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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 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Regeneration of anion-exchange resins for cyclic selenium removal from industrial wastewaters

Application of ion exchange for the removal of selenium (Se) oxyanions from industrial wastewaters is often limited by ineffective regeneration of the ion-exchange resins, particularly in complex systems containing competing ions, such as coal-ash leachate containing high-sulfate concentrations and heavy metal ions. Here, in this study, it was first demonstrated that while conventional regeneration with sodium chloride (NaCl) is effective for simulated wastewater, with ∼80% efficiency, NaCl fails to regenerate resin loaded with real industrial wastewater, achieving less than 20% efficiency. To overcome this challenge, a two-step regeneration process was investigated using a sodium carbonate (Na 2 CO 3 ) solution for elution, followed by a NaCl solution for restoration. Compared to the one-step NaCl regeneration, this integrated process restored more than 80% of the resin's capacity with real industrial wastewaters. Beyond demonstrating regeneration performance, this research emphasizes fundamental mechanistic interpretations of the observed regeneration behavior across different water matrices and experimental conditions. Particularly, accounting for pH-dependent carbonate speciation, it is proposed that the elution step exploits the resin's strong affinity for divalent carbonate ions to displace strongly bound contaminants, while the subsequent restoration step relies mainly on the mass action effects of chloride ions to regenerate the resin sites. The protocol was optimized to achieve rapid regeneration (<10 min) using moderate chemical concentrations (0.5 M) in treating real leachate. In batch cyclic experiments, Se regeneration reached nearly complete recovery after five consecutive sorption and desorption cycles, while in the fixed-bed system, the regeneration efficiency remained at approximately 80% after five cycles.

Anion-exchange resin↗
DOE OSTI2025

Structure and ultrafast dynamics of tri-nuclear Ag-/Tl–Pt 2 POP 4 complexes in solution

The energetics and dynamics of ion assembly in solution has broad influence in nanomaterials and inorganic synthesis. To investigate the fundamental processes involved, we present a time-resolved x-ray solution scattering (TR-XSS) study of the trinuclear silver and thallium complexes of the diplatinum ion PtPOP [Pt 2 (H 2 P 2 O 5 )$_4^{4−}$] in aqueous solution. These complexes, their structural properties, and their electronic structure are not well understood and afford a unique opportunity to study the metal–metal bond formation that influences molecular and material assembly in solution. We present model-independent analysis of the observed dynamics as well as an analysis incorporating time-resolved structural refinements of key bond lengths with $<$100 fs time resolution. We find that upon photoexcitation, the Pt atoms contract ∼0.25 Å toward the center of both the Ag- and the Tl-PtPOP complexes, as previously observed for the PtPOP anion. For the AgPtPOP system, an ultrafast Ag-Pt bond expansion of ∼0.2 Å is observed, whereas in contrast, the TlPtPOP system exhibits a Tl-Pt bond contraction of ∼0.3 Å upon photoexcitation. For both complexes, the change in electronic state leads to coherent (“wave-packet”) oscillations along the metal–Pt coordinates. Based on these structural dynamics, we propose an electronic structure model that describes the metal–metal bonding behavior in both the ground and excited state for both complexes.

Lenzen, Philipp [Technical Univ. of Denmark, Lyngb↗
NASA NTRS1978

Analysis of dynamic system response to product random processes

The response of dynamic systems to the product of two independent Gaussian random processes is developed by use of the Fokker-Planck and associated moment equations. The development is applied to the amplitude modulated process which is used to model atmospheric turbulence in aeronautical applications. The exact solution for the system response is compared with the solution obtained by the quasi-steady approximation which omits the dynamic properties of the random amplitude modulation. The quasi-steady approximation is valid as a limiting case of the exact solution for the dynamic response of linear systems to amplitude modulated processes. In the nonlimiting case the quasi-steady approximation can be invalid for dynamic systems with low damping.

Sidwell, K.↗
NASA NTRS2017

Model-Based Thermal System Design Optimization for the James Webb Space Telescope

Spacecraft thermal model validation is normally performed by comparing model predictions with thermal test data and reducing their discrepancies to meet the mission requirements. Based on thermal engineering expertise, the model input parameters are adjusted to tune the model output response to the test data. The end result is not guaranteed to be the best solution in terms of reduced discrepancy and the process requires months to complete. A model-based methodology was developed to perform the validation process in a fully automated fashion and provide mathematical bases to the search for the optimal parameter set that minimizes the discrepancies between model and data. The methodology was successfully applied to several thermal subsystems of the James Webb Space Telescope (JWST). Global or quasiglobal optimal solutions were found and the total execution time of the model validation process was reduced to about two weeks. The model sensitivities to the parameters, which are required to solve the optimization problem, can be calculated automatically before the test begins and provide a library for sensitivity studies. This methodology represents a crucial commodity when testing complex, large-scale systems under time and budget constraints. Here, results for the JWST Core thermal system will be presented in detail.

Cataldo, Giuseppe↗
DOE OSTI2024

A Three-in-One Hybrid Strategy for High-Performance Semiconducting Polymers Processed from Anisole

The development of semiconducting polymers with good processability in green solvents and competitive electrical performance is essential for realizing sustainable large-scale manufacturing and commercialization of organic electronics. A major obstacle is the processability-performance dichotomy that is dictated by the lack of ideal building blocks with balanced polarity, solubility, electronic structures, and molecular conformation. Herein, through the integration of donor, quinoid and acceptor units, an unprecedented building block, namely TQBT, is introduced for constructing a serial of conjugated polymers. The TQBT, distinct in non-symmetric structure and high dipole moment, imparts enhanced solubility in anisole—a green solvent—to the polymer TQBT-T. Furthermore, PTQBT-T possess a highly rigid and planar backbone owing to the nearly coplanar geometry and quinoidal nature of TQBT, resulting in strong aggregation in solution and localized aggregates in film. Remarkably, PTQBT-T films spuncast from anisole exhibit a hole mobility of 2.30 cm 2 V -1 s -1 , which is record high for green solvent-processable semiconducting polymers via spin-coating, together with commendable operational and storage stability. The hybrid building block emerges as a pioneering electroactive unit, shedding light on future design strategies in high-performance semiconducting polymers compatible with green processing and marking a significant stride towards ecofriendly organic electronics.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Life cycle energy demand and carbon emissions of scalable single-junction and tandem perovskite PV

Perovskite photovoltaics reached record efficiencies in the laboratory and, if sustainably commercialized, they would accelerate a green energy transition. Here, this article presents the development of life-cycle inventory material and energy databases of most promising four single-junction and three tandem scalable perovskite systems with assumptions regarding scalable production validated by industry experts. We conducted comprehensive “ex ante” Life Cycle Analysis (LCA) and Net Energy Analysis, analyzing their cumulative energy demand, global warming potential profiles, energy payback times and energy return on investment (EROI). LCA contribution analysis elucidates the most impactful material and process choices. It shows that solution-based perovskite manufacturing would have lower environmental impact than vapor-based methods, and that roll-to-roll (RtR) printing offers the lowest impact. Among material choices, MoOx/Al has lower impact than Ag, and fluorine-tin-oxide lower than indium-tin-oxide. Furthermore, we compare perovskites with commercial crystalline-silicon and thin-film PV, accounting for the most recent developments in crystalline-Si wafer production and differences in life expectancies and efficiencies. It is shown that perovskite systems produced with RtR manufacturing could reach in only 12 years of life the same EROI as that of single-crystalline-Si PV lasting 30-years. This work lays a foundation for sustainability investigations of perovskite large-scale deployment.

14 SOLAR ENERGY↗
DOE OSTI2021

Investigations of water/oxide interfaces by molecular dynamics simulations

Water/oxide interfaces are ubiquitous on earth and show significant influence on many chemical processes. For example, understanding water and solute adsorption as well as catalytic water splitting can help build better fuel cells and solar cells to overcome our looming energy crisis; the interaction between biomolecules and water/oxide interfaces is one hypothesis to explain the origin of life. However, knowledge in this area is still limited due to the difficulty of studying water/solid interfaces. As a result, research using increasingly sophisticated experimental techniques and computational simulations has been carried out in recent years. Although it is difficult for experimental techniques to provide detailed microscopic structural information, molecular dynamics (MD) simulations have satisfactory performance. In this report, we discuss classical and ab initio MD simulations of water/oxide interfaces. Generally, we are interested in the following questions: How do solid surfaces perturb interfacial water structure? How do interfacial water molecules and adsorbed solutes affect solid surfaces and how do interfacial environments affect solvent and solute behavior? Finally, we discuss progress in the application of neural network potential based MD simulations, which offer a promising future because this approach has already enabled ab initio level accuracy for very large systems and long trajectories.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

A Dataset of CFD Simulated Industrial Furnace Images for Conditional Automatic Generation with GANs

The steel industry is constantly looking for ways to automate processes and improve efficiency. A standard practice in industry is to simulate how complex systems will operate before they are actually used. Some complex systems, including steel industry processes such as blast furnaces, require complex physics-based simulations utilizing computational fluid dynamics (CFD). These CFD physics-based simulations are very accurate but can take significant time and computational resources to process, resulting in challenges for the implementation of the models in real-world operational environments. In recent years, deep learning (DL) has been considered as a substitute for these CFD models. DL models can be trained on validated CFD simulation data and then used for industrial process inference. Previous DL-based solutions have made great contributions for industrial automation but are currently missing the additional visualization component that CFD simulations also provide. In this paper, we propose a dataset for simple DL generative approaches that can help to address this issue. The dataset and methodology under development to approach this prediction are discussed in this work.

Calix, Ricardo↗
DOE OSTI2023

Gaussian process hydrodynamics

Abstract We present a Gaussian process (GP) approach, called Gaussian process hydrodynamics (GPH) for approximating the solution to the Euler and Navier-Stokes (NS) equations. Similar to smoothed particle hydrodynamics (SPH), GPH is a Lagrangian particle-based approach that involves the tracking of a finite number of particles transported by a flow. However, these particles do not represent mollified particles of matter but carry discrete/partial information about the continuous flow. Closure is achieved by placing a divergence-free GP prior ξ on the velocity field and conditioning it on the vorticity at the particle locations. Known physics (e.g., the Richardson cascade and velocity increment power laws) is incorporated into the GP prior by using physics-informed additive kernels. This is equivalent to expressing ξ as a sum of independent GPs ξ l , which we call modes, acting at different scales (each mode ξ l self-activates to represent the formation of eddies at the corresponding scales). This approach enables a quantitative analysis of the Richardson cascade through the analysis of the activation of these modes, and enables us to analyze coarse-grain turbulence statistically rather than deterministically. Because GPH is formulated by using the vorticity equations, it does not require solving a pressure equation. By enforcing incompressibility and fluid-structure boundary conditions through the selection of a kernel, GPH requires significantly fewer particles than SPH. Because GPH has a natural probabilistic interpretation, the numerical results come with uncertainty estimates, enabling their incorporation into an uncertainty quantification (UQ) pipeline and adding/removing particles (quanta of information) in an adapted manner. The proposed approach is suitable for analysis because it inherits the complexity of state-of-the-art solvers for dense kernel matrices and results in a natural definition of turbulence as information loss. Numerical experiments support the importance of selecting physics-informed kernels and illustrate the major impact of such kernels on the accuracy and stability. Because the proposed approach uses a Bayesian interpretation, it naturally enables data assimilation and predictions and estimations by mixing simulation data and experimental data.

Mathematics↗
DOE OSTI2026

How exudates production along a phosphorus gradient influences mineral dissolution across contrasting soil development stages

Harnessing rhizosphere processes offers a valuable opportunity to optimize nutrient use efficiency in agroecosystems. In nutrient-limited soils, plants discharge part of photosynthate surplus via root exudation, including carboxylates, which may enhance mineral dissolution and nutrient mobilization. We aimed to assess how plant responses to nutrient limitation translated into changes in exudate profiles, and how these exudates, in turn, drive bioweathering processes across soils of contrasting mineralogy and weathering degree. We conducted a hydroponic experiment with Lupinus albus grown under five phosphorus (P) concentrations (5, 10, 20, 30, and 50 µM) over seven weeks. We measured plant biomass and root traits, performed a metabolomics analysis and quantified seven carboxylates in root exudates using gas chromatography-mass spectrometry. To assess bioweathering processes across contrasted soil domains, we conducted batch dissolution tests with exudates using three soil horizons—35 each with distinct physicochemical properties: enriched in organic matter, iron oxides, or primary silicates. At the intermediate level of P supply, shoot biomass was comparable to that under high P, but plants produced more root biomass and a higher total carboxylate exudation rate. Despite low carboxylate concentrations (<100 ppb), exudates promoted the dissolution of Ca, Mg, Si, Fe, P and K in all horizons. Yet, the degree of element released varied among horizons. These findings highlight the importance of root exudates in enhancing mineral dissolution, with effects dependent on soil physicochemical properties. The results suggest that managing agroecosystems under moderate nutrient limitation could be a sustainable strategy to increase root-to-shoot ratios, enhance bioweathering processes and nutrient release in soil solution.

Pollet, Sasha L.↗
DOE OSTI2023

Oxidation mechanism in a refractory multiple-principal-element alloy at high temperature

Refractory multiple-principal-element alloys (RMPEAs) are promising structural materials to enable increased power efficiency in high-temperature oxidation environments, but the oxidation behavior and microstructures of the oxides, especially at the beginning of the oxidation, have received limited attention. Here, the oxidation mechanism in an equimolar W-Mo-Ta-Nb-V was investigated at 1300 °C and compared with the equimolar W-Mo-Ta-Nb alloy without V. The oxide scale on WMoTaNbV after 1 min exposure is shown to be composed of a degradation layer at the interface of the alloy/oxide, an initial oxide transition layer, followed by the main phase aggregate oxide layer, and an outermost oxide layer. At the early stage of oxidation, the absorption of oxygen by the RMPEA substrate forms a solid solution. Vanadium accelerates the initial degradation process as it forms VO. The initial oxidation-induced degradation of RMPEA follows a sequence governed by the free energy change accompanied by local element segregation. Liquid V-Mo oxides aggregate in the intermediate oxide layer. The inward growth of the oxide scale is controlled by the local composition changes, the orientation of the substrate, the crystal structure, and physical properties such as melting points of the oxides.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Machine learning-aided inverse design for biogas upgrading through biological CO 2 conversion

The biogas upgrading process through bioconversion of CO 2 to CH 4 by hydrogenotrophic methanogens is an attractive strategy for energy decarbonation. Many studies have optimized operational parameters to improve key performance indicators such as CH 4 % and H 2 utilization efficiency. However, inconsistent laboratory conditions make it challenging to compare results. Existing models for analyzing operating conditions can only assess the impact of individual conditions and lack the ability to simultaneously optimize multiple conditions. To address this, two XGBoost models were built with R 2 of 0.779 and 0.903 with data collected from literatures and were embedded into multi-objective partitive swarm optimization algorithm to optimal operating conditions. Predictions were compared with experimental validations under optimized conditions, revealing an 8.50% and 2.95% relative error in CH 4 % and H 2 conversion rate, respectively. This approach streamlines biogas upgrading processes, offering a data-driven solution to enhance efficiency and consistency in the pursuit of sustainable methane production.

Biogas upgrading↗
DOE OSTI2024

Optimizing iodine adsorption in functionalized metal-organic frameworks via an unprecedented positional isomerism strategy

Porous metal–organic frameworks (MOFs) have emerged as highly promising adsorbents for capturing radioiodine, a predominant fission product released during nuclear fuel reprocessing. However, systematic investigations into the correlation between MOF structure and iodine uptake capacity remain scarce. Here, we present a novel approach to enhance the iodine adsorption capacity of MOFs by optimizing linker functionalization. Using ligand-functionalized thorium-based MOFs as a structural platform, we demonstrate that ortho-amino-substitution near the node of the dicarboxylate linker significantly increases iodine adsorption capacity compared to meta-amino-substitution, where the amino groups are directed away from the node. Specifically, ortho-substituted Th-UiO-68-3,3”-(NH 2 ) 2 exhibits higher iodine uptake capacities than the meta-substituted Th-UiO-68-2,2”-(NH 2 ) 2 via both vapor diffusion-based (2.042 vs. 1.087 g/g) and solution-based (0.841 vs. 0.784 g/g) processes. Notably, the I 2 vapor adsorption capacity (2.042 g/g) of Th-UiO-68-3,3”-(NH 2 ) 2 represents the second highest among all reported Th-MOFs. Pair distribution function (PDF) studies reveal that the superior iodine uptake performance of ortho-functionalized MOFs can be attributed to the reduced steric hindrance of the amino groups compared with the meta-substituted variants. Finally, this research highlights how positional isomerism and its subtle alterations can significantly influence host–guest interactions, extending beyond simple structural considerations.

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

Fiber orientation effects on ultra-high performance concrete formed by 3D printing

Despite the growing interest in 3D concrete printing, its current progress is limited by reinforcing methods. Inclusion of steel fibers is a potential reinforcing solution; however, the effect of printing process on orientation of the fibers is still unknown. This study aims to quantitatively investigate the orientation distribution of steel fibers in 3D printed ultra-high performance concrete. The effects of extrusion nozzle size, Cartesian print speed, and fiber volume fraction on the orientation of fibers were evaluated using digital image analysis. The consequent effects of the fiber orientation on the mechanical properties of the 3D-printed specimens were also determined. The results were compared with those of the conventionally mold-cast specimens. The results revealed that the smaller nozzle size and higher fiber volume fraction significantly enhanced the fiber alignment parallel to the printing direction. This preferential fiber alignment led to superior mechanical performance of the printed specimens to the mold-cast specimens.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Energy storage planning for enhanced resilience of power systems against wildfires and heatwaves

Extreme weather events pose significant risks to power grid stability due to their severe consequences and potential for widespread failures. Energy storage systems hold great potential for enhancing grid resilience against such events by providing reliable power during peak demand periods. However, accurately quantifying the size, location, and investment costs of new energy storage assets is a complex task, as energy storage planning decisions depend on the investment choices of other generation technologies and the integration of new transmission projects. Here, this paper presents a novel capacity expansion planning framework that simultaneously optimizes investments in energy storage, generation, and transmission, determining their optimal size, location, and type, while incorporating extreme weather events into long-term planning. More specifically, our stress-event-informed planning framework integrates the impact of heatwaves and wildfires into the planning process, identifying least-cost investment solutions that comply with policy goals and enhance grid resilience. The proposed framework employs machine-learning-based modeling to project heatwave-induced loads and performance-based risk assessment to evaluate wildfire-driven transmission line derates. Using industry-standard datasets to accurately represent the transmission topology of the Western Interconnection (WI) system, the proposed framework is applied to the WI 40-zone system, with investment decisions reported for the years 2030, 2035, and 2040. Simulation results reveal that with just a 10% increase in investment costs, resilience against extreme events can be significantly improved, with investment decisions heavily favoring energy storage, particularly 4-hour energy storage systems.

25 ENERGY STORAGE↗
DOE OSTI2020

Thermodynamic Modeling of Aqueous LiCl, LiBr, LiI, and LiNO 3 Solutions

Thermodynamic models are essential to facilitate the advancement of process design, optimization, and operation of electrolyte systems. In this work, a comprehensive thermodynamic framework based on the Electrolyte Nonrandom Two-Liquid model is developed to calculate phase equilibria behavior and salt solubility of aqueous LiCl, LiBr, LiI, and LiNO 3 solutions. The model describes the non-ideality of the electrolyte solutions by using two binary interaction parameters for each electrolyte-molecule pair in the system. Each binary interaction parameter is further expressed with up to three temperature coefficients which are regressed from experimental data. To take into account the hydration of lithium ion, two separate chemistries for the dissociation of lithium salts are investigated. In the first case, the lithium ion is considered as a bare ion, Li + , while in the second case hydration of the lithium ion from Li + to Li(H 2 O) + is considered. Here, the calculated thermodynamic properties compare adequately with the experimental data for both sets of chemistries for concentrations up to saturation and temperatures from 273.15 K up to 623.15 K. Moderate to significant improvements are observed with the incorporation of the hydration chemistry for aqueous LiCl, LiBr, and LiI solutions when compared to the non-hydrated lithium ion model results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗