Directing Nanoparticle Organization in Response to Diverse Chemical Inputs

Signaling cascades are crucial for transducing stimuli in biological systems, enabling multiple stimuli to regulate a downstream target with precisely controlled timing and amplifying signals through a series of intermediary reactions. Developing a robust signaling system with such capabilities would be pivotal for programming complex behaviors in synthetic DNA-based molecular devices. However, although “software” such as nucleic acid circuits could potentially be harnessed to relay signals to DNA-based nanostructure hardware, such explorations have been limited. Here, in this study, we develop a platform for transducing a variety of stimuli via messenger-mediated reactions to regulate the release and reloading of gold nanoparticles (AuNPs) in a 3D DNA framework. In the first step, an in vitro transcription circuit is engineered to sense and amplify chemical stimuli, including arbitrary DNA sequences and proteins, producing RNA. In the second step, the RNA releases the DNA-coated AuNPs from the DNA framework via a strand displacement reaction. AuNP reloading is controlled by a separate step driven by degradation of the RNA. Our platform holds promise for applications requiring dynamic multiagent control over DNA-based devices, offering a versatile tool for advanced molecular device engineering.

36 MATERIALS SCIENCE↗

Degrees of Rate Control at Non(pseudo)steady-State Conditions

The degrees of rate control enable identification of rate-controlling transition states and species during (pseudo-)steady-state reaction. We demonstrate a method for identifying rate-controlling transition states and species at non-(pseudo-)steady-state conditions through modification of the definitions for degrees of rate control and sensitivities by superimposing the condition that time constants of the analytical rate function are kept constant when taking the partial derivatives of rate with respect to the rate constants/free energies. In conclusion, the utility of transient degrees of rate control is demonstrated for catalytic reaction networks to rationalize features of the transient rate including extrema and discontinuities.

42 ENGINEERING↗

Rapid activation of non-oriented mechanophores via shock loading and spallation

Mechanophores (MPs), stimuli-responsive molecules that respond chromatically to mechanochemical reactions, are important for understanding the coupling between mechanics and chemistry as well as in engineering applications. However, the atomic-level understanding of their activation originates from gas phase studies or under simple linear elongation forces directly on molecules or polymer chains containing MPs. The effect of many-body distortions, pervasive in condensed-phase applications, is not understood. Therefore, we performed large-scale molecular dynamics (MD) simulations of a poly(methyl methacrylate)-spiropyran copolymer under dynamic mechanical loading and studied the activation of the MP under various conditions from dynamical compression to tension during unloading. Detailed analysis of the all-atom MD trajectories shows that the MP blocks experience significant many-body intramolecular distortion that can significantly decrease the activation barrier as compared with when deformation rates are slow relative to molecular relaxation time scales. Here we find that the reactivity of MPs under material compression states is governed by many-body effects of intramolecular torsions, whereas under tension, the reactions are governed by tensile stresses.

36 MATERIALS SCIENCE↗

Measurement of the U 235 ( n , f ) prompt fission neutron spectrum from 10 keV to 10 MeV induced by neutrons of energy from 1 MeV to 20 MeV

The characterization of fission-driven nuclear systems primarily relies on calculations of neutron-induced chain reactions, and these calculations require evaluated nuclear data as input. Calculation accuracy heavily depends on input nuclear data evaluation accuracy, and thus high precision on the experimental input to the nuclear data evaluation is essential for fundamental quantities like the energy spectrum of neutrons emitted from neutron-induced fission (i.e., the prompt fission neutron spectrum, PFNS). Despite decades of measurement efforts, prior to the measurements described in this work there were only three literature data sets for the 235 U(n,f) PFNS at incident neutron energies above 1.0 MeV considered reliable for inclusion in nuclear data evaluations and no reliable data sets above 3.0 MeV incident neutron energy. In this work we report on new measurements of the 235 U(n,f) PFNS spanning a grid of 1.0–20.0 MeV in incident neutron energy and 0.01–10.0 MeV in outgoing (PFNS) neutron energy. These measurements were carried out at the Weapons Neutron Research facility at the Los Alamos Neutron Science Center and used a multifoil parallel-plate avalanche counter target with both a Li-glass and a liquid scintillator detector array in separate experiments to span the quoted outgoing neutron energy ranges. The PFNS results are shown in terms of the energy spectra themselves as well as the average PFNS energy $(\langle{E}\rangle)$ and ratios of $\langle{E}\rangle$ at forward and backward angles. Here, the results are compared with literature data and selected nuclear data evaluations. Generally, the data agree with the ENDF/B-VIII.0 evaluation below 5.0-MeV incident neutron energy and more closely with the JEFF-3.3 evaluation above 5.0 MeV, though no evaluations considered for comparison in this work agree with the data across all of the incident and outgoing neutron energies shown, especially in regions where the third-chance fission process becomes available. Additionally, we show a ratio of the present PFNS results for 235 U(n, f) with a recent and highly correlated experiment to measure the 239 Pu(n, f) PFNS at the same experimental facility and with nearly identical equipment and analysis procedures. Many observations reported in this work are the first of their kind and represent significant advancements for knowledge of the 235 U(n, f) PFNS.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

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↗

Review—Development of Highly Active and Stable Catalyst Supports and Platinum–Free Catalysts for PEM Fuel Cell

Metal-free, metal-containing, and template-assisted metal-containing nitrogen-modified carbon-based catalysts carbon composite supports, and highly active and electrochemically stable hybrid cathode catalysts for oxygen reduction reaction are reviewed in this manuscript. Here, novel procedures are developed for the synthesis of (i) highly catalytically active PGM-free catalyst and stable carbon composite catalyst supports. The carbon composite catalyst supports are engineered with optimized BET surface area and pore size distribution and with a well-defined kinetic and mass transfer region during the reaction and their performance is dicussed in detail in this review. The surface activation results in increasing carbon graphitization and inclusion of non-metallic active sites on the support surface. The USC catalysts exhibit the initial performance of 0.91 V and a maximum power density of 177 mW cm –2 , with well-defined kinetic and mass-transfer regions and ~2.5% H 2 O 2 production. Activated carbon composite support (ACCS) is modified to optimize its kinetic activity and its electrochemical stability shows excellent thermal stability and support stability under simulated start-up/shut-down operating conditions. The stabilities of various supports developed in this study are compared with those of a commercial Pt/C catalyst. The active sites for the ORR identified with electrochemical and physicochemical methods are pyridinic-N and quaternary-N.

25 ENERGY STORAGE↗

Identifying limitations in screening high-throughput photocatalytic bimetallic nanoparticles with machine-learned hydrogen adsorptions

The Sabatier principle is of fundamental importance to computational catalyst discovery, saving researchers time and expense by predicting catalytic activity in silico at scale. However, as polycrystalline and nanoscale catalysts increasingly dominate industry, computational screening tools must be adapted to these uses. In this work, we demonstrate the effectiveness of computational adsorption energy screening in nanocatalysis by comparing a multisite adsorption energy prediction workflow against a large experimental dataset of hydrogen evolution activities over bimetallic nanoparticles. Comparing 16 million hydrogen adsorption energy predictions with the hydrogen evolution activity of 5300 experiments across 84 monometallic and bimetallic systems, we discover that favorable adsorption energies are a necessary condition for experimental activity, but other factors often determine trends in practice. Finally, about half of the bimetallic search space can be excluded from experimental screens using hydrogen adsorption predictions, but this method may become significantly more powerful when combined with other screening tools.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Gas nitriding behavior of refractory metals and implications for multi-principal element alloy design

Multi-principal element alloys (MPEAs) comprise a large, flexible compositional space that enables tuning of their chemistry, structure, and properties. Here, to facilitate the development of nitriding-based surface-enhancement strategies that harness a broad compositional space, this study examined the gas nitriding behavior of Hf, Mo, Nb, Ta, Ti, and Zr as a function of time, temperature (750 and 1000 °C), and nitriding potential (i.e. ammonia-to-hydrogen ratio). These metals were selected because they have a strong driving force to form nitrides, and appear in many promising refractory MPEA compositions. The nitriding temperatures were selected based on the phase transformation temperature of Ti and Zr, and the nitriding potentials were chosen such that all elements are expected to form nitrides. Mass gain measurements indicate that all six elements follow parabolic kinetics. The microstructure observations and quantitative microchemical analysis show formation of dense and well-adhered compound layers for Mo, Nb, and Ta. Thick diffusion zones appear in Hf, Ta, Ti, and Zr, and diffusion coefficients were fit to the composition profiles. Partial delamination of the compound layer occurred for Ti and Zr. Peak hardness values above 30 GPa are obtained in the dense compound layers, and the solute hardening of the underlying alloy is correlated with the nitrogen content. The results provide insight into the dynamics of nitride compound formation relative to interstitial dissolution of nitrogen, and are discussed in the context of MPEA composition and processing design.

36 MATERIALS SCIENCE↗

Dynamic Bubbling Balanced Proactive CO 2 Capture and Reduction on a Triple-Phase Interface Nanoporous Electrocatalyst

The formation and preservation of the active phase of the catalysts at the triple-phase interface during CO 2 capture and reduction is essential for improving the conversion efficiency of CO 2 electroreduction toward value-added chemicals and fuels under operational conditions. Designing such ideal catalysts that can mitigate parasitic hydrogen generation and prevent active phase degradation during the CO 2 reduction reaction (CO 2 RR), however, remains a significant challenge. Herein, we developed an interfacial engineering strategy to build a new SnO x catalyst by invoking multiscale approaches. This catalyst features a hierarchically nanoporous structure coated with an organic F-monolayer that modifies the triple-phase interface in aqueous electrolytes, substantially reducing competing hydrogen generation (less than 5%) and enhancing CO 2 RR selectivity (~90%). This rationally designed triple-phase interface overcomes the issue of limited CO 2 solubility in aqueous electrolytes via proactive CO 2 capture and reduction. Concurrently, we utilized pulsed square-wave potentials to dynamically recover the active phase for the CO 2 RR to regulate the production of C1 products such as formate and carbon monoxide (CO). This protocol ensures profoundly enhanced CO 2 RR selectivity (~90%) compared with constant potential (~70%) applied at -0.8 V (V vs RHE). We further achieved a mechanistic understanding of the CO 2 capture and reduction processes under pulsed square-wave potentials via in situ Raman spectroscopy, thereby observing the potential-dependent intensity of Raman vibrational modes of the active phase and CO 2 RR intermediates. Finally, this work will inspire material design strategies by leveraging triple-phase interface engineering for emerging electrochemical processes, as technology moves toward electrification and decarbonization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Domain Wall Reactions in Multiple-Order Parameter Ferroelectrics

The motion of domain walls is crucial for ferroelectric switching. Conventionally, the switching dynamics is believed to be determined by the motion of one or a few low-energy domain wall types of dominant population. Here, we challenge this conventional idea in multiple-order-parameter ferroelectrics. Using hafnia as example, we show that the multiple-order-parameter nature not only provides various mobile domain walls and defectlike immobile domain walls, but also enables the domain wall reactions. In analogy with chemical reactions where substances react to form new substances, domain walls could also react to form other domain walls during switching. We identify several elementary domain wall reaction types including synthesis, decomposition, and exchange reactions. Domain walls are continually changed by these reactions during switching so that the switching behavior reflects the statistical average of many domain wall types with distinct mobility and stability. These reactions also lead to phenomenon like remanent nuclei and defect-site nucleation that facilitate switching and lower coercive field. Finally, the concept of domain wall reaction is not limited to hafnia but can be generalized to any multiple-order-parameter ferroelectric. As a result, this Letter conceptualizes domain wall reaction, expands the theory of ferroelectric switching, and suggests a practical way for defect engineering to control switching behavior.

36 MATERIALS SCIENCE↗

PlasMod0 v.1.0

SAND2022-12609 O PlasMod0 is a 0-dimensional plasma modeling which approximates a plasma as a well-stirred reactor. The model uses two temperatures, one for electrons and one for ions and neutrals. This model was originally developed for laser produced plasma in single-particle aerosol mass spectrometers. As a result, there are some specialized capabilities that include spherical expansion into vacuum at a user-specified rate and photon reactions. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Lietz, Amanda↗

Impact of Oxygen Storage Components in Prototype Pd-Based Three-Way Catalysts under Exhaust Conditions Relevant to Propane Engines

With increasing concerns about global warming, the push for sustainable and eco-friendly fuels is accelerating. Propane, recognized as liquefied petroleum gas or LPG, has garnered research interest as an alternative fuel due to its notable advantages, including a high-octane rating, reduced greenhouse gas emissions, and potential cost-effectiveness. However, to realize its full potential as an alternative fuel it is essential to develop catalysts that efficiently handle emissions at low temperatures. In our research, we investigated three distinct palladium (Pd)-based three-way catalyst (TWC) formulations (PdRh, Pd-only, and Pd-OSC) to investigate the influence of typical TWC components rhodium (Rh) and oxygen storage components (OSC) in exhaust scenarios relevant to propane-fueled engines. Among these, the formulation containing oxygen storage components (Pd-OSC) showed the highest reactivity for both NO and C 3 H 8 while minimizing performance degradation from hydrothermal aging (HTA). Notably, the temperature of 50% conversion (T50) for propane in the Pd-OSC fresh and HTA sample was lower by 30 °C and 13 °C, respectively, compared to the Pd-only sample, highlighting the role of oxygen storage materials in enhancing catalyst performance, even without dithering. Additionally, N 2 physisorption showed that the PdOSC sample has a higher surface area and increased pore volume. This underscores the idea that OSC materials not only augment the catalyst’s porosity but also optimize reactant accessibility to active sites, thus elevating catalytic efficiency. In addition to evaluating performance, we further explored the performance and characteristics of the catalysts using catalytic probe reactions, such as water–gas shift and steam reforming reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Prediction of local concentration fields in porous media with chemical reaction using a multi scale convolutional neural network

The study of solute transport in porous media is of interest in many chemical engineering systems. Some example applications include packed bed catalytic reactors, filtration devices, and batteries. The pore scale modeling of these systems is time consuming and may require large computing resources, for this reason computational fluid dynamics (CFD) simulations are not practical if a large number of simulations is required, like in multiscale modeling, where a model at a large scale calls for pore scale simulations. It has been shown that neural networks can be trained with a dataset of flow simulations and then predict fields orders of magnitude faster, and with less computational resources, in new domains. However, it is crucial to provide the neural network with an effective description of the domain and the undergoing operating conditions to be able to train models that generalize accurately in unseen samples. Therefore, research is needed to employ neural networks in new complex systems. The appropriate training of a network for predicting coupled flow and solute transport processes is an outstanding problem due to the complex interplay between geometry and operating conditions. In this work, we train a multi scale convolutional neural network (MSNet) with a diverse dataset of simulations of transport and chemical reaction in porous media to predict the local concentration fields in images of porous media. Our dataset contains a wide diversity of sphere pack arrangements under different operating conditions (Péclet and Reynolds numbers). Further, we train a robust model by employing different input descriptors that represent the medium and the different operating conditions of each system. Our trained model is able to provide nearly instantaneous predictions, compared to around twenty hours of the CFD workflow, with less than 3.5% error on new geometries and transport conditions. Thus the model could be easily integrated in a multiscale workflow where fast response is needed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Enhancement of effective thermal conductivity of rGO/Mg nanocomposite packed beds

Engineering thermophysical properties of metal hydrides nanocomposites is crucial for effective thermal management during hydrogen storage reactions; however, the effect of microstructure on thermal transport mechanisms is still unclear. Here, we employed an integrated experiment-modeling approach to investigate microstructural factors that determine the effective thermal conductivity of individual reduced graphene oxide-magnesium (rGO/Mg) nanocomposites and their packed bed. Here the effective thermal conductivity of the rGO/Mg nanocomposite packed bed was measured by using guarded hot-plate method under various atmospheric conditions (i.e., vacuum, Ar and He). A microstructure-aware mesoscopic modeling revealed that anisotropy of the effective thermal conductivity of individual rGO/Mg nanocomposites plays an important role in determining the effective thermal conductivity of their packed bed. The validated mesoscopic model also disclosed a nontrivial interplay between the intrinsic rGO properties and the extrinsic composite structural features. Finally, quantitative sensitivity analysis based on the modeling framework is used to provide practical engineering guidance for controlling the thermal transport within nanocomposite packed beds.

36 MATERIALS SCIENCE↗