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Results for “structure-property relationship”

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 OSTI2024

Growth of Well-Defined Model Catalysts for Electrochemistry: From Surface Science Studies to Electrocatalytic CO2 Conversion

We combined ultrahigh vacuum (UHV) surface science techniques, electrochemical measurements, and computational modeling to investigate electrocatalytic systems that are crucial components of the carbon management effort, including oxygen evolution reactions (OER) and CO2 reduction reactions (CO2RR). Well-defined Model catalysts were grown on substrates in the UHV chamber and characterized with X-ray photoelectron spectroscopy (XPS) and scanning tunneling microscopy (STM). Selected model electrocatalysts were then tested in electrochemical cells to establish the structure-property relationships in OER and CO2RR. Our results showed that the edge sites of Fe2O3 grown on Au(111) were the most active toward OER and incorporation of Ni at the edge sites (NiFeOx) further boosted their OER activity. We also resolved the size-dependent electrocatalytic CO2-to-CO conversion of the Ag nanoparticle electrocatalysts with average particle diameter between 2 to 6 nm: smaller diameter (< 3 nm) particles favored H2 evolution reaction (HER) due to a high population of Ag edge sites, whereas larger diameter particles favored CO2RR as the population of Ag(100) surface sites grew. We further discovered that electronic interactions between small diameter Ag particles and highly defective carbon supports could break the size-dependent CO2RR selectivity, resulting in highly selective (CO Faradaic Efficiency > 90%) and active Ag nanoparticle electrocatalysts with sizes < 2 nm diameter.

Deng, Xingyi↗
DOE OSTI2024

Microstructure Clones

Microstructure drives component behavior. Contemporary crystal plasticity studies compare strain measurements of polycrystal specimens to models. Because each specimen is unique, it is impossible to know which differences are significant. In this project, we invented microstructure clones and explored their use in understanding crystal plasticity. Microstructure clones are specimens with nearly identical microstructures, which allows for multiple destructive tests of a microstructure, insight into how a specimen will deform, variability quantification, and the ability to measure the effects of microstructural changes. Several sets of microstructure clones, pure nickel tensile bars, were tested. The techniques of digital image correlation, crystal plasticity finite element analysis, high resolution electron backscatter diffraction, transmission electron microscopy, and dislocation dynamics were used to understand the structural behavior of these microstructures. This work reshapes the fields of crystal plasticity and structure-property relationships by providing a technique to control for specific variables, quantify microstructural stochasticity, and replicate experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Unifying Quantum Materials Modeling and Experiments: The Role of Machine Learning Interatomic Potentials

Computational experiments have emerged as a powerful complement to traditional experiments in the design of new materials. The development of machine learning (ML) and deep learning techniques, combined with database construction and data mining, has significantly enhanced traditional quantum mechanical methods. This synergy enables the rapid development of structure-property relationships. In this talk, I will discuss our recent efforts in applying Machine Learning Interatomic Potentials (MLIAPs) to accelerate materials modeling across various material classes and challenging applications where traditional methods fall short. First, I will highlight the success of MLIAPs in accurately modeling the melting behavior of complex materials. Our results demonstrate high fidelity with experimental observations and also with calculated reference melting temperatures. In the second application, I will discuss how MLIAPs are trained and applied to elucidate the interplay between segregation tendencies and surface reconstructions in CuNi alloys under oxidizing conditions. A key factor in the success of these MLIAP applications is the design of minimalistic yet flexible datasets along with a computational framework for training MLIAPs.

Saidi, Wissam↗
DOE OSTI2025

Discovery, Design, Synthesis and Testing of High Performance Structural Alloys (Final Technical Report)

The overarching goal of this project is to understand the phase stability and mechanical behavior of non-stoichiometric multi-principal element alloy (MPEA) materials. In order to identify suitable alloys, we plan to use a combinatorial thin film screening approach, in collaboration with scientists at Lawrence Berkeley National Laboratory who are performing computational work as well as complementary experimental work. Specific tasks within the scope of this project include the fabrication, using thin film deposition from six sputtering targets, of combinatorial samples with multi-dimensional gradients in composition and microstructure. These samples are studied to screen MPEA systems for promising candidate alloys with specific composition(s), based on characterization of composition, structure and mechanical behavior across the thin film. We want to produce single-phase MPEAs with chemical homogeneity in a given thin film region, simple grain structures, and no intermetallic phases present. Gradient films facilitate first-pass screening for desirable characteristics and inform the next stage of work that involves fabrication of bulk MPEA specimens for (tensile) mechanical testing and characterization. To make the bulk alloys, metal (elemental) pieces are melted to form MPEAs, followed by heat treatment to homogenize the composition and microstructure. A subset of alloys is also cast, using vacuum arc melting, to yield larger samples (diameter ~1 cm and length ~5-10 cm) and these allow us to assess viability of scale-up for the alloys in structural applications. Further processing plans include rolling and heat treatment to recrystallize selected bulk MPEAs and grow grains to different extents, in order to investigate size effects in the mechanical behavior of MPEAs. Microspecimen testing will be performed (primarily in tension) to assess the mechanical behavior over a range of temperatures. The deformation microstructure of mechanically tested alloys will be characterized using transmission electron microscopy (TEM) to provide a scientific basis for understanding the structure-property relationships in MPEA mechanical behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2025

VISIONARY: Virtual Intelligence System for Optimizing Novel Analytical Research Yields

VISIONARY is an AI system that accelerates energy materials discovery by automatically generating hypotheses about structure-property relationships. It analyzes patterns in materials data, identifies promising correlations, and proposes testable scientific hypotheses without human intervention. By streamlining this reasoning process, VISIONARY helps researchers efficiently identify candidate materials with desired properties, significantly speeding up the materials development pipeline for energy applications. During the project, we developed a standalone application. The application uses a combination of papers provided by the user and data collected from FutureHouse’s dataset to build an understanding of the background that the user wants to explore for the hypothesis.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Identifying Decoherence Mechanisms in Superconducting Qubits through Advanced Materials Characterization

Although superconducting qubits have emerged as a leading technology platform for quantum computing through large improvements in device coherence times and gate fidelity in recent years, the presence of defects and impurities at the interfaces and surfaces in the constituent materials continue to limit performance and serve as a critical barrier in achieving scalable quantum systems. Understanding and eliminating these sources of quantum decoherence in superconducting qubit devices requires dedicated studies aimed at establishing robust structure-property relationships that will enable researchers to target and eliminate defects strategically. As part of the Superconducting Materials and Systems (SQMS) center, we have extensively employed state-of-the-art materials characterization techniques, including scanning/transmission electron microscopy, secondary ion mass spectrometry, atom probe tomography, x-ray diffraction, and x-ray photoelectron spectroscopy in conjunction with device measurements to elucidate such relationships. In this talk, I will discuss some of our recent findings, including linking atomic defects to microwave loss in surface oxides, linking impurities in the Josephson Junction to qubit parameters, and linking low temperature precipitates to device performance. By applying these insights, we have been able to strategically develop and implement mitigation strategies for reliable fabrication of high coherence superconducting qubits.

Murthy, A. [Fermilab] (ORCID:0000000176776866)↗
DOE OSTI2026

Identifying Decoherence Mechanisms in Superconducting Qubits through Advanced Materials Characterization

Although superconducting qubits have emerged as a leading technology platform for quantum computing through large improvements in device coherence times and gate fidelity in recent years, the presence of defects and impurities at the interfaces and surfaces in the constituent materials continue to limit performance and serve as a critical barrier in achieving scalable quantum systems. Understanding and eliminating these sources of quantum decoherence in superconducting qubit devices requires dedicated studies aimed at establishing robust structure-property relationships that will enable researchers to target and eliminate defects strategically. As part of the Superconducting Materials and Systems (SQMS) center, we have extensively employed state-of-the-art materials characterization techniques, including scanning/transmission electron microscopy, secondary ion mass spectrometry, atom probe tomography, x-ray diffraction, and x-ray photoelectron spectroscopy in conjunction with device measurements to elucidate such relationships. In this talk, I will discuss some of our recent findings, including linking atomic defects to microwave loss in surface oxides, linking impurities in the Josephson Junction to qubit parameters, and linking low temperature precipitates to device performance. By applying these insights, we have been able to strategically develop and implement mitigation strategies for reliable fabrication of high coherence superconducting qubits.

Murthy, A. [Fermilab] (ORCID:0000000176776866)↗
DOE OSTI2023

Defects go green: using defects in nanomaterials for renewable energy and environmental sustainability

Induction of point defects in nanomaterials can bestow upon them entirely new physics or augment their pre-existing physical properties, thereby expanding their potential use in green energy technology. Predicting structure-property relationships for defects a priori is challenging, and developing methods for precise control of defect type, density, or structural distribution during synthesis is an even more formidable task. Hence, tuning the defect structure to tailor nanomaterials for enhanced device performance remains an underutilized tool in materials design. We review here the state of nanomaterial design through the lens of computational prediction of defect properties for green energy technology, and synthesis methods to control defect formation for optimal performance. We illustrate the efficacy of defect-focused approaches for refining nanomaterial physics by describing several specific applications where these techniques hold potential. Most notably, we focus on quantum dots for reabsorption-free solar windows and net-zero emission buildings, oxide cathodes for high energy density lithium-ion batteries and electric vehicles, and transition metal dichalcogenides for electrocatalytic green hydrogen production and carbon-free fuels.

14 SOLAR ENERGY↗
DOE OSTI2023

High-Strength, High-Ductility, High Entropy Alloys with High-Efficiency Native Oxide Solar Absorbers for Concentrating Solar Power Systems

This EPSCoR Project has been investigating the synergy between the excellent high-temperature mechanical behavior of FeMnNiAlCr high entropy alloys (HEA) and the high solar absorptance of their native oxides for high efficiency concentrated solar thermal power (CSP) systems working at >700°C. While HEAs have attracted substantial interest in recent years, most investigations have focused on their applications as structural materials rather than functional materials. This EPSCoR project discovered that FeMnNiAlCr HEAs can potentially be applied synergistically as both a structural and functional material for high-efficiency concentrating solar thermal power (CSP) systems working at >700°C. The HEA itself would be used in high-temperature tubing to carry molten salts or supercritical CO 2 , while its surface oxide would act as a high-efficiency solar thermal absorber. With Fe and Mn being the major components in these HEAs (adding up to ~70 at.% of the alloy), these materials are much more cost-effective than the Ni-based superalloys currently being investigated for high-temperature CSP systems. Through this research, these Fe-Mn based HEAs have demonstrated yield strengths 2-3x greater than that of stainless steel at 700°C and a creep lifetime >800 h at 700ºC under a typical CSP tubing mechanical load of 35 MPa. Their Mn-rich surface oxides maintain a high optical-to-thermal conversion efficiency of ~87% under 1000x solar concentration ratio for 20 simulated day-night thermal cycles between 750ºC and room temperature. In preliminary corrosion studies, these HEAs have sustained immersion in unpurified bromide molten salts for 14 days at 750°C with <2% weight loss, in contrast to 70% weight loss from a 316 stainless steel reference. The simultaneous achievement of promising mechanical, optical, and thermochemical properties in this FeMnNiAlCr system opens the door to new applications of HEAs in solar energy harvesting. Partnerships with Ames Laboratory and Oak Ridge National Laboratory (ORNL) also advanced our understanding of the fundamental structure-property relationships through atomic scale material characterization and first-principles computational modeling. The key research results in this project can potentially be extended to other HEAs and their native oxides. In terms of applications, the proposed FeMnNiAlCr HEA/native oxide system could potentially exceed the mechanical and the optical performance of existing tubing and solar coating materials under EERE’s CSP program at lower cost, which also aligns well with the EPSCoR Science and Technology strategies of New Hampshire in boosting the deployment of renewable energy.

14 SOLAR ENERGY↗
DOE OSTI2023

Active Causal Machine Learning for Molecular Property Prediction

Predicting properties from molecular structures is paramount to design tasks in medicine, materials science, and environmental management. However, design rules derived from the structure-property relationships using correlative data-driven methods fail to elucidate underlying causal mechanisms controlling chemical phenomena. This preliminary work proposes a workflow to actively learn robust cause-effect relations between structural features and molecular property for a broad chemical space utilizing smaller subsets, entailing partial information.

Fox, Zach↗
DOE OSTI2025

Material Needs and Measurement Challenges for Advanced Semiconductor Packaging: Understanding the Soft Side of Science

This Perspective builds upon insights from the National Institute of Standards and Technology (NIST)-organized workshop, “Materials and Metrology Needs for Advanced Semiconductor Packaging Strategies,” held at the 35th annual Electronics Packaging Symposium in Binghamton, NY, on September 5, 2024. It outlines critical challenges and opportunities related to polymer-based “soft” materials in advanced semiconductor packaging, with emphasis on polymer science, measurement science (metrology), and the strategic development of Research-Grade Test Materials (RGTMs). These efforts, led by the NIST CHIPS team, aim to advance the fundamental understanding of structure-property-processing relationships, promote standardized guidelines and innovative methods for material characterization, and accelerate the development, qualification, and adoption of next-generation packaging materials. The Perspective also distills key insights from the panel discussion with industry experts, emphasizing the need for close collaboration among materials scientists, process engineers, and metrology experts to enable a holistic strategy, further highlighting the importance of cross-sector partnerships among industry, academia, and government to address pressing challenges in packaging materials and processes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Structure–property relationships of reduced graphene oxide membranes intercalated with polycyclic aromatics

Graphene oxide (GO) membranes intercalated with various organic moieties have shown excellent potential for a range of water processing applications. However, microstructure–functional property relationships in these structurally disordered membranes are not well understood. We demonstrate a practical methodology for developing such relationships for GO membranes intercalated with molecular species, with polycyclic aromatic toluidine blue O (TBO) as an example functional intercalant. We use solid-state UV–vis absorbance and fluorescence measurements to quantitatively track the arrangements of TBO in a series of TBO-loaded reduced GO (rGO) membranes. This study reveals the evolution of diverse arrangements including TBO monomers, lateral and stacked dimers, and other aggregates, as a function of overall TBO loading. These microstructures are then correlated to changes in overall properties such as interlayer d-spacings, permeate fluxes, and solute rejections. The characterization of these different intercalant microstructures explains non-intuitive flux and rejection trends, which can circumvent flux and solute rejection trade-offs.

02 PETROLEUM↗
DOE OSTI2023

Process Variability Effects on Tensile Response in Injection Molded, Fluorinated Thermoplastics

The mechanical properties of fluorinated thermoplastics (i.e., tensile strength and elongation) can vary with changes in injection molding processing parameters. Four fluoropolymers are examined: poly(vinylidene fluoride) (PVDF) and random poly(vinylidene fluoride-co-chlorotrifluoroethylene) (PVDF-CTFE) with three CTFE concentrations. Dog bones were manufactured with various cylinder dwell times and mold cooling times to assess the manufacturing sensitivity to the tensile response. Dwell and cooling times increasingly impact mechanical performance as CTFE concentration increases. Specimens exhibit higher tensile strength as a function of injection order. The first injected specimen exhibits the lowest tensile strength and highest elongation in all copolymers. This trend becomes more pronounced among fluoropolymers with higher CTFE concentration and lower weight-averaged molecular weight. Parallel plate rheology was used to obtain the zero-shear viscosity as a function of material type, process, and injection order. We found that in the copolymers, the first injected sample exhibited a lower zero-shear viscosity than the next, which indicates a lower molecular weight in the first injected specimen. This phenomenon was not presented for the PVDF homopolymer. Copolymer mechanical uncertainties are hypothesized to result from the shorter molecular weight chains extruding out of the specimens' sides as a flash due to higher mobility with CTFE segments.

36 MATERIALS SCIENCE↗
DOE OSTI2025

What causes the variation in superconducting properties of UTe 2 ?

Reaching a consensus on the superconducting order parameter of unconventional superconductors remains a central challenge in the field of magnetically-mediated superconductivity. Though UTe 2 is largely accepted as a rare example of an odd-parity superconductor, its precise order parameter remains highly debated, even at ambient conditions. A key underlying issue is the large sample-to-sample variation in superconducting properties at zero applied pressure and magnetic field. Here, we investigate the origin of the observed variation by means of single crystal x-ray diffraction (SC-XRD) and scanning transmission electron microscopy (STEM) measurements. Our results reveal highly ordered crystalline lattices, in agreement with the expected Immm structure, and no signs of uranium vacancies. Tiny amounts of interstitial defects, however, are observed on the Te2 layers that host Te chains along the b axis. We argue that these defects give rise to slightly enhanced atomic displacement parameters observed in SC-XRD data and are enough to disrupt the unconventional superconducting state in UTe 2 . Our findings highlight the need to focus future order parameter determination efforts on single crystals of UTe 2 with minimal amounts of structural disorder.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Complex Dynamics in Argyrodite Solid-State Ion Conductors

Argyrodites are a compositionally diverse family of materials that exhibit remarkable ion transport properties. While the average crystal structures of argyrodites have been extensively studied, ion transport in these materials is governed by a confluence of dynamic processes spanning the cation, anion, and polyanionic sublattices. This Perspective synthesizes recent advances in understanding the role of dynamics in structural behavior and ion transport properties. We examine the compositional and structural motifs that govern order−disorder transitions within the argyrodite family and further explore how ion hopping is facilitated by lattice dynamics, from long-range phonons to local rotational dynamics of polyanionic species. Through the lens of dynamics spanning multiple time and length scales, we establish guiding principles that govern transport phenomena and highlight avenues of future study for the argyrodite family of ion conductors.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Process Variability Effects on Tensile Response in Injection Molded, Fluorinated Thermoplastics

The mechanical properties of fluorinated thermoplastics (i.e., tensile strength and elongation) can vary with changes in injection molding processing parameters. Four fluoropolymers are examined: poly(vinylidene fluoride) (PVDF) and random poly(vinylidene fluoride-co-chlorotrifluoroethylene) (PVDF-CTFE) with three CTFE concentrations. Dog bones were manufactured with various cylinder dwell times and mold cooling times to assess the manufacturing sensitivity to the tensile response. Dwell and cooling times increasingly impact mechanical performance as CTFE concentration increases. Specimens exhibit higher tensile strength as a function of injection order. The first injected specimen exhibits the lowest tensile strength and highest elongation in all copolymers. This trend becomes more pronounced among fluoropolymers with higher CTFE concentration and lower weight-averaged molecular weight. Parallel plate rheology was used to obtain the zero-shear viscosity as a function of material type, process, and injection order. We found that in the copolymers, the first injected sample exhibited a lower zero-shear viscosity than the next, which indicates a lower molecular weight in the first injected specimen. This phenomenon was not present for the PVDF homopolymer. Copolymer mechanical uncertainties are hypothesized to result from the shorter molecular weight chains extruding out of the specimens’ sides as a flash due to higher mobility with CTFE segments.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Structure–property relations of sodium iron phosphate nuclear waste glasses: Effects of iron redox ratio and glass composition

Iron phosphate glasses, known for their exceptional chemical durability and potential applicability in nuclear waste management, have gained significant attention over the years. The structures of these glasses are complicated by the coexistence of Fe 3+ and Fe 2+ , which plays a crucial role in determining their structures and properties. Here, this work uses molecular dynamics simulations to study the structural changes in Na 2 O–Fe 2 O 3 –P 2 O 5 glasses with varying glass composition and Fe 2+ /Fe 3+ redox ratio. It was found that the redox ratio and modifier contents significantly affected the short-range and medium-range orders in the glasses. Significant changes in the local environments around P 5+ and Fe 3+ were observed, as reflected by the bond distances and coordination numbers. Na + cations are found to preferentially associate with Fe 3+ (rather than Fe 2+ ), whereas Fe 2+ has stronger association with P 5+ than Na + , confirming the structural role of Fe 2+ as a glass modifier. The disruptions in P–O–P linkages upon increasing FeO suggest that FeO causes glass depolymerization. These glasses achieved higher connectivity with increasing Fe 3+ / (Fe 3+ + Fe 2+ ) ratios, conerting phosphorous Q 2 to Q 3 units and iron Q 5 units to Q 4 units. The decrease of nonbridging oxygen fractions with increasing Fe 3+ / (Fe 3+ + Fe 2+ ) ratios, through creating P–O–Fe linkages, is the main reason of enhanced network connectivity. Quantitative structure–property relationship analyses with different structural descriptors were used to correlate with measured properties. The analyses provided valuable insights into structure–property relationships, emphasizing the importance of choosing relevant energy parameters and defining glass network connectivity, particularly in F net descriptors. It was found the Fe–O–P linkage density exhibits strong correlations to measured dissolution rates, supporting the importance of these linkages in improving the chemical durability in iron phosphate glasses.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗