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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 1,603 records · Page 89
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Methodology to determine printability criteria of highly concentrated pastes through rheological characterization

Material extrusion is an additive manufacturing technique that enables the creation of reproducible and complex hardware by depositing a viscous, shear-thinning ink onto a substrate in a custom-pattern via extrusion through a syringe. Here, the ability of an ink to be extruded onto a substrate in many layers, and maintain the desired shape is what defines the printability. Printability is often investigated by formulating, printing, and postmortem analysis of final parts in an iterative manner. Investigations of printability through rheological characterization have often been concerned with inks that straddle the line between printable and too thin, leaving out an entire class of inks that are highly-filled pastes, where extrudability is the limiting factor. Highly-filled pastes continue to pose issues for researchers as the effect of filler morphology, size, loading, and packing fraction on the ink rheology and corresponding printability is not understood. While traditional rheological characterizations may be useful for some inks, we show that protocols utilizing steady-shear, or large-amplitude oscillatory shear are difficult and unreliable for highly-filled pastes. Through transient rheology paired with real-time images we show that each traditional protocol produces inhomogeneous deformations that violate the assumptions that underly common rheological definitions. Instead, we demonstrate metrics measured with small-amplitude oscillatory shear that are correlated to the printability of various ink formulations ranging in loading. The rheological measures that accurately predict the printability of the inks are the axial stress measured at small amplitudes, and the critical stress amplitude above which rheological characterizations become impossible. In addition, we estimate the maximum packing fraction for each filler, based on the exponent common to hard sphere models, and show that the printability of each ink can be predicted by the ratio of the packing fraction to the theoretical maximum. We show how small-amplitude oscillatory shear allows users to develop printability criteria for any ink to enhance the workflow in the development of new inks, increase the performance of material extrusion printing, and improve the stability of printed parts, with less wasted time and materials.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A practical control strategy for demand flexibility with ensured occupant comfort in grid-interactive efficient buildings

This study proposes a practical and simplified demand response (DR) control strategy from the perspective of grid-interactive efficient buildings (GEBs), aiming to secure demand flexibility while ensuring occupant thermal comfort. Focusing on summer on-peak periods, a linear demand response (LDR) strategy that integrates cooling setpoint adjustment and lighting dimming was designed, and its performance was quantitatively evaluated. A case study was conducted using EnergyPlus-based simulations for a U.S. DOE small office prototype building under summer on-peak weather conditions. Compared with a conventional rapid demand response (RDR) strategy, the proposed LDR approach gradually reduced electrical loads while maintaining occupant thermal comfort indices, including predicted mean vote (PMV) and predicted percentage of dissatisfied (PPD), within acceptable comfort ranges. Quantitative analysis of demand flexibility using the grid-interactive impact index (GII) and the flexibility strength index (FSI) showed that the LDR strategy provided approximately 12.5% demand flexibility during DR periods and achieved an electricity cost reduction of about 8.8%. In addition, the results of the part-load ratio (PLR)-based cooling system performance analysis showed that, in the on-peak period, the LDR strategy exhibited improved cooling performance compared with the baseline. Overall, this study shows the potential of a practical DR control strategy that can simultaneously achieve occupant comfort and demand flexibility without relying on complex advanced control technologies.

Jung, Dong Eun↗
DOE OSTI2025

Deep learning model for fast, science-based forecasting of fluid migration along faults in geologic carbon storage scenarios

Effective long-term geologic storage depends on robust site selection and credible, science-based forecasting of subsurface behavior to ensure storage integrity. For this work, we develop a deep learning–based reduced-order model (ROM) to quantify potential carbon dioxide (CO₂) and brine migration through geological faults. The ROM combines a Transformer model for binary classification and a Stacked Ensemble for regression, trained on a comprehensive dataset generated from 1400 physics-based reservoir simulations. Key geologic and operational parameters—including fault geometry, reservoir structure, and injection conditions—were systematically varied to capture a wide range of fluid migration scenarios. The ROM accurately predicts the onset of migration, cumulative migration volumes of both CO₂ and brine, and associated migration rates, as compared to an independent set of validation simulations, while significantly reducing computational cost compared to traditional simulation methods. Model performance was evaluated across diverse fault configurations, revealing that shallow reservoir geometry and fault angle are among the most influential factors governing migration behavior. Sensitivity analysis using SHapley Additive exPlanations (SHAP) provided interpretability, revealing distinct patterns in how geological and operational features drive transient versus cumulative migration outcomes. The ROM’s ability to rapidly simulate fault migration scenarios enables efficient sensitivity analyses, scenario evaluations, and decision support for site selection and monitoring design. This approach enhances the safety, scalability, and long-term operational performance of geologic carbon storage (GCS) systems by providing a robust, interpretable tool for predicting subsurface fluid migration and assessing fault-related migration potential.

42 ENGINEERING↗
DOE OSTI2022

Modeling the non-Schmid crystallographic slip in MAX phases

We present a crystal plasticity constitutive relation for the description of experimentally observed non-Schmid crystallographic slip in a class of ternary carbides and nitrides commonly referred to as MAX phases. In the constitutive relation, we assume that the evolution of the slip system strength in MAX phases has two components – a classical component that depends on the Taylor cumulative shear strain and a non-Schmid component that depends on the stress normal to the slip plane. The non-Schmid crystal plasticity constitutive relation is then used to carry out finite element simulations of micropillar compression of single crystals of two MAX phases, Ti 2 AlC and Ti 3 AlC 2 . The finite element simulations not only quantitatively predict the stress – strain response of a wide range of crystallographic orientations of the micropillars but also rationalize the non-uniform deformation and the deformed shape of the micropillars observed in the experiments for the two materials. As a result, parametric studies are also carried out to quantify the role of the non-Schmid effect and understand the effects of key experimental parameters on the stress – strain response of the micropillars of the two MAX phases.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A hierarchical gray-box dynamic modeling methodology for direct-expansion cooling systems to support control stability analysis; Méthodologie de modélisation dynamique hiérarchique de type boîte grise pour les systèmes de refroidissement à détente directe afin de soutenir l'analyse de stabilité de la commande

In this paper, a gray-box dynamic modeling approach for direct-expansion cooling systems is presented. The overall approach incorporates a multi-stage training procedure that consists of 1) identification of component sub-models from quasi-steady-state performance data, 2) system model integration with estimation of refrigerant charge and 3) fine tuning of thermal capacitances of the evaporator and condenser to capture the system dynamic responses. Compared to traditional physics-based models, the proposed modeling approach has advantages including reduced engineering efforts in the model development phase, improved computational efficiency and enhanced prediction accuracy. The modeling method was validated using a 3-ton variable-speed heat pump and proved to be capable of accurately predicting the system transient behaviors over a wide range of operating conditions. The established dynamic model was then applied for control stability analysis, with a specific goal of determining a proper control execution time step. The case study results showed that the stable control execution time step could change significantly, from 3 sec to 19 sec, as the operating conditions and control settings vary, and a proper selection of the execution time step is critical to ensure stable and reliable operations.

42 ENGINEERING↗
DOE OSTI2026

Mechanistic mass transfer in hollow fiber membrane solvent extraction for bio-based isobutanol

Membrane solvent extraction (MSE) has emerged as a promising method for selectively recovering bioproducts from complex aqueous streams. Bio-isobutanol, a next-generation feedstock for biofuel, remains challenging to recover because of its low concentration and the presence of inhibitory substances. This study explores the potential of hollow fiber (HF) MSE for bio-isobutanol recovery and systematically examines the coupled effects of fiber packing, shell-side flow dynamics, and aqueous chemistry on performance. A resistance-in-series model is applied to understand mass transfer in the HF MSE modules, quantify local resistances, and validate overall performance. The results show that increasing the fiber packing provides a larger interfacial area but induces poor flow distribution and channeling, hindering effective isobutanol transport. Meanwhile, increasing the shell-side velocity improves isobutanol recovery due to reductions in the boundary layer thickness. The presence of salts, added to mimic fermentation broth, increases the partition coefficient through salting-out effects, further improving isobutanol flux. A modified correlation for the shell-side mass transfer coefficient (k s,ϕ+v ), integrating geometric and hydrodynamic effects, was developed and validated. The proposed model achieves highly predictive accuracy (r 2 = 0.9808) across a wide range of conditions, outperforming previous models. The findings provide mechanistic insight into the interaction of geometric packing, hydrodynamics, and chemistry in governing mass transfer in HF MSE. Overall, this work demonstrates the potential of HF MSE for efficient bio-isobutanol recovery and also provides practical guidelines on critical factors (packing fraction, partition coefficient, and shell-side velocity), aiding in the design and scaling of MSE systems for resource recovery.

Aqueous chemistry↗
DOE OSTI2024

Constraining nucleon effective masses with flow and stopping observables from the S π RIT experiment

Properties of the nuclear equation of state (EoS) can be probed by measuring the dynamical properties of nucleus-nucleus collisions. In this study, we present the directed flow (υ 1 ), elliptic flow (υ 2 ) and stopping (VarXZ) measured in fixed target Sn + Sn collisions at 270 AMeV with the SπRIT Time Projection Chamber. We perform Bayesian analyses in which EoS parameters are varied simultaneously within the Improved Quantum Molecular Dynamics-Skyrme (ImQMD-Sky) transport code to obtain a multivariate correlated constraint. The varied parameters include symmetry energy, S 0 , and slope of the symmetry energy, L, at saturation density, isoscalar effective mass, $m^{⁎}_{S}$/$m_{N}$ , isovector effective mass, $m^{⁎}_{υ}$/$m_{N}$ and the in-medium cross-section enhancement factor η. We find that the flow and VarXZ observables are sensitive to the splitting of proton and neutron effective masses and the in-medium cross-section. Comparisons of ImQMD-Sky predictions to the SπRIT data suggest a narrow range of preferred values for $m^{⁎}_{S}$/$m_{N}$, $m^{⁎}_{υ}$/$m_{N}$ and η.

Astronomy & Astrophysics↗
DOE OSTI2022

Near-infrared spectra and molar absorption coefficients of trivalent lanthanides dissolved in molten LiCl–KCl eutectic

Determining the concentration of the dissolved lanthanide species in LiCl–KCl eutectic salt is important to the development of pyrochemical reprocessing of used nuclear fuel. In this process, lanthanide fission products are found dissolved in the electrorefiner electrolyte in their trivalent oxidation state. The presence of dissolved trivalent lanthanides increases the liquidus temperature of the electrolyte mixture and can lead to the formation of insoluble oxide or oxychloride phases and must therefore be continuously monitored and controlled during the operation. Absorbance spectroscopy is a promising method for continuous measurement of the concentration of lanthanides and other elements dissolved in the electrolyte. The absorption of light by elements is linearly proportional to the concentration of the element for relatively dilute solutions according to the Beer-Lambert law. Although measurement of the absorption of ultraviolet and visible range light by lanthanides in LiCl–KCl eutectic molten salt have been explored previously, near infrared (NIR) absorption spectroscopy has received far less attention. It may, however, provide a better analytical signal when insoluble phases are present due to less Raleigh scattering compared to shorter wavelength radiation. Additionally, it may allow for concentration determination for certain elements using NIR absorption features where UV and visible range features are overlapping with features from other species. In this study, we report the UV–Vis–NIR spectra of the trivalent lanthanide chlorides of neodymium, samarium, and dysprosium in LiCl–KCl eutectic. Molar absorption coefficients are reported for analytically useful absorption maxima, with a focus on the molar absorption coefficients for NIR absorption maxima which have not been reported previously. Additionally, we observe a NIR-range absorption band of Nd3+ which was previously predicted but never experimentally observed. Here, we compare the calculated crystal field levels to the newly observed absorbance band and find them to be in good agreement with previous predictions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Regulation of the normalized rate of driven magnetic reconnection through shocked flux pileup

Magnetic reconnection is explored on the Terrestrial Reconnection Experiment (TREX) for asymmetric inflow conditions and in a configuration where the absolute rate of reconnection is set by an external drive. Magnetic pileup enhances the upstream magnetic field of the high-density inflow, leading to an increased upstream Alfvén speed and helping to lower the normalized reconnection rate to values expected from theoretical consideration. In addition, a shock interface between the far upstream supersonic plasma inflow and the region of magnetic flux pileup is observed, important to the overall force balance of the system, thereby demonstrating the role of shock formation for configurations including a supersonically driven inflow. Despite the specialized geometry where a strong reconnection drive is applied from only one side of the reconnection layer, previous numerical and theoretical results remain robust and are shown to accurately predict the normalized rate of reconnection for the range of system sizes considered. This experimental rate of reconnection is dependent on system size, reaching values as high as 0.8 at the smallest normalized system size applied.

Physics↗
DOE OSTI2026

Machine-Learning-Driven Discovery of Water Splitting BaFe 2 O 4 and Human-in-the-Loop Improvement via Al-Substitution for Increased Thermal Stability

Thermochemical hydrogen (TCH) production offers a promising method for converting thermal energy into hydrogen fuel through heat-driven redox cycles of metal oxides. Here, in this work a defect graph neural network (dGNN) was used to predict oxygen vacancy formation energies ΔH V O combined with Materials Project predictions of oxygen chemical potential stability to screen candidate oxides via high-throughput database analysis. BaFe 2 O 4 was identified as a promising material for experimental validation based on its predicted ΔH V O , oxygen chemical potential stability range, and potential for tunable substitutions to improve thermal properties. Experimental validation using thermogravimetric analysis (TGA), stagnation flow reactor (SFR), X-ray diffraction (XRD), and electron microscopy confirmed positive water-splitting behavior but also revealed limitations in thermal stability under aggressive reduction conditions. To address this, a human-in-the-loop modification strategy was employed introducing Al substitution in BaFe 2–x Al x O 4 ; this modification improves thermal stability, alters the crystal structure and enhances overall performance. These results demonstrate a combined computational and experimental workflow in which machine learning accelerates identification of promising candidates, while targeted experimental design enables optimization of functional performance. This approach advances the development of robust, cost-effective TCH materials and highlights the importance of integrating data-driven discovery with human-guided materials design in paving the way for scalable hydrogen production technologies.

organic↗
DOE OSTI2025

The Crucial Role of Vacancy Concentration in Enabling Superatomic Diffusion in Lithium Intermetallics

Anode-free solid-state Li batteries promise significant increases in energy densities compared to current commercial batteries that rely on liquid electrolytes. Major challenges persist in controlling morphological evolution during the plating and stripping of lithium metal at the anode current collector. Elemental additives that alloy with lithium have been found to modify the plating and stripping behavior of lithium. Many alloying elements form intermetallics with lithium and the mobility of Li through these intermetallics is believed to have an important effect on morphological evolution. This study shows that Li transport coefficients through intermetallics span a wide range in values, with the B32 LiAl intermetallic predicted to have a Li tracer diffusion coefficient as high as 10 –6 cm 2 /s at room temperature, which is 8 orders of magnitude larger than that of isostructural B32 LiZn. This work demonstrates the crucial role of vacancy concentration in controlling the mobility of Li atoms through intermetallics. While the migration barriers for Li-vacancy exchanges in both LiAl and LiZn are remarkably low, the superatomic conductivity in LiAl is shown to arise from the unique electronic structure of the B32 LiAl compound, which favors high concentrations of vacancies.

25 ENERGY STORAGE↗
DOE OSTI2026

Mixed Nd 4+/3+ and Cluster Magnetism in Hexagonal Perovskite 12R-Ba 4 NdMn 3 O 12−γ

Hexagonal perovskite oxides with 12R stacking host well-separated face-sharing octahedral metal trimers with short metal–metal distances, leading in some cases to large degrees of magnetic frustration and cluster magnetism. Introducing magnetic ions in proximity to these trimers can influence the degree of frustration and cluster magnetism, but the extent to which the magnetism can be tuned by varying neighboring metal cations remains an open question. In this work, we test the impacts of using Nd in proximity to Mn trimers in the hexagonal perovskite 12R-Ba 4 NdMn 3 O 12−γ . Given this stoichiometry, Nd should assume the 4+ oxidation state with a spin state of S = 1, which would be the first realization of Nd 4+ in an oxide environment. Through detailed bulk magnetic, X-ray absorption spectroscopic, and powder neutron diffraction (PND) measurements, we find that Nd 4+ is realized in this material, but there is also partial reduction to Nd 3+ , which is charge-balanced by O vacancies. Magnetometry measurements indicate an antiferromagnetic ordering temperature T N ≈ 16 K, and PND measurements reveal a surprising collinear antiferromagnetic structure with magnetic space group Pc2/m (no. 10.49 in BNS notation), which has not previously been seen in this class of materials. Our results represent a comprehensive analysis of the structural, electronic, and magnetic properties of 12R-Ba 4 NdMn 3 O 12−γ , showing the first observation of partial Nd 4+ in an oxide, and demonstrating that this structural class can host a broad range of magnetic structures which are not easily predicted based on compositional trends.

14 SOLAR ENERGY↗
DOE OSTI2023

Range and strength of mechanical interactions of force dipoles in elastic fiber networks

Mechanical forces generated by myosin II molecular motors drive diverse cellular processes, most notably shape change, division and locomotion. These forces may be transmitted over long range through the cytoskeletal medium – a disordered, viscoelastic network of biopolymers. The resulting cell size scale force chains can in principle mediate mechanical interactions between distant actomyosin units, leading to self-organized structural order in the cell cytoskeleton. Inspired by such force transmission through elastic structures in the cytoskeleton, we consider a percolated fiber lattice network, where fibers are represented as linear elastic elements that can both bend and stretch, and the contractile activity of myosin motors is represented by force dipoles. Then, by using a variety of metrics, we show how two such contractile force dipoles interact with each other through their mutual mechanical deformations of the elastic fiber network. As a prelude to two-dipole interactions, we quantify how forces propagate through the network from a single anisotropic force dipole by analyzing clusters of nodes connected by highly strained bonds, as well as through the decay rate of strain energy with distance from a force dipole. We show that predominant fiber bending screens out force propagation, resulting in reduced and strongly network configuration-dependent dipole interactions. On the other hand, stretching-dominated networks support longer-ranged inter-dipole interactions that recapitulate the predictions of linear elasticity theory. By characterizing the differences between tensile and compressive force propagation in the fiber network, we show how inter-dipole interaction depends on the dipoles’ mutual separation and orientation. The resulting elastic interaction energy may mediate a force between multiple distant dipoles, leading to their self-organization into ordered configurations. In conclusion, this provides a potential pathway for active mechanical force-driven structural order in elastic biopolymer networks.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Machine learning to accelerate screening for Marcus reorganization energies

Understanding and predicting the charge transport properties of π-conjugated materials is an important challenge for designing new organic electronic devices, such as solar cells, plastic transistors, light-emitting devices, and chemical sensors. A key component of the hopping mechanism of charge transfer in these materials is the Marcus reorganization energy which serves as an activation barrier to hole or electron transfer. While modern density functional methods have proven to accurately predict trends in intramolecular reorganization energy, such calculations are computationally expensive. In this work, we outline active machine learning methods to predict computed intramolecular reorganization energies of a wide range of polythiophenes and their use toward screening new compounds with low internal reorganization energies. Our models have an overall root mean square error (RMSE) of ±0.113 eV, but a much smaller RMSE of only ±0.036 eV on the new screening set. Since the larger error derives from high-reorganization energy compounds, the new method is highly effective to screen for compounds with potentially efficient charge transport parameters.

14 SOLAR ENERGY↗
DOE OSTI2021

Ion-dependent protein–surface interactions from intrinsic solvent response

Significance Hard–soft interfaces between inorganic surfaces and biomolecules promote self-assembly processes with broad implications in biogeochemistry, energy sciences, nanomedicine, and origins of life. Yet, detailed molecular-scale understanding of inorganic–biomolecule interactions and their dependence on solution conditions is missing. We present a theory for the initial stages of inorganic–biomolecule assembly based on the far-field response of water, using experimentally characterized interactions between muscovite surfaces and mica-binding proteins as model systems. Our work connects molecular details of the solution to assembly outcomes and suggests the initial driving forces for assembly are dominated by long-range, ion-specific interactions. The connections made between interfacial structure and long-range surface–biomolecule interactions provide insights toward a predictive understanding of biomolecular self-assembly on mineral surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Unusual magnetotransport in twisted bilayer graphene from strain-induced open Fermi surfaces

Anisotropic hopping in a toy Hofstadter model was recently invoked to explain a rich and surprising Landau spectrum measured in twisted bilayer graphene away from the magic angle. Suspecting that such anisotropy could arise from unintended uniaxial strain, we extend the Bistritzer–MacDonald model to include uniaxial heterostrain and present a detailed analysis of its impact on band structure and magnetotransport. We find that such strain strongly influences band structure, shifting the three otherwise-degenerate van Hove points to different energies. Coupled to a Boltzmann magnetotransport calculation, this reproduces previously unexplained nonsaturating B 2 magnetoresistance over broad ranges of density near filling ν = ± 2 and predicts subtler features that had not been noticed in the experimental data. In contrast to these distinctive signatures in longitudinal resistivity, the Hall coefficient is barely influenced by strain, to the extent that it still shows a single sign change on each side of the charge neutrality point—surprisingly, this sign change no longer occurs at a van Hove point. The theory also predicts a marked rotation of the electrical transport principal axes as a function of filling even for fixed strain and for rigid bands. More careful examination of interaction-induced nematic order versus strain effects in twisted bilayer graphene could thus be in order.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Understanding atom probe’s analytical performance for iron oxides using correlation histograms and ab initio calculations

Abstract Field evaporation from ionic or covalently bonded materials often leads to the emission of molecular ions. The metastability of these molecular ions, particularly under the influence of the intense electrostatic field (10 10 Vm −1 ), makes them prone to dissociation with or without an exchange of energy amongst them. These processes can affect the analytical performance of atom probe tomography (APT). For instance, neutral molecules formed through dissociation may not be detected at all or with a time of flight no longer related to their mass, causing their loss from the analysis. Here, we evaluated the changes in the measured composition of FeO, Fe 2 O 3 and Fe 3 O 4 across a wide range of analysis conditions. Possible dissociation reactions are predicted by density-functional theory calculations considering the spin states of the molecules. The energetically favoured reactions are traced on to the multi-hit ion correlation histograms, to confirm their existence within experiments, using an automated Python-based routine. The detected reactions are carefully analyzed to reflect upon the influence of these neutrals from dissociation reactions on the performance of APT for analysing iron oxides.

74 ATOMIC AND MOLECULAR PHYSICS↗