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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Ultrasound Thermal Field Imaging of Opaque Fluids

We have initiated an experimental program to develop an ultrasound system for non-intrusively imaging the thermal field in opaque fluids under an externally imposed temperature gradient. Many industrial processes involve opaque fluids, such as molten metals, semiconductors, and polymers, often in situations in which thermal gradients are important. For example, one may wish to understand semiconductor crystal growth dynamics in a Bridgman apparatus. Destructive testing of the crystal after the process is completed gives only indirect information about the fluid dynamics of the formation process. Knowledge of the coupled thermal and velocity fields during the growth process is then essential. Most techniques for non-intrusive velocity and temperature measurement in fluids are optical in nature, and hence the fluids studied must be transparent. In some cases (for example, LDV (laser Doppler velocimetry) and PIV (particle imaging velocimetry)) the velocities of small neutrally buoyant seed particles suspended in the fluid, are measured. Without particle seeding one can use the variation of the index of refraction of the fluid with temperature to visualize, through interferometric, Schlieren or shadowgraph techniques, the thermal field. The thermal field in turn gives a picture of the pattern existing in the fluid. If the object of study is opaque, non-optical techniques must be used. In this project we focus on the use of ultrasound, which propagates easily through opaque liquids and solids. To date ultrasound measurements have almost exclusively relied on the detection of sound scattered from density discontinuities inside the opaque material of interest. In most cases it has been used to visualize structural properties, but more recently the ultrasound Doppler velocimeter has become available. As in the optical case, it relies on seed particles that scatter Doppler shifted sound back to the detector. Doppler ultrasound techniques are, however, not useful for studying convective fluid flow in crystal growth, because particle seeding is unacceptable and flow velocities are typically too low to be resolved, and may be even lower in microgravity conditions where buoyancy forces are negligible. We will investigate a different use of ultrasound to probe the flows of opaque fluids non-intrusively and without the use of seed particles: our goal is to ultrasonically visualize the thermal field of opaque fluids with relatively high spatial resolution. The proposed technique relies upon the variation of sound speed with temperature of the fluid. A high frequency ultra-sound pulse passing through a fluid-filled chamber will traverse the chamber in a time determined by the relevant chamber dimension and the temperature of the fluid through which the pulse passes. With high time-resolution instrumentation that compares the excitation signal with the received pulse we can detect the influence of the fluid temperature on the pulse travel time. This is effectively an interferometric system, which in its optical form is an extremely sensitive approach to measuring thermal fields in fluids. Moreover, the temperature dependence of sound velocity in liquid metals is comparable to the temperature dependence of the speed of light required for accurate interferometric thermal images in transparent fluids. With an array of transducers scanned electronically a map of the thermal field over the chamber could be produced. An alternative approach would be to use the ultrasound analog of the shadowgraph technique. In the optical version, collimated light passes through the fluid, where it is focused or defocused locally by temperature field induced variations of the index of refraction. The resulting image reveals the thermal field through the spatial pattern of light intensity variations. By analogy, an ultrasound plane wave traversing an opaque fluid sample would be also locally focused or defocused depending on the speed of sound variations, giving rise to spatial variations in sound intensity that will reveal the thermal field pattern. These approaches could be applied to any situation in which temperature differences are expected to occur, and will rapidly provide information about the flow that simply cannot be obtained by any current intrusive or non-intrusive diagnostic technique. As materials processing in microgravity matures it will become increasingly important to have available simple and versatile diagnostic tools, such as we will develop, for studying the flows of opaque fluids under thermal forcing.

Andereck, C. David↗
DOE OSTI2024

Accelerating uncertainty quantification in incremental dynamic analysis using dimension reduction-based surrogate modeling

We propose a surrogate modeling framework based on dimension reduction to facilitate the quantification of seismic risk of structural systems in performance-based earthquake engineering. The framework adopts incremental dynamic analysis (IDA) for addressing hazard variability, and promotes significant computational efficiency improvement for propagating epistemic uncertainties associated with the structural models. It utilizes both linear and nonlinear dimension reduction approaches, equipped with inverse mappings, to learn a functional between the input parameter space (e.g., the epistemic uncertainties of the structure) to the high-dimensional output space created through the IDA implementation across different ground motions and seismic intensity levels. Polynomial chaos expansion is adopted as the surrogate model to learn this functional in the reduced space. A nine-story steel moment-resisting frame with uncertain structural properties is used as a testbed. Furthermore, we select the seismic fragility curves as a measure of the structure’s seismic performance, since it provides an estimate of the probability of entering specified damage states for given levels of ground shaking.

42 ENGINEERING↗
DOE OSTI2022

Generative Adversarial Networks and Mixture Density Networks-Based Inverse Modeling for Microstructural Materials Design

Abstract There are two broad modeling paradigms in scientific applications: forward and inverse. While forward modeling estimates the observations based on known causes, inverse modeling attempts to infer the causes given the observations. Inverse problems are usually more critical as well as difficult in scientific applications as they seek to explore the causes that cannot be directly observed. Inverse problems are used extensively in various scientific fields, such as geophysics, health care and materials science. Exploring the relationships from properties to microstructures is one of the inverse problems in material science. It is challenging to solve the microstructure discovery inverse problem, because it usually needs to learn a one-to-many nonlinear mapping. Given a target property, there are multiple different microstructures that exhibit the target property, and their discovery also requires significant computing time. Further, microstructure discovery becomes even more difficult because the dimension of properties (input) is much lower than that of microstructures (output). In this work, we propose a framework consisting of generative adversarial networks and mixture density networks for inverse modeling of structure–property linkages in materials, i.e., microstructure discovery for a given property. The results demonstrate that compared to baseline methods, the proposed framework can overcome the above-mentioned challenges and discover multiple promising solutions in an efficient manner.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Learning interpretable surface elasticity properties from bulk properties via neural network equation learners

Surface elasticity is central to understanding the mechanics and stability of surfaces and interfaces. It is characterized by quantities such as surface tension, residual surface stress, and surface stiffness. However their analytical expressions are typically difficult to derive from atomistic data, and depend strongly on modeling choices. This work presents a neural network-based equation learner which combines customized activation functions and connection-based pruning to discover parsimonious, closed-form equations for surface elasticity from atomistic simulations. Applying the method to seven face-centered cubic (FCC) metals, our equation learner uncovers interpretable equations that describe both low-Miller index and high-Miller index surface properties, capturing long-tail property distributions accurately. The discovered expressions are decoupled into two components: a universal, geometry-driven orientation function, and material-specific baseline coefficients. We find that lower-order properties such as surface tension are fundamentally geometry dependent, while higher-order properties such as surface stress and elasticity show more complex geometry and material dependence. We also relate material dependent coefficients to bulk properties, forming a clear map from bulk material properties to surface elasticity. Overall, this approach demonstrates that interpretable neurosymbolic machine learning can bridge the gap between atomistic simulations and physical laws, enabling the discovery of generalizable structure–property relationships for materials science phenomena such as surface elasticity.

Equation learning↗
DOE OSTI2023

Impedance-Based Detection of NO 2 Using Ni-MOF-74: Influence of Competitive Gas Adsorption

Chemically robust, low-power sensors are needed for the direct electrical detection of toxic gases. Metal–organic frameworks (MOFs) offer exceptional chemical and structural tunability to meet this challenge, though further understanding is needed regarding how coadsorbed gases influence or interfere with the electrical response. To probe the influence of competitive gases on trace NO 2 detection in a simulated flue gas stream, a combined structure–property study integrating synchrotron powder diffraction and pair distribution function analyses was undertaken, to elucidate how structural changes associated with gas binding inside Ni-MOF-74 pores correlate with the electrical response from Ni-MOF-74-based sensors. Data were evaluated for 16 gas combinations of N 2 , NO 2 , SO 2 , CO 2 , and H 2 O at 50 °C. Fourier difference maps from a rigid-body Rietveld analysis showed that additional electron density localized around the Ni-MOF-74 lattice correlated with large decreases in Ni-MOF-74 film resistance of up to a factor of 6 × 10 3 , observed only when NO 2 was present. These changes in resistance were significantly amplified by the presence of competing gases, except for CO 2 . Without NO 2 , H 2 O rapidly (<120 s) produced small (1–3×) decreases in resistance, though this effect could be differentiated from the slower adsorption of NO 2 by the evaluation of the MOF’s capacitance. Furthermore, samples exposed to H 2 O displayed a significant shift in lattice parameters toward a larger lattice and more diffuse charge density in the MOF pore. Evaluating the Ni-MOF-74 impedance in real time, NO 2 adsorption was associated with two electrically distinct processes, the faster of which was inhibited by competitive adsorption of CO 2 . Together, this work points to the unique interaction of NO 2 and other specific gases (e.g., H 2 O, SO 2 ) with the MOF’s surface, leading to orders of magnitude decrease in MOF resistance and enhanced NO2 detection. Finally, understanding and leveraging these coadsorbed gases will further improve the gas detection properties of MOF materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Evidence for In-Plane Electrical Polarization in 3R-β’-In 2 Se 3 Thin Films Grown by Molecular Beam Epitaxy

β-In 2 Se 3 has been identified as a potential ferroelectric. This work describes the growth of β-In 2 Se 3 via molecular beam epitaxy along with a description of its properties, including the search for switchable polarization in 3R-β’-In2Se3. The thin-film morphology, crystal structure, and phase maps of β-In 2 Se 3 on Si(111) and Al 2 O 3 (0001) were evaluated by atomic force microscopy, X-ray diffraction, and Raman spectroscopy as a function of the atomic Se/In flux ratio and growth temperature. Smooth β-In 2 Se 3 thin films were successfully realized on Si(111) at a substrate temperature of 150 °C using a Se/In flux ratio of 5.7, as well as on Al 2 O 3 (0001) at 450 °C using a Se/In flux ratio of 5.5. Scanning transmission electron microscopy (STEM) confirms the 3R polytype of β-In 2 Se 3 in films on both substrates, with a minor disorder associated with the 2H polytype at the interface. Indications of in-plane Se atom displacements characteristic of the 3R-β’-In 2 Se 3 polytype were found by STEM and second harmonic generation analysis in films on Al 2 O 3 (0001), but not in films on Si(111). Furthermore, attempts at electrical polarization switching did not produce compelling evidence for ferroelectricity. Instead, electrical transport measurements demonstrated locally varying anisotropic responses with the applied electric fields along different in-plane directions, with some hysteresis associated with the trapping of charges.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Autonomous Nanoparticle Synthesis Guided by In Situ Multiscale Structural Characterization

Autonomous synthesis platforms promise rapid exploration of vast parameter spaces; yet, integrating in situ structural characterization in closed-loop synthesis optimization remains challenging. We demonstrate a realization of such a closed-loop platform coupled with a droplet-flow microreactor, in situ X-ray scattering methods (SAXS/WAXS), and Gaussian process optimization to synthesize citrate-reduced Au nanoparticles with targeted characteristics. The system efficiently explored ∼19,000 synthesis recipes through 365 experiments, achieving precise control over size (4–60 nm) and polydispersity (σ < 0.11) across large citrate/gold ratios, exceeding traditional synthesis boundaries (1–10). Beyond confirming classical Turkevich–Frens trends, partial-dependence analysis revealed strong nonlinear coupling among precursor, citrate, and pH effects. Combining quantitative SAXS/WAXS analysis with electron microscopy characterization, we uncovered that crystallite size (d c ) and particle size (d) follow d c = 0.18d + β, where synthesis chemistry controls the intercept β while maintaining a universal slope. This parallel-band structure enables independent tuning of crystallite domain size at fixed particle diameter through a combination of chloride, gold precursor, citrate, and pH contributions (cross-validated Spearman ρ = 0.7 ± 0.1). High-resolution electron microscopy shows multiple lattice-fringe orientations within single particles, directly confirming polycrystalline domains and the ability to tune d c at the fixed d. The platform’s validation includes indistinguishable static versus flowing measurements, stable droplet transport at 100 °C, and <5% run-to-run variation, establishing a robust framework for mapping and controlling multiscale nanoparticle structure across expansive chemical spaces. In conclusion, the developed closed-loop platform can be applied to a borad range of nanosyntheis processes.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Time-resolved Brownian tomography of single nanocrystals in liquid during oxidative etching

Colloidal nanocrystals inherently undergo structural changes during chemical reactions. The robust structure-property relationships, originating from their nanoscale dimensions, underscore the significance of comprehending the dynamic structural behavior of nanocrystals in reactive chemical media. Moreover, the complexity and heterogeneity inherent in their atomic structures require tracking of structural transitions in individual nanocrystals at three-dimensional (3D) atomic resolution. In this study, we introduce the method of time-resolved Brownian tomography to investigate the temporal evolution of the 3D atomic structures of individual nanocrystals in solution. The methodology is applied to examine the atomic-level structural transformations of Pt nanocrystals during oxidative etching. The time-resolved 3D atomic maps reveal the structural evolution of dissolving Pt nanocrystals, transitioning from a crystalline to a disordered structure. Our study demonstrates the emergence of a phase at the nanometer length scale that has received less attention in bulk thermodynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Disentangling multiple scattering with deep learning: application to strain mapping from electron diffraction patterns

Abstract A fast, robust pipeline for strain mapping of crystalline materials is important for many technological applications. Scanning electron nanodiffraction allows us to calculate strain maps with high accuracy and spatial resolutions, but this technique is limited when the electron beam undergoes multiple scattering. Deep-learning methods have the potential to invert these complex signals, but require a large number of training examples. We implement a Fourier space, complex-valued deep-neural network, FCU-Net, to invert highly nonlinear electron diffraction patterns into the corresponding quantitative structure factor images. FCU-Net was trained using over 200,000 unique simulated dynamical diffraction patterns from different combinations of crystal structures, orientations, thicknesses, and microscope parameters, which are augmented with experimental artifacts. We evaluated FCU-Net against simulated and experimental datasets, where it substantially outperforms conventional analysis methods. Our code, models, and training library are open-source and may be adapted to different diffraction measurement problems.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Inverse mapping of properties to composition through generative modeling for designing molten salts

Generative modeling (GM) has been increasingly used for the inverse design and optimization of materials, yet its application to molten salt mixtures remains unexplored despite how a successful approach to the inverse design of molten salts would contribute to efficiently exploiting their customizability and unlocking their advantages in applications, such as energy production and energy storage. This work presents a workflow for the inverse design of molten salts with targeted density values, addressing the challenge of representing these complex mixtures in GM. A dataset of critically evaluated molten salt densities is used to train a variational autoencoder coupled with a predictive deep neural network, which then can be used to generate new molten salt compositions with desired density values. The effectiveness of the approach is demonstrated by designing mixtures with distinct densities and validating the predicted values using ab initio molecular dynamics simulations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

The hierarchical structure of organic mixed ionic–electronic conductors and its evolution in water

Polymeric organic mixed ionic–electronic conductors underpin several technologies in which their electrochemical properties are desirable. These properties, however, depend on the microstructure that develops in their aqueous operational environment. We investigated the structure of a model organic mixed ionic–electronic conductor across multiple length scales using cryogenic four-dimensional scanning transmission electron microscopy in both its dry and hydrated states. Four-dimensional scanning transmission electron microscopy allows us to identify the prevalent defects in the polymer crystalline regions and to analyse the liquid crystalline nature of the polymer. The orientation maps of the dry and hydrated polymers show that swelling-induced disorder is mostly localized in discrete regions, thereby largely preserving the liquid crystalline order. Therefore, the liquid crystalline mesostructure makes electronic transport robust to electrolyte ingress. Furthermore, this study demonstrates that cryogenic four-dimensional scanning transmission electron microscopy provides multiscale structural insights into complex, hierarchical structures such as polymeric organic mixed ionic–electronic conductors, even in their hydrated operating state.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Ground state property calculations of LiH n complexes using IBM Qiskit’s quantum simulator

In this study, the variational quantum eigensolver (VQE) on a quantum simulator is used in calculating ground state electronic structure properties of the LiH n , n = 1–3, complexes including their singly charged ions. Results calculated using classical electronic structure algorithms are also included. We investigate the use of the unitary coupled cluster with singles and doubles (UCCSD) Ansatz using VQE within Qiskit and compare results to full configuration interaction (FCI) calculations. Computed ground state energies, electron affinities, ionization potentials, and dipole moments are considered. We report the first-of-its-kind simulated quantum computing results of selected LiH n species and use the parity orbital to qubit mapping scheme. We find that VQE/UCCSD results are comparable to classical coupled clusters with singles and doubles for all considered systems with respect to FCI. A VQE calculation cost evaluation is included in which we evaluate performance using both Jordan–Wigner and parity orbital to qubit mapping schemes. We also discuss some of the current limitations of utilizing VQE for the study of chemical systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Origin of insulating and nonferromagnetic SrRuO 3 monolayers

The electro-magnetic properties of ultrathin epitaxial ruthenate films have long been the subject of debate. Here we combine experimental with theoretical investigations of (SrTiO 3 ) 5 -(SrRuO 3 ) n -(SrTiO 3 ) 5 (STO 5 -SRO n -STO 5 ) heterostructures with n = 1 and 2 unit cells, including extensive atomic-resolution scanning-transmission-electron-microscopy imaging, electron-energy-loss-spectroscopy chemical mapping, as well as transport and magneto-transport measurements. The experimental data demonstrate that the STO 5 -SRO 2 -STO 5 heterostructure is nearly stoichiometric, metallic, and ferromagnetic with T C ~ 128 K, even though it lacks the characteristic bulk-SRO octahedral tilts and matches the cubic STO structure. In contrast, the STO 5 -SRO 1 -STO 5 heterostructure features Ru-Ti intermixing in the RuO 2 layer, also without octahedral tilts, but is accompanied by a loss of metallicity and ferromagnetism. Density-functional-theory calculations show that stoichiometric n = 1 and n = 2 heterostructures are metallic and ferromagnetic with no octahedral tilts, while non-stoichiometry in the Ru sublattice in the n = 1 case opens an energy gap and induces antiferromagnetic ordering. Furthermore, the results indicate that the observed non-stoichiometry is the cause of the observed loss of metallicity and ferromagnetism in the n = 1 case.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Jahn–Teller-driven phase segregation in Mn x Co 3–x O 4 spinel thin films

Transition metal spinel oxides comprised of earth-abundant Mn and Co have long been explored for their use in catalytic reactions and energy storage. However, understanding functional properties can be challenging due to differences in sample preparation and the ultimate structural properties of the materials. Epitaxial thin film synthesis provides a novel means of producing precisely controlled materials to explore the variations reported in the literature. In this work, Mn x Co 3–x O 4 samples from x = 0 to x = 1.28 were synthesized through molecular beam epitaxy and characterized to develop a material properties map as a function of stoichiometry. Here, films were characterized via in situ x-ray photoelectron spectroscopy, x-ray diffraction, scanning transmission electron microscopy, and polarized K-edge x-ray absorption spectroscopy. Mn cations within this range were found to be octahedrally coordinated, in line with an inverse spinel structure. Samples largely show mixed Mn 3+ and Mn 4+ character with evidence of phase segregation tendencies with the increasing Mn content and increasing Mn 3+ formal charge. Phase segregation may occur due to structural incompatibility between cubic and tetragonal crystal structures associated with Mn 4+ and Jahn–Teller active Mn 3+ octahedra, respectively. Our results help in explaining the reported differences across samples in these promising materials for renewable energy technologies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Rheo-Structural Spectroscopy: Fingerprinting the In Situ Response of Fluids to Arbitrary Flow Fields

The objectives of this project were to develop new sample environments, measurement methodologies and associated modeling tools for characterizing the structural response to arbitrarily complex processing flows using small angle scattering, and to apply these new tools for understanding the fundamental physics governing the structuring of anisotropic particulate and polymeric materials under flow histories and conditions relevant to industrial processing flows. The research resulted in the development and implementation of a new sample environment, the fluidic four roll mill (FFoRM), for in situ small angle neutron and X-ray scattering (SANS/SAXS) measurements. These measurements are capable of generating large data sets that “fingerprint” how a complex fluid responds to a wide range of flow histories involving time variations in deformation type and rate. New modeling tools were developed to extract detailed microstructural information from such data sets, including orientation distribution functions and interparticle correlation functions, as well as reduced-order parametric descriptors of these high-dimensional functions that can be used to readily map, visualize and interpret a fluid’s structural response to its flow history. These new tools were applied to a range of model materials involving elongated particle suspensions in order to provide new insights into the physics of how flow couples with orientational and structural order in complex flows, particularly under non-dilute conditions for which no accurate theories currently exist. Using these investigations, we elucidated a number of new insights into the fundamental phenomena driving such process-structure-property relationships. These findings provide guidance for the further development of rheological models, and ultimately can inform the rational and model-based design of flow processes to achieve optimized orientational ordering that is key to the properties and function of a wide range of energy-relevant materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Accelerating Biomimetic Solar - Energy Harvesting: Mapping the Interaction Landscape of Plasmonic-Excitonic Hybrid Nanosystems (Final Report)

In general, excitonic and plasmonic nanoscale materials in close proximity show high potential for significant breakthroughs in energy related materials research. The interactions between these two kinds of materials result in coupled optical transitions (plexcitons), distinct from those of both the individual exciton and plasmon as well as from those of the sum of their constituents (synergistic effects). By linking together materials-research and physical-research approaches, this project contributes to a concerted approach on nanomaterials energy research. The project’s overall goal is to accelerate the development of well-defined plexcitonic model systems consisting of carefully engineered plasmonic and excitonic nanomaterial— essential for both gaining a fundamental understanding of plexcitonic nanomaterials and the development of novel design principles for biomimetic solar energy harvesting. During the 3-year project period and the terminal renewal with limited support for a 12-month period, we successfully synthesized and characterized (1) a robust excitonic nanomaterial and (2) a library of plasmonic nanoparticles as well as developed (3) a microfluidic platform for homogenous nanosynthesis as summarized below: (1) Robust Excitonic Nanomaterial. Supramolecular assemblies are Nature’s most successful material system for solar energy harvesting. However, photovoltaic devices based on artificial supramolecular assemblies continue to be stymied by disappointing efficiencies and poor stability. The conceptual failure may lie in current solar cell architectures, which rely on solidifying supramolecular assemblies as an ensemble into a solid matrix, neglecting the intrinsic fragility of the assemblies’ internal structure, thus disrupting or even destroying their delicate optoelectronic properties, that is, delicate Frenkel excitonic properties. Supramolecular assemblies may finally serve as usable light harvesting material systems for solar energy conversion technologies, only if they meet the following criteria: (a) Stability, that is, the fragile structure including its delicate Frenkel excitonic character needs to be stable, (b) Robustness, that is, resistant against elevated and fluctuating temperatures, and (c) Viability for device integration, that is, capable of being immobilized onto solid substrates. Here, by developing a nanocomposite via a tunable, cage-like scaffold design, we successfully provided stable supramolecular nanocomposites, that inhabit robust Frenkel excitons despite harming environmental conditions such as extreme heat stress. (2) Library of Plasmonic Nanoparticles. Naturally, current models describing plasmonic hybrid quantum states—plasmonic hybridizations—parallel those developed for molecular orbitals, equating individual plasmonic nanostructures with “atoms” and the plasmonic nanoassemblies with “molecules.” In analogy to organic synthesis, a suitably robust fabrication method would allow for “atom-like” manipulation of “molecule-like” plasmonic nanoassemblies; of high value for next-generation energy nanotechnologies. Despite this frequent comparison, current plasmonic nanoassembly fabrication methods favor top-down templating over wet-chemical synthesis, however, achieving precise control over nanostructure’s geometry and surface characteristics remain an art and a scientific challenge. The conceptual failure may lie in the current wet-chemical synthesis paradigm, as it relies on the accessibility of a multi-dimensional synthesis parameter space through limited, rather one-dimensional synthesis procedures by employing step-by-step approaches. Solution-based nanoarchitectonics for rational design of precisely built plasmonic nanoassemblies via solution-based fabrication may finally be possible only if multi-dimensional syntheses approaches are available that allow for comprehensive control over the plasmonic nanomaterials’ (a) Structural Properties and (b) Surface Properties. Here, by developing an innovative multidimensional 1,3-propanediol based polyol synthesis, we successfully provided control over the plasmonic building-block’s geometry (size and shape) together with its surface characteristics. Our results present a critical step toward the vision of a “periodic table-like” system for plasmonic materials based on straightforward wet-chemical syntheses for energy nanotechnologies. Developing deliberate modifications on this synthesis, we generated a library of plasmonic nanostructures covering the vast parameter space—opening the door for fundamental investigation of plexcitonic model systems. (3) Microfluidic Platform for Homogenous Nanosynthesis. Control over structural properties of plexcitonic nanocomposites remains a challenge due to current limitations in nanosynthesis techniques. Slight variations in nanostructure’s geometry impact their optoelectronic properties, demanding precise synthesis beyond the capabilities of solution-based (batch) synthesis processes. In contrast, the small, confined liquid volumes used in microfluidics—a reaction technique where the manipulation of fluids takes place in channels with dimensions of tens of micrometers—allows for homogenous synthesis conditions, providing excellent control of the reaction and, as a result, of the materials’ geopmetry and composition. However, thus far, the majority of plexcitonic systems has been developed via batch synthesis. Here, by successfully developing a two-channel microreactor, our microfluidic-supported synthesis approach combines the advantages of both microfluidics and batch platforms, allowing for precise spatio-temporal control over all synthesis parameters opening the possibility for homogenous nanosythnesis of well-defined plexcitonic model systems.

14 SOLAR ENERGY↗
DOE OSTI2023

An Investigation of Nanoindentation as Quality Control [Slides]

Nanoindentation Continuous Stiffness Measurement (CSM) mapping, and Strain Rate Jump Testing (SRJT) proved effective to highlight and visualize the extent of property differences between the samples. From the analysis, Lot A has a significant dead zone at its center, especially when compared with the cross section of Lot B. Quick identification of property issues from one of the two feed stocks, both of which fit the specification. Mechanical performance was connected to the microstructure. Thus, using the structure-property results, it is noted that the processing of Lot A may have been insufficient. Nanoindentation allows for the sampling of quality control variables such as hardness and modulus in a short time span at high resolution, which is cheaper and faster than traditional strength experiments (tension and compression tests).

36 MATERIALS SCIENCE↗
DOE OSTI2023

Exploring internal structures and properties of terpolymer fibers via real-space characterizations

While significant research has investigated the processing and properties of high-performance terpolymer fibers, much remains to be understood about the internal nano- and microstructures of these fibers, and how these morphologies relate to fiber properties. Here we use a focused ion beam notch technique and multifrequency atomic force microscope mapping to characterize the internal structure and local mechanical properties within Technora ® fibers. We find a highly fibrillated structure that appears to connect with both the fiber’s molecular chemistry and full-fiber mechanical properties. In addition, through detailed comparisons with Kevlar ® K29 fibers, we find remarkable differences between the internal structures of the two fibers, and posit connections between our measurements and multifunctional performance studies from the literature.

36 MATERIALS SCIENCE↗