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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 469 records · Page 26

Electrocoagulation Combined with Ultrafiltration Membranes as Pretreatment for RO Desalination of Synthetic Cooling Tower Blowdown Water

Electrocoagulation (EC), an electrochemical water treatment process, is commonly used to remove particulate and colloidal matter from water. Here, in this study, we demonstrate that EC, when coupled with membrane filtration, is also capable of removing dissolved species, such as Ca + , Mg 2+ , and SiO x . The removal of such species is important for downstream membrane-based desalination treatment of the water that can suffer from reduced performance due to membrane scaling. Here, we describe how EC can be combined with a low-pressure membrane (LPM) system to offer efficient (and potentially universal) pretreatment for downstream membrane desalination. Synthetic water, simulating cooling tower blowdown (CTBD) with elevated concentrations of hardness and silicates (Ca: 418 ppm, Mg: 63 ppm, SiO 2 : 50 ppm) is treated using EC coupled to ultrafiltration (UF) to remove Mg up to 30 ± 1%, Ca up to 29 ± 1%, and silica up to 99 ± 1%. We evaluated the effectiveness of the EC-UF pretreatment system in reducing downstream RO scaling using thermodynamic modeling to predict the saturation index (SI) at the RO membrane/water interface. An SI value below zero (SI < 0) indicates under-saturated conditions (with respect to a particular mineral) where mineral scaling does not take place, which correlates with improved water recovery. Our findings suggest that the EC-UF pretreatment system was able to increase water recovery by up to 30%, compared to 0% recovery without pretreatment, under optimal conditions (feed solution pH of 7 and an EC charge loading of 1800 C/L). Finally, we conducted an economic analysis showing that implementing an EC-UF system for CTBD water could yield a cost benefit of up to $\$$14.13 per m 3 compared to direct brine disposal.

cooling tower blowdown↗

Hierarchical Epoxy Structures via Tunable Polymerization-Induced Phase Separation Combined with Additive Manufacturing

Polymerization-induced phase separation (PIPS) allows for the control of thermoset morphologies and properties, enabling the tuning of domain sizes and thermomechanical response. However, its use in generating substructural features in additively manufactured materials has been limited. In this work, we combine epoxy PIPS with UV curable acrylate and rheological modifiers to print nano- to macro-phase separating materials via a two-step, dual-cure approach. This method enables direct ink write printing of hierarchical structures with both controlled morphologies through phase separation and macroscale architecture through print design. We find that formulations for phase-separating materials require judicious incorporation of additives to enable printability and to provide sufficient green strength. Atomic force microscopy-nano infrared mapping reveals tunable, reticulated nano- to micron-scale domains of the resultant multiphase materials and their morphology changes due to additives, resulting in alterations to thermomechanical and tensile properties. Shape memory behavior is also demonstrated through multimaterial additive manufacturing of epoxies with functionally graded internal morphology using active mixing techniques, highlighting this method’s ability to fabricate complex architectures with controlled morphologies and thermomechanical response.

Van Meter, Kylie E [Organic Materials Science, San↗

Near-Real-Time Material Tracking: Combining Vis–NIR Spectroscopy with Flow Sensing for Accurate Nd(III) Quantification

A fiber-optic visible–near-infrared (vis–NIR) absorption spectroscopy and flow sensor system has been developed for near-real-time tracking of Nd mass in the effluent stream from a column in a fume hood. The approach leverages two unique data streams and a partial least-squares regression (PLSR) model trained on vis–NIR absorption spectra of Nd(III) (0–1.5 M) in 1 M HNO 3 . In-line volumetric flow rate and vis–NIR spectra are measured in sequence after a chromatography column. The time stamps from each data stream are then synchronized, which allows integrated volumes to be combined with Nd(III) molarities predicted by a PLSR model to accurately calculate the Nd mass flowing through the column. This integrated measurement provides instantaneous mass flow and accumulates these data over time to obtain the total mass processed. The methodology developed in this study contributes critical technical infrastructure to improve monitoring capabilities to support chemical separations and the production of strategic materials and isotopes.

Irvine, Sawyer B. [Oak Ridge National Laboratory (↗

Exploring Microphase Separation in Semi-Fluorinated Diblock Copolymers: A Combined Experimental and Modeling Investigation

We report the combined experimental and theoretical study of the bulk self-assembly behavior of polystyrene-blockpoly( 2,3,4,5,6-pentafluorostyrene) diblock copolymers. These block copolymers were designed to create highly antagonistic blocks (with a high Flory−Huggins interaction parameter, χ) with minimum disruption to the molecular construct (i.e., only replacing five hydrogen atoms with five fluorine atoms). A large library of diblock copolymers (41 samples) was synthesized by reversible addition− fragmentation chain transfer (RAFT) polymerization to map out a major portion of the phase space. All block copolymers exhibited narrow molecular weight distributions with dispersity (D) values between 1.07 and 1.32, and subsequent thermal annealing revealed phase separation into well-defined nanoscale morphologies depending on their molecular composition, as determined from small-angle X-ray scattering and transmission electron microscopy analyses, with an experimental phase diagram being constructed. The χ value at 25 °C for this block copolymer was estimated to be 0.2 using strong segregation theory, based on trends in phase-separated domain spacing and interfacial width. When applying theoretical approaches, the majority of the domain spacing data trends were captured by a coil−coil diblock copolymer model; however, a better fit to the data for samples with shorter fluorinated blocks was obtained with a rod−coil model, indicating that the chains in these fluorinated blocks likely have a higher inherent stiffness and were thus rod-like. This observation demonstrates that, due to the very high value of χ, a transition from coil−coil to rod−coil behavior can be obtained purely by reducing the length of the stiffer of the two blocks and without varying temperature or the chemical composition of the polymers. Here, this work showcases the presence of strong microphase separation within AB diblock copolymers despite the relatively similar chemical composition of the constituent “A” and “B” units, with a clear transition from rod−coil to coil−coil segregation behavior.

RAFT polymerization↗

Mechanistic Study of 1,2-Dichloroethane Hydrodechlorination on Cu-Rich Pt–Cu Alloys: Combining Reaction Kinetics Experiments with DFT Calculations and Microkinetic Modeling

Cu-rich Pt–Cu bimetallic catalysts are among the most promising candidates for actively catalyzing the hydrodechlorination of 1,2-dichloroethane (1,2-DCA) toward ethylene production. Combining reaction kinetics experiments with density functional theory (DFT) calculations and mean-field microkinetic modeling, we present a systematic mechanistic study for 1,2-DCA hydrodechlorination on Cu-rich Pt–Cu alloy catalysts. Our DFT (PBE+(TS+SCS)) results suggest that increasing Cu content in the Pt–Cu alloy destabilizes C 2 -species adsorption while stabilizing the binding of atomic chlorine. The reaction energetics of all the elementary steps in the 1,2-DCA reaction network were calculated on a Pt 1 Cu 3 (111) model surface. The DFT results were then used to construct a microkinetic model, and the model-predicted reaction rates were compared with our reaction kinetics experimental results on a Cu-rich SiO 2 -supported Pt–Cu alloy catalyst through a parameter estimation procedure. Both the reaction kinetics experiments and the microkinetic model after parameter adjustments yielded 100% selectivity to ethylene. The microkinetic model pointed to a reaction pathway involving two sequential chlorine-removal steps on the Pt–Cu alloy catalyst, a mechanism distinct from the one previously identified on pure Pt/SiO 2 catalysts, which involved an initial hydrogen-removal step. Adjustments to the DFT-derived parameters indicate the possible formation of chlorine-induced Cu-enriched surface sites during 1,2-DCA hydrodechlorination conditions, sites that are more active than those encountered in the bulk Pt 1 Cu 3 (111) alloy surface. Furthermore, our study offers valuable initial insights on the 1,2-DCA hydrodechlorination reaction mechanism and the nature of the active sites on PtCu bimetallic catalysts.

1,2-Dichloroethane↗

Investigating Lignin Aggregation and Interactions with Solvents during γ-Valerolactone (GVL) Pretreatment: A Combined Small Angle Neutron Scattering and Molecular Simulations Study

The strong tendency of lignin to aggregate in solution, coupled with limited understanding of how its molecular structure governs this behavior, hinders its effective utilization in biorefineries. Here, in this study, we investigated the solution behavior of lignin extracted from poplar using γ-valerolactone/water (GVL/H2O, 9:1 wt/wt) through combined small-angle neutron scattering (SANS) and molecular dynamics (MD) simulations. Lignin samples obtained at 100 °C (L100) and 120 °C (L120) differed in β–O–4 content, hydroxyl distribution, and S/G ratio, enabling direct assessment of how molecular composition governs solvation and aggregation. SANS showed that L120 formed rigid and elongated cylindrical aggregates at 25 °C that transitioned to more flexible spheroidal structures by 50 °C and remained stable up to 80 °C, whereas L100 adopted globular aggregates that progressively collapsed with increasing temperature. MD simulations reinforced these observations by showing that S-rich (L120-like) oligomers had larger radii of gyration, stronger solvent coordination driven by methoxy groups, and fewer lignin–lignin contacts. In contrast, G-rich (L100-like) oligomers displayed persistent aggregation and lower solubility. Collectively, these results reveal that increased aromatic methoxylation enhances lignin–solvent interactions and suppresses self-association, whereas reduced methoxylation and higher β–O–4 content promote persistent aggregation into colloid-like structures with restricted solvent penetration into the aggregate interior.

biorefinery pretreatment↗

In Situ Identification of Reaction Intermediates and Mechanistic Understandings of Methane Oxidation over Hematite: A Combined Experimental and Theoretical Study

Effective methane utilization for either clean power generation or value-added chemical production has been a subject of growing attention worldwide for decades, yet challenges persist mostly in relation to methane activation under mild conditions. Here, we report hematite, an earth-abundant material, to be highly effective and thermally stable to catalyze methane combustion at low temperatures (<500 °C) with a low light-off temperature of 230 °C and 100% selectivity to CO 2 . The reported performance is impressive and comparable to those of precious-metal-based catalysts, with a low apparent activation energy of 17.60 kcal·mol –1 . Our theoretical analysis shows that the excellent performance stems from a tetra-iron center with an antiferromagnetically coupled iron dimer on the hematite (110) surface, analogous to that of the methanotroph enzyme methane monooxygenase that activates methane at ambient conditions in nature. Isotopic oxygen tracer experiments support a Mars van Krevelen redox mechanism where CH 4 is activated by reaction with a hematite surface oxygen first, followed by a catalytic cycle through a molecular-dioxygen-assisted pathway. Surface studies with in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and density functional theory (DFT) calculations reveal the evolution of reaction intermediates from a methoxy CH 3 –O–Fe, to a bridging bidentate formate b-HCOO–Fe, to a monodentate formate m-HCOO–Fe, before CO 2 is eventually formed via a combination of thermal hydrogen-atom transfer (HAT) and proton-coupled electron transfer (PCET) processes. Finally, the elucidation of the reaction mechanism and the intermediate evolutionary profile may allow future development of catalytic syntheses of oxygenated products from CH 4 in gas-phase heterogeneous catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Combining Force Fields and Neural Networks for an Accurate Representation of Chemically Diverse Molecular Interactions

A key goal of molecular modeling is the accurate reproduction of the true quantum mechanical potential energy of arbitrary molecular ensembles with a tractable classical approximation. The challenges are that analytical expressions found in general purpose force fields struggle to faithfully represent the intermolecular quantum potential energy surface at close distances and in strong interaction regimes; that the more accurate neural network approximations do not capture crucial physics concepts, e.g., nonadditive inductive contributions and application of electric fields; and that the ultra-accurate narrowly targeted models have difficulty generalizing to the entire chemical space. We therefore designed a hybrid wide-coverage intermolecular interaction model consisting of an analytically polarizable force field combined with a short-range neural network correction for the total intermolecular interaction energy. Here, we describe the methodology and apply the model to accurately determine the properties of water, the free energy of solvation of neutral and charged molecules, and the binding free energy of ligands to proteins. The correction is subtyped for distinct chemical species to match the underlying force field, to segment and reduce the amount of quantum training data, and to increase accuracy and computational speed. For the systems considered, the hybrid ab initio parametrized Hamiltonian reproduces the two-body dimer quantum mechanics (QM) energies to within 0.03 kcal/mol and the nonadditive many-molecule contributions to within 2%. Simulations of molecular systems using this interaction model run at speeds of several nanoseconds per day.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Combined Optical and Radio-Frequency Measurements of a Lightning Megaflash by the FORTE Satellite

The optical and VHF instrumentation on the Fast On-Orbit Recording of Transient Events (FORTE) satellite is used to document the combined phenomenology evolution of a lightning “megaflash” – mesoscale lightning that propagates laterally over exceptional distances. We identify a FORTE flash whose maximum extent was 82 km and inferred length over multiple distinct branches exceeded 100 km. This flash lasted 1.2 s and produced 250 optical and 591 RF events. We find that the channel development mapped by FORTE’s pixelated lightning imager (LLS) occurred at a typical speed of 2.6x10 5 m s -1 and was accompanied by sustained periods of VHF emission that could individually exceed 100 ms in duration. The impulsive IC events generated by the flash indicate that this development occurred at altitudes between 3 and 8 km. Four +CG strokes were identified in the VHF waveform data that are responsible for two of the three highly-radiant LLS groups (two of the +CGs were not as optically bright as the others). These strokes occurred at different locations throughout the flash footprint with the most distant strokes separated by approximately 50 km. These space-based observations match previous observations of megaflashes as well as ground-based measurements of negative leader development during “spider” lightning, suggesting that FORTE is sensing the same phenomena.

Peterson, Michael Jay↗

Combined Optical and Radio–Frequency Perspectives on the Time Evolution of Lightning Measured by the FORTE Satellite

We use a cluster feature data set for the Fast On-orbit Recording of Transient Events (FORTE) satellite that combines detections from its pixelated Lightning Locating System (LLS), photodiode detector (PDD) and Radio-Frequency (RF) instrumentation to generate statistics describing the frequency and timing of lightning events detected by each instrument during lightning flashes. Coincident observations from the same vantage point allow us to directly compare flash details that can be resolved by the wide Field of View (FOV) instruments relative to the pixelated LLS—whose design is based on NASA's Lightning Imaging Sensor. We find that both the PDD and RF system typically generate more detections than the lightning imager (mean: 1.5 PDD events per LLS group, 2 RF events per LLS group) from pulses that are either not sufficiently bright in the optical band (in the case of RF) or that lack the optical energy density (in the case of the PDD) required to trigger one of the pixels on the LLS imaging array. This includes additional activity before the first LLS group or after the final LLS group. These FORTE results demonstrate that certain lightning processes would be better resolved by wide-FOV optical and RF instruments than lightning imagers. Current/future space-based missions that use/plan to use similar instruments will improve our understanding of flash evolution by resolving details missed by lightning imagers.

47 OTHER INSTRUMENTATION↗

Investigating the Diurnal Radiative, Turbulent, and Biophysical Processes in the Amazonian Canopy‐Atmosphere Interface by Combining LES Simulations and Observations

Abstract We investigate the atmospheric diurnal variability inside and above the Amazonian rainforest for a representative day during the dry season. To this end, we combine high‐resolution large‐eddy simulations that are constrained and evaluated against a comprehensive observation set, including CO 2 concentrations, gathered during GoAmazon2014/15. We design systematic numerical experiments to quantify whether a multilayer approach in solving the explicit canopy improves our canopy‐atmosphere representation. We particularly focus on the relationship between photosynthesis and plant transpiration, and their distribution at leaf and canopy scales. We found the variability of photosynthesis drivers like vapor pressure deficit and leaf temperature to be about 3 times larger for sunlit leaves compared to shaded leaves. This leads to a large spread on leaf stomatal conductance values with minimum and maximum values varying more than 100%. Regarding the turbulent structure, we find wind‐driven stripe‐like shapes at the canopy top and structures resembling convective cells at the canopy. Wind‐related variables provide the best spatiotemporal agreement between model and observations. The potential temperature and heat flux profiles agree with an observed decoupling near the canopy top interface, although with less variability and cold biases of up to 3 K. The increasing complexity on the biophysical processes leads to the largest disagreements for evaporation, CO 2 plant assimilation and soil efflux. The model is able to capture the correct dependences and trends with the magnitudes still differing. We finally discuss the need to revise leaf and soil models and to complete the observations at leaf and canopy levels.

54 ENVIRONMENTAL SCIENCES↗

Combined Meteorological and Hydrologic Uncertainties Shape Projections of Future Soil Moisture in the Eastern United States

Physical hazards pose risks to many critical systems. Designing adaptive measures to mitigate these risks is challenging due to large uncertainties in modeling future hazards and the associated sectoral responses. Here, we help address this challenge in a hydrologic context by examining the combined role of meteorological forcing and hydrologic parameter uncertainties in shaping projections of future soil moisture. By encoding a simple conceptual water balance model in a differentiable programming framework, we facilitate fast runtimes and an efficient calibration, enabling an improved uncertainty analysis. We characterize uncertainty in model parameters by calibrating against different target data sets and by using several loss functions. We then convolve the resulting parameter ensemble with a set of Earth system model projections to produce a large ensemble (2,340 members) of daily soil moisture simulations. Focusing on the eastern United States, we find that most ensemble members project a drying of soils across the region, although some simulate wetter conditions throughout this century. Our ensemble shows an increase in the frequency and intensity of dry extremes while there is less agreement for wet extremes. We conduct sensitivity analyses on several soil moisture signatures to measure the relative influence of meteorological and hydrologic uncertainties across space and time. Both meteorological and hydrologic factors contribute consistently to uncertainty surrounding long-term trends, while changes to both wet and dry soil extremes are typically more sensitive to hydrologic parameter uncertainty. Our results underscore the need to account for varied sources of uncertainty when developing long-term hydrometeorological projections.

Lafferty, David C. [University of Illinois Urbana‐↗

Tailoring poplar lignin without yield penalty by combining a null and haploinsufficient CINNAMOYL-CoA REDUCTASE2 allele

Lignin causes lignocellulosic biomass recalcitrance to enzymatic hydrolysis. Engineered low-lignin plants have reduced recalcitrance but often exhibit yield penalties, offsetting their gains in fermentable sugar yield. Here, CRISPR/Cas9-generated CCR2(–/*) line 12 poplars have one knockout CCR2 allele while the other contains a 3-bp deletion, resulting in a 114I115A-to-114T conversion in the corresponding protein. Despite having 10% less lignin, CCR2(–/*) line 12 grows normally. On a plant basis, the saccharification efficiency of CCR2(–/*) line 12 is increased by 25–41%, depending on the pretreatment. Analysis of monoallelic CCR2 knockout lines shows that the reduced lignin amount in CCR2(–/*) line 12 is due to the combination of a null and the specific haploinsufficient CCR2 allele. Analysis of another CCR2(–/*) line shows that depending on the specific CCR2 amino-acid change, lignin amount and growth can be affected to different extents. Furthermore, our findings open up new possibilities for stably fine-tuning residual gene function in planta.

59 BASIC BIOLOGICAL SCIENCES↗

Combining data and theory for derivable scientific discovery with AI-Descartes

Abstract Scientists aim to discover meaningful formulae that accurately describe experimental data. Mathematical models of natural phenomena can be manually created from domain knowledge and fitted to data, or, in contrast, created automatically from large datasets with machine-learning algorithms. The problem of incorporating prior knowledge expressed as constraints on the functional form of a learned model has been studied before, while finding models that are consistent with prior knowledge expressed via general logical axioms is an open problem. We develop a method to enable principled derivations of models of natural phenomena from axiomatic knowledge and experimental data by combining logical reasoning with symbolic regression. We demonstrate these concepts for Kepler’s third law of planetary motion, Einstein’s relativistic time-dilation law, and Langmuir’s theory of adsorption. We show we can discover governing laws from few data points when logical reasoning is used to distinguish between candidate formulae having similar error on the data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ferricyanide photo-aquation pathway revealed by combined femtosecond Kβ main line and valence-to-core x-ray emission spectroscopy

Reliably identifying short-lived chemical reaction intermediates is crucial to elucidate reaction mechanisms but becomes particularly challenging when multiple transient species occur simultaneously. Here, we report a femtosecond x-ray emission spectroscopy and scattering study of the aqueous ferricyanide photochemistry, utilizing the combined Fe Kβ main and valence-to-core emission lines. Following UV-excitation, we observe a ligand-to-metal charge transfer excited state that decays within 0.5 ps. On this timescale, we also detect a hitherto unobserved short-lived species that we assign to a ferric penta-coordinate intermediate of the photo-aquation reaction. We provide evidence that bond photolysis occurs from reactive metal-centered excited states that are populated through relaxation of the charge transfer excited state. Beyond illuminating the elusive ferricyanide photochemistry, these results show how current limitations of Kβ main line analysis in assigning ultrafast reaction intermediates can be circumvented by simultaneously using the valence-to-core spectral range.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding capacity fade in organic redox-flow batteries by combining spectroscopy with statistical inference techniques

Organic redox-active molecules are attractive as redox-flow battery (RFB) reactants because of their low anticipated costs and widely tunable properties. Unfortunately, many lab-scale flow cells experience rapid material degradation (from chemical and electrochemical decay mechanisms) and capacity fade during cycling (>0.1%/day) hindering their commercial deployment. In this work, we combine ultraviolet-visible spectrophotometry and statistical inference techniques to elucidate the Michael attack decay mechanism for 4,5-dihydroxy-1,3-benzenedisulfonic acid (BQDS), a once-promising positive electrolyte reactant for aqueous organic redox-flow batteries. We use Bayesian inference and multivariate curve resolution on the spectroscopic data to derive uncertainty-quantified reaction orders and rates for Michael attack, estimate the spectra of intermediate species and establish a quantitative connection between molecular decay and capacity fade. Our work illustrates the promise of using statistical inference to elucidate chemical and electrochemical mechanisms of capacity fade in organic redox-flow battery together with uncertainty quantification, in flow cell-based electrochemical systems.

25 ENERGY STORAGE↗

Challenging thermodynamics: combining immiscible elements in a single-phase nano-ceramic

Abstract The Hume-Rothery rules governing solid-state miscibility limit the compositional space for new inorganic material discovery. Here, we report a non-equilibrium, one-step, and scalable flame synthesis method to overcome thermodynamic limits and incorporate immiscible elements into single phase ceramic nanoshells. Starting from prototype examples including (NiMg)O, (NiAl)O x , and (NiZr)O x , we then extend this method to a broad range of Ni-containing ceramic solid solutions, and finally to general binary combinations of elements. Furthermore, we report an “encapsulated exsolution” phenomenon observed upon reducing the metastable porous (Ni 0.07 Al 0.93 )O x to create ultra-stable Ni nanoparticles embedded within the walls of porous Al 2 O 3 nanoshells. This nanoconfined structure demonstrated high sintering resistance during 640 h of catalysis of CO 2 reforming of methane, maintaining constant 96% CH 4 and CO 2 conversion at 800 °C and dramatically outperforming conventional catalysts. Our findings could greatly expand opportunities to develop novel inorganic energy, structural, and functional materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗