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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Implementation of disruptive designs for gas turbine components using direct energy deposition additive manufacturing

This research aims to develop a framework for establishing the correlation between in-situ monitoring data, process parameters, and microstructure evolution in blown-powder laser-directed energy deposition (DED) additive manufacturing (AM). To achieve this, a comprehensive manufacturing framework has been developed, spanning from in-situ data acquisition, melt-pool simulation, microstructure modeling, and statistical microstructure quantification. A machine learning-based surrogate model is constructed to predict melt pool geometry directly from in-situ coaxial camera data. The surrogate model is trained using outputs from a high-fidelity melt pool simulation, which provides accurate melt pool dimension data under varying process conditions. The predicted melt pool geometry is then used as input to a microstructure model to predict microstructural features. To rigorously compare and analyze microstructures, the project introduces statistical metrics that quantify differences based on key features such as morphology and texture. Microstructures are represented using advanced statistical descriptors including angular chord length distribution, two-point spatial statistics, orientation distribution function, and global spherical harmonic. These representations are used to compute four distinct “dissimilarity scores” that quantitatively capture differences in texture and morphology. This framework is demonstrated to enable automated calibration of simulation parameters by minimizing discrepancies between simulated and target microstructures. The technology developed in this project enables direct correlation between in-situ monitoring data and resulting microstructure, paving the way for adaptive microstructure control in metal AM. This capability strengthens the connection between process parameters and final material properties, facilitating more precise and reliable material design.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Experimental Studies and Energy Modeling for Evaluating Performance of Various Deep Wall Retrofits

The Pacific Northwest National Laboratory, Oak Ridge National Laboratory, and the University of Minnesota conducted a three-year, multipart study on residential retrofit wall assemblies. The project, which was funded by the U.S. Department of Energy’s Building Technology Office, aimed to compare a range of residential wall retrofit systems that prioritized affordability, durability, and energy savings potential. The research team identified, constructed, tested, simulated, and analyzed the feasibility and economics of 16 wall retrofit assemblies (14 test configurations and two baseline configurations) that can be applied to the exterior side of existing walls (either with or without the existing cladding). The 16 wall assemblies were installed in an in-situ laboratory environment, to evaluate the ease of construction and study the thermal and hygrothermal performance of the walls. This paper presents the methodology used to evaluate the thermal performance of the walls and discusses the energy modeling results of the study. The results from the experiments were used to calibrate a THERM model of each wall assembly, which was then applied to a whole building using the EnergyPlus 8.6 simulation engine. A residential prototype building was used to extrapolate whole-building energy savings in each U.S. climate zone. To capture the conditions of the largest number of homes in the United States, the most frequent building characteristics (e.g., attic insulation level, window specifications, foundation insulation, etc.) were extracted from ResStock data and applied to the prototype model. Results from the energy modeling showed that the climate zones with the highest potential for retrofit savings are those which are heating-dominated (i.e., Cold and Very Cold climate designations). In these climate zones, heating and cooling energy savings due to the wall retrofits alone ranged from 21.5% to 38.2%.

Nagda, Harshil↗
DOE OSTI2020

Characterizing material transitions in large-scale Additive Manufacturing

Integrating Multiple Materials (MM) into large-scale Additive Manufacturing (AM) is a key for various industrial applications wishing to incorporate site-specific properties into geometrically complex designs that are difficult to manufacture with traditional techniques. Printing with multiple materials is typically accomplished by using layers as natural material boundaries, but having the capability to switch between materials within a single layer without pausing would further expand MM possibilities. This study used Cincinnati Incorporated’s Big Area Additive Manufacturing (BAAM) system to explore material transitions with a novel dual-hopper that enables in-situ material blending of a pelletized feedstock. Constructing MM and functionally graded material (FGM) structures requires depositing a specific material composition at a specific geometric location to achieve a desired performance. Furthermore, accurately implementing this with the BAAM’s blended extrusion system requires a thorough understanding of the transition between distinct material compositions. This study characterizes a step-change transition between neat acrylonitrile butadiene styrene (ABS) and carbon fiber-reinforced ABS. Three distinct techniques were compared for analyzing the fiber content, and the transition zone between materials was characterized as a function of transition direction. The transition process was consistent to within 0.7 wt% carbon fiber variation between different layers and prints. The transition between materials was found to be directionally dependent, with ABS to CF/ABS having a transition length of 3.5 m compared to 3.2 m for CF/ABS to ABS. Furthermore, the transition from Material A to Material B was found to be repeatable with a possible variance in transition length of 0.3 m.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Sea Surface Salinity Reemergence in an Updated North Atlantic In Situ Salinity Dataset

Monthly sea surface salinity (SSS) fields are constructed from observations, using objective mapping on a 1° x 1° grid in the Atlantic between 30°S and 50°N in the 1970-2016 period in an update of the dataset of Reverdin et al. Data coverage is heterogeneous, with increased density in 2002 when Argo floats become available, high density along Voluntary Observing Ship lines, and low density south of 10°S. Using lag correlation, the seasonal reemergence of SSS anomalies is investigated between 20° and 50°N in 5° x 5° boxes during the 1993-2016 period, both locally and remotely following the displacements of the deep mixed-layer waters estimated from virtual float trajectories derived from the daily AVISO surface geostrophic currents. Although SSS data are noisy, local SSS reemergence is detected in about half of the boxes, notably in the northeast and southeast, while little reemergence is seen in the central and part of the eastern subtropical gyre. In the same period, sea surface temperature (SST) reemergence is found only slightly more frequently, reflecting the short data duration. However, taking geostrophic advection into account degrades the detection of remote SSS and even SST reemergence. When anomalies are averaged over broader areas, robust evidence of a second and third SSS reemergence peak is found in the northeastern and southeastern parts of the domain, indicating long cold-season persistence of large-scale SSS anomalies, while only a first SST reemergence is seen. Finally, an oceanic reanalysis is used to confirm that the correlation analysis indeed reflects the reemergence of subsurface salinity anomalies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

In-situ effect in cross-ply laminates under various loading conditions analyzed with hybrid macro/micro-scale computational models

In this article, multi-scale finite element analyses based on three-dimensional (3D) hybrid macro/micro-scale computational models subjected to various loading conditions are carried out to examine the in-situ effect imposed by the neighboring plies on the failure initiation and propagation of cross-ply laminates. A detailed comparative study on crack suppression mechanisms due to the effect of embedded laminar thickness and adjacent ply orientation is presented. Furthermore, we compare the results of in-situ transverse failure strain and strength between the computational models and analytical predictions. Good agreements are generally observed, indicating the constructed computational models are highly accurate to quantify the in-situ effect. Subsequently, empirical formulas for calculating the in-situ strengths as a function of embedded ply thickness and different ply angle between embedded and adjacent plies are developed, during which several material parameters are obtained using a reverse fitting method. Finally, a new set of failure criteria for σ 22 -τ 12 , σ 22 -τ 23 , and σ 11 -τ 12 accounting for the in-situ strengths are proposed to predict laminated composites failure under multi-axial stress states. This study demonstrates an effective and efficient computational technique towards the accurate prediction of the failure behaviors and strengths of cross-ply laminates by including the in-situ effects.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Extrusion parameter control optimization for DIW 3D printing using image analysis techniques

Material extrusion is a well-recognized facet of additive manufacturing that involves the fabrication of parts through the deposition of structural material from an extrusion head from a bulk supply. In the subdivision of Direct Ink Writing (DIW) additive manufacturing, challenges arise when the structural material is flowable, synchronous extrusion control and tool movement becomes critical for achieving high-quality parts with low defect populations. DIW techniques are most used in laboratory settings using expensive custom instruments and may require specialized 3D slicing software. Here, in this study, the fabrication of an inexpensive, consumer-friendly progressive cavity pump dispensing system is detailed, in which can create high-quality parts by executing G-code commands produced from a commercial slicing software. The precision and repeatability of the movement-synchronized material extrusion is demonstrated through a series of optimization schemes, entailing the alteration of various control parameters, which directly affect the extrusion properties demonstrated during a print. In situ diagnostics were implemented to evaluate the results of the established optimization experiment. Using a machine vision technique, images of the optimization prints are processed. Following this, a supervised machine learning model was trained to autonomously judge whether or not the extrusion parameters produced a passing or failing result. The machine learning scheme serves as a preliminary benchmark for future layer-by-layer evaluation of more complex DIW parts. The construction of the printer and development of in situ characterization capabilities demonstrates the ability for this printer to create high-fidelity DIW parts for a fraction of the price of other systems.

42 ENGINEERING↗
DOE OSTI2024

Adsorbate-induced adatom formation on Au-Cu bimetallic alloys and its possible consequences for CO 2 electroreduction

The adsorbate-induced formation of sub-nanometer clusters on transition-metal single crystals observed in previous high-pressure microscopic studies hinted at the in-situ formation of unique active sites even on large nanoparticle catalysts. We propose that the adatom formation energy can be used as an energetic descriptor for the initial step toward the adsorbate-induced metal-cluster formation process. This descriptor can be efficiently computed using density functional theory (DFT) calculations and applied for screening and identification of metal catalysts where this phenomenon may play an important role in generating active sites in-situ. As a proof of concept, here, we construct an adatom formation energy database for three Au x Cu y alloys (x:y = 3:1, 1:1, or 1:3) and eighteen adsorbates (H, C, N, O, F, S, Cl, Br, I, CH x , NH x (x = 1 – 3), CO, NO, and OH) commonly involved in catalytic reactions. The energetics of adatom formation were examined in all cases where the (111) terrace, (211) step-edge, and (874) kink were the sources of the adatom. We demonstrate that the presence of an adsorbate could alter not only the energetics for adatom formation but also the elemental nature of the preferred adatom being formed. Using our database, we identified promising systems which favor adsorbate-induced adatom formation under near-ambient conditions. Specifically, CO-induced adatom formation on all three Au-Cu alloy surfaces could occur under CO 2 electroreduction (CO 2 RR) conditions. This phenomenon offers a qualitative explanation for the experimentally observed CO 2 RR activity on Au-Cu alloy catalysts. As a result, our methodology offers an easily expandable and efficient approach for large-scale catalyst screening with regards to adatom/cluster formation under reaction conditions and provides insight into the possible nature of active sites on alloy catalysts from a novel perspective.

Active site↗
DOE OSTI2021

Self-regeneration of supported transition metals by a high entropy-driven principle

The sintering of Supported Transition Metal Catalysts (STMCs) is a core issue during high temperature catalysis. Perovskite oxides as host matrix for STMCs are proven to be sintering-resistance, leading to a family of self-regenerative materials. However, none other design principles for self-regenerative catalysts were put forward since 2002, which cannot satisfy diverse catalytic processes. Herein, inspired by the principle of high entropy-stabilized structure, a concept whether entropy driving force could promote the self-regeneration process is proposed. To verify it, a high entropy cubic Zr 0.5 (NiFeCuMnCo) 0.5 O x is constructed as a host model, and interestingly in situ reversible exsolution-dissolution of supported metallic species are observed in multi redox cycles. Notably, in situ exsolved transition metals from high entropy Zr 0.5 (NiFeCuMnCo) 0.5 O x support, whose entropic contribution (TΔS config = T$\star$12.7 J mol -1 K -1 ) is predominant in ΔG, affording ultrahigh thermal stability in long-term CO 2 hydrogenation (400 °C, >500 h). Current theory may inspire more STWCs with excellent sintering-resistance performance.

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

Mechanistic insight of KBiQ 2 (Q = S, Se) using panoramic synthesis towards synthesis-by-design

Solid-state synthesis has historically focused on reactants and end products; however, knowledge of reaction pathways, intermediate phases and their formation may provide mechanistic insight of solid-state reactions. With an increased understanding of reaction progressions, design principles can be deduced, affording more predictive power in materials synthesis. In pursuit of this goal, in situ powder X-ray diffraction is employed to observe crystalline phase evolution over the course of the reaction, thereby constructing a “panoramic” view of the reaction from beginning to end. We conducted in situ diffraction studies in the K–Bi–Q (Q = S, Se) system to understand the formation of phases occurring in this system in the course of their reactions. Powder mixtures of K 2 Q to Bi 2 Q 3 in 1:1 and 1.5:1 ratios were heated to 800 °C or 650 °C, while simultaneously collecting diffraction data. Three new phases, K 3 BiS 3 , β-KBiS 2 , and β-KBiSe 2 , were discovered. Panoramic synthesis showed that K 3 BiQ 3 serves an important mechanistic role as a structural intermediate in both chalcogen systems (Q = S, Se) in the path to form the KBiQ 2 structure. Thermal analysis and calculations at the density functional theory (DFT) level show that the cation-ordered β-KBiQ 2 polymorphs are the thermodynamically stable phase in this compositional space, while Pair Distribution Function (PDF) analysis shows that all α-KBiQ 2 structures have local disorder due to stereochemically active lone pair expression of the bismuth atoms. The formation of the β-KBiQ 2 structures, both of which crystallize in the α-NaFeO 2 structure type, show a boundary where the structure can be disordered or ordered with regards to the alkali metal and bismuth. A cation radius tolerance for six-coordinate cation site sharing of ($\frac{r^+}{r^{3+}}$) ~ 1.3 is proposed. The mechanistic insight the panoramic synthesis technique provides in the K–Bi–Q system is progress towards the overarching goal of synthesis-by-design.

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

All solid thick oxide cathodes based on low temperature sintering for high energy solid batteries

Solid-state batteries (SSBs) could significantly improve the safety and energy density over conventional liquid cells. One key enabling technology is the use of solid electrolytes. NASICON-type Li 1.3 Al 0.3 Ti 1.7 (PO 4 ) 3 (LATP) is a very attractive solid-state electrolyte for the cathode side due to its high oxidation potential and high ionic conductivity. The usage, however, is limited by its large interfacial resistance against most of the cathode materials as well as the thermodynamic instability during high temperature sintering needed to achieve high mass density. Here we construct thin, percolative, and mixed conductive interphases through in situ low-melting-point liquid sintering. These mixed conductive interphases drastically improve the kinetics, leading to high-loading solid LATP/LiCoO 2 cathodes achieving capacity loading of up to ~6 mA h cm –2 . The technique is also applicable to Ni-rich cathode materials, achieving up to ~10 mAh cm –2 , which can lead to more than 400 W h kg –1 cells in SSBs. Furthermore, our composite cathodes show a ten-times and three-times area capacity improvement over the state-of-the-art cathodes using oxide and sulfide SSEs, respectively.

25 ENERGY STORAGE↗
DOE OSTI2021

Role of Polysulfide Anions in Solid-Electrolyte Interphase Formation at the Lithium Metal Surface in Li–S Batteries

Delineating intricate interactions between highly reactive Li-metal electrodes and the diverse constituents of battery electrolytes has been a long-standing scientific challenge in materials design for advanced energy storage devices. Here, we isolated lithium polysulfide anions (LiS 4 - ) from an electrolyte solution based on their mass-to-charge ratio and deposited them on Li-metal electrodes under clean vacuum conditions using ion soft landing (ISL), a highly controlled interface preparation technique. The molecular level precision in the construction of these model interfaces with ISL, coupled with in situ x-ray photoelectron spectroscopy and ab initio theoretical calculations, allowed us to obtain unprecedented insight into the parasitic reactions of well-defined polysulfides on Li-metal electrodes. Our study reveals that the oxide-rich surface layer, which is amenable to direct electron exchange, drives multielectron sulfur oxidation (S o → S 6+ ) processes. Furthermore, our results have substantial implications for the rational design of future Li-S batteries with improved efficiency and durability.

25 ENERGY STORAGE↗
DOE OSTI2025

Online learning of quadratic manifolds from streaming data for nonlinear dimensionality reduction and nonlinear model reduction

Here, this work introduces an online greedy method for constructing quadratic manifolds from streaming data, designed to enable in situ analysis of numerical simulation data on the Petabyte scale. Unlike traditional batch methods, which require all data to be available upfront and take multiple passes over the data, the proposed online greedy method incrementally updates quadratic manifolds in one pass as data points are received, eliminating the need for expensive disk input/output operations as well as storing and loading data points once they have been processed. A range of numerical examples demonstrate that the online greedy method learns accurate quadratic manifold embeddings while being capable of processing data that far exceed common disk input/output capabilities and volumes as well as main-memory sizes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

EGS Stimulation Design with Uncertainty Quantification at the EGS Collab Site

Engineering a robust hydraulic connection between wells is one of the most difficult aspects of enhanced geothermal systems (EGS). Designing and constructing such hydraulic connections requires and understanding of the in situ state of stress and the heterogeneities and discontinuities that naturally exist and may control the stimulation. Even with comprehensive stress and formation characterization programs substantial uncertainty remains in these key parameters. This is especially the case in high-temperature EGS environments where drilling conditions are often difficult and a far fewer logging and testing options are available. This paper presents a new approach for explicitly quantifying the uncertainties in the state of stress using a Bayesian Markov Chain Monte Carlo method. This approach produces a probability distribution for the stress tensor, including a general 3D orientation, that reflects the uncertainties in all the observations or indicators used to constrain the stress state. This method is demonstrated on the characterization data for the EGS Collab Experiment 2 site. The output of the analysis is used to guide the design of the planned stimulations. In the case of research projects like EGS Collab, explicitly quantifying the uncertainties in the stress state allow for more rigorous hypothesis testing by allowing conclusions drawn from the experiments to be interpreted in the context of the uncertain knowledge about conditions in the test bed.

Burghardt, Jeffrey A.↗
DOE OSTI2020

Real-Time Defect Correction in Large-Scale Polymer Additive Manufacturing via Thermal Imaging and Laser Profilometer

Defects can result in a failed part and are costly in terms of time and material. This cost is even greater in the context of large-scale additive manufacturing where the objects can be very large. As a result, a great deal of research has focused on defect identification and mitigation. To address defects during object construction, researchers at Oak Ridge National Laboratory’s Manufacturing Demonstration Facility investigated an in-situ control system comprised of two sensors: a thermal camera and laser profilometer. This control system adjusted material flow and build speed to mitigate three types of defects: low layer times, underfill, and overfill. Several test objects were constructed. The control system was found to adjust build parameters to handle low layer times of approximately 15 seconds and height deviations from -100% underfill (the absence of a layer) to 50% overfill. Within two layers, height deviations could be returned to within 10% of the expected layer height. Further, preliminary results suggest the system can compensate for uneven build surfaces.

Borish, Michael↗
DOE OSTI2021

Evaluation of precipitation indices in suites of dynamically and statistically downscaled regional climate models over Florida

Abstract The present work evaluates historical precipitation and its indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) in suites of dynamically and statistically downscaled regional climate models (RCMs) against NOAA’s Global Historical Climatology Network Daily (GHCN-Daily) dataset over Florida. The models examined here are: (1) nested RCMs involved in the North American CORDEX (NA-CORDEX) program, (2) variable resolution Community Earth System Models (VR-CESM), (3) Coupled Model Intercomparison Project phase 5 (CMIP5) models statistically downscaled using localized constructed analogs (LOCA) technique. To quantify observational uncertainty, three in situ-based (PRISM, Livneh, CPC) and three reanalysis (ERA5, MERRA2, NARR) datasets are also evaluated against the station data. The reanalyses and dynamically downscaled RCMs generally underestimate the magnitude of the monthly precipitation and the frequency of the extreme rainfall in summer. The models forced with CanESM2 miss the phase of the seasonality of extreme precipitation. All models and reanalyses severely underestimate both the mean and interannual variability of mean wet-day precipitation (SDII), consecutive dry days (CDD), and overestimate consecutive wet days (CWD). Metric analysis suggests large uncertainty across NA-CORDEX models. Both the LOCA and VR-CESM models perform better than the majority of models. Overall, RegCM4 and WRF models perform poorer than the median model performance. The performance uncertainty across models is comparable to that in the reanalyses. Specifically, NARR performs poorer than the median model performance in simulating the mean indices and MERRA2 performs worse than the majority of models in capturing the interannual variability of the indices.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Atomistic Origins of Reversible Noncatalytic Gas–Solid Interfacial Reactions

Noncatalytic gas-solid reactions are a large group of heterogeneous reactions that are usually assumed to occur irreversibly because of the strong driving force to favor the forward direction toward the product formation. Using the example of Ni oxidation into NiO with CO 2 , herein we demonstrate the existence of the reverse element that results in the NiO reduction from the countering effect of the gaseous product of CO. Using in-situ electron microscopy observations and atomistic modeling, we show that the oxidation process occurs via preferential CO 2 adsorption along step edges that results in step-flow growth of NiO layers, and the presence of Ni atoms on the flat NiO surface promotes the nucleation of NiO layers. Simultaneously, the NiO reduction happens via preferential step-edge adsorption of CO that leads to the receding motion of atomic steps, and the presence of Ni vacancies in the NiO surface facilitates the CO adsorption induced surface pitting. Based on the in-situ TEM observations, temperature and CO 2 pressure effect maps are constructed to illustrate the spatiotemporal dynamics of the competing NiO redox reactions. We report, these results demonstrate the rich gas-solid surface reaction dynamics induced by the co-existing forward and reverse reaction elements and have practical applicability in manipulating gas-solid reactions via controlling the gas environment or atomic structure of the solid surface to steer the reaction toward the desired direction.

25 ENERGY STORAGE↗
DOE OSTI2021

Towards Trustworthy and Interpretable Deep Learning-assisted Ecohydrological Models

The transformational science question we plan to address is: How do we leverage in-situ observations and simulations from process-based ecohydrological model to construct interpretable and trustworthy deep learning (DL) models for improved reliability of prediction of quantities of interest (QoIs) under hydro-climatic extremes?

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

In situ detection and characterization of alkali-silica reaction damage in concrete using contactless ultrasonic wavefield imaging

Here we present work to characterize cracking damage in concrete caused by alkali-silica reactivity distress. We apply contactless ultrasonic scan inspection, exploiting Rayleigh wave scattering from concrete inhomogeneities. The scanning system utilizes a multi-channel MEMS sensor array to collect ultrasonic wavefield data from concrete subjected to ASR-promoting environments. The location and extent of ASR damage are established by internal expansion measurements from embedded strain gauges, scanning electron microscope images of cored samples, and expansion measurements from companion samples. A wavefield data processing method extracts oscillatory fields from the ultrasonic wavefield data to detect distinct zones of ASR damage. A damage index is proposed to further characterize the extent of ASR damage. The results confirm the feasibility and accuracy of the approach to characterize ASR damage in concrete. The fully contactless ultrasonic scanning measurement system does not require separate material samples and enables in situ characterization of ASR damage within concrete structures.

36 MATERIALS SCIENCE↗