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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Sequence-Structure–Property Relationships in Short-Chain Polyesters: How Primary Structure Governs Macroscopic Performance

While polymer properties are fundamentally linked to their nanostructure, the influence of monomer sequence remains less understood than stereochemical factors like tacticity. This study examines how sequence distribution affects the thermal behavior and morphology of homo- and copolyesters, specifically comparing polymers derived from constitutionally identical monomers but with varying degrees of sequence regularity depending on monomer structure or polymerization selectivity. Our findings show that increasing sequence defects progressively diminish thermal stability, crystallinity, melting temperatures, and morphological order. As new materials become more compositionally complex, this work underscores the importance of sequence control in the design of advanced polymers for emerging applications.

Bocharova, Vera [Oak Ridge National Laboratory (OR↗
DOE OSTI2024

Design of intrinsically disordered protein variants with diverse structural properties

Intrinsically disordered proteins (IDPs) perform a broad range of functions in biology, suggesting that the ability to design IDPs could help expand the repertoire of proteins with novel functions. Computational design of IDPs with specific conformational properties has, however, been difficult because of their substantial dynamics and structural complexity. We describe a general algorithm for designing IDPs with specific structural properties. We demonstrate the power of the algorithm by generating variants of naturally occurring IDPs that differ in compaction, long-range contacts, and propensity to phase separate. We experimentally tested and validated our designs and analyzed the sequence features that determine conformations. We show how our results are captured by a machine learning model, enabling us to speed up the algorithm. Our work expands the toolbox for computational protein design and will facilitate the design of proteins whose functions exploit the many properties afforded by protein disorder.

Science & Technology - Other Topics↗
NASA NTRS1975

Structural Properties and Estimation of Delay Systems

Two areas in the theory of delay systems were studied: structural properties and their applications to feedback control, and optimal linear and nonlinear estimation. The concepts of controllability, stabilizability, observability, and detectability were investigated. The property of pointwise degeneracy of linear time-invariant delay systems is considered. Necessary and sufficient conditions for three dimensional linear systems to be made pointwise degenerate by delay feedback were obtained, while sufficient conditions for this to be possible are given for higher dimensional linear systems. These results were applied to obtain solvability conditions for the minimum time output zeroing control problem by delay feedback. A representation theorem is given for conditional moment functionals of general nonlinear stochastic delay systems, and stochastic differential equations are derived for conditional moment functionals satisfying certain smoothness properties.

Kwong, R. H. S.↗
DOE OSTI2024

Tutorial on In Situ and Operando (Scanning) Transmission Electron Microscopy for Analysis of Nanoscale Structure–Property Relationships

In situ and operando (scanning) transmission electron microscopy [(S)TEM] is a powerful characterization technique that uses imaging, diffraction, and spectroscopy to gain nano-to-atomic scale insights into the structure–property relationships in materials. This technique is both customizable and complex because many factors impact the ability to collect structural, compositional, and bonding information from a sample during environmental exposure or under application of an external stimulus. In the past two decades, in situ and operando (S)TEM methods have diversified and grown to encompass additional capabilities, higher degrees of precision, dynamic tracking abilities, enhanced reproducibility, and improved analytical tools. Much of this growth has been shared through the community and within commercialized products that enable rapid adoption and training in this approach. This tutorial aims to serve as a guide for students, collaborators, and nonspecialists to learn the important factors that impact the success of in situ and operando (S)TEM experiments and assess the value of the results obtained. As this is not a step-by-step guide, readers are encouraged to seek out the many comprehensive resources available for gaining a deeper understanding of in situ and operando (S)TEM methods, property measurements, data acquisition, reproducibility, and data analytics.

(S)TEM↗
NASA NTRS1994

Determinants of Long Bone Structural Properties

The objective of our research is to determine whether a non-invasive determination of long bone cross-sectional areal properties using only the mineral component of bone accurately predicts the true structural properties. In this study section properties of a whole long bone were compared using two methods: (1) special analysis of bone densitometry data, and (2) experimental determination of flexural rigidities from bone surface strain measurements during controlled loading.

Cleek, T. M.↗
DOE OSTI2022

The influence of molecular design on structure–property relationships of a supramolecular polymer prodrug

Supramolecular self-assemblies of hydrophilic macromolecules functionalized with hydrophobic, structure-directing components have long been used for drug delivery. In these systems, loading of poorly soluble compounds is typically achieved through physical encapsulation during or after formation of the supramolecular assembly, resulting in low encapsulation efficiencies and limited control over release kinetics, which are predominately governed by diffusion and carrier degradation. To overcome these limitations, amphiphilic prodrugs that leverage a hydrophobic drug as both the therapeutic and structure-directing component can be used to create supramolecular materials with higher loading and controlled-release kinetics using biodegradable or enzymatically cleavable linkers. Here, we report the design, synthesis, and characterization of a library of supramolecular polymer prodrugs based on poly(ethylene glycol) (PEG) and the proregenerative drug 1,4-dihydrophenonthrolin-4-one-3-carboxylic acid (DPCA). Structure–property relationships were elucidated through experimental characterization of prodrug behavior in both the wet and dry states using scattering techniques and electron microscopy and corroborated by coarse-grained modeling. Molecular architecture and the hydrophobic-to-hydrophilic ratio of PEG–DPCA conjugates strongly influenced their physical state in water, ranging from fully soluble to supramolecular spherical assemblies and nanofibers. Molecular design and supramolecular structure, in turn, were shown to dramatically alter hydrolytic and enzymatic release and cellular transport of DPCA. In addition to potentially expanding therapeutic options for DPCA through control of supramolecular assemblies, the design principles elaborated here may inform the development of other supramolecular prodrugs based on hydrophobic small-molecule compounds.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
NASA NTRS1998

Process-Parameter-Dependent Optical and Structural Properties of ZrO2MgO Mixed-Composite Films Evaporated from the solid Solution

The process-parameter-dependent optical and structural properties of ZrO2MgO mixed-composite material have been investigated. Optical properties were derived from spectrophotometric measurements. By use of atomic force microscopy, x-ray diffraction analysis, and energy-dispersive x-ray (EDX) analysis, the surface morphology, grain size distributions, crystallographic phases, and process-dependent material composition of films have been investigated. EDX analysis made evident the correlation between the oxygen enrichment in the films prepared at a high level of oxygen pressure and the very low refractive index. Since oxygen pressure can be dynamically varied during a deposition process, coatings constructed of suitable mixed-composite thin films can benefit from continuous modulation of the index of refraction. A step modulation approach is used to develop various multilayer-equivalent thin-film devices.

Sahoo, N. K.↗
DOE OSTI2023

Artificial Neural Network Models for Octane Number and Octane Sensitivity: A Quantitative Structure Property Relationship Approach to Fuel Design

Octane sensitivity (OS), defined as the research octane number (RON) minus the motor octane number (MON) of a fuel, has gained interest among researchers due to its effect on knocking conditions in internal combustion engines. Compounds with a high OS enable higher efficiencies, especially within advanced compression ignition engines. RON/MON must be experimentally tested to determine OS, requiring time, funding, and specialized equipment. Thus, predictive models trained with existing experimental data and molecular descriptors (via quantitative structure-property relationships (QSPRs)) would allow for the preemptive screening of compounds prior to performing these experiments. Here, the present work proposes two methods for predicting the OS of a given compound: using artificial neural networks (ANNs) trained with QSPR descriptors to predict RON and MON individually to compute OS (derived octane sensitivity (dOS)), and using ANNs trained with QSPR descriptors to directly predict OS. Twenty-five ANNs were trained for both RON and MON and their test sets achieved an overall 6.4% and 5.2% error, respectively. Twenty-five additional ANNs were trained for both dOS and OS; dOS calculations were found to have 15.3% error while predicting OS directly resulted in 9.9% error. A chemical analysis of the top QSPR descriptors for RON/MON and OS is conducted, highlighting desirable structural features for high-performing molecules and offering insight into the inner mathematical workings of ANNs; such chemical interpretations study the interconnections between structural features, descriptors, and fuel performance showing that connectivity, structural diversity, and atomic hybridization consistently drive fuel performance.

09 BIOMASS FUELS↗
DOE OSTI2022

Sparse Data Machine Learning Integration with Theory, Experiment and Uncertainty Quantification: Process-Structure-Property-Performance of Friction Deformation Processing

Computer vision and deep learning tools that advance the ability to establish processing-structure-property-performance (PSPP) relations are presented. The Bayesian binning method for image segmentation enables quantitative analysis of microstructural features in an automated way, while the analysis of shapes and relative orientation of these features reveals local deformation maps indicative of both, material flow and residual stresses due to materials processing. The deep learning method leads to the previous knowledge agnostic mapping of empirically observed microstructural zones in friction stir welding (FSW) process and synthetic microstructure generation capability that is statistically equivalent to experimentally collected data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Materials structure–property factorization for identification of synergistic phase interactions in complex solar fuels photoanodes

Abstract Properties can be tailored by tuning composition in high-order composition spaces. For spaces with complex phase behavior, modeling the properties as a function of composition and phase distribution remains a formidable challenge. We present materials structure–property factorization (MSPF) as an approach to automate modeling of such data and identify synergistic phase interactions. MSPF is an interpretable machine learning algorithm that couples phase mapping via Deep Reasoning Networks (DRNets) to matrix factorization-based modeling of the representative properties of each phase in a dataset. MSPF is demonstrated for Bi–Cu–V oxide photoanodes for solar fuel generation, which contains 25 different phase combinations and correspondingly exhibits complex composition-structure-photoactivity relationships. Comparing the measured photoactivity to a learned model for non-interacting phases, synergistic phase interactions are identified to guide further photoactivity optimization and understanding. MSPF identifies synergistic interactions of a BiVO 4 -like phase with both Cu 2 V 2 O 7 -like and CuV 2 O 6 -like phases, creating avenues for understanding complex photoelectrocatalysts.

36 MATERIALS SCIENCE↗
NASA NTRS1978

A method for determining structural properties of RCC thermal protection material

A method was developed for evaluation and prediction of effects of oxidation of the graphitic substrate on structural properties of Reinforced Carbon-Carbon (RCC) thermal protection material. Test specimens of RCC material were exposed to successive periods of convective heating in a plasma-jet facility to simulate the chemical reactions of Shuttle atmospheric entry. After each period of testing, the test specimen mass loss and performance in a nondestructive flexure test were determined. A computational model of the RCC specimen was developed for the NASA Structural Analysis (NASTRAN) program and validated by comparison of calculated and experimental results of flexure tests. The elastic moduli and ultimate loads in tension and compression were then computed for various levels of substrate oxidation.

Wakefield, R. M.↗
NASA NTRSDate not supplied

Uncertainty Quantification and Sensitivity Analysis in Process-Structure-Property Simulations for Laser Powder Bed Fusion Additive Manufacturing

Process variations and process-induced defects like porosity cause significant uncertainty in the microstructure and mechanical behavior of additively manufactured metals. Establishing process-structure-property (PSP) relationships and quantifying uncertainty using experiments alone is costly, especially for structural applications where mechanical allowables must be established for qualification and certification. This work presents a PSP simulation framework for laser powder bed fusion with a focus on uncertainty quantification through probabilistic calibration and multi-fidelity uncertainty propagation. Motivated by phenomenological input parameters related to grain nucleation and growth that are difficult to characterize, a global sensitivity analysis (GSA) is completed. Through GSA, the most important input parameters are identified based on their influence on the statistical distributions of microstructural metrics that influence mechanical behavior, including grain size, morphology, and crystallographic texture. The results provide insight on what experiments are necessary to quantify and control PSP uncertainties, particularly those associated with the more challenging input parameters.

additive manufacturing↗
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 OSTI2021

Structure-Property Relationships and Idiosyncrasies of Bulk, 2D Hybrid Lead Bromide Perovskites

Bulk, 2D hybrid lead bromide perovskites comprise a robust family of halide perovskites with a rich structural and photophysical chemistry witnessed thus far. In an attempt to boost focus on systematically charting the phase space of 2D lead bromide perovskites, it is timely and critical to review the structure-property relationships that are emerging in this family of materials. In this review, we assess the multitude of (100)-orientated lead bromide perovskites, as well as the idiosyncratic (110)-orientated members. We examine the underpopulated phase space of bulk, thick-layer (n>1) lead bromide perovskites, highlighting several examples of structures violating Goldschmidt's tolerance factor with large organic spacers in the cuboctahedral perovskite cages. The narrow and broadband emission is discussed, along with the developed optoelectronic profile of bulk, lead bromide perovskites, as yet. Lastly, we summarize the integration of 2D lead bromide perovskites in optoelectronic devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1991

Structure-property study of keto-ether polyimides

As part of an on-going effort to develop an understanding of how changes in the chemical structure affect polymer properties, an empirical study was performed on polyimides containing only ether and/or carbonyl connecting groups in the polymer backbone. During the past two decades the structure-property relationships in linear aromatic polyimides have been extensively investigated. More recently, work has been performed to study the effect of isomeric attachment of keto-ether polyimides on properties such as glass transition temperature and solubility. However, little work has been reported on the relation of polyimide structure to mechanical properties. The purpose of this study was to determine the effect of structural changes in the backbone of keto-ether polyimides on their mechanical properties, specifically, unoriented thin film tensile properties. This study was conducted in two stages. The purpose of the initial stage was to examine the physical and mechanical properties of a representative group (four) of polyimide systems to determine the optimum solvent and cure cycle requirements. These optimum conditions were then utilized in the second stage to prepare films of keto-ether polyimides which were evaluated for mechanical and physical properties. All of the polyimides were prepared using isomers of oxydianiline (ODA) and diaminobenzophenone (DABP) in combination with 3,3',4,4'-benzophenonetetracarboxylic dianhydride (BTDA) and 4,4'-oxydiphthalic anhydride (ODPA).

Dezern, James F.↗
NASA NTRS2002

Investigation of Structural Properties of Carbon-Epoxy Composites Using Fiber-Bragg Gratings

Fiber Bragg-gratings are embedded in carbon-epoxy laminates as well as bonded on the surface of cylindrical structures fabricated out of such composites. Structural properties of such composites is investigated. The measurements include stress-strain relation in laminates and Poisson's ratio in several specimens with varying orientation of the optical fiber Bragg-sensor with respect to the carbon fiber in an epoxy matrix. Additionally, Bragg gratings are bonded on the surface of cylinders fabricated out of carbon-epoxy composites and longitudinal and hoop strain on the surface is measured.

Grant, J.↗
DOE OSTI2023

Chemical structure–property relationships in nanocelluloses

Abstract Nanocelluloses, nanoscale cellulosic particles or fibrils, are an appealing class of nanomaterials with enormous potential for sustainable development. They have great promise to target some of the 17 Sustainable Development Goals outlined by the United Nations. Nanocelluloses are derived from the most abundant biopolymer in the world, cellulose, which have multiple hydroxyl groups on their surface, enabling a vast range of chemical modifications. The interplay between the chemical structure and physicochemical properties of nanocelluloses is crucial to engineering the next generation of green, functional nanomaterials. In this review paper, we provide a comprehensive account of the structure–property relationships in nanocelluloses, which may establish the basis for the design of precision bio‐based materials. Chemical modifications of nanocelluloses, including hydrolysis, oxidation, esterification, amidation, and polymer grafting, provide an array of chemical and physical properties that open opportunities in a diverse spectrum of applications. We review how chemical modifications affect the physicochemical properties of nanocelluloses, such as thermal stability, hydrophobicity, and dispersibility in nonpolar media. Understanding nanocellulose chemical structure–property relationships is integral to the development of sustainable material platforms based on the most renewable biopolymer on earth.

59 BASIC BIOLOGICAL SCIENCES↗