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At least 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Enzymatic depolymerization of polyester: Foaming as a pretreatment to increase specific surface area

Abstract Poly(ethylene terephthalate) (PET) is widely used for its high strength‐to‐weight ratio, gas barrier properties, and chemical resistance. The growing PET use highlights the demand for a better recycling system. Enzymatic recycling, alongside mechanical and chemical methods, is eco‐friendly and yields properties similar to virgin PET. Substrate properties ( T g , crystallinity, and specific surface area [SSA]) and enzyme stability significantly impact conversion efficiency. Higher SSA and lower crystallinity tend to yield improved depolymerization when employing leaf compost‐cutinase (LCC‐ICCG) enzymes. This study explored melt extrusion and foaming as pretreatment techniques to modify PET structural properties, using a low‐cost chemical foaming agent (CFA). The monomer conversion rate and efficiency during depolymerization were measured and related to the processing, extrudate micro‐ and meso‐structure, and polyester type. Pretreated PET substrates showed reduced T g , crystallinity, density, and enhanced SSA, resulting in a 90% mass loss for foamed RPET and VPET substrates within 2 days. In contrast, PET with ~30% of cyclohexanedimethanol comonomer exhibited a nearly 50% lower depolymerization rate, with zero BHET production. It indicates that the combination of low crystallinity, low T g , and high SSA leads to improved monomer conversion. These findings emphasize the significance of amorphization and foaming in enhancing PET enzymatic depolymerization.

42 ENGINEERING↗
DOE OSTI2022

Fatigue-crack propagation behavior in a high-carbon chromium SUJ2 bearing steel: Role of microstructure

High-carbon chromium martensite steels are commonly selected for bearing components in the power generation, automotive and aerospace industries where fatigue failure is a major concern. Accordingly, it is of importance to elucidate the structure-property relationships governing the fatigue properties of such bearing steels. Here, the role of microstructure in influencing the fatigue-crack propagation behavior of a high-carbon chromium SUJ2 bearing steel is examined with emphasis on three martensitic structures: (i) a fine-grained (~10 μm) structure with intragranular (but no intergranular) carbides, (ii) a coarser-grained (~25 μm) structure with discontinuous grain-boundary carbides primarily near triple junctions, and (iii) a coarse-grained (~31 μm) structure with continuous grain-boundary carbides. Although growth rates were fairly similar above ~10 -8 m/cycle, significant differences in behavior were observed at lower, near-threshold growth rates; specifically at a load ratio of 0.1, the ΔKth fatigue threshold was increased from 3.8 MPa m ½ in the fine-grained structure to 5.9 to 6.3 MPa m ½ in the two coarser-grained structures. The dominant factor governing such near-threshold behavior was found to be crack-tip shielding from roughness-induced crack closure, which was most pronounced in the coarser-grained structures; additionally, shielding from crack deflection and branching was apparent in these structures as the crack propagated through the network of intersecting martensite lamellae within the coarse grains. Compared to high-strength stainless steels and low-strength carbon steels, the fine-grained SUJ2 steel displays an exceptional combination of high strength and fatigue-crack growth resistance and is considered to be a superior structural alloy for bearing applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Flat-histogram extrapolation as a useful tool in the age of big data

In this work, we review recent work by the authors to revisit the concept of extrapolating thermodynamic properties of classical systems using statistical mechanical principles. Specifically, we discuss how the combination of these principles with biased sampling techniques enables the prediction of free energy landscapes and other detailed information, such as structural properties, of the system in question. Remarkably accurate estimates of physical properties across a broad range of conditions have been achieved using this approach, greatly reducing the number of simulations needed to explore a given system's behaviour. While approximate, these extrapolations significantly amplify the amount of reasonably accurate information that can be extracted from simulations enabling a small set of them to feed data-intensive regression algorithms such as neural networks. Thus, this extrapolation methodology represents a useful tool for performing tasks such as high-throughput screening of physical properties, optimising force field parameters, exploring equilibrium phase behaviour, and enabling theory-guided data science for these systems.

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

Separating the Impact of Nuclear Skin and Nuclear Deformation in High-Energy Isobar Collisions

Bulk nuclear structure properties, such as radii and deformations, leave distinct signatures in the final state of relativistic heavy-ion collisions. Isobaric collisions offer an easy route to establish explicit connections between the colliding nuclei's structure and the observable outcomes. Here, we investigate the effects of nuclear skin thickness and nuclear deformations on the elliptic flow (v 2 ) and its fluctuations in high-energy 96 Ru + 96 Ru and 96 Zr + 96 Zr collisions. Furthermore, our findings reveal that the difference in skin thickness between these isobars only influences the inherent ellipticity of the collision systems, $v_2^{rp}$. In contrast, differences in nuclear deformations solely impact the fluctuations of v 2 around $v_2^{rp}$. Hence, we have identified a data-driven method to disentangle the effects of nuclear skin and nuclear deformations, marking a significant step toward assessing the consistency of nuclear phenomena across energy scales.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Materials Characterization, Prediction and Control Project: Summary Report on Data Analytics Framework

This report summarizes the activities performed under the data analytics Vertex in the Materials Characterization, Prediction and Control Project funded under laboratory directed research and development at Pacific Northwest National Laboratory. The data analytics Vertex developed models for associating global or local process parameters, microstructural features, and performance properties of friction-stir-processed 316L stainless steel plates. Statistical, machine learning, and deep learning models, as well as generative artificial intelligence approaches, were used to develop the associations between the process-structure-property data streams. These associations formed the basis for predicting global properties of parts manufactured under different process envelopes, providing a basis for predicting performance using data driven as well as physics-informed and physics-constrained approaches. Additionally, the associations were used to predict local process parameters and microstructural features of the product, predictive relationships that have the potential to form the basis of a control framework that could eventually modulate a friction-stir process to maintain product quality.

316L stainless steel↗
DOE OSTI2025

Laser Powder Directed Energy Deposition of Steels for Nuclear Applications

This comprehensive investigation examines the structure–property relationships in two nuclear alloy systems—Alloy 709 (A709) austenitic stainless steel and Grade 92 (G-92) ferritic/martensitic (F/M) steel—manufactured via directed energy deposition (DED) for sodium-cooled fast reactor applications. This study establishes the fundamental mechanisms for controlling microstructures for optimizing the mechanical performance of additively manufactured nuclear materials through systematic heat treatment optimization and multiscale characterization. As-deposited A709 steel develops a complex multiscale strengthening architecture consisting of a fine cellular solidification structure with diameter of 2-3 µm within10–50 µm grains, elevated dislocation densities from rapid thermal cycling, and grain boundary precipitates that activate concurrent Hall–Petch, dislocation, and precipitation hardening mechanisms to achieve exceptional properties [yield strength (YS): 603 MPa, ultimate tensile strength (UTS): 844 MPa, Vickers hardness: 220 HV] that achieve a 44% superior strength compared to that of the wrought material. Heat treatments produce different results. Solution annealing (SA) dissolves the cellular structure and reduces the hardness to 190 HV. Precipitation treatment (PT) keeps the cellular structure but adds carbides, allowing the hardness to reach 205 HV. The best approach combines both treatments (SA+PT) and creates uniform precipitate distributions with M 23 C 6 carbides at the grain boundaries and MX carbonitrides in the matrix, achieving a hardness of 195 HV. However, directional differences persist, with a 12%–15% strength variation between orientations due to the inherited layered microstructural architecture that survives aggressive heat treatment. While tensile testing at 550°C demonstrates 40%–50% thermal softening with dynamic strain aging, DED A709 steel still maintains a 71% higher YS than that of the wrought material. Ion irradiation studies (100–400 dpa) of DED A709 steel reveal progressive radiation damage with increasing void density and radiation-induced segregation causing nickel enrichment and chromium depletion, which will ultimately compromise mechanical properties. As-deposited G-92 exhibits exceptional strength (UTS: 1650–1700 MPa, 430 HV) through a complex microstructure containing both ferrite and martensite phases, a high geometrically necessary dislocation (GND) density (17.04×10 14 /m 2 ), and fine carbides. Heat treatments create distinct changes. Normalizing produces fresh martensite with the highest hardness (460 HV) and an increased GND density (20.23×10 14 /m 2 ). Tempering develops dual precipitation systems and reduces the hardness to 290 HV. The optimal approach uses sequential normalizing plus tempering, achieving balanced properties with the lowest hardness (250 HV) and a reduced GND density (11.01×10 14 /m 2 ). A processing-dependent anisotropy is observed: horizontal specimens achieve superior ductile behavior, while vertical specimens exhibit brittle failure. A tempering heat treatment successfully mitigates this anisotropic behavior by transforming the hard martensitic as-deposited structure into tempered martensite enabling both horizontal and vertical specimens to exhibit similar stress–strain characteristics with visible necking behavior. Remarkably, testing at 550°C reveals a reversal in the anisotropy, where as-deposited specimens achieve near isotropy with superior thermal stability (a 15%–20% strength reduction), while tempered specimens develop an orientation dependence with a 25%–30% strength reduction. Both alloy systems demonstrate that DED processing creates specimens with a superior strength through refined microstructural features, though with distinct strengthening mechanisms—austenitic through cellular structures and precipitates versus F/M through phase transformations and precipitates. Heat treatment optimization requires alloy-specific approaches, with A709 benefiting from controlled precipitation while G-92 requires careful phase transformation control. The results show that DED manufacturing can produce nuclear materials with exceptional performance, but directional effects and temperature-dependent behavior must be carefully considered for reactor component design and qualification.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Nondestructive ultrasonic characterization of a triple-weld-bead wire arc additively manufactured ER70S-6 S-curved wall

Understanding build-scale microstructural variation in wire arc additive manufacturing (WAAM) of low-carbon steels is essential for ensuring consistent structure–property relationships throughout large components. Conventional destructive characterization techniques, such as scanning electron microscopy (SEM) and electron backscatter diffraction (EBSD), are time-intensive and limited to localized regions, making comprehensive evaluation of large WAAM structures challenging. In this study, a nondestructive ultrasonic approach was employed to characterize a 252 mm tall ER70S-6 S-curved WAAM wall produced using a triple-bead deposition strategy. Optical and SEM analysis revealed a repeating dual-region microstructure consisting of uniform polygonal ferrite at melt pool centers and heterogeneous ferrite with coarse and fine grains near melt pool boundaries, attributed to cyclic thermal conditions. Longitudinal ultrasonic backscatter imaging was used to evaluate the continuity of this periodicity along the full build height. The ultrasonic response exhibited a consistent repeating pattern that correlated with the observed layer-wise microstructural variation. X-ray computed tomography confirmed the absence of detectable porosity, indicating that ultrasonic contrast is primarily governed by grain morphology. Overall, the results indicate that longitudinal backscatter ultrasound is a promising nondestructive characterization technique for validating microstructural variations along the s-curved WAAM wall, with significant potential for microstructure optimization and process control.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Revisiting group contribution theory for estimating fractional free volume of microporous polymer membranes

Fractional free volume (FFV) is a commonly used metric for the development of structure–property relationships for polymer membranes. The most common method to calculate FFV uses Bondi's group contribution method, first introduced in 1964. While updated in 1997, there has not been a significant compilation of new structural motifs since the advent of linear microporous polymers. Here, in this study, we critically examined the assumptions in Bondi's original method and provide four recommendations to streamline and improve the accuracy of calculating van der Waals volume (V W ) for any group. Using these recommendations, we created an updated list of (V W ) values for structural groups commonly present in microporous polymers. The (V W ) and FFV values were then calculated for a database of 123 microporous and high free volume polymers from the literature, showing an average 7% decrease in (V W ) and corresponding increase in FFV by a factor of 24% when compared to prior group contribution correlations in the literature. The significant apparent increase in estimated FFV provides a new perspective to understand and interpret the role of free volume on the separation performance of linear microporous polymers. Additionally, standardization of the group contribution method allows for the direct comparison of FFV values across studies.

42 ENGINEERING↗
DOE OSTI2022

Forest structure and solar-induced fluorescence across intact and degraded forests in the Amazon

Tropical forest degradation (e.g., anthropogenic disturbances such as selective logging and fires) alters forest structure and function and influences the forest's carbon sink. In this study, we explored structure-function relationships across a variety of degradation levels in the southern Brazilian Amazon by 1) investigating how forest structural properties vary as a function of degradation history using airborne lidar data; 2) assessing the effects of degradation on solar-induced chlorophyll fluorescence (SIF) seasonality using TROPOMI data; and 3) quantifying the contribution of structural variables to SIF using multiple regression models with stepwise selection of lidar metrics. Forest degradation history was obtained through Landsat time-series classification. We found that fire, logging, and time since disturbance were major determinants of forest structure, and that forests affected by fires experienced larger variability in leaf area index (LAI), canopy height and vertical structure relative to logged and intact forests. Moreover, only recently burned forests showed significantly depressed SIF during the dry season compared to intact forests. Canopy height and the vertical distribution of foliage were the best predictors of SIF. Unexpectedly, we found that wet-season SIF was higher in active regenerating forests (~ 4 years after fires or logging) compared with intact forests, despite lower LAI. Furthermore, our findings help to elucidate the mechanisms of carbon accumulation in anthropogenically disturbed tropical forests and indicate that they can capture large amounts of carbon while recovering.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Rapid and Simultaneous Characterization of Drug Conjugation in Heavy and Light Chains of a Monoclonal Antibody Revealed by High-Resolution Ion Mobility Separations in SLIM

Antibody-drug conjugates (ADCs) have recently gained traction in the biomedical community due to their promise for human therapeutics and an alternative to chemotherapy for cancer. Crucial metrics for ADC efficacy, safety, and selectivity are their drug-antibody ratios (DARs). However, DAR characterization (i.e., determining the average number of conjugated drugs on the antibody) through analytical methods remains challenging due to the heterogeneity of drug conjugation as well as the numerous post-translational modifications possible in the monoclonal antibody. In this work, we report on the use of high-resolution ion mobility spectrometry separations in our structures for lossless ion manipulations coupled to mass spectrometry (SLIM IMS-MS) platform for the rapid and simultaneous characterization of the drug load profile (i.e., stoichiometric distribution of the number of conjugated drugs present on the mAb), determination of the weighted average DAR in both the heavy and light chains of a model antibody-drug conjugate, and calculation of the overall DAR of the ADC. After chemical reduction of the ADC and a subsequent 31.5 meter SLIM IMS separation the various drug bound antibody species could be well resolved for both chains. Furthermore, we also show that higher resolution separations were possible with SLIM IMS as compared to ones performed on a commercially available (~1 meter) drift tube IMS-MS platform. Interestingly, additional gas-phase substructures become evident with longer path length SLIM IMS, potentially providing insight related to how drug conjugation may alter the structural properties of a monoclonal antibody and thus affect its overall potency and/or selectivity for a given antigen. We expect high-resolution SLIM IMS separations will augment the existing toolbox for ADC characterization, particularly for structural confirmation to enable the rapid optimization of DAR for a given ADC and thus better understand its potential toxicity and potency.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1979

Survey of inorganic polymers

A literature search was carried out in order to identify inorganic, metallo-organic, and hybrid inorganic-organic polymers that could serve as potential matrix resins for advanced composites. The five most promising candidates were critically reviewed and recommendations were made for the achievement of their potential in terms of performance and cost. These generic polymer classes comprise: (1) Poly(arylsil sesquioxanes); (2) Poly(silyl arylene siloxanes); (3) Poly(silarylenes); (4) Poly(silicon-linked ferrocenes); and (5) Poly(organo phosphazenes). No single candidate currently possesses the necessary combination of physicomechanical properties, thermal stability, processability, and favorable economics. The first three classes exhibit the best thermal performance. On the other hand, poly (organo phosphazenes), the most extensively studied polymer class, exhibit the best combination of structure-property control, processability, and favorable economics.

Gerber, A. H.↗
NASA NTRS1987

On orbit damage assessment for large space structures

The need for monitoring the dynamic characteristics of large structural systems, for the purpose of assessing the potential degradation of structural properties, has been established. This paper develops a theory for assessing the occurrence, location, and extent of potential damage utilizing on-orbit response measurements. The feasibility of the method is demonstrated using a simple structural system as an example.

Chen, Jay-Chung↗
NASA NTRS1988

Effects of model deficiencies on parameter estimation

Reliable structural dynamic models will be required as a basis for deriving the reduced-order plant models used in control systems for large space structures. Ground vibration testing and model verification will play an important role in the development of these models; however, fundamental differences between the space environment and earth environment, as well as variations in structural properties due to as-built conditions, will make on-orbit identification essential. The efficiency, and perhaps even the success, of on-orbit identification will depend on having a valid model of the structure. It is envisioned that the identification process will primarily involve parametric methods. Given a correct model, a variety of estimation algorithms may be used to estimate parameter values. This paper explores the effects of modeling errors and model deficiencies on parameter estimation by reviewing previous case histories. The effects depend at least to some extent on the estimation algorithm being used. Bayesian estimation was used in the case histories presented here. It is therefore conceivable that the behavior of an estimation algorithm might be useful in detecting and possibly even diagnosing deficiencies. In practice, the task is complicated by the presence of systematic errors in experimental procedures and data processing and in the use of the estimation procedures themselves.

Hasselman, T. K.↗
NASA NTRSDate not supplied

Understanding Variability in Mechanical Behavior of Adhesively Bonded Sandwich Joints due to Stochastic Material Damage

A mesoscale progressive damage analysis was applied to the analysis of recently tested adhesively bonded sandwich panels, in which ten nominally identical tension loaded panels failed in three different failure modes, with peakloads ranging from 13.0 –16.1 kips. A parametric finite element model for progressive damage analysis of an adhesively bonded joint (ABJ) considering matrix and fiber damage, and delamination cracks in unidirectional and fabric composite sections of the joint, as well as core crushing, and adhesive fracture was developed. The model was developed using Abaqus/Explicit and utilized continuum damage mechanics material models for intralaminar damage in the facesheet and doubler plies, cohesive elements for delamination and adhesive debonding, and discretized cells considering plasticity to model crushing of the aluminum honeycomb core. Analysis predictions obtained with a pristine model agreed well with the average experimental peak load, strain in the joint, and post-test damage states. Then, various methods to incorporate stochastic material variability into ABJ model were evaluated. These methods included simulation of pre-existing matrix damage, pre-existing adhesive porosity, and uniform modification of adhesive properties. These material and manufacturing defects changed the damage mode predictions in some cases. The analysis of stochastic strength due to the considered defects revealed unintuitive damage mode interaction in the ABJ, explaining some structure-property relationships observed experimentally.

Richard Larson↗
NASA NTRS1998

Structures and Mechanical Properties of Natural and Synthetic Diamonds

A revolution in diamond technology is in progress as the low-pressure process becomes an industrial reality. It will soon be possible to take advantage of the demanding properties of diamond to develop a myriad of new applications, particularly for self-lubricating, wear, and superhard coatings. The production of large diamond films or sheets at low cost, a distinct possibility in the not-too-distant future, may drastically change tribology technology, particularly solid lubricants and lubricating materials and systems. This chapter reviews the structures and properties of natural and synthetic diamond to gain a better understanding of the tribological properties of diamond and related materials to be described in the following chapters. Atomic and crystal structure, impurities, mechanical properties, and indentation hardness of diamond are described.

Miyoshi, Kazuhisa↗
DOE OSTI2021

Charge Density Waves and Electronic Properties of Superconducting Kagome Metals

We report that kagome metals AV 3 Sb 5 (A = K, Rb, and Cs) exhibit intriguing superconductivity below 0.9 ~ 2.5 K, a charge density wave (CDW) transition around 80 ~ 100 K, and $\mathbb{Z}$ 2 topological surface states. The nature of the CDW phase and its relation to superconductivity remains elusive. In this work, we investigate the electronic and structural properties of CDW by first-principles calculations. We reveal an inverse Star of David deformation as the 2 x 2 x 2 CDW ground state of the kagome lattice. The kagome lattice shows softening breathing-phonon modes, indicating the structural instability. However, electrons play an essential role in the CDW transition via Fermi surface nesting and van Hove singularity. The inverse Star of David structure agrees with recent experiments by scanning tunneling microscopy (STM). The CDW phase inherits the nontrivial $\mathbb{Z}$ 2 -type topological band structure. Further, we find that the electron-phonon coupling is too weak to account for the superconductivity T c in all three materials. It implies the existence of unconventional pairing of these kagome metals. Our results provide essential knowledge toward understanding the superconductivity and topology in kagome metals.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Evaluating causal‐based feature selection for fuel property prediction models

Abstract In‐silico screening of novel biofuel molecules based on chemical and fuel properties is a critical first step in the biofuel evaluation process due to the significant volumes of samples required for experimental testing, the destructive nature of engine tests, and the costs associated with bench‐scale synthesis of novel fuels. Predictive models are limited by training sets of few existing measurements, often containing similar classes of molecules that represent just a subset of the potential molecular fuel space. Software tools can be used to generate every possible molecular descriptor for use as input features, but most of these features are largely irrelevant and training models on datasets with higher dimensionality than size tends to yield poor predictive performance. Feature selection has been shown to improve machine learning models, but correlation‐based feature selection fails to provide scientific insight into the underlying mechanisms that determine structure–property relationships. The implementation of causal discovery in feature selection could potentially inform the biofuel design process while also improving model prediction accuracy and robustness to new data. In this study, we investigate the benefits causal‐based feature selection might have on both model performance and identification of key molecular substructures. We found that causal‐based feature selection performed on par with alternative filtration methods, and that a structural causal model provides valuable scientific insights into the relationships between molecular substructures and fuel properties.

Nguyen, Bernard↗
DOE OSTI2021

Electrochemistry of Thin Films with In Situ/Operando Grazing Incidence X-Ray Scattering: Bypassing Electrolyte Scattering for High Fidelity Time Resolved Studies

Electroactive polymer thin films undergo repeated reversible structural change during operation in electrochemical applications. While synchrotron X-ray scattering is powerful for the characterization of stand-alone and ex situ organic thin films, in situ/operando structural characterization has been underutilized-in large part due to complications arising from supporting electrolyte scattering. This has greatly hampered the development of application relevant structure property relationships. Therefore, a new methodology for in situ/operando X-ray characterization that separates the incident and scattered X-ray beam path from the electrolyte is developed. As a proof of concept, the operando structural characterization of weakly-scattering, organic mixed conducting thin films in an aqueous electrolyte environment is demonstrated, accessing previously unexplored changes in the $\pi-\pi$ peak and diffuse scatter, while capturing the solvent swollen thin film structure which is inaccessible in previous ex situ studies. These in situ/operando measurements improve the sensitivity to structural changes, capturing minute changes not possible ex situ, and have multimodal potential such as combined Raman measurements that also serve to validate the true in situ/operando conditions of the cell. Finally, new directions enabled by this in situ/operando cell design are examined and state of the art measurements are compared.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗