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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

The structural fate of lipid nanoparticles in the extracellular matrix

Drug-loaded liposomes are the most successful nanomedicine to date, with multiple FDA-approved systems for a myriad of diseases. While liposome circulation time in blood and retention in tissues have been studied in detail, the structural fate of liposomes—and nanoparticles in general—in the body has not been extensively investigated. In this work, we explore the interactions of liposomes with synthetic and natural hydrogel materials to understand how the natural extracellular matrix influences liposome structural characteristics. Small angle X-ray scattering, confocal microscopy, and cryogenic transmission electron microscopy data demonstrate that poly(ethylene glycol) (PEG), gelatin, alginate, and Matrigel ® hydrogels cause 200 nm liposomes of 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC) to transform into micrometer-sized aggregates. These aggregates are composed of multilamellar vesicles around 100 nm in diameter with a mean interlamellar separation of 5.5 nm. Protecting the liposomes with a corona of PEG damps this restructuring effect, making the multilamellar vesicles less stable. We attribute this unilamellar to multilamellar transition to an osmotic driving force from the hydrogel environment. This lipid restructuring has broad ramifications in the design and use of nanomedicines, and in understanding the fate and function of natural lipid-based materials within the tissue microenvironment.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Investigation of radiated-power for low aspect ratio fusion plasmas

Investigating radiated power in fusion plasmas is of utmost importance to understand the effect of undesired impurities, such as metals, in present devices, or also desired impurities, such as noble gasses, to purposefully radiate a large fraction of power in future devices. These studies are especially important for high Z impurities which will play a crucial role in future generation fusion pilot plants. In this work, we have developed a power radiation analysis module, which is used to investigate 2D distributions of impurity densities and radiated power asymmetries caused due to both plasma rotation and the cooling rate dependence on temperature profile for the cases of experimental NSTX plasmas and designed scenarios for the spherical tokamak advanced reactor (STAR), both being low aspect ratio tokamaks. Two different atomic databases have been tested during this work to study their impact on the radiated power distribution, especially for high Z impurities. Also in PRAM, self-consistent calculations of two-dimensional electron, main ion, and impurity ion densities are carried out using one-dimensional input density, temperature, and rotation profiles. In the case of NSTX, discharges with high rotation of ∼ 170 km s, measured with charge exchange recombination spectroscopy, have been investigated. Rotation-induced charge separation, leading to an electrostatic potential, is calculated iteratively to a self-consistent solution while testing high Z impurities to observe any 2D asymmetry in the core radiated power due to centrifugal forces. The STAR design, being much larger (R = 4 m), is projected to have a much lower rotation, and is shown to have low rotation-induced asymmetries, on the order of ten percent or less, between the low field and high field sides. However, another effect not due to rotation but to the dependence of impurity cooling rates on temperature can lead to radiation peaking off-axis, near the plasma edge. This effect is noticeable for argon in NSTX, for example, but can also be enhanced for certain impurities at much higher temperatures projected for STAR (T e0 ~ 32 keV), for example for undesired tungsten or possibly desired xenon.

NSTX↗
DOE OSTI2024

Community Data Contribution to M.E.T.A. with ATF-relevant Hydrided Zr cladding (Coated and Uncoated)

Since the aftermath of the Fukushima Daiichi loss-of-coolant accident, accident-tolerant fuel (ATF) claddings have been developed to improve the coping times in such events. However, the mechanical performance of ATF cladding is crucial in ensuring that it does not negatively impact the mechanical integrity during all other stages of the nuclear fuel cycle, and the validity of the existing safe operating margins must be verified. However, due to the cladding’s tube geometry and textured anisotropy, determination of apparent mechanical properties under certain deformation paths is challenging. In the uniaxial hoop direction, for instance, the measured mechanical stresses include frictional forces caused by loading mandrels or varying deformation paths in the sample during traditional ring tensile testing. This experimental difficulty is exacerbated by the specimen size. However, addressing these challenges enables irradiation separate-effects investigations in which the materials can be inserted in reactors like the High Flux Isotope Reactor, and reducing the material consumption of commercially irradiated material allows for further post-irradiation examinations. Despite the advantages of reduced-scale mechanical testing, any drawbacks from new specimen geometries must be evaluated, and uncertainties from specimen preparation, setup, and analysis methodologies must be understood.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Arrested coarsening and large density fluctuations in driven particle mixtures in two dimensions

Abstract Using molecular dynamics simulations, we study a driven, nonadditive binary mixture of spherical particles confined to move in two dimensions and immersed in an explicit solvent consisting of point particles with purely repulsive interactions. We show that, without a drive, the mixture of spherical particles phase separates and coarsens with kinetics consistent with an Ising-like conserved dynamics. Conversely, when the drive is applied, the coarsening is arrested and the system develops large density fluctuations. We show that the drive creates domains of a characteristic size which decreases with an increasing force. Furthermore, we find that these domains are anisotropic and can be oriented either parallel or perpendicular to the drive direction. Finally, we connect our findings to existing theories of strongly-driven systems, pointing out the importance of introducing the explicit solvent particles to break the Galilean invariance of the system.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Multimorphic Materials: Spatially Tailoring Mechanical Properties via Selective Initiation of Interpenetrating Polymer Networks

Access to multimaterial polymers with spatially localized properties and robust interfaces is anticipated to enable new capabilities in soft robotics, such as smooth actuation for advanced medical and manufacturing technologies. Here, orthogonal initiation is used to create interpenetrating polymer networks (IPNs) with spatial control over morphology and mechanical properties. Base catalyzes the formation of a stiff and strong polyurethane, while blue LEDs initiate the formation of a soft and elastic polyacrylate. IPN morphology is controlled by when the LED is turned “on”, with large phase separation occurring for short time delays (≈1–2 min) and a mixed morphology for longer time delays (>5 min), which is supported by dynamic mechanical analysis, small angle X-ray scattering, and atomic force microscopy. Through tailoring morphology, tensile moduli and fracture toughness can be tuned across ≈1–2 orders of magnitude. Furthermore, a simple spring model is used to explain the observed mechanical behavior. Photopatterning produces “multimorphic” materials, where morphology is spatially localized with fine precision (<100 µm), while maintaining a uniform chemical composition throughout to mitigate interfacial failure. As a final demonstration, the fabrication of hinges represents a possible use case for multimorphic materials in soft robotics.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Role of Fe Doping on Local Structure and Electrical and Magnetic Properties of PbTiO 3

In this work, the local structure and multiferroic properties of iron-doped lead titanate (PbTi 1-x Fe x O 3-δ ) samples was investigated over the entire composition range (x = 0-1). Inherent polarization in PbTiO 3 decreases due to Fe 3+ incorporation up to the solubility limit (x similar to 0.3), although homogeneous doping persists only up to x = 0.1. Ti prefers highly distorted oxygen octahedra for any x value, while Fe prefers more symmetric O-deficient polyhedra (Fe-O n ). The charge compensating oxygen vacancies induce local tilting of the Fe-O n polyhedra beyond a critical x value (x ≥ 0.2), promoting magnetic interaction between two adjacent Fe atoms. The strain induced by local heterogeneity could act as a coupling force between magnetic and ferroelectric properties. Fe-rich clusters evolve into ferromagnetic PbFe 12 O 19 with increased Fe doping. PbTi 1-x Fe x O 3-δ (x ≥ 0.3) samples therefore have separate origins for the ferroelectric (PbTi 1-x Fe x O 3-δ ) and magnetic (PbFe 12 O 19 ) phases.

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

Effect of Block Length on the Properties of Multiblock Polysulfone-Poly(diallylpiperidinium hydroxide) Anion Exchange Membranes

Research in anion exchange membranes (AEM)s has continued with the development of materials bearing base stable cations. Designing AEMs that microphase separate into hydroxide conductive, hydrophilic domains within a hydrophobic and mechanically robust matrix has been shown to be successful for improving AEM performance. A series of multiblock polysulfone-poly(diallylpiperidinium hydroxide) copolymers (PSf-PDApipOH) of similar hydrophobic/hydrophilic composition was prepared in which the molecular weight of the hydroxide conducting PDApipOH segments was varied. The variable hydrophilic segment molecular weight was designed to assess the impact on microphase separation, hydroxide conductivity, and water management. The multiblock copolymers investigated were prepared by condensation polymerization of preformed4-fluorophenyl sulfone terminated poly(diallylpiperidinium hexafluorophosphate) (PDApipPF6) oligomers with polysulfone monomers. The structure-property relationship between the molecular weight of the conductive PDApipOH segments and AEM performance was demonstrated by evaluation of the microphase separation, water uptake, and hydroxide conductivity. Further, membranes fabricated from the polysulfone-poly(diallylpiperidinium hexafluorophosphate) (PSf-PDApipPF6) multiblock copolymers were shown to form well-connected conductive domains by SAXS and atomic force microscopy experiments. The PSf-PDApipOH membranes were highly conductive with the maximum hydroxide conductivity reaching 62.9 mS∙cm -1 at 60°C and 95% relative humidity. Furthermore, it was demonstrated that the conductivity increased with increasing PDApipOH segment molecular weight.

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

Reweighting configurations generated by transferable, machine learned models for protein sidechain backmapping

Multiscale modeling requires the linking of models at different levels of detail, with the goal of gaining accelerations from lower fidelity models while recovering fine details from higher resolution models. Communication across resolutions is particularly important in modeling soft matter, where tight couplings exist between molecular-level details and mesoscale structures. While multiscale modeling of biomolecules has become a critical component in exploring their structure and self-assembly, backmapping from coarse-grained to fine-grained, or atomistic, representations presents a challenge, despite recent advances through machine learning. A major hurdle, especially for strategies utilizing machine learning, is that backmappings can only approximately recover the atomistic ensemble of interest. We demonstrate conditions for which backmapped configurations may be reweighted to exactly recover the desired atomistic ensemble. By training separate decoding models for each sidechain type, we develop an algorithm based on normalizing flows and geometric algebra attention to autoregressively propose backmapped configurations for any protein sequence. Critical for reweighting with modern protein force fields, our trained models include all hydrogen atoms in the backmapping and make probabilities associated with atomistic configurations directly accessible. We also demonstrate, however, that reweighting is extremely challenging despite state-of-the-art performance on recently developed metrics and generation of configurations with low energies in atomistic protein force fields. Through detailed analysis of configurational weights, we show that machine-learned backmappings must not only generate configurations with reasonable energies, but also correctly assign relative probabilities under the generative model. These are broadly important considerations in generative modeling of atomistic molecular configurations.

Monroe, Jacob I. [Univ. of Arkansas, Fayetteville,↗
DOE OSTI2019

Method for separating solids suspended or entrained in a liquid

A method of separating solids from a slurry or suspension is disclosed. The method includes: providing a slurry or suspension containing solids and liquid to an input port of a first side of a filter, the filter providing a filtering size between 2 microns and 70 microns; providing a liquid discharge port on a second side of the filter which receives the liquid that passes through the filter; and separating the solids from the liquid by pressing the solids into a pressure regulating solids discharge port on the first side of the filter, thereby compacting solids on the first side of the filter, forcing at least some of the liquid of the slurry or suspension through the first side of the filter to the second side of the filter causing pressure regulated solids to be discharged through a pressure regulating solids discharge port into a pressurized chamber.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Edge States Drive Exciton Dissociation in Ruddlesden–Popper Lead Halide Perovskite Thin Films

Efficient photovoltaic cells based on thin films of solution-processed 2D Ruddlesden–Popper hybrid perovskites (RPPs) represent an exciting breakthrough due to their enhanced tunability and chemical stability relative to those fabricated from 3D phases. However, reports of efficient charge separation and current collection are in apparent contradiction with the well-known enhancement of the exciton binding energy in multilayered halide perovskites, which should lower the device’s internal quantum efficiency and voltage. This controversy has led to various proposals for the electronic and physical structure of RPP thin films, including phase inhomogeneity as the driving force for exciton dissociation and transport. We address this apparent paradox in high-quality hot-cast RPP films by correlating ultrafast transient absorption spectroscopy with X-ray scattering measurements. We show that a hot-casting fabrication method produces highly phase pure n = 3 (BA) 2 (MA) n-1 Pb n I 3n+1 RPP structures. The high-phase purity and large grain sizes allow us to observe vertical transport of excitons via a diffusive process and allow us to determine that charge separation is primarily driven by dissociation at surface localized subgap electronic states. Furthermore, we analyze the differential absorption kinetics in films of varying thickness to directly determine that the excitonic diffusion constant is ~0.18 cm 2 s –1 . We propose that a surface localized structural distortion, observed using surface selective grazing incidence X-ray scattering measurements, is responsible for the creation of the surface localized defect states. We find that the density and spatial distribution of these defect states is a function of preparation conditions.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Accelerated Discovery of CH 4 Uptake Capacity Metal–Organic Frameworks Using Bayesian Optimization

Abstract High‐throughput computational studies for discovery of metal–organic frameworks (MOFs) for separations and storage applications are often limited by the costs of computing thermodynamic quantities. Recent such studies at the time of writing may use ab initio results for a narrow selection of MOFs or empirical force‐field methods for larger selections. Here, a proof‐of‐concept study is conducted using Bayesian optimization on CH 4 uptake capacity of hypothetical MOFs for an existing dataset (Wilmer et al., Nature Chem. 2012, 4 , 83). It is shown that less than 0.1% of the database needs to be screened with the Bayesian optimization approach to recover the top candidate MOFs. This opens the possibility for efficient screening of MOF databases using accurate ab initio calculations for future adsorption studies on a minimal subset of MOFs. Furthermore, Bayesian optimization and the surrogate model presented here can offer interpretable material design insights and the framework will be applicable in the context of other target properties.

Taw, Eric↗
DOE OSTI2025

Modeling the Behavior of Complex Aqueous Electrolytes Using Machine Learning Interatomic Potentials: The Case of Sodium Sulfate

Understanding the structure and thermodynamics of solvated ions is essential for advancing applications in electrochemistry, water treatment, and energy storage. While ab initio molecular dynamics methods are highly accurate, they are limited by short accessible time and length scales whereas classical force fields struggle with accuracy. Herein, we explore the structure and thermodynamics of complex monovalent-divalent ion pairs using Na 2 SO 4 (aq) as a case study by applying a machine learning interatomic potential (MLIP) trained on density functional theory (DFT) data. Our MLIP-based approach reproduces key bulk properties such as density and radial distribution functions of water. We provide the hydration structure of the sodium and sulfate ions in the 0.1–2 M concentration range and the one-dimensional and two-dimensional potentials of mean force for the sodium–sulfate ion pairing at the low concentration limit (0.1 M), which are inaccessible to DFT. At low concentrations, the sulfate ion is strongly solvated, leading to the stabilization of solvent-separated ion pairs over contact ion pairs. Minimum energy pathway analysis revealed that coordinating two sodium ions with a sulfate ion is a multistep process whereby the sodium ions coordinate to the sulfate ion sequentially. Finally, we demonstrate that MLIPs allow the study of solvated ions beyond simple monovalent pairs with DFT-level accuracy in their low concentration limit (0.1 M) via statistically converged properties from ns-long simulations.

anions↗
DOE OSTI2022

Splitting the Ring: Impact of Ortho and Meta Pi Conjugation Pathways through Disjointed [8]Cycloparaphenylene Electronic Materials

In this report, we describe the synthesis and electronic properties of small-molecule and polymeric [8]cycloparaphenylenes ([8]CPPs) with disjointed pi conjugated substituents. Arylene-ethynylene linkers were installed on opposite sides of the [8]CPP nanohoop as separated by three phenyl units on either side such that the monomer systems have syn (C2 symmetry) and anti (C1 symmetry) conformers with a small energy gap (0.1-0.6 kcal/mol). This disjoined substitution pattern necessarily forces delocalization through and around the CPP radial structure. We demonstrate new electronic states from this radial/linear mixing in both the small molecules and the pi extended polymers. Quantum chemical calculations reveal these electronic processes to arise from multiple operative radial/linear conjugation pathways, as the disjoint pattern results in both ortho and meta connections to the CPP ring. Furthermore, these results affirm the unique nature of hybrid radial and linear pi electron delocalization operative in these new conjugation pathways.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Spatiotemporal Adaptive Passive Direct Air Capture

Carbon Collect Inc., along with Arizona State University, the Electric Power Research Institute (EPRI), PM Group, and Trimeric Corporation, completed an initial design of a commercial-scale, passive direct air capture (DAC) system termed “carbon trees” that will capture, separate, and store at least 100,000 tonnes/year of carbon dioxide (CO2) from air (net basis). Passive DAC is unique among DAC technologies in that passive air delivery by wind avoids the energy penalty of forced convection. Carbon Collect Inc.’s sorbent-agnostic approach offers the flexibility to choose sorbents for a wide range of climates. A combination of steam, low-grade heat, and vacuum releases the CO2 from the sorbent, which is extracted from the chamber and purified and compressed for geological storage. A commercial carbon tree forest combines the output of several thousand trees for compression and purification with high heat and energy integration. The project team prepared an initial engineering design package for each of three geographically diverse host sites throughout the United States to better understand the effect of local/regional ambient conditions on DAC system performance and project costs. A techno-economic analysis, life cycle analysis, business case analysis, and an environmental, health, and safety risks assessment were also completed for each of the three geographically diverse host sites.

14 SOLAR ENERGY↗
DOE OSTI2023

Mixed Nanosphere Assemblies at a Liquid–Liquid Interface

The in-plane packing of gold (Au), polystyrene (PS), and silica (SiO 2 ) spherical nanoparticle (NP) mixtures at a water–oil interface is investigated in situ by UV–vis reflection spectroscopy. All NPs are functionalized with carboxylic acid such that they strongly interact with amine-functionalized ligands dissolved in an immiscible oil phase at the fluid interface. This interaction markedly increases the binding energy of these nanoparticle surfactants (NPSs). The separation distance between the Au NPSs and Au surface coverage are measured by the maximum plasmonic wavelength (λ max ) and integrated intensities as the assemblies saturate for different concentrations of non-plasmonic (PS/SiO 2 ) NPs. Further, as the PS/SiO 2 content increases, the time to reach intimate Au NP contact also increases, resulting from their hindered mobility. λ max changes within the first few minutes of adsorption due to weak attractive inter-NP forces. Additionally, a sharper peak in the reflection spectrum at NP saturation reveals tighter Au NP packing for assemblies with intermediate non-plasmonic NP content. Grazing incidence small angle X-ray scattering (GISAXS) and scanning electron microscopy (SEM) measurements confirm a decrease in Au NP domain size for mixtures with larger non-plasmonic NP content. The results demonstrate a simple means to probe interfacial phase separation behavior using in situ spectroscopy as interfacial structures densify into jammed, phase-separated NP films.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Physical discovery in representation learning via conditioning on prior knowledge

Recent advances in electron, scanning probe, optical, and chemical imaging and spectroscopy yield bespoke data sets containing the information of structure and functionality of complex systems. In many cases, the resulting data sets are underpinned by low-dimensional simple representations encoding the factors of variability within the data. The representation learning methods seek to discover these factors of variability, ideally further connecting them with relevant physical mechanisms. However, generally, the task of identifying the latent variables corresponding to actual physical mechanisms is extremely complex. Here, we present an empirical study of an approach based on conditioning the data on the known (continuous) physical parameters and systematically compare it with the previously introduced approach based on the invariant variational autoencoders. The conditional variational autoencoder (cVAE) approach does not rely on the existence of the invariant transforms and hence allows for much greater flexibility and applicability. Interestingly, cVAE allows for limited extrapolation outside of the original domain of the conditional variable. However, this extrapolation is limited compared to the cases when true physical mechanisms are known, and the physical factor of variability can be disentangled in full. We further show that introducing the known conditioning results in the simplification of the latent distribution if the conditioning vector is correlated with the factor of variability in the data, thus allowing us to separate relevant physical factors. We initially demonstrate this approach using 1D and 2D examples on a synthetic data set and then extend it to the analysis of experimental data on ferroelectric domain dynamics visualized via piezoresponse force microscopy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Real-Time Coupling of Geographically Distributed Research Infrastructures: Taxonomy, Overview, and Real-World Smart Grid Applications

Novel concepts enabling a resilient future power system and their subsequent experimental evaluation are experiencing a steadily growing challenge: large scale complexity and questionable scalability. The requirements on a research infrastructure (RI) to cope with the trends of such a dynamic system therefore grow in size, diversity and costs, making the feasibility of rigorous advancements questionable by a single RI. Analysis of large scale system complexity has been made possible by the real-time coupling of geographically separated RIs undertaking geographically distributed simulations (GDS), the concept of which brings the equipment, models and expertise of independent RIs, in combination, to optimally address the challenge. This article presents the outputs of IEEE PES Task Force on Interfacing Techniques for Simulation Tools towards standardization of GDS as a concept. First, the taxonomy for setups utilized for GDS is established followed by a comprehensive overview of the advancements in real-time couplings reported in literature. The overview encompasses fundamental technological design considerations for GDS. The article further presents four application oriented case studies (real-world implementations) where GDS setups have been utilized, demonstrating their practicality and potential in enabling the analysis of future complex power systems.

distributed laboratories↗
DOE OSTI2023

Investigating Electric Field and Light Induced Degradation in Perovskite Solar Cells through Nanometer-Scale Potential Imaging

Electric field and light induced degradations in perovskite solar cells were evaluated through nanometer-scale potential imaging across the device by using in-situ Kelvin probe force microscopy (KPFM). We derived the electric field profile from potential profiles at different bias voltages to evaluate the locations and quality of junctions across the device. We found relative changes in electric field peak intensity at the HTL/perovskite and perovskite/ETL interfaces upon stressing devices separately under voltage or light. KPFM results during 12-hour stress/rest cycling under electrical bias show both reversible and irreversible changes in the device's interfacial fields. We also observed change in the electric field profile between control and degraded devices after 100 hours of stress/rest cycling under light. Our results demonstrate how nanometer-scale potential imaging can be used to understand the impacts of external electric fields and light soaking on both irreversible degradation and reversible metastability in perovskite solar cells.

Kelvin probe force microscopy↗