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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 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Mechanical properties of zeolite-templated carbons from approximate density functional theory calculations

Zeolite-templated carbon (ZTC) is a unique porous carbonaceous material whose structure is ordered at the nanometre scale, enabling a representative periodic description at the atomistic level. Utilizing an existing, well-defined reference model for ZTCs, a structural library of varying compositions was developed by refinement using density-functional tight-binding (DFTB) potentials parameterized for materials science applications. We first determined the quantum chemical-refined structures of models with CH, CHO, CHON, CHOB, and CHOBN compositions with various degrees of heteroatom substitution. These structural models comprise the characteristic morphological features of highly porous carbon materials, such as open-blade surfaces, edges, saddles, and closed-strut formations, spanning a range of curvatures and characteristic sizes. Second, we carried out alternating compression and expansion of the CHO model unit cell to determine the lowest energy structure as well as to obtain its bulk modulus in order to demonstrate a close connection between macroscopic observations and atomic-scale structures. Further, the agreement between experimental measurements and the computational model is remarkable and demonstrates the power of approximate density functional theory as a cost-effective computational tool with chemical accuracy for the investigation of structure/property relationships in real-world carbon-based solids.

03 NATURAL GAS↗
DOE OSTI2019

“Teamwork Makes the Dream Work”: Tribal Competition Evolutionary Search as a Surrogate for Free-Energy-Based Structural Predictions

Crystal structure prediction has been a grand challenge in material science owing to the large configurational space that one must explore. Evolutionary (genetic) algorithms coupled with first principles calculations are commonly used in crystal structure prediction to sample the ground and metastable states of materials based on configurational energies. However, crystal structure predictions at finite temperature (T), pressure (P), and composition (X) require a free-energy-based search that is often computationally expensive and tedious. Here in this paper, we introduce a new machine-learning workflow for structure prediction that is based on a concept inspired by the evolution of human tribes in primitive society. Our tribal genetic algorithm (GA) combines configurational sampling with evolutionary optimization to accurately predict entropically stabilized phases at finite (T, P, X), at a computational cost that is an order of magnitude smaller than that required for a free-energy-based search. In a departure from standard GA techniques, the populations of individuals are divided into multiple tribes based on a bond-order fingerprint, and genetic operations are modified to ensure that cluster configurations are sampled adequately to capture entropic contributions. Team competition introduced into the evolutionary process allows winning teams (representing a better set of individuals) to expand their sizes; this translates into a more expanded search of the phase space allowing us to explore solutions near possible global minimum. Each team explores a specific section of the structural phase space and avoids bias on solutions arising from the use of individual populations in a purely energy-based search. We demonstrate the efficacy of our approach by performing the structural prediction of a representative two-dimensional two-body system as well as Lennard-Jones clusters over a range of temperatures up to its melting point. Our approach outperforms the standard GA approaches and enables structural search under “real nonambient conditions” on both bulk systems and finite-sized clusters.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Solving Stochastic Inverse Problems for Property–Structure Linkages Using Data-Consistent Inversion and Machine Learning

Determining process–structure–property linkages is one of the key objectives in material science, and uncertainty quantification plays a critical role in understanding both process–structure and structure–property linkages. In this work, we seek to learn a distribution of microstructure parameters that are consistent in the sense that the forward propagation of this distribution through a crystal plasticity finite element model matches a target distribution on materials properties. This stochastic inversion formulation infers a distribution of acceptable/consistent microstructures, as opposed to a deterministic solution, which expands the range of feasible designs in a probabilistic manner. Furthermore, to solve this stochastic inverse problem, we employ a recently developed uncertainty quantification framework based on push-forward probability measures, which combines techniques from measure theory and Bayes’ rule to define a unique and numerically stable solution. This approach requires making an initial prediction using an initial guess for the distribution on model inputs and solving a stochastic forward problem. To reduce the computational burden in solving both stochastic forward and stochastic inverse problems, we combine this approach with a machine learning Bayesian regression model based on Gaussian processes and demonstrate the proposed methodology on two representative case studies in structure–property linkages.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Modeling of the Kinetics of Carbonitride Precipitation Process in High-Strength Low-Alloy Steels Using Cellular Automata Method

Proposition of a cellular automata (CA) model of carbonitride precipitation to simulate image of microstructure in HSLA steels and to predict the mechanical properties is presented in the paper. CA model proved to be very efficient in modeling various phenomena in material science. Numerical modeling played an important role in development of new processing technologies taking advantage of precipitation. By modeling, we mean a mathematical description of the relation between the main process variables and the resulting material properties, based on sound physical principles. In microalloyed steels, the microalloying elements Ti, Nb and V are added in order to control their microstructure and mechanical properties. High chemical affinity of these elements for interstitials (C, N) results in precipitation of binary compound, nitrides and carbides and products of their mutual solubility—carbonitrides. The model accounts for an increase in dislocation density due to plastic deformation and predicts kinetics of precipitation as well as shape of precipitates.

36 MATERIALS SCIENCE↗
DOE OSTI2021

ACCELERATED CREEP TEST (ACT) QUALIFICATION OF CREEP RESISTANCE USING THE WCS CONSTITUTIVE MODEL AND STEPPED ISOSTRESS METHOD (SSM)

In this study, a qualification of accelerated creep-resistance of Inconel 718 is assessed using the novel Wilshire-Cano-Stewart (WCS) model and the stepped isostress method (SSM) and predictions are made to conventional creep data. Conventional creep testing (CCT) is a long-term continuous process, in fact, the ASME B&PV III requires that 10,000+ hours of experiments must be conducted to each heat for materials employed in boilers and/or pressure vessel components. This process is costly and not feasible for rapid development of new materials. As an alternative, accelerated creep testing techniques have been developed to reduce the time needed to characterize the creep resistance of materials. Most techniques are based upon the time-temperature-stress superposition principle (TTSSP) that predicts minimum-creep-strain-rate (MCSR) and stress-rupture behaviors but lack the ability to predict creep deformation and consider deformation mechanisms that occur for experiments of longer duration. The stepped isostress method (SSM) has been developed which enables the prediction of creep deformation response as well as reduce the time needed for qualification of materials. The SSM approach has been successful for polymer, polymeric composites, and recently has been introduced for metals. In this study, the WCS constitutive model, calibrated to SSM test data, qualifies the creep resistance of Inconel 718 at 750°C and predictions are compared to CCT data. The WCS model has proven to make long-term predictions for stress-rupture, minimum-creep-strain-rate (MCSR), creep deformation, and damage in metallic materials. The SSM varies stress levels after time interval adding damage to the material, which can be tracked by the WCS model. The SSM data is calibrated into the model and the WCS model generates realistic predictions of stress-rupture, MSCR, damage, and creep deformation. The calibrated material constants are used to generate predictions of stress-rupture and are post-audit validated using the National Institute of Material Science (NIMS) database. Similarly, the MCSR predictions are compared from previous studies. Finally the creep deformation predictions are compared with real data and is determined that the results are well in between the expected boundaries. Material characterization and mechanical properties can be determined at a faster rate and with a more cost-effective method. This is beneficial for multiple applications such as in additive manufacturing, composites, spacecraft, and Industrial Gas Turbines (IGT).

36 MATERIALS SCIENCE↗
DOE OSTI2020

Polyphenol-Sensitized Atomic Layer Deposition for Membrane Interface Hydrophilization

Improvements in energy-water systems will necessitate fabrication of high-performance separation membranes. To this end, interface engineering is a powerful tool for tailoring properties, and atomic layer deposition (ALD) has recently emerged as a promising and versatile approach. However, most non-polar polymeric membranes are not amenable to ALD processing due to the absence of nucleation sites. Here, a sensitization strategy for ALD-coating is presented, illustrated by membrane interface hydrophilization. Facile dip-coating with polyphenols effectively sensitizes hydrophobic polymer membranes to TiO2 ALD coating. Tannic acid-sensitized ALD-coated membranes exhibit outstanding underwater crude oil repulsion and rigorous mechanical stability through bending and rinsing tests. As a result, these membranes demonstrate outstanding crude oil-in-water separation and reusability compared to untreated membranes or those treated with ALD without polyphenol pretreatment. A possible polyphenol-sensitized ALD mechanism is proposed involving initial island nucleation followed by film intergrowth. This polyphenol sensitization strategy enriches the functionalization toolbox in material science, interface engineering, and environmental science.

36 MATERIALS SCIENCE↗
DOE OSTI2024

ToF-SIMS in material research: A view from nanoscale hydrogen detection

Hydrogen in materials has attracted tremendous interest as its incorporation leads to significant alterations in nanoscale structure, composition, and chemistry, impacting functional properties. It has also been integral to nuclear fusion reactors and is considered a future clean energy source. However, nanoscale characterization and manipulation of hydrogen in materials are challenging as only a selected few analytical techniques can readily detect hydrogen, among which time-of-flight secondary ion mass spectrometry (ToF-SIMS) is a unique and powerful one due to its excellent detection limit along with decent depth and lateral resolutions. Here, in this review, we discuss, using selected examples, how to detect and quantify hydrogen in materials by ToF-SIMS and its impact on revealing the hydrogenation/protonation-induced novel functional states in different classes of materials. In addition, we present our protocols on sample preparation and experimental conditions optimization, allowing us to achieve the best possible results. Finally, we highlight future research directions that can lead to the discovery of novel functional states and ultimately provide a deeper understanding of scientific questions in materials science.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Data Archive and Portal (DAP) Platform for Solid Phase Processing Technologies

The scale and speed of data generated by modern scientific experiments have constantly challenged the research community to store, curate, manage and optimally use it to drive scientific discoveries. In this work, we have developed a data archive and portal (DAP) platform including analytics capabilities to collect, curate, and manage data and metadata stream for solid phase processing (SPP) techniques. We successfully hosted around ~347K files of data related to processing parameters, microscopic images, and spectroscopic data related to solid phase processing. The DAP platform for SPP will establish an enduring capability to support machine learning and grow collaboration at the intersection of materials science and data science.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Artificial High-Transition Temperature Superconductors

In this work, we have used the well-understood quantum Hall (QH) stripes in high quality two-dimensional electron gases to mimic charge stripes in high transition temperature (Tc) superconductors. The science question we want to address is “Can QH stripes mimic high Tc superconductor stripes and provide a controlled experimental setup to pin-down the role of stripes in high Tc superconductivity?”. We have observed anomalous superconducting transition like behavior in GaAs double quantum well systems (DQWs) when each quantum well (QW) is tuned to the charge stripe states but with different Landau level fillings. Furthermore, we have shown that the transition like behavior is sharper in the DQWs when the two QWs are more strongly coupled. Our results suggest, for the first time, experimental evidence of the paired charge stripes model, which might lead to room-temperature superconductors that have enormously wide applications in computing, energy, and transportation industries. Advancing the science of high transition temperature superconductivity will have a profound impact in advancing energy technologies, ranging from the next generation microchips, new energy transfer grid to public transportation, and thus is important to nation’s energy security and relevant across the landscape of many mission spaces. Sandia has been a leader in materials science research and development. The proposed research takes advantage of Sandia’s state-ofthe-art MBE facilities at the Center for Integrated Nanotechnologies (CINT) and utilizes Sandia’s extensive advanced materials characterization resources. We envision a significant impact on the nation’s energy research and security challenges by investing in this research.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Synchrotron-based ambient pressure X-ray photoelectron spectroscopy of hydrogen and helium

Contrary to popular belief, it is possible to obtain X-ray photoelectron spectra for elements lighter than lithium, namely hydrogen and helium. The literature is plagued with claims of this impossibility, which holds true for lab-based X-ray sources. However, this limitation is merely technical and is related mostly to the low X-ray photoionization cross-sections of the 1s orbitals of hydrogen and helium. Here, we show that, using ambient pressure X-ray photoelectron spectroscopy (XPS), a bright-enough X-ray source allows the study of these elusive elements. This has important implications in the understanding of the limitations of one of the most useful techniques in materials science, and moreover, it potentially opens the possibility of using XPS to directly study the most abundant element in the universe.

36 MATERIALS SCIENCE↗
DOE OSTI2023

MST e-News Summer 2023

David Andersson (Materials Science in Radiation and Dynamic Extremes, MST-8) is the recipient of the 2023 American Nuclear Society (ANS) Mishima Award. The award recognizes outstanding contributions of an individual in research and development work on nuclear fuels and materials. Andersson is a staff scientist on MST-8’s Modeling of Radiation Effects team. An expert in atomistic modeling of nuclear fuels—both traditional UO 2 light water reactor fuel and advanced accident tolerant fuel concepts—he has been involved in numerous international and national multiscale simulation efforts to develop models for use in nuclear fuel performance simulations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Cryo-FIB for TEM Investigation of Soft Matter and Beam Sensitive Energy Materials

Primarily driven by structural biology, the rapid advances in cryogenic electron microscopy techniques are now being adopted and applied by materials scientists. Samples that inherently have electron transparency can be rapidly frozen (vitrified) in amorphous ice and imaged directly on a cryogenic transmission electron microscopy (cryo-TEM), however this is not the case for many important materials systems, which can consist of layered structures, embedded architectures, or be contained within a device. Cryogenic focused ion beam (cryo-FIB) lift-out procedures have recently been developed to extract intact regions and interfaces of interest, that can then be thinned to electron transparency and transferred to the cryo-TEM for characterization. Several detailed studies have been reported demonstrating the cryo-FIB lift-out procedure, however due to its relative infancy in materials science improvements are still required to ensure the technique becomes more accessible and routinely successful. Here, we review recent results on the preparation of cryo-TEM lamellae using cryo-FIB and show that the technique is broadly applicable to a range of soft matter and beam sensitive energy materials. We then present a tutorial that can guide the materials scientist through the cryo-FIB lift-out process, highlighting recent methodological advances that address the most common failure points of the technique, such as needle attachment, lift-out and transfer, and final thinning.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Cryo-FIB for TEM Investigation of Soft Matter and Beam Sensitive Energy Materials

Primarily driven by structural biology, the rapid advances in cryogenic electron microscopy techniques are now being adopted and applied by materials scientists. Samples that inherently have electron transparency can be rapidly frozen (vitrified) in amorphous ice and imaged directly on a cryogenic transmission electron microscopy (cryo-TEM), however this is not the case for many important materials systems, which can consist of layered structures, embedded architectures, or be contained within a device. Cryogenic focused ion beam (cryo-FIB) lift-out procedures have recently been developed to extract intact regions and interfaces of interest, that can then be thinned to electron transparency and transferred to the cryo-TEM for characterization. Several detailed studies have been reported demonstrating the cryo-FIB lift-out procedure, however due to its relative infancy in materials science improvements are still required to ensure the technique becomes more accessible and routinely successful. Here, we review recent results on the preparation of cryo-TEM lamellae using cryo-FIB and show that the technique is broadly applicable to a range of soft matter and beam sensitive energy materials. We then present a tutorial that can guide the materials scientist through the cryo-FIB lift-out process, highlighting recent methodological advances that address the most common failure points of the technique, such as needle attachment, lift-out and transfer, and final thinning.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Nanoindentation’s imprint on an advanced society: Toward application conditions at the extremes

Abstract As society strives for a more sustainable future, key technologies depend on advanced materials development. Nanoindentation enables highly localized nanoscale measurement of mechanical properties, crucial for optimizing the performance of functional materials. Coupled with chemical charging, variable temperatures, or high deformation speeds, it offers insights into pressing materials science challenges necessary for sustainable energy transitions. This article explores the role of nanoindentation in advancing vital next-generation technologies. Graphical abstract

36 MATERIALS SCIENCE↗
DOE OSTI2024

Effects of residual oxygen on superconducting niobium films

The integration of niobium (Nb) into emerging superconducting circuits can enhance their performance and function. However, growth of high purity Nb can be challenging due to its high reactivity with oxygen. Here, in this study, we examine the role of residual oxygen inside the growth chamber in transforming the structural, chemical, and superconducting properties of Nb films. We demonstrate that an increase in unintentional oxygen impurities lowers the superconducting critical temperature of Nb. This evolution coincides with the reduction of Nb crystal domains, which are separated by highly disordered oxygen-rich regions. Moreover, chemical analysis reveals the formation of niobium monoxide within the film during growth. These findings provide a comprehensive picture of how residual oxygen in the growth chamber can affect the properties of the Nb films. This study contributes to the materials science and engineering knowledge of superconducting Nb growth.

36 MATERIALS SCIENCE↗