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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Reactor scale simulations of ALD and ALE: Ideal and non-ideal self-limited processes in a cylindrical and a 300 mm wafer cross-flow reactor

Here, we have developed a simulation tool to model self-limited processes such as atomic layer deposition (ALD) and atomic layer etching inside reactors of arbitrary geometry as well the output of in situ quartz crystal microbalance and mass spectrometry. We have applied this model to two standard types of cross-flow reactors: a cylindrical tube reactor and a model 300 mm wafer reactor, and explored both ideal and nonideal self-limited kinetics. The model results are in agreement with experimental results and analytic expressions obtained using a simple plug-flow model for the cylindrical tube reactor. We also extended the simulations to consider two nonideal self-limited processes: soft-saturating processes characterized by a slow reaction pathway and processes where surface by-products can compete with the precursor for the same pool of adsorption sites. Our results show that it is possible to have a self-limited process with saturated yet inhomogeneous growth profiles due to the competition of reactor by-products. This is in agreement with experimental observations for titanium dioxide ALD from titanium tetraisopropoxide and titanium tetrachloride precursors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Wildfire-Power Grid Interactions: Feedback, Impacts, Monitoring, Modeling, and Mitigation Strategies

Wildfires are increasingly interacting with electric power systems through a two-way hazard chain: fires damage grid assets and trigger cascading outages, while grid faults can ignite new fires under hot, dry, and windy conditions. This review synthesizes the state of knowledge across five domains: (i) physical impacts of flames, heat, and smoke on lines, towers, insulators, and substations; (ii) power-infrastructure-initiated ignitions via conductor clash, high-impedance faults, and corona discharge; (iii) widespread blackouts and disproportionate societal impacts; (iv) multi-scale monitoring spanning laboratory tests, in-situ and grid-integrated sensors, and Earth observation; (v) coupled modeling that links fire behavior with grid operations; and (vi) technological and strategic mitigation pathways spanning prevention, response, and recovery. We integrate these domains into a novel 'feedback-aware' socio-technical framework. Through a longitudinal analysis (2005-2025) of global incidents, we identify that while vegetation contact remains the most frequent ignition source, aging infrastructure failure has emerged as a critical driver of catastrophic 'mega-fires'. We further identify persistent gaps, including limited interoperability of high-frequency grid and environmental data, scarce real-time data assimilation, and under-developed equity metrics for outage management. We conclude by outlining a research agenda to (1) deploy interoperable sensing architectures, (2) advance feedback-coupled fire-grid simulations, and (3) evaluate mitigation portfolios through techno-economic and fairness lenses. Recognizing wildfire-grid interactions as coupled socio-technical systems is essential for protecting infrastructure and communities and for ensuring reliable, sustainable electricity in a changing world.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Chlorophyll- a dynamics in the lower Amazon River: insights from in situ and hyperspectral remote sensing using OCI-PACE

Chlorophyll-a concentration (Chla) is a key indicator of phytoplankton biomass and aquatic trophic status. However, satellite-derived Chla in sediment-rich waters, such as those found in the Lower Amazon River, remains challenging. The present study characterizes in situ Chla levels and their relationships with geographic, physical, and biogeochemical parameters in the Lower Amazon. Data collected between 2014 and 2017 across four hydrological seasons included measurements of Chla, remote sensing reflectance, and water quality parameters such as total suspended sediment, conductivity, water surface temperature, dissolved oxygen, pH, dissolved organic carbon and coloured dissolved organic matter. An empirical model was developed to estimate Chla using simulated hyperspectral bands from NASA’s PACE mission, achieving high performance (R 2 = 0.76; RMSE = 0.11 μg·L −1 ). Red bands proved particularly effective for Chla retrieval, while the addition of ultraviolet bands further enhanced model accuracy. The application of the developed model to satellite imagery yielded results consistent with in situ observations for the same hydrologic season. Seasonal variation and geographic location were major factors influencing Chla dynamics. This study provides a novel contribution to Chla estimation in optically complex, highly turbid waters and highlights the potential of the PACE mission to enhance global aquatic ecosystem monitoring. In conclusion, by offering freely available hyperspectral data with high radiometric resolution, PACE represents a significant advancement in the realm of remote sensing of aquatic environments.

Amazon River↗
DOE OSTI2022

Pressure cells for in situ neutron total scattering: time and real-space resolution during deuterium absorption

In situ gas-loading sample holders for two-dimensionally arranged detectors in time-of-flight neutron total scattering experiments have been developed to investigate atomic arrangements during deuterium absorption using time and real-space resolution. A single-crystal sapphire container was developed that allows conditions of 473 K and 10 MPa hydrogen gas pressure. High-resolution transient measurements detected deuterium absorption by palladium that proceeded within a few seconds. A double-layered container with thick- and thin-walled vanadium allowed conditions of 423 K and 10 MPa hydrogen gas pressure. The deuterium occupation sites of a lanthanum–nickel–aluminium alloy are discussed in detail on the basis of real-space high-resolution data obtained from in situ neutron scattering measurements and reverse Monte Carlo structural modeling.

08 HYDROGEN↗
DOE OSTI2022

Passive Oxide Film Growth Observed On the Atomic Scale

Despite of the ubiquitous presence of passivation on most metal surfaces, the microscopic-level picture of how surface passivation occurs has been hitherto unclear. Using the canonical example of the surface passivation of aluminum, here we employ in situ atomistic transmission electron microscopy observations and computational modeling to disentangle entangled microscopic processes and identify the atomic processes leading to the surface passivation. Based on atomic-scale observations of the layer-by-layer expansion of the metal lattice and its subsequent transformation into the amorphous oxide, it is shown that the surface passivation occurs via a two-stage oxidation process, in which the first stage is dominated by intralayer atomic shuffling whereas the second stage is governed by interlayer atomic disordering upon the progressive oxygen uptake. The first stage can be bypassed by increasing surface defects to promote the interlayer atomic migration that results in direct amorphization of multiple atomic layers of the metal lattice. The identified two-stage reaction mechanism and the effect of surface defects in promoting interlayer atomic shuffling can find broader applicability in utilizing surface defects to tune the mass transport and passivation kinetics, as well as the composition, structure and transport properties of the passivation films.

25 ENERGY STORAGE↗
DOE OSTI2024

Snow Distribution Patterns Revisited: A Physics-Based and Machine Learning Hybrid Approach to Snow Distribution Mapping in the Sub-Arctic

Snowpack distribution in Arctic and alpine landscapes often occurs in repeating, year-to-year patterns due to local topographic, weather, and vegetation characteristics. Previous studies have suggested that with years of observational data, these snow distribution patterns can be statistically integrated into a snow process modeling workflow. Recent advances in snow hydrology and machine learning (ML) have increased our ability to predict snowpack distribution using in-situ observations, remote sensing data sets, and simple landscape characteristics that can be easily obtained for most environments. Here, we propose a hybrid approach to couple a ML snow distribution pattern (MLSDP) map with a physics-based, snow process model. We trained a random forest ML algorithm on tens of thousands of snow survey observations from a subarctic study area on the Seward Peninsula, Alaska, collected during peak snow water equivalent (SWE). We validated hybrid model outputs using in-situ snow depth and SWE observations, as well as a light detection and ranging data set and a distributed temperature profiling sensor data set. When the hybrid results were compared with the physics-based method, the hybrid method more accurately depicted the spatial patterns of the snowpack, areas of drifting snow, and years when no in-situ observations were used in the random forest ML training data set. The hybrid method also showed improvements in root mean squared error at 61% of locations where time-series estimations of snow depth were observed. These results can be applied to any physics-based model to improve the snow distribution patterning to reflect observed conditions in high latitude and high elevation cold region environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Deep learning closure models for large-eddy simulation of flows around bluff bodies

Near-wall flow simulation remains a central challenge in aerodynamics modelling: Reynolds-averaged Navier–Stokes predictions of separated flows are often inaccurate, and large-eddy simulation (LES) can require prohibitively small near-wall mesh sizes. A deep learning (DL) closure model for LES is developed by introducing untrained neural networks into the governing equations and training in situ for incompressible flows around rectangular prisms at moderate Reynolds numbers. The DL-LES models are trained using adjoint partial differential equation (PDE) optimization methods to match, as closely as possible, direct numerical simulation (DNS) data. They are then evaluated out-of-sample – for aspect ratios, Reynolds numbers and bluff-body geometries not included in the training data – and compared with standard LES models. The DL-LES models outperform these models and are able to achieve accurate LES predictions on a relatively coarse mesh (downsampled from the DNS mesh by factors of four or eight in each Cartesian direction). We study the accuracy of the DL-LES model for predicting the drag coefficient, near-wall and far-field mean flow, and resolved Reynolds stress. A crucial challenge is that the LES quantities of interest are the steady-state flow statistics; for example, a time-averaged velocity component $\langle {u}_i\rangle (x) = \lim _{t \rightarrow \infty } ({1}/{t}) \int _0^t u_i(s,x)\, {\rm d}s$ . Calculating the steady-state flow statistics therefore requires simulating the DL-LES equations over a large number of flow times through the domain. It is a non-trivial question whether an unsteady PDE model with a functional form defined by a deep neural network can remain stable and accurate on $t \in [0, \infty )$ , especially when trained over comparatively short time intervals. Our results demonstrate that the DL-LES models are accurate and stable over long time horizons, which enables the estimation of the steady-state mean velocity, fluctuations and drag coefficient of turbulent flows around bluff bodies relevant to aerodynamics applications.

Mechanics↗
DOE OSTI2021

Dynamically Unveiling Metal–Nitrogen Coordination during Thermal Activation to Design High‐Efficient Atomically Dispersed CoN 4 Active Sites

Abstract We elucidate the structural evolution of CoN 4 sites during thermal activation by developing a zeolitic imidazolate framework (ZIF)‐8‐derived carbon host as an ideal model for Co 2+ ion adsorption. Subsequent in situ X‐ray absorption spectroscopy analysis can dynamically track the conversion from inactive Co−OH and Co−O species into active CoN 4 sites. The critical transition occurs at 700 °C and becomes optimal at 900 °C, generating the highest intrinsic activity and four‐electron selectivity for the oxygen reduction reaction (ORR). DFT calculations elucidate that the ORR is kinetically favored by the thermal‐induced compressive strain of Co−N bonds in CoN 4 active sites formed at 900 °C. Further, we developed a two‐step (i.e., Co ion doping and adsorption) Co‐N‐C catalyst with increased CoN 4 site density and optimized porosity for mass transport, and demonstrated its outstanding fuel cell performance and durability.

He, Yanghua↗
DOE OSTI2021

Dynamically Unveiling Metal–Nitrogen Coordination during Thermal Activation to Design High-Efficient Atomically Dispersed CoN 4 Active Sites

We elucidate the structural evolution of CoN 4 sites during thermal activation by developing a zeolitic imidazolate framework (ZIF)-8-derived carbon host as an ideal model for Co 2+ ion adsorption. Subsequent in situ X-ray absorption spectroscopy analysis can dynamically track the conversion from inactive Co-OH and Co-O species into active CoN 4 sites. The critical transition occurs at 700 °C and becomes optimal at 900 °C, generating the highest intrinsic activity and four-electron selectivity for the oxygen reduction reaction (ORR). DFT calculations elucidate that the ORR is kinetically favored by the thermal-induced compressive strain of Co-N bonds in CoN 4 active sites formed at 900 °C. Further, we developed a two-step (i.e., Co ion doping and adsorption) Co-N-C catalyst with increased CoN 4 site density and optimized porosity for mass transport, and demonstrated its outstanding fuel cell performance and durability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

In Situ/Operando Probing of Dynamic Phase Structures of Alumina‐Supported Ultrasmall Copper‐Gold Alloy Nanoparticles Under Reaction Conditions

Abstract The ability to control phase structures and surface sites of ultrasmall alloy nanoparticles under reaction conditions is essential for preparing catalysts by design. This is, however, challenging due to limited understanding of the atomic‐scale phases and their correlation with the ensemble‐averaged structures and activities of catalysts during catalytic reactions. We reveal here a dynamic structural stability of alumina‐supported ultrasmall and equiatomic copper‐gold alloy nanoparticles under reaction conditions as a model system in the in situ/operando study. In situ atomic‐scale morphological tracking under oxygen reveals temperature‐dependent dynamic crystalline‐amorphous dual‐phase structures, showing dynamic stability over an elevated temperature range. This atomic‐scale dynamic phase stability coincides with a “conversion plateau” observed for carbon monoxide oxidation on the catalyst. It is substantiated by the stable lattice ordering/disordering structures and surface sites with oscillatory characteristics shown by operando ensemble‐average structural tracking of the catalyst during the oxidation reaction. The understanding of the atomic‐scale dynamic phase structures in correlation with the ensemble‐average dynamic ordering/disordering phase structures and surface sites provides fresh insights into the unique synergy of the supported alloy nanoparticles. This understanding has implications for the design and structural tuning of active and stable ultrasmall alloy catalysts under elevated temperatures.

Chemistry↗
DOE OSTI2022

A study of in situ reduction of MoO 3 to MoO 2 by X-ray Photoelectron Spectroscopy

Results from X-ray Photoelectron Spectroscopy (XPS) of molybdenum oxide samples are presented to elucidate how Mo (VI) oxide evolves to Mo (IV) oxide upon heating of a MoO 3 sample. XPS data analysis techniques based on manipulation of spectra treated as vectors are shown and allow insights into intermediate phases of Mo oxide which suggest how the original oxide changes under the influence of heat but also supports an interpretation of as-received tetravalent Mo powders as multivalent materials. In particular, several new spectral components were observed and assigned to the Magnéli phase as well as MoO 3 domains that have been modified by the presence of X-rays or temperature. Finally, these assignments comprise a new method of data processing where sample modification is used to inform XPS data interpretation and differ from previous work where the linear relationship of the binding energy of molybdenum oxides has been used.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Deformation and Fracture Behaviors of Cylindrical Battery Shell During Thermal Runaway

Thermal runaway is one of the catastrophic failure modes of lithium-ion cells. During thermal runaway in cylindrical cells, sidewall shell rupture has been identified as a contributing factor for thermal runaway propagation in battery packs. Herein, the deformation and fracture behaviors of the battery shell during thermal runaway are investigated based on in-situ and ex-situ characterization as well as physics-based modeling. The deformation and fracture modes of the battery shell with/without Carbon Fiber Reinforced Polymer (CFRP) sleeves are identified. In the simulation, the strain introduced by thermal expansion of the system is considered, as well as the thermal and strain rate effects on the plastic stage. The final cell shell modeling is validated by cell thermal runaway tests. Results reveal the quantitative relation between shell deformation behaviors and the pressure and temperature distribution. Both the experiment and model demonstrate the effectiveness of adding a tight-fitting CFRP sleeve around the cell in limiting the side-wall rupture of the shell. The use of CFRP tubes introduces a novel phenomenon in the context of uneven temperature distribution. Results shed light on the mechanistic analysis of a cell side-wall rupture during thermal runaway and provide essential guidance for the next-generation safe battery design.

battery casing↗
DOE OSTI2020

Controlling Metal–Organic Framework/ZnO Heterostructure Kinetics through Selective Ligand Binding to ZnO Surface Steps

Metal–organic framework (MOF) heterostructures exhibit unique properties beyond those of individual components, but their design requires an understanding of energetic and kinetic controls at MOF–substrate interfaces. Although the structural relationship has been widely used in heterostructure design, it overlooks the interplay between the organic ligand and the substrate which controls the kinetics and energetics of growth of the final structure. In this study, we used zeolitic imidazolate frameworks (ZIF-8) on ZnO as a model system to evaluate this interplay via in situ monitoring and simulations. Our results demonstrate multiple roles of the 2-methyl-imidazole (2-MIM) ligand as “dissolution-promoter”, “step-pinner”, and “terrace-binder” on the ZnO (001) face and “dissolution-promoter” and “terrace-binder” on the ZnO (100) face. Through these multiple face-specific roles, 2-MIM modulates ZnO dissolution kinetics and, hence, the Zn 2+ release rate, tuning local supersaturations that dictating the characteristic ZIF-8 crystallization kinetics on different substrate faces. The critical thickness for transition from 2D to 3D growth is dictated by competition between interfacial and strain energies. The atomic-scale mechanism of the coupled substrate dissolution and MOF growth, mediated by selective linker–substrate binding, furnishes a new synthesis pathway for other complex heterostructures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Real Time 3D Observations of Portland Cement Carbonation at CO2 Storage Conditions

Depleted oil reservoirs are considered a viable solution to the global challenge of CO 2 storage. A key concern is whether the wells can be suitably sealed with cement to hinder the escape of CO 2 . Under reservoir conditions, CO 2 is in its supercritical state, and the high pressures and temperatures involved make real-time microscopic observations of cement degradation experimentally challenging. Here, we present an in situ 3D dynamic X-ray micro computed tomography (μ-CT) study of well cement carbonation at realistic reservoir stress, pore-pressure, and temperature conditions. The high-resolution time-lapse 3D images allow monitoring the progress of reaction fronts in Portland cement, including density changes, sample deformation, and mineral precipitation and dissolution. By switching between flow and nonflow conditions of CO 2 -saturated water through cement, we were able to delineate regimes dominated by calcium carbonate precipitation and dissolution. For the first time, we demonstrate experimentally the impact of the flow history on CO 2 leakage risk for cement plugging. In-situ μ-CT experiments combined with geochemical modeling provide unique insight into the interactions between CO 2 and cement, potentially helping in assessing the risks of CO 2 storage in geological reservoirs.

58 GEOSCIENCES↗
DOE OSTI2021

Linking Perfluorosulfonic Acid Ionomer Chemistry and High-Current Density Performance in Fuel-Cell Electrodes

Transport phenomena are key in controlling the performance of electrochemical energy-conversion technologies and can be highly complex, involving multiple length scales and materials/phases. Material designs optimized for one reactant species transport however may inhibit other transport processes. We explore such trade-offs in the context of polymer-electrolyte fuel-cell electrodes, where ionomer thin films provide the necessary proton conductivity but retard oxygen transport to the Pt reaction site and cause interfacial resistance due to sulfonate/Pt interactions. We examine the electrode overall gas-transport resistance and its components as a function of ionomer content and chemistry. Low-equivalent-weight ionomers allow better dissolved-gas and proton transport due to greater water uptake and low crystallinity but also cause significant interfacial resistance due to the high density of sulfonic acid groups. These effects of equivalent weight are also observed via in situ ionic conductivity and CO displacement measurements. Of critical importance, the results are supported by ex situ ellipsometry and X-ray scattering of model thin-film systems, thereby providing direct linkages and applicability of model studies to probe complex heterogeneous structures. Structural and resultant performance changes in the electrode are shown to occur above a threshold sulfonic-group loading, highlighting the significance of ink-based interactions. Furthermore, our findings and methodologies are applicable to a variety of solid-state energy-conversion devices and material designs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Flexible Zn-MOF with Rare Underlying scu Topology for Effective Separation of C6 Alkane Isomers

Adsorptive separation by porous solids provides an energy-efficient alternative for the purification of important chemical species compared to energy-intensive distillations. Particularly, the separation of linear hexane isomers from its branched counterparts is crucial to produce premium grade gasoline with high research octane number (RON). Herein, we report the synthesis of a new, flexible zinc-based metal-organic framework, [Zn 5 (μ 3 -OH) 2 (adtb) 2 (H 2 O) 5 ·5 DMA] (Zn-adtb), constructed from a butterfly shaped carboxylate linker with underlying (4,8)-connected scu topology capable of separating the C6 isomers nHEX, 3MP, and 23DMB. The sorbate-sorbent interactions and separation mechanisms were investigated and analyzed through in situ FTIR, solid state NMR measurements and computational modeling. Here these studies reveal that Zn-adtb discriminates the nHEX/3MP isomer pair through a kinetic separation mechanism and the nHEX/23DMB isomer pair through a molecular sieving mechanism. Column breakthrough measurements further demonstrate the efficient separation of linear nHEX from the mono- and dibranched isomers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Metal–Organic Framework Based Hydrogen-Bonding Nanotrap for Efficient Acetylene Storage and Separation

The removal of carbon dioxide (CO 2 ) from acetylene (C 2 H 2 ) is a critical industrial process for manufacturing high purity C 2 H 2 . However, it remains challenging to address the trade-off between adsorption capacity and selectivity, on account of their similar physical properties and molecular sizes. To overcome this difficulty, here we report a novel strategy involving the regulation of hydrogen-bonding nanotrap on the pore surface to promote the separation of C 2 H 2 /CO 2 mixtures, in three isostructural metal-organic frameworks (MOFs, named as MIL-160, CAU-10H, and CAU-23, respectively). Among them, MIL-160, which has abundant hydrogen-bonding acceptors as nanotraps, can selectively capture acetylene molecules and demonstrates ultra-high C 2 H 2 storage capacity (191 cm 3 g –1 , or 213 cm 3 cm –3 ) but much less CO 2 uptake (90 cm 3 g –1 ) under ambient conditions. The C 2 H 2 adsorption amount of MIL-160 is remarkably higher than the other two isostructural MOFs (86 cm 3 g –1 and 119 cm 3 g –1 for CAU-10H and CAU-23 respectively) under the same conditions. More importantly, both simulation and experimental breakthrough results show that MIL-160 sets a new benchmark for equimolar C 2 H 2 /CO 2 separation in terms of the separation potential (Δq break = 5.02 mol/kg) and C 2 H 2 productivity (6.8 mol/kg). In addition, in-situ FT-IR experiments combined with computational modeling further reveal that the unique host-guest multiple hydrogen-bonding interactions between the nanotrap and C 2 H 2 is the key factor for achieving extraordinary acetylene storage capacity and superior C 2 H 2 /CO 2 selectivity. Furthermore, this work provides a novel and powerful approach to address the trade-off of this extremely challenging gas separation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗