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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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Investigation of Gallium–Boron Spin-On Codoping for poly-Si/SiO x Passivating Contacts
A doping technique for p-type poly-Si/SiOx passivating contacts using a spin-on method for different mixtures of Ga and B glass solutions is presented. Effects of solution mixing ratios on the contact performance (implied open circuit voltage iV oc , contact resistivity ..rho..c) are investigated. For all as-annealed samples at different drive-in temperatures, increasing the percentage of Ga in the solution shows a decrement in iV oc (from ~680 to ~610 mV) and increment in ..rho..c (from ~3 to ~800 mO cm 2 ). After a hydrogenation treatment by depositing a SiN x /AlO x stack followed by forming gas annealing, all samples show improved iVoc (~700 mV with Ga-B co-doped, and ~720 mV with all Ga). Interestingly, when co-doping Ga with B, even a small amount of B in the mixing solution shows negative effects on the surface passivation. Active and total dopant profiles obtained by electrical capacitance voltage and secondary-ion mass spectrometry measurements, respectively, reveal a relatively low percentage of electrically-active Ga and B in the poly-Si and Si layers. Overall, these results help understand the different features of the two dopants: a low ρ c with B, a good passivation with Ga, their degree of activation inside the poly-Si and Si layers, and the annealing effects.
Multi-task Parallelism for Robust Pre-training of Graph Foundation Models on Multi-source, Multi-fidelity Atomistic Modeling Data
Graph foundation models using graph neural networks promise sustainable, efficient atomistic modeling. To tackle challenges of processing multi-source, multi-fidelity data during pre-training, recent studies employ multi-task learning, in which shared message passing layers initially process input atomistic structures regardless of source, then route them to multiple decoding heads that predict data-specific outputs. This approach stabilizes pre-training and enhances a model’s transferability to unexplored chemical regions. Preliminary results on approximately four million structures are encouraging, yet questions remain about generalizability to larger, more diverse datasets and scalability on supercomputers. We propose a multi-task parallelism method that distributes each head across computing resources with GPU acceleration. Implemented in the open-source HydraGNN architecture, our method was trained on over 24 million structures from five datasets and tested on the Perlmutter, Aurora, and Frontier supercomputers, demonstrating efficient scaling on all three highly heterogeneous super-computing architectures.
Scalable training of trustworthy and energy-efficient predictive graph foundation models for atomistic materials modeling: a case study with HydraGNN
We present our work on developing and training scalable, trustworthy, and energy-efficient predictive graph foundation models (GFMs) using HydraGNN, a multi-headed graph convolutional neural network architecture. HydraGNN expands the boundaries of graph neural network (GNN) computations in both training scale and data diversity. It abstracts over message passing algorithms, allowing both reproduction of and comparison across algorithmic innovations that define nearest-neighbor convolution in GNNs. This work discusses a series of optimizations that have allowed scaling up the GFMs training to tens of thousands of GPUs on datasets consisting of hundreds of millions of graphs. Our GFMs use multitask learning (MTL) to simultaneously learn graph-level and node-level properties of atomistic structures, such as energy and atomic forces. Using over 154 million atomistic structures for training, we illustrate the performance of our approach along with the lessons learned on two state-of-the-art US Department of Energy (US-DOE) supercomputers, namely the Perlmutter petascale system at the National Energy Research Scientific Computing Center and the Frontier exascale system at Oak Ridge Leadership Computing Facility. The HydraGNN architecture enables the GFM to achieve near-linear strong scaling performance using more than 2000 GPUs on Perlmutter and 16,000 GPUs on Frontier.
Crystallographic dependence of CO 2 hydrogenation pathways over HCP-Co and FCC-Co catalysts
We report efficient conversion of CO 2 is of great significance for sustainable supply of chemicals and fuels. While Co-based catalysts are known to be effective for CO hydrogenation in Fischer-Tropsch synthesis, they work very differently in CO 2 hydrogenation. This study reveals a crystallographic dependence of reaction pathways for CO 2 hydrogenation on Co catalyst showing a new type of structure sensitivity and structure-activity-selectivity relationship for CO 2 conversion to chemicals and fuels. The experimental work on CO 2 conversion including steady-state isotopic transient kinetic analysis (SSITKA) using 13 C-labeled CO 2 shows a preferential CH 4 formation over HCP-Co but dominant CO formation over FCC-Co. The density functional theory calculations indicate that CO 2 does dissociate directly into chemisorbed CO * and O * on both HCP-Co and FCC-Co, but the CO * intermediates on HCP-Co prefer to be hydrogenated to form CH 4 whereas the CO* on FCC-Co preferentially desorb to form CO. The significantly altered adsorption strength of CO * due to the presence of chemisorbed O * and CO 2 * species on the catalyst surface is responsible for the mechanistic disconnection in product selectivity between the CO 2 and CO hydrogenation over Co catalysts. This study also shows that the addition of K to Co diminishes the direct impact of Co crystal structure, but improves the selectivity to C 2 + hydrocarbons along with higher CO 2 conversion. This seems to result from another pathway originating from HCOO* intermediate from bonding interaction of surface Co atoms with carbon in CO 2 , leading to the formation of CH x * whose coupling subsequently give rises to C 2 + products. The present study sheds new light into the crystallographic structural sensitivity of CO 2 hydrogenation towards the rational design of more selective catalysts for CO 2 conversion.
Revealing the interplay between “intelligent behavior” and surface reconstruction of non-precious metal doped SrTiO 3 catalysts during methane combustion
The impact of surface reconstruction of a model perovskite, SrTiO 3 (STO), on CH 4 activation for combustion and oxidative coupling was previously revealed that the reaction rate was proportional to the creation of Srterminated step sites. Doped perovskites (SrTi 1-x M x O 3 , M=metal dopant) present yet another form of reconstruction throughout the surface and the bulk, where the metal dopant can migrate in and out of the perovskite lattice, also known as "intelligent behavior". In this work, understanding the interplay between perovskite surface reconstruction (surface termination) and the "intelligent behavior" is tackled for the first time, and the catalytic consequences are probed with CH 4 combustion as a model reaction. A set of experimental techniques, including XRD, Raman spectroscopy, X-ray adsorption spectroscopy, kinetic measurements, as well as DFT calculations were used to understand the catalytic behavior of the reconstructed surfaces of Ni and Cu-doped STO for methane combustion. Here, we found that during methane oxidation, the diffusion of Ni and Cu into the lattice due to the "intelligent behavior" is accompanied by Sr enrichment on the surface of the perovskite. This Srenrichment process is reversible when Cu or Ni species exsolute as clusters/nanoparticles upon H 2 treatment. Such a surface reconstruction is found to greatly impact the catalytic activity of doped perovskites towards methane combustion.
In situ visualisation of zeolite anisotropic framework flexibility during catalysis
Zeolites exhibit framework flexibility driving their chemical and catalytic properties. Since the zeolitic pores are extremely small, a slight strain generated in the crystal induces compelling changes in shape, connectivity, accessibility, and the framework chemical properties. These modifications affected the adsorption and desorption of reactants/products and the diffusion within the channels during reaction. Using in situ 3D Bragg coherent X-ray diffraction imaging, we unveil the dynamics of the zeolite structure during catalysis, contraction and/or expansion of its framework also known as zeolite framework flexibility. Here, we imaged three-dimensionally a single faujasite zeolite crystal during the ethanol dehydration reaction revealing anisotropic lattice dynamics simultaneously to guest molecules formation. Understanding zeolite flexibility could permit to tune zeolites properties towards potentially higher adsorption and selectivity.
CH 4 combustion over a commercial Pd/CeO 2 -ZrO 2 three-way catalyst: Impact of thermal aging and sulfur exposure
Thermal aging and sulfur poisoning are major problems influencing the efficiency and lifetime of natural gas three-way catalysts (TWCs) during real-world operation. In the present study, thermal aging and sulfur-induced deactivations on CH 4 combustion were investigated over commercial monolithic honeycombs, i.e., Pd/CexZr 1-x O 2 (CZ)-based TWCs that are thermally aged in the bench (HTA), followed by being operated behind the stoichiometric natural gas engine in high sulfur fuel (HTA + S). In this work, both HTA and HTA + S samples show degraded performance in CH 4 combustion relative to the fresh one, which are caused by the reconstruction of Pd species induced by thermal aging and the decreased reducibility of the support. The 18 O 2 labelling experiments show that in all cases CH 4 combustion proceeds via a MvK mechanism in which lattice O (OL) plays a key role. The sulfation aging (HTA + S sample) promotes the activation of CH 4 and O 2 by forming Pd δ+ -(SO$_4^{2-}$) δ- and Ce 3+ -VO couples at the interface as compared to HTA sample. However, such a promotion effect could be compromised by the blocking effect of sulfate on the exchange of O L from the bulk to the surface and across the surface. The fundamental understanding of thermal and S deactivation mechanisms from this study could help to predict a real-world lifetime use curve of natural gas TWCs.
Mechanistic insights into the digestion of complex dietary fibre by the rumen microbiota using combinatorial high-resolution glycomics and transcriptomic analyses
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Development of copper thiolate organometallic compound as thermal sensitive coating for energy storage system safety
Safety and reliability are primary concerns for the deployment of lithium-ion batteries, especially in electric vehicles (EV) and larger-scale energy storage systems (ESS). Current technology in battery management systems (BMS) includes cell voltage monitoring and positioning temperature sensors in selected locations. For a system with hundreds to thousands of individual batteries, single-point temperature monitoring is inadequate to detect hot spots and cell overheating, which could lead to thermal runaway. Here, we have developed a temperature-sensitive copper-thiol compound that can be directly coated onto battery pouch foils to enable early detection of thermal runaway. Upon reaching specific temperatures, this compound releases a sulfur-containing detectable gas, which can be identified using chemically specific gas sensors to trigger an early warning signal. Such a signal propagate through air offers broad signal coverage and enables a more comprehensive approach to large-area temperature monitoring. The Cu-ethanethiol coating is designed to release volatile gases when the substrate surface temperature exceeds 70 °C, with continuous outgassing as the temperature increases. The compound is composed of Cu, S, Cl, hydrocarbons and trace amounts of oxygen. Upon heating, the oxidation state of Cu(I) transitions to Cu (II), accompanied by gas release. Thermogravimetric analysis coupled with mass spectrometry correlated well with the onset of gas release temperature and emission of sulfur-containing volatile gases. Additionally, an acrylic overcoat is applied to enhance the adhesion of the thermally sensitive compound film to the battery pouch foil. This coating is expected to offer an additional safety layer for ESS, alerting possible thermal runaway events before a failure occurs, thereby allowing sufficient time to implement a mitigation plan.
An experimental toolbox for the physical characterization of thermal insulating polymeric foams
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Ultrasound-mediated synthesis of nanoporous fluorite-structured high-entropy oxides toward noble metal stabilization
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Stabilization and manipulation of highly concentrated copper single atoms by high entropy oxides
Facile and controllable methodologies capable of providing single atom catalysts (SACs) with high-density active metal sites and sintering-resistance under harsh conditions are highly desired and grand challenges in heterogeneous catalysis. Herein, the entropy effect was leveraged to stabilize and manipulate the electronic properties of copper SACs. The as-developed ultrasonication-driven approach could integrate highly concentrated Cu SAs within the lattice of fluorite-structured high entropy oxide (HEFO) under ambient conditions (CuO-HEFO). The dual benefits from the high entropy effect of the support and the in-situ lattice engineering led to the generation of abundant Cu 1+ species and oxygen defects, together with ultra-high stability and sintering-resistance under extremely harsh conditions. This was confirmed by deploying non-high entropy support (CuO-CeO 2 ) or Cu sites located on the surface of HEFO (CuO@HEFO). In conclusion, the catalytic activity of CuO-HEFO surpassed that of CuO-CeO 2 and CuO@HEFO in CO oxidation together with well-maintained long-term stability and resistance to gas impurities.
Synthesis and application of thermally responsive nanofiber coatings for overtemperature monitoring
This study presents a one-pot synthesis route to organometallic nanofibers based on copper thiolate, exhibiting distinctive chemical and physical characteristics. Electron microscopy analysis of morphology and composition revealed 2-10 μm-long, 50-90 nm-diameter hollow and non-hollow fibers composed of copper, sulfur, oxygen, hydrocarbon, and chlorine. Thermogravimetric analysis showed a pronounced mass loss within 120°C-135°C. To elucidate the thermal responsive pathways, the nanofibers were characterized before and after heating. X-ray photoelectron spectroscopy indicates that an initially mixed Cu(I)/Cu(II) oxidation states transition to predominantly Cu(I) upon heating. A layer of nanofiber was coated on battery pouch foil and evaluated as a candidate thermally sensitive coating. At elevated temperature (100-130°C), nanofiber coating released volatile organic compounds, sulfide and sulfur dioxide as detected using multiple gas sensors. This thermally responsive gas release/sensing approach provides a potential large-area temperature monitoring strategy, which is particularly relevant where direct temperature measurements of individual batteries is impractical. The results established proof of concept for nanofiber-coated battery pouch foil as overtemperature warning platform that can provide alerts when surface temperatures exceed a critical threshold. More broadly, the ability to form interconnected fiber networks positions copper thiolate nanofiber coatings as promising materials for advanced applications.
Changes in Hydrogen Concentration and Defect State Density at the Poly-Si/SiOx/c-Si Interface Due to Firing
We determined the density of defect states of poly-Si/SiOx/c-Si junctions featuring a wet chemical interfacial oxide from lifetime measurements using the MarcoPOLO model to calculate recombination and contact resistance in poly-Si/SiOx/c-Si-junctions. In samples that did not receive any hydrogen treatment, the Dit,cSi is about 2 × 1012 cm-2 eV1 before firing and rises to 3–7 × 1012 cm2 eV1 during firing at measured peak temperatures between 620 °C and 863 °C. To address the question of why AlOx/SiNy stacks in contrast to pure SiNy layers for hydrogenation during firing provides better passivation quality, we have measured the hydrogen concentrations at the poly-Si/SiOx/c-Si interface as a function of AlOx layer thickness and compared these to J0 and calculated Dit,c-Si values. We observe an increase of the hydrogen concentration at the SiOx/c-Si interface upon firing as a function of the firing temperature that exceeds the defect concentrations at the interface several times. However, the AlOx layer thickness appears to cause an increase in hydrogen concentration at the SiOx/c-Si interface in these samples rather than exhibiting a hydrogen blocking property.
Encapsulation of plant extract compounds using cyclodextrin inclusion complexes, liposomes, electrospinning and their combinations for food purposes
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Neutron Scattering Studies of Heterogeneous Catalysis
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Adsorbate-Induced Strong Metal–Support Interactions: Implications for Catalyst Design
Since the discovery of strong metal–support interactions (SMSIs) over supported metal catalysts in the 1970s, researchers have studied ways to harness this type of catalyst reconstruction to achieve enhanced stability of metal particles against sintering and to create catalytic sites with novel electronic and bonding properties. The motivation to elucidate performance–structure relationships in catalytic transformations has led researchers to take a closer look into catalytic surfaces under reaction conditions rather than a postreaction analysis. These investigations of operating catalysts have made it clear that SMSIs are more common than initially thought. Recent reports show how various adsorbed species, rather than traditional H 2 /O 2 treatment, can promote SMSI in various catalytic systems, a phenomenon named adsorbate-induced SMSI (A-SMSI). Researching the occurrence of A-SMSI has allowed fundamental understanding of catalyst stability, catalytic rates, and product selectivity. The present Perspective discusses the state-of-the-art regarding A-SMSI, the current challenges, and the opportunities ahead in heterogeneous catalysis.