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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Soft matter roadmap

Soft materials are usually defined as materials made of mesoscopic entities, often self-organised, sensitive to thermal fluctuations and to weak perturbations. Archetypal examples are colloids, polymers, amphiphiles, liquid crystals, foams. The importance of soft materials in everyday commodity products, as well as in technological applications, is enormous, and controlling or improving their properties is the focus of many efforts. From a fundamental perspective, the possibility of manipulating soft material properties, by tuning interactions between constituents and by applying external perturbations, gives rise to an almost unlimited variety in physical properties. Together with the relative ease to observe and characterise them, this renders soft matter systems powerful model systems to investigate statistical physics phenomena, many of them relevant as well to hard condensed matter systems. Understanding the emerging properties from mesoscale constituents still poses enormous challenges, which have stimulated a wealth of new experimental approaches, including the synthesis of new systems with, e.g. tailored self-assembling properties, or novel experimental techniques in imaging, scattering or rheology. Theoretical and numerical methods, and coarse-grained models, have become central to predict physical properties of soft materials, while computational approaches that also use machine learning tools are playing a progressively major role in many investigations. This Roadmap intends to give a broad overview of recent and possible future activities in the field of soft materials, with experts covering various developments and challenges in material synthesis and characterisation, instrumental, simulation and theoretical methods as well as general concepts.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Data-driven particle dynamics: Structure-preserving coarse-graining for emergent behavior in non-equilibrium systems

Multiscale systems are ubiquitous in science and technology, but are notoriously challenging to simulate as short spatiotemporal scales must be appropriately linked to emergent bulk physics. When expensive high-dimensional dynamical systems are coarse-grained into low-dimensional models, the entropic loss of information leads to emergent physics which are dissipative, history-dependent, and stochastic. To machine learn coarse-grained dynamics from time-series observations of particle trajectories, we propose a framework using the metriplectic bracket formalism that preserves these properties by construction; most notably, the framework guarantees discrete notions of the first and second laws of thermodynamics, conservation of momentum, and a discrete fluctuation-dissipation balance crucial for capturing non-equilibrium statistics. We introduce the mathematical framework abstractly before specializing to a particle discretization. As labels are generally unavailable for entropic state variables, we introduce a novel self-supervised learning strategy to identify emergent structural variables. We validate the method on benchmark systems and demonstrate its utility on two challenging examples: (1) coarse-graining star polymers at challenging levels of coarse-graining while preserving non-equilibrium statistics, and (2) learning models from high-speed video of colloidal suspensions that capture coupling between local rearrangement events and emergent stochastic dynamics. We provide open-source implementations in both PyTorch and LAMMPS, enabling large-scale inference and extensibility to diverse particle-based systems.

Computational Engineering, Finance, and Science (c↗
DOE OSTI2023

An artificial intelligence’s interpretation of complex high-resolution in situ transmission electron microscopy data

Complicated nano- and atomic-scale processes with sub-angstrom spatial resolution and millisecond time resolution visualized by in situ transmission electron microscopy (TEM) are often highly dynamical and time consuming to analyze and interpret. Here, we report how variational autoencoders (VAEs) can provide an artificial intelligence’s interpretation of high-resolution in situ TEM data by condensing and deconvoluting complicated atomic-scale dynamics into a latent space with reduced dimensionality. We designed a VAE model with high latent dimensions capable of deconvoluting information from complex high-resolution TEM data. We demonstrate how this model, with high latent dimensions trained on atomically resolved TEM images of lead sulfide (PbS) nanocrystals, is able to capture movements and perturbations of periodic lattices in both simulated and real in situ TEM data. Importantly, the VAE model shows the capability of detecting and deconvoluting dynamical nanoscale physical processes, such as the rotation of crystal lattices and intra-particle ripening during the annealing of semiconductor nanocrystals.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Modeling Structural Colors from Disordered One-Component Colloidal Nanoparticle-Based Supraballs Using Combined Experimental and Simulation Techniques

Bright, saturated structural colors in birds have inspired synthesis of self-assembled, disordered arrays of assembled nanoparticles with varied particle spacings and refractive indices. However, predicting colors of assembled nanoparticles, and thereby guiding their synthesis, remains challenging due to the effects of multiple scattering and strong absorption. In this work, we use a computational approach to first reconstruct the nanoparticles’ assembled structures from small-angle scattering measurements and then input the reconstructed structures to a finite-difference time-domain method to predict their color and reflectance. This computational approach is successfully validated by comparing its predictions against experimentally measured reflectance and provides a pathway for reverse engineering colloidal assemblies with desired optical and photothermal properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Probing Metastable Domain Dynamics via Automated Experimentation in Piezoresponse Force Microscopy

The dynamics of complex topological defects in ferroelectric materials is explored using automated experimentation in piezoresponse force microscopy. Specifically, a complex trigger system (i.e., “FerroBot”) is employed to study metastable domain-wall dynamics in Pb 0.6 Sr 0.4 TiO 3 thin films. Several regimes of superdomain wall dynamics have been identified, including smooth domain-wall motion and significant reconfiguration of the domain structures. We have further demonstrated that microscopic mechanisms of the domain-wall dynamics can be identified; i.e., domain-wall bending can be separated from irreversible domain reconfiguration regimes. In conjunction, phase-field modeling was used to corroborate the observed mechanisms. As such, the observed superdomain dynamics can provide a model system for classical ferroelectric dynamics, much like how colloidal crystals provide a model system for atomic and molecular systems.

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

Actinide (III/IV) - Silica Colloids in the WIPP

During the completeness process for the 2019 Compliance Recertification Application (CRA) for the Waste Isolation Pilot Plant (WIPP), the US Environmental Protection Agency (EPA) raised concerns about the possible presence of actinide-silica colloids in the WIPP. Several publications that studied the An(IV)- silica system indicated that these colloids could form under conditions similar to WIPP. Colloids are important for WIPP Performance Assessment (PA) as these are a mobile fraction of actinides that contribute to release. As the previously published papers did not explore the formation of actinide-silica colloids under the high ionic strength environment expected in WIPP, an experimental strategy to study these systems was developed.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Particle anisotropy tunes emergent behavior in active colloidal systems

Studies of active particle systems have demonstrated that particle anisotropy can impact the collective behavior of a system, motivating a systematic study. Here, we report a systematic computational investigation of the role of anisotropy in shape and active force director on the collective behavior of a two-dimensional active colloidal system. We find that shape and force anisotropy can combine to produce critical densities both lower and higher than those of disks. Furthermore, we demonstrate that changing particle anisotropy tunes what we define as a “collision efficiency” of inter-particle collisions in leading to motility-induced phase separation (MIPS) of the system. We use this efficiency to determine the relative critical density across systems. Additionally, we observe that local structure in phase-separated clusters is the same as the particle's equilibrium densest packing, suggesting a general connection between equilibrium behavior and non-equilibrium cluster structure of self-propelled anisotropic particles. In engineering applications for active colloidal systems, shape-controlled steric interactions such as those described here may offer a simple route for tailoring emergent behaviors.

42 ENGINEERING↗
DOE OSTI2025

Automated Nanocrystal Synthesis: Lessons from 25 Years of Robots, Microfluidics, and Machine Learning

Here, this perspective highlights the evolution of techniques for automating the synthesis of colloidal nanocrystals. Over the past 25 years, microfluidic reactors and robotic workflows have been developed to enhance the reproducibility of nanocrystal synthesis, facilitate rapid screening of reaction conditions, optimize material properties, and perform multistep syntheses of high-quality nanoparticles with complex heterostructures. Modern automated systems are now valued for their ability to generate robust data sets for validating physical models, supporting chemical mechanisms, training machine learning models, and for directing autonomous experimentation. We discuss the early challenges and limitations of these technologies and present key lessons for effectively utilizing automated and ML-guided tools to accelerate nanocrystal discovery for the next 25 years.

Nanocrystals↗
DOE OSTI2022

Alkaline-Earth Chalcogenide Nanocrystals: Solution-Phase Synthesis, Surface Chemistry, and Stability

Increasing demand for effective energy conversion materials and devices has renewed interest in semiconductors comprised of earth-abundant and biocompatible elements. Alkaline-earth sulfides doped with rare earth ions are versatile optical materials. However, relatively little is known about controlling the dimensionality, surface chemistry, and inherent optical properties of the undoped versions of alkaline-earth monoand polychalcogenides. Here, we describe the colloidal synthesis of alkaline-earth chalcogenide nanocrystals through the reaction of metal carboxylates with carbon disulfide or selenourea. Systematic exploration of the synthetic phase space allows us to tune particle sizes over a wide range using a mixture of commercially available carboxylate precursors. Solid-state NMR spectroscopy confirms the phase purity of the selenide compositions. Surface characterization reveals that bridging carboxylates and amines preferentially terminate the surface of the nanocrystals. While these materials are colloidally stable in the mother solution, the selenides are susceptible to oxidation over time, eventually degrading to selenium metal through polyselenide intermediates. As part of these investigations, we have developed the colloidal syntheses of barium di- and triselenides, two among few reported nanocrystalline alkaline-earth polychalcogenides. Electronic structure calculations reveal that both materials are indirect band gap semiconductors. The colloidal chemistry presented here may enable the synthesis of more complex, multinary chalcogenide materials containing alkaline-earth elements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

The Path to Enlightenment: Progress and Opportunities in High Efficiency Halide Perovskite Light-Emitting Devices

Besides the flourishment in photovoltaics, halide perovskites hold great promise to compete with leading contenders among solution-processed emitters, such as organics and semiconductor colloidal nanocrystals, in the field of light emission. Halide perovskites exhibit outstanding optoelectronic properties, including high photoluminescence quantum yields, facile bandgap tunability, narrow emission line widths, and respectable carrier mobilities, promoting them to thrive in versatile light-emitting applications such as light-emitting diodes, lasers, X-ray scintillators, and circularly polarized light sources. Herein, we discuss the underlying physics of light emission in state-of-the-art perovskite light-emitting devices and focus on promising strategies for further improvement of device performance.

42 ENGINEERING↗
NASA NTRSDate not supplied

Rational Design of Nanoplasmonic Array Geometries for Biosensing

Background: Molecular diagnostics provide early and accurate diagnosis, which is essential for the prevention and treatment of infectious as well as chronic diseases. These tests are designed to detect disease-specific bioanalytes such as nucleic acid (DNA or RNA) or protein (antigens, antibodies) biomarkers. In the context of infectious disease diagnosis, nucleic acid-based detection methods are known to provide more specific and sensitive results. Here, the presence of a unique sequence belonging to the pathogenic genomic material is targeted to identify species, organism, genera and/or antimicrobial resistant gene markers. The majority of the common nucleic acid based diagnostic techniques require amplification (polymerase chain reaction, isothermal amplification etc.) of the pathogenic genetic material prior to detection impacting diagnostic speed, complexity, and cost thereby limiting ease of use. Thus, the development of simplified nucleic acid-based diagnostics that can be even used in resource-poor settings may hugely benefit patients across the globe. Nanopath is a molecular diagnostics company utilizing a solid-state nanosensor to enable sequence-specific detection of target nucleic acids without the need of amplification. These nanostructures enable ultra-sensitive biomarker detection using geometric, feature-dependent properties highly dependent on the local dielectric environment, allowing them to be sensitive to low concentration binding events. This paper describes an application of this approach to provide highly relevant clinical information within a single doctor’s office visit. Intro: The Nanopath team is in collaboration with NASA (National Aeronautics and Space Administration) and NIST (National Institute of Standards and Technology) to push the bounds of the fundamental physics associated with their biosensing platform. The ability of metals to support electromagnetic surface waves gives rise to surface plasmons when optically illuminated. This property, and its strong sensitivity to changes in the local refractive index, allows for the use of metal nanoparticles as ultra-sensitive transducers. In prior work by members of this team, ensembles of randomly oriented nanoparticles (i.e., colloidal nanorods dispersed on chip) were employed for sequence-specific nucleic acid sensing (1-3). While these particle sensors have the advantage of rapid fabrication, they suffer from low sensitivity and quality factor due to the random particle dispersity. In contrast, in this study we employ ordered array nanoparticle ensembles which can be used to improve sensor sensitivity and figure-of-merit. Study Methods Overview: In this talk, we detail the results of sensing experiments and computational simulations to outline a rational design of the structure of these plasmonic nanoparticle arrays for biomolecular sensing. Through simulation and experiment, we iteratively tailor nanostructure dimension to provide high quality signal and large resonance shifts upon modeled nucleic acid binding. In particular, full-wave electromagnetic simulations were conducted using Lumerical photonic simulation software in which periodic boundary conditions were applied in the x- and y- dimensions for each of the nanoplasmonic sensor geometries. To simulate the resonance response to changes in the bulk solution in contact with the sensor surface, the refractive index of the surrounding media was changed appropriately. Nucleic acid hybridization events were modeled using either using spherical structures approximating the relevant radius of genomic material as estimated by polymer models, or as conformal layers with the known refractive indices for nucleic acids. On the basis of initial simulations, nanosensors were fabricated using traditional electron-beam lithography protocols at NIST. To evaluate consensus between simulations and experiments, bulk sensing experiments were carried out in which the resonance peaks were obtained by submerging the sensors in refractive index standards. Key nanosensor characteristics including resonance peak locations, resonance peak shifts as a function of refractive index, and figure of merit (FOM) of extinction curves were examined between the experimental and simulation results prior to proceeding with simulations on additional geometries and more complex solution conditions, and further device fabrication. This iterative process is repeated toward a rational design of nanoplasmonic array geometries for biosensing optimizing response for targeted disease detection. In summary, this study puts forth a methodology for rational design and characterization of regularly spaced nanoparticle arrays for optics-based biosensing. The results of this study will allow for more informed design of nanostructure geometries towards sequence-specific nucleic acid detection. These improved designs have the potential to improve clinical sensitivity and limit-of-detection across disease indication.

sensor↗
DOE OSTI2020

Materials and methods for the preparation of nanocomposites

Disclosed herein is an isolable colloidal particle comprising a nanoparticle and an inorganic capping agent bound to the surface of the nanoparticle, a method for making the same in a biphasic solvent mixture, and the formation of structures and solids from the isolable colloidal particle. The process can yield photovoltaic cells, piezoelectric crystals, thermoelectric layers, optoelectronic layers, light emitting diodes, ferroelectric layers, thin film transistors, floating gate memory devices, phase change layers, and sensor devices.

36 MATERIALS SCIENCE↗
NASA NTRS2012

Combustion, Complex Fluids, and Fluid Physics Experiments on the ISS

From the very early days of human spaceflight, NASA has been conducting experiments in space to understand the effect of weightlessness on physical and chemically reacting systems. NASA Glenn Research Center (GRC) in Cleveland, Ohio has been at the forefront of this research looking at both fundamental studies in microgravity as well as experiments targeted at reducing the risks to long duration human missions to the moon, Mars, and beyond. In the current International Space Station (ISS) era, we now have an orbiting laboratory that provides the highly desired condition of long-duration microgravity. This allows continuous and interactive research similar to Earth-based laboratories. Because of these capabilities, the ISS is an indispensible laboratory for low gravity research. NASA GRC has been actively involved in developing and operating facilities and experiments on the ISS since the beginning of a permanent human presence on November 2, 2000. As the lead Center for combustion, complex fluids, and fluid physics; GRC has led the successful implementation of the Combustion Integrated Rack (CIR) and the Fluids Integrated Rack (FIR) as well as the continued use of other facilities on the ISS. These facilities have supported combustion experiments in fundamental droplet combustion; fire detection; fire extinguishment; soot phenomena; flame liftoff and stability; and material flammability. The fluids experiments have studied capillary flow; magneto-rheological fluids; colloidal systems; extensional rheology; pool and nucleate boiling phenomena. In this paper, we provide an overview of the experiments conducted on the ISS over the past 12 years.

Motil, Brian↗
DOE OSTI2023

Learning effective SDEs from Brownian dynamic simulations of colloidal particles

We construct a reduced, data-driven, parameter dependent effective stochastic differential equation (eSDE) for electric-field mediated colloidal crystallization using data obtained from Brownian dynamics simulations. We use diffusion maps (a manifold learning algorithm) to identify a set of useful latent observables. In this latent space we identify an eSDE using a deep learning architecture inspired by numerical stochastic integrators and compare it with the traditional Kramers–Moyal expansion estimation. We show that the obtained variables and the learned dynamics accurately encode the physics of the Brownian dynamic simulations. We further illustrate that our reduced model captures the dynamics of corresponding experimental data. Further, our dimension reduction/reduced model identification approach can be easily ported to a broad class of particle systems dynamics experiments/models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

High Energy Density and Stable Three-Dimensionally Structured Se-Loaded Bicontinuous Porous Carbon Battery Electrodes

Here, 3D structured Se-loaded bicontinuous porous carbon (BPC) electrodes were fabricated through colloidal templating of BPC followed by pulsed-voltage Se electrodeposition. The resultant electrodes were found to deliver a specific capacity of 665 mA h g -1 at a rate of 0.1 C, near the theoretical value for Se. When a vinylene carbonate containing electrolyte was utilized, the capacity fade over 500 cycles at 1 C rate was as small as a few percent. Impedance measurements and physical characterization of cycled electrodes indicated the exceptionally stable cycling performance was possibly due to vinylene carbonate resulting in formation of a stable SEI during cycling. Along with cycling stability, the rate performance of the 3D Se/BPC electrodes was also good. Due to the bicontinuous structure of carbonaceous current collector at rates as high as 5 C, the deliverable capacity was about 300 mA h g -1 .

25 ENERGY STORAGE↗