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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Robust Molecular Predictive Methods for Novel Polymer Discovery and Applications

Polymeric materials are ubiquitous in modern society and they play an instrumental role in almost all industries, undoubtedly including the energy and environment sectors. Increased demand of energy and awareness to sustainability both necessitates the development of novel polymers with enhanced properties. Unfortunately, their structural and behavioral complexity render such discovery challenging and impeded. To address this problem, scientists are developing various computational modeling techniques and leveraging their power to depict the relationship between structural characteristics of polymers and their properties (such as rheological behaviors), and use such prediction to guide the design and syntheses of novel polymeric materials with enhanced performances. Unfortunately, predicting the relationships between polymer structure and composition with rheological properties via atomistic modeling is still a major challenge because of the extended time and length scales involved. Studying dynamic shear viscosity and linear viscoelasticity using molecular models requires capabilities that have been elusive, including representation of large molecular weight chains with an effective internal scale capable of describing entanglement, shear-rates that are in the s-1 scale with accurate quantitative stresses, and chemically-realistic combinations of both homogeneous and heterogeneous systems. Motivated by these unmet challenges, the overall technical objective of this DOE-STTR Phase II project is to develop robust molecular predictive methods for advanced polymer discovery and applications and especially for designing and demonstrating the “smart” polymer-based waterflooding enhanced oil recovery (EOR) process. In particular, we apply state-of-the-art molecular modeling methods developed by our academic partner, Materials Stimulation Center (MSC) at California Institute of Technology (Caltech), to facilitate and accelerate the experimental discovery processes. During the Phase I of this project, we had focused on development and demonstration of the molecular modeling methods to describe rheological properties of non-Newtonian polymer fluids, and to improve our fundamental understandings of shear-thickening mechanism and kinetics. In Phase II, we further apply the theoretical models to guide our experimental programs to improve our design of smart rheology modifier (SRM) polymers and their optimization for EOR. Specifically, we have three objectives in the Phase II study: (1) to further improve out computational modeling methods, coupling with the advanced machine learning algorithms; (2) to develop cost-effective and efficient SRM-flooding process suitable for EOR applications under typical reservoir conditions; and (3) to further explore the application of our molecular predictive models for innovative material discovery in other industrial applications. The recent development of our multiscale predictive framework allows the successful prediction of rheological properties from the chemical structure for polymers of experimentally relevant molecular weights, and provides an in-silico machine learning engine for screening novel compositions and structures with optimized non-Newtonian response, required for both shear-thinning and shear-thickening applications. Our framework provides: (1) procedures and tools for systematic coarsening from atomistic models and reverse mapping of coarse-grain models to atomistic, (2) unique ab initio methods to characterize the atomistic origin of colloidal and interfacial interactions and phenomena, (3) systematic structure and composition builders based on practical descriptors that drive rheological changes in polymer melts and diluted polymer mixtures, (4) a rheological properties engine capable of predicting viscosity in the zero-shear limit and under realistic dynamic conditions (for shear-rates commensurate with experiments) for large heterogeneous systems, (5) coarse-grain force fields with improved non-bond descriptions based on accurate quantum mechanics, (6) an in-silico screening machine learning engine that feeds from the systematic model builders to cover the descriptors search space, computes the rheological properties from converged trajectories spanning sub-milliseconds and ranks them for each structure/composition using an automated viscosity-vs-shear rate fitness function that can be tuned for shear-thickening, shear-thinning and other rheological responses.

02 PETROLEUM↗
DOE OSTI2022

Thermal photonics with broken symmetries

Abstract Nanophotonic engineering provides an effective platform to manipulate thermal emission on-demand, enabling unprecedented heat management superior to conventional bulk materials. Amongst a plethora of nanophotonic structures, symmetries play an important role in controlling radiative heat transfer in both near-field and far-field. In physics, broken symmetries generally increase the degree of freedom in a system, enriching the understanding of physical mechanisms and bringing many exciting opportunities for novel applications. In this review, we discussed the underlying physics and functionalities of nanophotonic structures with broken geometrical symmetries, engineered mode symmetries, and broken reciprocity for the control of thermal emission. We overview a variety of physical phenomena and interesting applications, and provide the outlook for future development.

Liu, Tianji↗
DOE OSTI2020

Accounting for erroneous model structures in biokinetic process models

In engineering practice, model-based design requires not only a good process-based model, but also a good description of stochastic disturbances and measurement errors to learn credible parameter values from observations. However, typical methods use Gaussian error models, which often cannot describe the complex temporal patterns of residuals. Consequently, this results in overconfidence in the identified parameters and, in turn, optimistic reactor designs. Here, we assess the strengths and weaknesses of a method to statistically describe these patterns with autocorrelated error models. This method produces increased widths of the credible prediction intervals following the inclusion of the bias term, in turn leading to more conservative design choices. However, we also show that the augmented error model is not a universal tool, as its application cannot guarantee the desired reliability of the resulting wastewater reactor design.

42 ENGINEERING↗
DOE OSTI2018

Layer-by-layer epitaxial growth of defect-engineered strontium cobaltites

Here, control over structure and composition of (ABO 3 ) perovskite oxides offers exciting opportunities since these materials possess unique, tunable properties. Perovskite oxides with cobalt B-site cations are particularly promising, as the range of the cation’s stable oxidation states leads to many possible structural frameworks. Here, we report growth of strontium cobalt oxide thin films by molecular beam epitaxy, and conditions necessary to stabilize different defect concentration phases. In situ X-ray scattering is used to monitor structural evolution during growth, while in situ X-ray absorption near-edge spectroscopy is used to probe oxidation state and measure changes to oxygen vacancy concentration as a function of film thickness. Experimental results are compared to kinetically-limited thermodynamic predictions, in particular, solute trapping, with semi-quantitative agreement. Agreement between observations of dependence of cobaltite phase on oxidation activity and deposition rate, and predictions indicates that a combined experimental/theoretical approach is key to understanding phase behavior in the strontium cobalt oxide system.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Achieving high tensile strength and ductility in refractory alloys by tuning electronic structure

The energy efficiency of heat engines (gas and steam turbines) for electricity production and propulsion is determined by the Carnot cycle and scales with operating temperature. Commercial nickel- and cobalt-based superalloys melt near 1,500 °C and rapidly lose mechanical strength beyond 1,000 °C. Refractory metals melt well above 2,000 °C but have inherent manufacturability challenges that are barriers to adoption, such as high ductile-to-brittle transition temperatures. Using density functional theory-guided design, we demonstrate tailored local lattice distortions that promote phase-stable, non-equiatomic refractory concentrated solid solutions with both high ductility and strength. Here, we exemplify this for single-phase, body-centred cubic Nb 4 Ta 4 V 3 Ti that exhibits castability, excellent room-temperature tensile yield strength (∼1 GPa) and ductility (approaching 20% uniform strain), and exceptional high-temperature tensile strength (500 MPa at 1,000 °C). These findings illustrate a path for designing materials that hold great potential for advancing next-generation technologies such as Generation IV fission reactors, first-generation fusion-plasma reactors, and more efficient gas turbines for electricity generation and propulsion.

DFT↗
DOE OSTI2020

Developing a sustainability science approach for water systems

We convened a workshop to enable scientists who study water systems from both social science and physical science perspectives to develop a shared language. This shared language is necessary to bridge a divide between these disciplines’ different conceptual frameworks. As a result of this workshop, we argue that we should view socio-hydrological systems as structurally co-constituted of social, engineered, and natural elements and study the “characteristic management challenges” that emerge from this structure and reoccur across time, space, and socioeconomic contexts. This approach is in contrast to theories that view these systems as separately conceptualized natural and social domains connected by bi-directional feedbacks, as is prevalent in much of the water systems research arising from the physical sciences. A focus on emergent characteristic management challenges encourages us to go beyond searching for evidence of feedbacks and instead ask questions such as: What types of innovations have successfully been used to address these challenges? What structural components of the system affect its resilience to hydrological events and through what mechanisms? Are there differences between successful and unsuccessful strategies to solve one of the characteristic management challenges? If so, how are these differences affected by institutional structure and ecological and economic contexts? To answer these questions, social processes must now take center stage in the study and practice of water management. We also argue that water systems are an important class of coupled systems with relevance for sustainability science because they are particularly amenable to the kinds of systematic comparisons that allow knowledge to accumulate. Indeed, the characteristic management challenges we identify are few in number and recur over most of human history and in most geographical locations. This recurrence should allow us to accumulate knowledge to answer the above questions by studying the long historical record of institutional innovations to manage water systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Microstructure-Sensitive Uncertainty Quantification for Crystal Plasticity Finite Element Constitutive Models Using Stochastic Collocation Methods

Uncertainty quantification (UQ) plays a major role in verification and validation for computational engineering models and simulations, and establishes trust in the predictive capability of computational models. In the materials science and engineering context, where the process-structure-property-performance linkage is well known to be the only road mapping from manufacturing to engineering performance, numerous integrated computational materials engineering (ICME) models have been developed across a wide spectrum of length-scales and time-scales to relieve the burden of resource-intensive experiments. Within the structure-property linkage, crystal plasticity finite element method (CPFEM) models have been widely used since they are one of a few ICME toolboxes that allows numerical predictions, providing the bridge from microstructure to materials properties and performances. Several constitutive models have been proposed in the last few decades to capture the mechanics and plasticity behavior of materials. While some UQ studies have been performed, the robustness and uncertainty of these constitutive models have not been rigorously established. In this work, we apply a stochastic collocation (SC) method, which is mathematically rigorous and has been widely used in the field of UQ, to quantify the uncertainty of three most commonly used constitutive models in CPFEM, namely phenomenological models (with and without twinning), and dislocation-density-based constitutive models, for three different types of crystal structures, namely face-centered cubic (fcc) copper (Cu), body-centered cubic (bcc) tungsten (W), and hexagonal close packing (hcp) magnesium (Mg). Our numerical results not only quantify the uncertainty of these constitutive models in stress-strain curve, but also analyze the global sensitivity of the underlying constitutive parameters with respect to the initial yield behavior, which may be helpful for robust constitutive model calibration works in the future.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Transforming a Simple Structure Model to Represent a Complex Dynamic System with Unknown Boundary Restraints

Imposing a boundary condition on a structure can significantly alter its dynamic properties. However, sometimes the specifics of the new boundary conditions are not known. When the effects of a boundary condition are uncertain or there is not enough information, engineers need to excite the complex structure to obtain these modified properties. In order to experimentally obtain the new properties, engineers need multiple experiments and many outputs for interpolation in order to sufficiently represent the entire structure. In this study, the researchers attached a stinger to a cantilever beam, acting as a new transverse restraint of unknown properties. This paper presents a conversion expression that predicts the dynamic behavior of any point in the system with the new boundary condition. This expression relies only on one impact hammer experiment with one output and the model of the stinger-free cantilever beam, referred to as the simple structure. Researchers estimated the Transfer Function (TRF) of the beam and compared it with an experimentally measured TRF to validate the method. The mean absolute error of the estimated TRF compared to the experimental TRF is 1.99 dB. This demonstrates the use of the proposed method for estimating unmeasured TRFs in a system with an uncertain boundary condition using a single input, single output (SISO) test and a model of the simple structure.

42 ENGINEERING↗
DOE OSTI2024

GIS Supported Optimal Site Selection for Coastal Structure Integrated Wave Energy Converters: Preprint

There is an urgent need for adaptative engineering towards more resilient coastal communities, and Coastal Structure Integrated Wave Energy Converters (CSI-WECs) are a promising solution. CSI-WECs are wave energy converters (WECs) that are built into coastal protection structures, such as breakwaters. These devices provide the dual benefits of coastal protection and local energy production, and unlike other WECs, maximizing energy production is not always the main objective. CSI-WECs are located near the shore, where the wave resource is lower, thus site selection for these devices differs from the typical offshore WECs. Other attributes of a site that may be more important than wave power include existing coastal structures, port proximity, electric transmission line proximity, and location of disadvantaged communities. Geospatial information systems (GIS) interfaces can be used to easily visualize geospatial data that represents these difference kinds of criteria important for the determination of optimal marine energy sites. Multi-Criteria Decision Analysis (MCDA) is a geospatial analysis method that allows for the evaluation of multiple, usually overlapping, criteria. This project applies GIS-based MCDA methods to two distinct case studies in Puerto Rico and California for CSI-WEC site selection. The two study sites contrast in terms of wave resource, coastal hazards, and local energy needs. This research demonstrates the utility of applying an MCDA framework within GIS to facilitate efficient site selection for devices with unique characteristics in different use cases.

coastal protection↗
DOE OSTI2017

Structural Evidence of a Major Conformational Change Triggered by Substrate Binding in DapE Enzymes: Impact on the Catalytic Mechanism

In this paper, the X-ray crystal structure of the dapE-encoded N-succinyl-l,l-diaminopimelic acid desuccinylase from Haemophilus influenzae (HiDapE) bound by the products of hydrolysis, succinic acid and l,l-DAP, was determined at 1.95 Å. Surprisingly, the structure bound to the products revealed that HiDapE undergoes a significant conformational change in which the catalytic domain rotates ~50° and shifts ~10.1 Å (as measured at the position of the Zn atoms) relative to the dimerization domain. This heretofore unobserved closed conformation revealed significant movements within the catalytic domain compared to that of wild-type HiDapE, which results in effectively closing off access to the dinuclear Zn(II) active site with the succinate carboxylate moiety bridging the dinculear Zn(II) cluster in a μ-1,3 fashion forming a bis(μ-carboxylato)dizinc(II) core with a Zn–Zn distance of 3.8 Å. Surprisingly, His194.B, which is located on the dimerization domain of the opposing chain ~10.1 Å from the dinuclear Zn(II) active site, forms a hydrogen bond (2.9 Å) with the oxygen atom of succinic acid bound to Zn2, forming an oxyanion hole. As the closed structure forms upon substrate binding, the movement of His194.B by more than ~10 Å is critical, based on site-directed mutagenesis data, for activation of the scissile carbonyl carbon of the substrate for nucleophilic attack by a hydroxide nucleophile. Employing the HiDapE product-bound structure as the starting point, a reverse engineering approach called product-based transition-state modeling provided structural models for each major catalytic step. Finally, these data provide insight into the catalytic reaction mechanism and also the future design of new, potent inhibitors of DapE enzymes.

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

De novo designed ice-binding proteins from twist-constrained helices

Attaining molecular-level control over solidification processes is a crucial aspect of materials science. To control ice formation, organisms have evolved bewildering arrays of ice-binding proteins (IBPs), but these have poorly understood structure–activity relationships. We propose that reverse engineering using de novo computational protein design can shed light on structure–activity relationships of IBPs. We hypothesized that the model alpha-helical winter flounder antifreeze protein uses an unusual undertwisting of its alpha-helix to align its putative ice-binding threonine residues in exactly the same direction. We test this hypothesis by designing a series of straight three-helix bundles with an ice-binding helix projecting threonines and two supporting helices constraining the twist of the ice-binding helix. Our findings show that ice-recrystallization inhibition by the designed proteins increases with the degree of designed undertwisting, thus validating our hypothesis, and opening up avenues for the computational design of IBPs.

Science & Technology - Other Topics↗
DOE OSTI2019

Multi-degree of Freedom Energy Analysis for Identification of Failure Risk in Structural Components Subjected to Random Vibration and Shock Loading

When designing or analyzing a mechanical system, energy quantities provide insight into the severity of shock and vibration environments; however, the energy methods in the literature do not address localized behavior because energy quantities are usually computed for an entire structure. The main objective of this paper is to show how to compute the energy in the components of a mechanical system. The motivation for this work is that most systems fail functionally due to component failure, not because the primary structure was overloaded, and the ability to easily compute the spatial distribution of energy helps identify failure sensitive components. The quantity of interest is input energy. That input energy can be decoupled modally is well known. What is less appreciated is that input energy can be computed at the component level exactly, using the component effective modal mass. We show the steady state input energy can be decomposed both spatially and modally and computed using input power spectra. A numerical example illustrates the spatial and modal decomposition of input energy and its utility in identifying components at risk of damage in random vibration and shock environments. Our work shows that the modal properties of the structure and the spectral content of the input must be considered together to assess damage risk. Because input energy includes absorbed energy as well as relative kinetic energy and dissipated energy, it is the recommended energy quantity for assessing the severity for both random vibration and shock environments on a structure.

42 ENGINEERING↗
DOE OSTI2019

Semicoherent oxide heterointerfaces: Structure, properties, and implications

In the quest for enhanced functionality of all sorts, nanostructured materials are becoming ever more common. This is particularly true of oxide/oxide heterostructures in which the high density of interfaces has been implicated in enhanced properties and used to engineer strain in oxide composite structures. These interfaces are often characterized by a network of misfit dislocations that relieve the lattice mismatch strain between the two materials, and these dislocations themselves are often suggested as the source of either enhancements or degradation of properties. Despite the importance and pervasiveness of misfit dislocations, however, there is still much that is unknown about their structure and properties, particularly in oxide/oxide heterostructures. Here, we give a perspective on the importance of these dislocation networks and the need to interrogate their impact on functionality.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Predicting Microstructural Void Nucleation in Discontinuous Fiber Composites through Coupled in-situ X-ray Tomography Experiments and Simulations

Composite materials have become widely used in engineering applications, in order to reduce the overall weight of structures while retaining their required strength. In this work, a composite material consisting of discontinuous glass fibers in a polypropylene matrix is studied at the microstructural level through coupled experiments and simulations, in order to uncover the mechanisms that cause damage to initiate in the microstructure under macroscopic tension. Specifically, we show how hydrostatic stresses in the matrix can be used as a metric to explain and predict the exact location of microvoid nucleation that occurs during damage initiation within the composite’s microstructure. Furthermore, this work provides evidence that hydrostatic stresses in the matrix can lead to coupled microvoid nucleation and early fiber breakage, and that small fragments of fibers can play an important role in the process of microvoid nucleation. These results significantly improve our understanding of the mechanics that drive the initiation of damage in the complex microstructures of discontinuous fiber reinforced thermoplastics, while also allowing scientists and engineers to predict the microstructural damage behavior of these composites at sub-fiber resolution and with high accuracy.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Re Doping in 2D Transition Metal Dichalcogenides as a New Route to Tailor Structural Phases and Induced Magnetism

Alloying in 2D results in the development of new, diverse, and versatile systems with prospects in bandgap engineering, catalysis, and energy storage. Tailoring structural phase transitions using alloying is a novel idea with implications in designing all 2D device architecture as the structural phases in 2D materials such as transition metal dichalcogenides are correlated with electronic phases. In this paper, this study develops a new growth strategy employing chemical vapor deposition to grow monolayer 2D alloys of Re-doped MoSe 2 with show composition tunable structural phase variations. The compositions where the phase transition is observed agree well with the theoretical predictions for these 2D systems. Finally, it is also shown that in addition to the predicted new electronic phases, these systems also provide opportunities to study novel phenomena such as magnetism which broadens the range of their applications.

2D materials↗
DOE OSTI2019

Magnetism in iridate heterostructures leveraged by structural distortions

Abstract Fundamental control of magnetic coupling through heterostructure morphology is a prerequisite for rational engineering of magnetic ground states. We report the tuning of magnetic interactions in superlattices composed of single and bilayers of SrIrO 3 inter-spaced with SrTiO 3 in analogy to the Ruddlesden-Popper series iridates. Magnetic scattering shows predominately c -axis antiferromagnetic orientation of the magnetic moments for the bilayer, as in Sr 3 Ir 2 O 7 . However, the magnetic excitation gap, measured by resonant inelastic x-ray scattering, is quite different between the two structures, evidencing a significant change in the stability of the competing magnetic phases. In contrast, the single layer iridate hosts a more bulk-like gap. We find these changes are driven by bending of the c -axis Ir-O-Ir bond, which is much weaker in the single layer, and subsequent local environment changes, evidenced through x-ray diffraction and magnetic excitation modeling. Our findings demonstrate how large changes in the magnetic interactions can be tailored and probed in spin-orbit coupled heterostructures by engineering subtle structural modulations.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Taming Molecular Folding: Anion-Templated Foldamers with Tunable Quaternary Structures

Higher-order foldamers represent a unique class of supramolecules at the forefront of molecular design. Herein we control quaternary folding using a novel approach that combines halogen bonding (XBing) and hydrogen bonding (HBing). We present the first anion-templated double helices induced by halogen bonds (XBs) and stabilized by “hydrogen bond enhanced halogen bonds” (HBeXBs). Our findings demonstrate that the number and orientation of hydrogen bond (HB) and XB donors significantly affect the quaternary structure and guest selectivity of two similar oligomers. Finally, this research offers new design elements to engineer foldamers and tailor their quaternary structure for specific guest binding.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗