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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Structural evaluation of curved stiffened composite panels fabricated using a THERM-Xsm process

The use of composites in aircraft structures is often limited by material and manufacturing costs which, for some designs and applications, are prohibitively high. To increase the frequency of application of composites in primary airframe components alternative manufacturing processes are sought that reduce cost and/or enhance structural efficiency. One alternative process involves the use of THERM-Xsm as the pressure transfer medium during autoclave curing. THERM-Xsm, a silicon-based flow able polymer which behaves like a liquid under autoclave presssure, transmits quasi-hydrostatic pressure to all contacting surfaces of the part to be cured. Once the autoclave pressure is relieved, THERM-Xsm reverts back to the powdery solid state and can be reused many times. The THERM-Xsm process to be evaluated is depicted and consists of (1) enclosing the tool and part to be cured by a set of frames that create a box, (2) pouring THERM-Xsm powder onto the part and filling the box, and (3) placing a vacuum bag over the box assembly. In this program, a separating non-porous film (Teflon) was placed between the part to be cured and THERM-Xsm powder to avoid any contamination. The use of THERM-Xsm has two significant advantages over conventional manufacturing procedures. First, it eliminates complicated hard tooling since it guarantees uniform pressure transfer and thus, good compaction at complex structural details (such as frame-stiffener intersections and corners). Second, it greatly simplifies vacuum bagging, since once the part to be cured is covered by THERM-Xsm powder, the vacuum bag need only conform to a relatively flat shape reducing significantly the number of pleats required. A program is on-going at Sikorsky Aircraft to evaluate the structural performance of complex composite fuselage structures made with this THERM-Xsm process and to quantify the impact of THERM-Xsm on manufacturing labor hours and cost. The program involves fuselage panel optimization analysis, a building block test program where structural details representative of the full-scale article are analyzed and tested, and static and fatigue test/analysis of the full-scale test articles. The main results of this program are reported.

Kassapoglou, Christos↗
DOE OSTI2024

Analyzing the impact of design factors on solar module thermomechanical durability using interpretable machine learning techniques

Solar modules in utility-scale systems are expected to maintain decades of lifetime to rival conventional energy sources. However, cyclic thermomechanical loading often degrades their long-term performance, highlighting the importance of effective design to mitigate thermal expansion mismatches between module materials. Given the complex composition of solar modules, isolating the impact of individual components on overall durability remains a challenging task. In this work, we analyze a comprehensive data set that comprises bill-of-materials (BOM) and thermal cycling power loss from 251 distinct module designs to identify the predominant design factors and their impacts on the thermomechanical durability of modules. The methodology of our analysis combines machine learning modeling (random forest) and Shapley additive explanation (SHAP) to correlate design factors with power loss and interpret the model’s decision-making. The interpretation reveals that silicon type (monocrystalline or polycrystalline), encapsulant thickness, busbar numbers, and wafer thickness predominantly influence the degradation. With lower power loss of around 0.6% on average in the SHAP analysis, monocrystalline cells present better durability than polycrystalline cells. This finding is further substantiated by statistical testing on our raw data set. The SHAP analysis also demonstrates that while thicker encapsulants lead to reduced power loss, further increasing their thickness over around 0.6 to 0.7 mm does not yield additional benefits, particularly for the front side one. In addition, other important BOM features such as the number of busbars are analyzed. This study provides a blueprint for utilizing explainable machine learning techniques in a complex material system and can potentially guide future research on optimizing the design of solar modules.

14 SOLAR ENERGY↗
DOE OSTI2023

Synchrotron X-ray diffraction analysis of constituent phases in transition joint between nickel alloy 738LC and a MnFeCoNiCu alloy

Synchrotron x-ray diffraction (XRD) analysis was performed on transition joints between a single-phase MnFeCoNiCu alloy and Ni-base Alloy 738LC to efficiently identify the constituent phases across the interface, with different levels of material intermixing generated by laser-welding with variable power. Here, the intermixing extent was quantified by postmortem energy dispersive x-ray spectroscopy mapping. Diffraction-based analyses on complex composition spaces with limited prior data present significant challenges because elemental substitution in both disordered and ordered phases is more extensive than in conventional alloy spaces, which may effectuate relatively large shifts in the observed lattice parameters that convolute the analysis. Therefore, thermodynamic simulations and crystallographic literature data were employed to construct a system-specific diffraction library of twelve prospective phases for the composition space investigated. Subsequently, for predicted disordered cubic phases, statistical hard-sphere models were established to estimate the lattice parameters and predict diffraction peak positions for inclusion in the library. The library was then employed to analyze diffraction profiles measured from the variably intermixed transition joints, with focus on accounting for both high and low-intensity peaks. 99.0 % of diffraction peaks with relative intensity greater than 0.001 were assigned to phases from the system-specific library, exemplifying rigorous peak accounting and indicating that no unexpected phases were present. Up to six of the twelve library phases were experimentally found in the transition joints. The lattice parameters predicted by the statistical hard-sphere model based upon thermodynamic simulations agree reasonably well with the measured values for the disordered FCC matrix phase.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Mesoscopic Modeling and Rapid Simulation of Incremental Changes in Epidemic Scenarios on GPUs

In simulation-based studies and analyses of epidemics, a major challenge lies in resolving the conflict between fidelity of models and the speed of their simulation. Another related challenge arises in dealing with the large number of what–if scenarios that need to be explored. Here, we describe new computational methods that together provide an approach to dealing with both challenges. A mesoscopic modeling approach is described that strikes a middle ground between macroscopic models based on coupled differential equations and microscopic models built on fine-grained behaviors at the individual entity level. The mesoscopic approach offers the ability to incorporate complex compositions of multiple layers of dynamics even while retaining the potential for aggregate behaviors at varying levels. It also is an excellent match to the accelerator-based architectures of modern computing platforms in which graphical processing units (GPUs) can be exploited for fast simulation via the parallel execution mode of single instruction multiple thread (SIMT). The challenge of simulating a large number of scenarios is addressed via a method of sharing model state and computation across a tree of what–if scenarios that are localized, incremental changes to a large base simulation. A combination of the mesoscopic modeling approach and the incremental what–if scenario tree evaluation has been implemented in the software on modern GPUs. Synthetic simulation scenarios are presented to demonstrate the computational characteristics of our approach. Results from the experiments with large population data, including USA, UK, and India, illustrate the modeling methodology and computational performance on thousands of synthetically generated what–if scenarios. Execution of our implementation scaled to 8192 GPUs of supercomputing platforms demonstrates the ability to rapidly evaluate what–if scenarios several orders of magnitude faster than the conventional methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Constructing Polymorphic Nanodomains in BaTiO 3 Films via Epitaxial Symmetry Engineering

Ferroelectric materials owning a polymorphic nanodomain structure usually exhibit colossal susceptibilities to external mechanical, electrical, and thermal stimuli, thus holding huge potential for relevant applications. Despite the success of traditional strategies by means of complex composition design, alternative simple methods such as strain engineering have been intensively sought to achieve a polymorphic nanodomain state in lead-free, simple-composition ferroelectric oxides in recent years. Here, a nanodomain configuration with morphed structural phases is realized in an epitaxial BaTiO3 film grown on a (111)-oriented SrTiO3 substrate. Using a combination of experimental and theoretical approaches, it is revealed that a threefold rotational symmetry element enforced by the epitaxial constraint along the [111] direction of BaTiO3 introduces considerable instability among intrinsic tetragonal, orthorhombic, and rhombohedral phases. Such phase degeneracy induces ultrafine ferroelectric nanodomains (1-10 nm) with low-angle domain walls, which exhibit significantly enhanced dielectric and piezoelectric responses compared to the (001)-oriented BaTiO3 film with uniaxial ferroelectricity. Therefore, the finding highlights the important role of epitaxial symmetry in domain engineering of oxide ferroelectrics and facilitates the development of dielectric capacitors and piezoelectric devices.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Deep-Learning-Enabled Crack Detection and Analysis in Commercial Lithium-Ion Battery Cathodes

We report in Li-ion batteries, the mechanical degradation initiated by micro cracks is one of the bottlenecks for enhancing the performance. Quantifying the crack formation and evolution in complex composite electrodes can provide important insights into electrochemical behaviors under prolonged and/or aggressive cycling. However, observation and interpretation of the complicated crack patterns in battery electrodes through imaging experiments are often time-consuming, labor intensive, and subjective. Herein, a deep learning-based approach is developed to extract the crack patterns from nanoscale hard X-ray holo-tomography data of a commercial 18650-type battery cathode. Efficient and effective quantification of the damage heterogeneity with automation and statistical significance is demonstrated. The crack characteristics are further associated with the active particles’ packing densities and a potentially viable architectural design is discussed for suppressing the structural degradation in an industry-relevant battery configuration.

25 ENERGY STORAGE↗
DOE OSTI2024

Strong‐Yet‐Ductile Eutectic Alloys Employing Cocoon‐Like Nanometer‐Sized Dislocation Cells

Abstract Eutectic alloys (EAs) with superior fluidity are known to be the easiest to cast into high‐quality ingots, making them the alloys of choice for making large‐sized structural parts. However, conventional EAs (CEAs) have never reached strength–ductility combinations on par with the best in other alloy categories. Via thermomechanical processing of cast Ni‐32.88wt%Fe‐9.53wt%Al CEAs, a cocoon‐like nano‐meshed (as fine as 26 nm) network of dislocations (CNN‐D) is produced via recovery annealing, through the rearrangement of cold‐work‐accumulated dislocations anchored by dense pre‐existing nanoprecipitates. In lieu of traditional plasticity mechanisms, such as TWIP and TRIP, the CNN‐D is particularly effective in eutectic lamellae with alternating phases, as it instigates nanometer‐spaced planar slip bands that not only dynamically refine the microstructure but also transmit from the FCC (face‐centered‐cubic) layers into the otherwise brittle B2 layers. These additional mechanisms for strengthening and strain hardening sustain stable tensile flow, resulting in a striking elevation of both strength and ductility to outrank not only all previous CEAs, but also the state of the art—additively manufactured eutectic high‐entropy alloys. The CNN‐D thus adds a novel microstructural strategy for performance enhancement, especially for compositionally complex alloys that increasingly make use of nanoprecipitates or local chemical order.

Chemistry↗
DOE OSTI2023

Pulsed Light Synthesis of High Entropy Nanocatalysts with Enhanced Catalytic Activity and Prolonged Stability for Oxygen Evolution Reaction

The ability to synthesize compositionally complex nanostructures rapidly is a key to high-throughput functional materials discovery. In addition to being time-consuming, a majority of conventional materials synthesis processes closely follow thermodynamics equilibria, which limit the discovery of new classes of metastable phases such as high entropy oxides (HEO). Herein, a photonic flash synthesis of HEO nanoparticles at timescales of milliseconds is demonstrated. By leveraging the abrupt heating and cooling cycles induced by a high-power-density xenon pulsed light, mixed transition metal salt precursors undergo rapid chemical transformations. Hence, nanoparticles form within milliseconds with a strong affinity to bind to the carbon substrate. Oxygen evolution reaction (OER) activity measurements of the synthesized nanoparticles demonstrate two orders of magnitude prolonged stability at high current densities, without noticeable decay in performance, compared to commercial IrO 2 catalyst. This superior catalytic activity originates from the synergistic effect of different alloying elements mixed at a high entropic state. It is found that Cr addition influences surface activity the most by promoting higher oxidation states, favoring optimal interaction with OER intermediates. The proposed high-throughput method opens new pathways toward developing next-generation functional materials for various electronics, sensing, and environmental applications, in addition to renewable energy conversion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Non‐Equilibrium Synthesis Methods to Create Metastable and High‐Entropy Nanomaterials

Stabilizing multiple elements within a single phase enables the creation of advanced materials with exceptional properties arising from their complex composition. However, under equilibrium conditions, the Hume–Rothery rules impose strict limitations on solid-state miscibility, restricting combinations of elements with mismatched crystal structures, atomic radii, valence states, or electronegativities. This severely narrows the accessible compositional space for creating new inorganic materials. In this review, we highlight how non-equilibrium synthesis methods, featuring ultrafast heating and quenching, can overcome these thermodynamic barriers, enabling integration of immiscible elements into metastable and high-entropy nanostructures. The resulting materials benefit from both kinetic trapping and stabilization by high configurational entropy, leading to enhanced phase stability. These materials can exhibit unique structural and functional properties that are needed for advancing catalysis, energy storage, thermoelectrics, and sensing. Furthermore, the ability of non-equilibrium methods to generate unconventional compositions and structures expands the material design space dramatically, offering rich datasets for AI-guided materials discovery. When combined with their inherent high-throughput and scalable characteristics, these approaches enable rapid, iterative optimization and accelerate the development and industrial production of next-generation inorganic materials.

high-entropy materials↗
DOE OSTI2025

Refining T c Prediction in Hydrides via Symbolic‐Regression‐Enhanced Electron‐Localization‐Function‐Based Descriptors

Hydrogen‐based materials are able to possess extremely high superconducting critical temperatures, T c s , due to hydrogen's low atomic mass and strong electron–phonon interaction. Recently, a descriptor based on the Electron Localization Function (ELF) has enabled the rapid estimation of the T c of hydrogen‐containing compounds from electronic networking properties, but its applicability has been limited by the small size and homogeneity of the training dataset used. Herein, the model is re‐examined, compiling a publicly available combined dataset of 244 binary and ternary hydride superconductors. The analysis shows that though ELF‐based networking remains a valuable descriptor, its predictive power declines with increasing compositional complexity. However, by introducing the molecularity index, defined as the highest value of the ELF at which two hydrogen atoms connect, and applying symbolic regression, the accuracy of the predictions can be substantially enhanced. These results establish a more robust framework for assessing superconductivity in hydride materials, facilitating accelerated screening of novel candidates through integration with crystal structure prediction methods or high‐throughput searches.

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

Mosaic Cu I –Cu II –In III 2D Perovskites: Pressure–Dependence of the Intervalence Charge Transfer and a Mechanochemical Alloying Method

The perovskite (BA) 4 [Cu II (Cu I In III ) 0.5 ]Cl 8 (1 BA ; BA + =butylammonium) allows us to study the high-pressure structural, optical, and transport properties of a mixed-valence 2D perovskite. Compressing 1 BA reduces the onset energy of Cu I/II intervalence charge transfer from 1.2 eV at ambient pressure to 0.2 eV at 21 GPa. The electronic conductivity of 1 BA increases by 4 orders of magnitude upon compression to 20 GPa, when the activation energy for conduction decreases to 0.16 eV. In contrast, Cu II perovskites achieve similar conductivity at ≈50 GPa. The solution-state synthesis of these perovskites is complicated, with more undesirable side products likely from the precursor mixtures containing three different metal ions. Finally, to circumvent this problem, we demonstrate an efficient mechanochemical synthesis to expand this family of halide perovskites with complex composition by simply pulverizing together powders of 2D Cu II single perovskites and Cu I In III double perovskites.

2D perovskite↗
DOE OSTI2023

Mosaic Cu I −Cu II −In III 2D Perovskites: Pressure‐Dependence of the Intervalence Charge Transfer and a Mechanochemical Alloying Method

Abstract The perovskite (BA) 4 [Cu II (Cu I In III ) 0.5 ]Cl 8 ( 1 BA ; BA + =butylammonium) allows us to study the high‐pressure structural, optical, and transport properties of a mixed‐valence 2D perovskite. Compressing 1 BA reduces the onset energy of Cu I/II intervalence charge transfer from 1.2 eV at ambient pressure to 0.2 eV at 21 GPa. The electronic conductivity of 1 BA increases by 4 orders of magnitude upon compression to 20 GPa, when the activation energy for conduction decreases to 0.16 eV. In contrast, Cu II perovskites achieve similar conductivity at ≈50 GPa. The solution‐state synthesis of these perovskites is complicated, with more undesirable side products likely from the precursor mixtures containing three different metal ions. To circumvent this problem, we demonstrate an efficient mechanochemical synthesis to expand this family of halide perovskites with complex composition by simply pulverizing together powders of 2D Cu II single perovskites and Cu I In III double perovskites.

Li, Jiayi↗
DOE OSTI2025

Visualizing and analyzing 3D biomolecular structures using Mol* at RCSB.org: Influenza A H5N1 virus proteome case study

The easiest and often most useful way to work with experimentally determined or computationally predicted structures of biomolecules is by viewing their three-dimensional (3D) shapes using a molecular visualization tool. Mol* was collaboratively developed by RCSB Protein Data Bank (RCSB PDB, RCSB.org) and Protein Data Bank in Europe (PDBe, PDBe.org) as an open-source, web-based, 3D visualization software suite for examination and analyses of biostructures. It is capable of displaying atomic coordinates and related experimental data of biomolecular structures together with a variety of annotations, facilitating basic and applied research, training, education, and information dissemination. Across RCSB.org, the RCSB PDB research-focused web portal, Mol* has been implemented to support single-mouse-click atomic-level visualization of biomolecules (e.g., proteins, nucleic acids, carbohydrates) with bound cofactors, small-molecule ligands, ions, water molecules, or other macromolecules. RCSB.org Mol* can seamlessly display 3D structures from various sources, allowing structure interrogation, superimposition, and comparison. Using influenza A H5N1 virus as a topical case study of an important pathogen, we exemplify how Mol* has been embedded within various RCSB.org tools—allowing users to view polymer sequence and structure-based annotations integrated from trusted bioinformatics data resources, assess patterns and trends in groups of structures, and view structures of any size and compositional complexity. In addition to being linked to every experimentally determined biostructure and Computed Structure Model made available at RCSB.org, Standalone Mol* is freely available for visualizing any atomic-level or multi-scale biostructure at rcsb.org/3d-view.

3D biostructure↗
DOE OSTI2023

How Atomic Bonding Plays the Hardness Behavior in the Al–Co–Cr–Cu–Fe–Ni High Entropy Family

A systematic study on a face-centered cubic-based compositionally complex alloy system Al–Co–Cr–Cu–Fe–Ni in its single-phase state is carried out, where a mother senary compound Al 8 Co 17 Cr 17 Cu 8 Fe 17 Ni 33 and five of its suballoys, obtained by removing one element at a time, are investigated and exhaustively analyzed determining the contribution of each alloying element in the solid solution. The senary and the quinaries are compared using experimental techniques including X-ray absorption spectroscopy, X-ray diffraction, transmission electron microscopy, and first principles hybrid Monte Carlo/molecular dynamics simulations. Chemical short-range order and bond length distances have been determined both at the experimental and computational level. Electronic structure and local atomic distortions up to 5.2 Å have been correlated to the microhardness values. A linear regression model connecting hardness with local lattice distortions is presented.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Using defects as a ‘fossil record’ to help interpret complex processes during additive manufacturing: as applied to raster-scanned electron beam powder bed additively manufactured Ti–6Al–4V

Abstract Defects in parts produced by additive manufacturing, instead of simply being perceived as deleterious, can act as important sources of information associated with the complex physical processes that occur during materials deposition and subsequent thermal cycles. Indeed, they act as materials-state ‘fossil’ records of the dynamic AM process. The approach of using defects as epoch-like records of prior history has been developed while studying additively manufactured Ti–6Al–4V and has given new insights into processes that may otherwise remain either obscured or unquantified. Analogous to ‘epochs,’ the evolution of these defects often is characterized by physics that span across a temporal length scale. To demonstrate this approach, a broad range of analyses including optical and electron microscopy, X-ray computed tomography, energy-dispersive spectroscopy, and electron backscatter diffraction have been used to characterize a raster-scanned electron beam Ti–6Al–4V sample. These analysis techniques provide key characteristics of defects such as their morphology, location within the part, complex compositional fields interacting with the defects, and structures on the free surfaces of defects. Observed defects have been classified as banding, spherical porosity, and lack of fusion. Banding is directly related to preferential evaporation of Al, which has an influence on mechanical properties. Lack-of-fusion defects can be used to understand columnar grain growth, fluid flow of melt pools, humping, and spattering events. Graphical abstract

36 MATERIALS SCIENCE↗
DOE OSTI2021

Structural and chemical disorder enhance point defect diffusion and atomic transport in Ni 3 Al-based γ' phase

The ordered L1 2 γ' Ni 3 Al intermetallic inclusions are routinely used as strengthening constituents in Ni-based superalloys and recent high-entropy alloys. As there are different metallic elements relative to the alloy matrix, the composition of γ' phase inclusions usually suffers some variations. In this work, we studied the elemental partition and its influence on atomic transport properties in a model (NiCo) 3 Al γ' phase with chemical and structural disorder. Combining the Monte Carlo and molecular static techniques, we first determined the elemental distribution in such compositionally-complexed γ' phase. The results suggest that Co tends to segregate, which profoundly influences defect energetics and diffusion properties. By modeling thermally activated diffusion by molecular dynamics, we found that chemical disorder induced by Co can enhance vacancy diffusion while significantly suppress diffusion via interstitial atom migration, as compared to the stoichiometric γ' Ni 3 Al. We further reveal that these observations are closely related to the defect energetics in these systems. Furthermore, our results explain the effects of disorder, long- and short-range orders on the diffusion properties in multicomponent intermetallic alloys, which helps to understand the stability and, thus, γ'-phase-assisted strengthening at different conditions including annealing and irradiation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Phase transformation dynamics guided alloy development for additive manufacturing

Fusion-based additive manufacturing technologies enable the fabrication of geometrically and compositionally complex parts unachievable by conventional manufacturing methods. However, the non-uniform and far-from-equilibrium heating/cooling conditions pose a significant challenge to consistently obtaining desirable phases in the as-printed parts. Here, in this study, we report a martensite stainless steel development guided by phase transformation dynamics revealed by in-situ high-speed, high-energy, high-resolution X-ray diffraction. This developed stainless steel consistently forms desired fully martensitic structure across a wide range of cooling rates (10 2 –10 7 °C/s), which enables direct printing of parts with fully martensitic structure. The as-printed material exhibits a yield strength of 1157 ± 23 MPa, comparable to its wrought counterpart after precipitation-hardening heat-treatment. The as-printed property is attributed to the fully martensitic structure and the fine precipitates formed during the intrinsic heat treatment in additive manufacturing. The phase transformation dynamics guided alloy development strategy demonstrated here opens the path for developing reliable, high-performance alloys specific for additive manufacturing.

17–4 PH stainless steel↗
DOE OSTI2024

Assessment of two benzylation strategies for the analysis of nerve-agent derived ethyl- and pinacolyl methyl phosphonic acids in sandy loam soil by GC–MS

Despite their prohibition by the Chemical Weapons Convention, nerve agents (NAs) remain in use against military and civilian targets. Due to their high reactivity, NAs readily degrade to phosphonic acids, making them important markers in the inspection of areas of presumed NA use. In this work, we assess the use of benzylation to modify ethyl- and pinacolyl methylphosphonic acids, degradation products of VX and Soman respectively, for their efficient detection in a soil matrix at ~10 and ~1 μg/g using GC–MS. The soil matrix, Sandy Loam (SL), was chosen for its ubiquitous nature, complex composition with silica particles embedded in clay, and low organic content. In this study, we demonstrate that benzylation via benzyl bromide yields a LOD = 25.6 ng/mL for benzylated-EMPA and LOD = 30.1 ng/mL for benzylated-PMPA. This is superior to the use of p-methoxybenzyl trichloroacetimidate in providing stable phosphonic acid ester derivatives for analysis. A base-modified procedure for p-methoxybenzylation was explored in this study yielding a LOD = 29.1 ng/mL for p-methoxybenzylated-EMPA and LOD = 39.8 ng/mL for p-methoxybenzylated-PMPA. Both benzylation pathways (benzyl bromide and p-methoxybenzyl trichloroacetimidate) can be used to yield phosphonic acid derivatives that provide further confirmation of these Soman and VX degradation products in soil samples in investigative scenarios. The work herein represents the first application of benzylation methods for the analysis of these NA markers in the acidic, silicon-based SL soil.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗