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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Probing the Effect of Electrode Thermodynamics on Reaction Heterogeneity in Thick Battery Electrodes

Thick electrodes present a viable strategy for enhancing energy density and reducing manufacturing costs of lithium-ion batteries. However, reaction heterogeneity during cycling compromises their rate capability and cycle life. While this nonuniformity is commonly attributed to sluggish charge transport, it is demonstrated here that the thermodynamic properties of the electrode material play an equally critical role. Through combined X-ray fluorescence microscopy and absorption near-edge structure spectroscopy, reaction distributions in LiFePO 4 (LFP) and LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC) thick electrodes with matched porosity and tortuosity are compared. LFP electrodes develop pronounced depth-oriented state-of-charge (SOC) gradients that worsen with increasing discharge rates, whereas NMC maintains much more uniform SOC distributions under such conditions. This difference originates from their distinct SOC dependence of equilibrium potentials and is quantifiable through a dimensionless “reaction uniformity” number. Intriguingly, LFP thick electrodes also exhibit lateral SOC variations that strengthen during slow discharge. In conclusion, the enhanced reaction uniformity in NMC correlates with better active material utilization and slower capacity fade than LFP, highlighting electrode thermodynamics as a key design consideration for thick electrodes.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Design of a V–Ti–Ni alloy with superelastic nano-precipitates

Stress-induced martensitic transformations enable metastable alloys to exhibit enhanced strain hardening capacity, leading to improved formability and toughness. As is well-known from transformation-induced plasticity (TRIP) steels, however, the resulting martensite can limit ductility and fatigue life due to its intrinsic brittleness. In this work, we explore an alloy design strategy that utilizes stress-induced martensitic transformations but does not retain the martensite phase. This strategy is based on the introduction of superelastic nano-precipitates, which exhibit reverse transformation after initial stress-induced forward transformation. To this end, utilizing ab-initio simulations and thermodynamic calculations we designed and produced a V 45 Ti 30 Ni 25 (at%) alloy. In this alloy, TiNi is present as nano-precipitates uniformly distributed within a ductile V-rich base-centered cubic (bcc) β matrix, as well as being present as a larger matrix phase. We characterized the microstructure of the produced alloy using various scanning electron microscopy (SEM) and transmission electron microscopy (TEM) methods. Furthermore, the bulk mechanical properties of the alloy are demonstrated through tensile tests, and the reversible transformation in each of the TiNi morphologies were confirmed by in-situ TEM micro-pillar compression experiments, in-situ high-energy diffraction synchrotron cyclic tensile tests, indentation experiments, and differential scanning calorimetry experiments. The observed transformation pathways and variables impacting phase stability are critically discussed.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

AlphaBuilding ResCommunity: A multi-agent virtual testbed for community-level load coordination

Training and validating algorithms in a simulation testbed can accelerate research and applications of optimal control of residential loads to improve energy flexibility and grid resilience. We developed an open-source simulation environment, AlphaBuilding ResCommunity, that can be used to train and validate algorithms to control a single thermostatically controlled load (TCL) or coordinate a group of TCLs. We used reduced-order models to simulate the thermodynamics of TCLs, and the parameter values were determined from the connected smart thermostat data of real households. The environment was built upon the standardized OpenAI Gym interface. Ancillary functions, such as retrieving the parameters and weather forecasts, are provided to facilitate control strategies that require predictive information. Compared with existing efforts, AlphaBuilding ResCommunity has three advantages: (1) more realistic model settings because the parameter values are identified from actual household operating data, and modelling and measurement uncertainty are considered; (2) passive thermal storage control; and (3) ease of use due to a simple software dependency and standardized interface. We demonstrated the applications of the environment by implementing a Kalman Filter and Model Predictive Control on a single TCL and a Priority-Stack-Based Control and Alternating Direction Method of Multipliers to coordinate multiple TCLs for load tracking.

Wang, Z↗
DOE OSTI2020

Modeling the dynamic response of rock masses with multiple compliant fluid saturated joint sets—Part I: Mesoscale simulations

Recently a mesoscale model was developed that includes thermomechanically consistent constitutive equations with dissipation due to porous compaction, inelastic distortional deformation rate, and slipping on persistent dry joint surfaces. In this Part I of a two-part paper, we describe enhancements of the mesoscale model which include: normal compliance with hysteresis, non-persistent joints with finite area, joint sets with angular deviation, and the weakening effect of fluid pressure in the joints. Examples study the influences of these effects on average strength. These computationally expensive simulations are used to inspire functional forms in a continuum model, described in Part II, which is needed for large scale simulations of real applications.

42 ENGINEERING↗
DOE OSTI2025

Intermetallic phase formation in Al-Si-Zr alloys during hot isostatic pressing revealed by experiments and molecular dynamics

Understanding phase transformations at alloy interfaces is critical for the design of advanced structural materials. Here, in this study, we investigate the formation mechanisms of the Al 2 SiZr intermetallic phase in the Al-Si-Zr system under hot isostatic pressing (HIP) using molecular dynamics (MD) simulations and thermodynamic analysis. A unique aspect of our approach in MD involves the replacement of a disordered Al 2 SiZr stoichiometry with an ordered phase at the Al-Zr interface once HIP results in the desired Al 2 SiZr stoichiometry, allowing us to compute the total energetic cost of transformation by accounting for both formation energies and diffusion barriers. Diffusion coefficients and activation energies, extracted across a range of temperatures, reveal that HIP substantially enhances atomic mobility, creating favorable stoichiometry for phase evolution. Our results show that Al 2 SiZr phase formation is kinetically unfavorable at lower temperatures but becomes feasible when the thermodynamic driving energy surpass a critical energy threshold.

Roy, Ankit [Pacific Northwest National Laboratory ↗
DOE OSTI2023

Uncovering metallic glasses hidden vacancy-like motifs using machine learning

Vacancies are a ubiquitous type of defect in crystalline materials that can affect their properties and behavior, including atomic diffusivity, deformation processes, thermal conductivity, and electrical conductivity. While well-defined in crystals, it is challenging to identify such topological footprints in the amorphous structure of metallic glasses (MGs). Here, we uncover an unforeseen vacancy-like structural motif named Q7, which refers to an atomic Voronoi polyhedron with seven quadrangular faces, by investigating MG local atomic configurations with the help of machine learning. The Q7 motif exhibits characteristics similar to crystalline vacancies and plays a significant role in short-range structural disorder in MGs. The atoms at the center of the Q7 motif display larger local entropy, atomic volume, and local tension. Additionally, its concentration follows an Arrhenius-like relationship with temperature, accurately indicating the glass transition temperature, and is strongly correlated with the yield and failure of MGs during mechanical deformation. The discovery of the Q7 motif provides new insights into understanding the intricate relationship between local disorder and structural relaxation in MGs, offering a remarkable ability to predict their thermal and mechanical behavior. This potentially paves the way for enhancements in the design and manufacturing processes of MGs and other amorphous materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

On the effect of elemental partitioning to secondary phases after solution and aging heat treatments in a Co-Ni-based superalloy

Here, this paper presents the phase stability and elemental partitioning in a Co-40Ni-10Al-7.5W-10Cr-3Nb-0.06B-0.6C (at.%) superalloy (referred to as 3Nb) after a two-step heat treatment. The resulting microstructure consisted of γ, γ', MC carbides and µ-Co 7 W 6 phase decorating the regions near and at the grain boundaries. Nb preferentially partitioned to the γ'-phase and other elements such as Ni, Cr and W were responsible for the μ-phase formation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Synergistic Enhancement of Lead and Selenate Uptake at the Barite (001)–Water Interface

The interactions of heavy metals with minerals influence the mobility and bioavailability of toxic elements in natural aqueous environments. The sorption of heavy metals on covalently bonded minerals is generally well described by surface complexation models (SCMs). However, understanding sorption on sparingly soluble minerals is challenging because of the dynamically evolving chemistry of sorbent surfaces. The interpretation can be even more complicated when multiple metal ions compete for sorption. In the present study, we observed synergistically enhanced uptake of lead and selenate on the barite (001) surface through two sorption mechanisms: lattice incorporation that dominates at lower coverages and two-dimensional monolayer growth that dominates at higher coverages. Further, we also observed a systematic increase in the sorption affinity with increasing co-sorbed ion coverages, different from the assumption of invariant binding constants for individual adsorption processes in classical SCMs. Computational simulations showed thermodynamically favorable co-incorporation of lead and selenate by simultaneously substituting for barium and sulfate in neighboring sites, resulting in the formation of molecular clusters that locally match the net dimension of the substrate lattice. These results emphasize the importance of ion–ion interactions at mineral–water interfaces that control the fate and transport of contaminants in the environment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Chemistry Informed Machine Learning-Based Heat Capacity Prediction of Solid Mixed Oxides

Knowing heat capacity is crucial for modeling temperature changes with the absorption and release of heat and for calculating the thermal energy storage capacity of oxide mixtures with energy applications. The current prediction methods (ab initio simulations, computational thermodynamics, and the Neumann–Kopp rule) are computationally expensive, not fully generalizable, or inaccurate. Machine learning has the potential of being fast, accurate, and generalizable, but it has been scarcely used to predict mixture properties, particularly for mixed oxides. Here, we demonstrate a method for the generalizable prediction of heat capacity of solid oxide pseudobinary mixtures using heat capacity data obtained from computational thermodynamics and descriptors from ab initio databases. Further, models trained through this workflow achieved an error (mean absolute error of 0.43 J mol –1 K –1 ) lower than the uncertainty in differential scanning calorimetry measurements, and the workflow can be extended to predict other properties derived from the Gibbs free energy and for higher-order oxide mixtures.

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

Structural and Electronic Transitions in Liquid FeO Under High Pressure

Abstract FeO represents an important end‐member for planetary interiors mineralogy. However, its properties in the liquid state under high pressure are poorly constrained. Here, in situ high‐pressure and high‐temperature X‐ray diffraction experiments, ab initio simulations, and thermodynamic calculations are combined to study the local structure and density evolution of liquid FeO under extreme conditions. Our results highlight a strong shortening of the Fe‐Fe distance, particularly pronounced between ambient pressure and ∼40 GPa, possibly related with the insulator to metal transition occurring in solid FeO over a similar pressure range. Liquid density is smoothly evolving between 60 and 150 GPa from values calculated for magnetic liquid to those calculated for non‐magnetic liquid, compatibly with a continuous spin crossover in liquid FeO. The present findings support the potential decorrelation between insulator/metal transition and the high‐spin to low‐spin continuous transition, and relate the changes in the microscopic structure with macroscopic properties, such as the closure of the Fe‐FeO miscibility gap. Finally, these results are used to construct a parameterized thermal equation of state for liquid FeO providing densities up to pressure and temperature conditions expected at the Earth's core‐mantle boundary.

Morard, Guillaume↗
DOE OSTI2025

Stress-dependent χ phase transformation in a Ni-based superalloy

The ongoing push to elevate operating temperatures in aerospace gas turbine engines – driven by goals of enhanced fuel efficiency and reduced CO 2 emissions – mandates advancements in the creep resistance of Ni- and Co-based superalloys, which are integral for critical engine components. This study elucidates the role of stress assisted localized phase transformations in the creep properties of these alloys. By leveraging chemo-mechanical coupling, self-healing γ′ precipitates are designed to immobilize planar defects, thereby increasing creep resistance. Employing advanced characterization techniques such as high-resolution Scanning Transmission Electron Microscopy (HR-STEM), in conjunction with atomistic simulations and thermodynamic calculations, novel deformation pathways facilitated by χ local phase transformation (LPT) strengthening have been uncovered; notably, the formation of χ nano-laths through microtwinning and superlattice intrinsic stacking fault (SISF) shearing. This study highlights critical insights into the compositional boundaries necessary for optimizing LPT strengthening while avoiding deleterious bulk formation of η/χ phases. These advancements will guide the design of new alloys maximizing high-temperature creep strength for advanced aerospace applications.

Egan, Ashton J. [Friedrich-Alexander University Er↗
DOE OSTI2026

An Ab Initio Molecular Dynamics Study of Key Thermodynamic Input Parameters for Computer Simulation of U-6Nb Solidification

The key to metallic fuel development is the fabrication of uranium metal and alloys into fuel forms. U-Nb alloys are one of the best candidates for a metallic fuel alloy with high-temperature strength sufficient to support the core, acceptable nuclear properties, good fabricability, and compatibility with usable coolant media. Melt processing has been a key component of the metallic fuel cycle, and process models require thermophysical parameters at elevated temperatures, particularly above the melting temperatures, regarding which experimental data are scarce, for accurate simulations and process development. By means of ab initio density-functional theory (DFT) quantum molecular dynamics (QMD), we have calculated the main thermophysical parameters—the density, thermal expansion coefficient, specific heat, thermal conductivity, melting temperature, latent heat of fusion, and viscosity—used in the modeling of the U-6 wt.% Nb alloy casting. The melting temperature of the U-6 wt.% Nb alloy at ambient pressure is obtained by means of QMD simulations using the Z-method. The ambient volume change and latent heat of melting of U-6 wt.% Nb are also derived from QMD simulations in conjunction with analytical fitting for the energy and pressure. The thermal conductivity for the solid U-Nb alloy is calculated from the semi-classical Boltzmann transport equation combined with an estimate of the electron relaxation time obtained from DFT simulations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Understanding Dynamics and Thermodynamics of ENSO and Its Complexity Simulated by E3SM and Other Climate Models

Despite the seeming success of most state-of-the-art climate models in simulating the El Niño-Southern Oscillation (ENSO), there is strong evidence that models achieve realistic levels of ENSO activity do so often for wrong reasons. This is owing to an often occurred near cancelation of large errors in terms of contributions to ENSO growth rate from coupled dynamic and thermodynamic feedback processes. Climate models remain deficient in simulating the observed ENSO’s spatial and temporal complexity that involves interplays of coupled dynamic and thermodynamic feedbacks, interactions across multiple scales, nonlinear processes in the tropical atmosphere and ocean system, biases in mean sate and physical processes, and influences external to equatorial Pacific coupled ENSO dynamics. Our proposed research aims at advancing predictive and process-level understandings of ENSO simulated in E3SM and other climate models under current and future climate conditions with two main objectives: (i) better understanding the aforementioned broad range interactive processes and sources that control fundamental properties of ENSO in E3SM and CIMP6 outputs as well as in observational (reanalysis) data sets, using a hierarchical of coupled dynamical frameworks consisting of theoretical analysis, intermediate complexity modeling, and coupled dynamic diagnostics; (ii) to use this understanding to explore pathways towards improving E3SM’s capability of simulating ENSO and its complexity. More specifically, we will focus on four main thrusts of research: (1) ENSO’s dynamic and thermodynamic feedbacks; (2) the across-scale interactions of ENSO with annual cycle and MJO/WWB/TIW (Madden Julian Oscillation/Westerly Wind Burst/Tropical Instability Wave) activity; (3) key nonlinear processes of ENSO involving atmospheric convective thresholds, nonlinear ocean dynamic heating, and thermocline outcropping; and (4) the impacts of climate mean-state biases/changes and perturbed physical processes on simulated ENSO and its complexity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

The Novel Hybrid Ab Initio Model of High-Performance Structural Alloys Design for Fossil Energy Power Plants

The current project developed a novel HT-CALPHAD/DFT approach, which can quickly design new high-performance structural alloys for the application of FE power plants. The PI will mainly take charge of high-throughput DFT simulations and computational thermodynamics of the selected multicomponent alloy systems for the FE power plant applications. At the end of the project, a novel hybrid model based on high throughput CALPHAD/DFT simulations and computational thermodynamics will be developed to provide guidance on how to identify multi-component new high-performance structural alloys with much less computational effort needed. It will address the extensive computation time needed for DFT on the new alloys design. In addition, it will also address the well-known headache of DFT, i.e. how to make the accurate prediction of the high-temperature equilibria. The novel hybrid model the PI proposed will not only be applied to the design of high-performance structural alloys in FE power plants but in many different applications, such as nuclear reactors. This hybrid modeling approach includes four sections: 1) HT-CALPHAD modeling of Al-Co-Cr-Ni-Fe system with FCC and BCC phase. In this section, 3561 non-equiatomic compositions were randomly generated in order to investigate the phase stability of single FCC and BCC phases. Meanwhile, we proposed a data screening procedure to screen out the good candidates within these compositions, considering the temperature range, average density, and melting temperature, etc. 2) Investigation of FCC-Cr lattice stability in Fe-Cr system. We systematically assessed the reliability of FCC-Cr lattice stability derived by DFT and CALPHAD approaches. Meanwhile, the Fe-Cr binary system was chosen as a case study to verify the Cr lattice stability obtained by both approaches. 3) High-throughput DFT modeling on elastic properties of Al-Co-Cr-Ni-Fe systems. We predicted and established the FCC quinary elastic constant database of the Al-Co-Cr-Fe-Ni systems at 0K by using special quasi-random structure (SQS) approach. The predictions will start with pure elements of Al-Co-Cr-Fe-Ni system and will be continued with binaries, ternaries, quaternaries, and finally the quinary compositions. 3) Modeling of temperature-dependent elastic properties in Al-Co-Cr-Ni-Fe systems. In this part, we predict the thermal expansion coefficient and elastic stiffness coefficient as a function of temperature by applying quasiharmonic approximation. With this approach, the elastic properties of HEAs at elevate temperature can be estimated.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Evaluation of the CAM6 Climate Model Using Cloud Observations at McMurdo Station, Antarctica

A comparative analysis between observational data from McMurdo Station, Antarctica and the Community Atmosphere Model version 6 (CAM6) simulation is performed focusing on cloud characteristics and their thermodynamic conditions. Ka-band Zenith Radar (KAZR) and High Spectral Resolution Lidar (HSRL) retrievals are used as the basis of cloud fraction and cloud phase identifications. Radiosondes released at 12-hour increments provide atmospheric profiles for evaluating the simulated thermodynamic conditions. Our findings show that the CAM6 simulation consistently overestimates (underestimates) cloud fraction above (below) 3 km in four seasons of a year. Normalized by total in-cloud samples, ice and mixed phase occurrence frequencies are underestimated and liquid phase frequency is overestimated by the model at cloud fractions above 0.6, while at cloud fractions below 0.6 ice phase frequency is overestimated and liquid-containing phase frequency is underestimated by the model. The cloud fraction biases are closely associated with concurrent biases in relative humidity (RH), i.e., high (low) RH biases above (below) 2 km. Frequencies of correctly simulating ice and liquid-containing phase increase when the absolute biases of RH decrease. Cloud fraction biases also show a positive correlation with RH biases. Water vapor mixing ratio biases are the primary contributor to RH biases, and hence, likely a key factor controlling the cloud biases. Finally, this diagnosis of the evident shortfalls of representations of cloud characteristics in CAM6 simulation at McMurdo Station brings new insight in improving the governing model physics therein.

54 ENVIRONMENTAL SCIENCES↗