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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Highly Ordered Eutectic Mesostructures via Template‐Directed Solidification within Thermally Engineered Templates

Template-directed self-assembly of solidifying eutectics results in emergence of unique microstructures due to diffusion constraints and thermal gradients imposed by the template. Here, the importance of selecting the template material based on its conductivity to control heat transfer between the template and the solidifying eutectic, and thus the thermal gradients near the solidification front, is demonstrated. Simulations elucidate the relationship between the thermal properties of the eutectic and template and the resultant microstructure. The overarching finding is that templates with low thermal conductivities are generally advantageous for forming highly organized microstructures. When electrochemically porosified silicon pillars (thermal conductivity < 0.3 Wm −1 K −1 ) are used as the template into which an AgCl-KCl eutectic is solidified, 99% of the unit cells in the solidified structure exhibit the same pattern. In contrast, when higher thermal conductivity crystalline silicon pillars (≈100 Wm −1 K −1 ) are utilized, the expected pattern is only present in 50% of the unit cells. The thermally engineered template results in mesostructures with tunable optical properties and reflectances nearly identical to the simulated reflectances of perfect structures, indicating highly ordered patterns are formed over large areas. This work highlights the importance of controlling heat flows in template-directed self-assembly of eutectics.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Learning Spectral Templates for Photometric Redshift Estimation from Broadband Photometry

Estimating redshifts from broadband photometry is often limited by how accurately we can map the colors of galaxies to an underlying spectral template. Current techniques utilize spectrophotometric samples of galaxies or spectra derived from spectral synthesis models. Both of these approaches have their limitations: either the sample sizes are small and often not representative of the diversity of galaxy colors, or the model colors can be biased (often as a function of wavelength), which introduces systematics in the derived redshifts. In this paper, we learn the underlying spectral energy distributions from an ensemble of ∼100 K galaxies with measured redshifts and colors. We show that we are able to reconstruct emission and absorption lines at a significantly higher resolution than the broadband filters used to measure the photometry for a sample of 20 spectral templates. We find that our training algorithm reduces the fraction of outliers in the derived photometric redshifts by up to 28%, bias up to 91%, and scatter up to 25%, when compared to estimates using a standard set of spectral templates. We discuss the current limitations of this approach and its applicability for recovering the underlying properties of galaxies. Our derived templates and the code used to produce these results are publicly available in a dedicated Github repository: https://github.com/dirac-institute/photoz-template-learning.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Template Assisted Lithium Superoxide Growth for Lithium-Oxygen Batteries

Developing batteries with energy densities comparable to internal combustion technology is essential for a worldwide transition to electrified transportation. Li-O2 batteries are seen as the ‘holy grail’ of battery technologies since they have the highest theoretical energy density of all battery technologies. Current lithium-oxygen (Li-O2) batteries suffer from large charge overpotentials related to electronic resistivity of the insulating lithium peroxide (Li2O2) discharge product. One potential solution is the formation and stabilization of a lithium superoxide (LiO2) discharge intermediate that exhibits good electronic conductivity. However, LiO2 is reported to be unstable at ambient temperature despite its favorable formation energy at -1.0 eV/atom. In this paper, based on our recent work on the development of cathode materials for aprotic lithium oxygen batteries including two intermetallic compounds, LiIr3 and LiIr, that are found to form good template interfaces with LiO2, a simple goodness of fit R factor to gauge how well a template surface structure can support LiO2 growth is developed. The R factor is a quantitative measurement to calculate the geometric difference in the unit cells of specific Miller Index 2D planes of the template surface and LiO2. Using this as a guide, the R factors for LiIr3, LiIr, and La2NiO4+, are found to be good. This guide is attested by simple extension to other noble metal intermetallics with electrochemical cycling data including LiRh3, LiRh, and Li2Pd. Finally, the template concept is extended to main group elements and the R factors for LiO2 (111) and Li2Ca suggest that Li2Ca is a possible candidate for the template assisted LiO2 growth strategy.

Intermetallics↗
DOE OSTI2023

Hierarchically Templated Synthesis of 3D‐Printed Crosslinked Cyclodextrins for Lycopene Harvesting

Abstract Plants produce a wide range of bioactive phytochemicals, such as antioxidants and vitamins, which play crucial roles in aging prevention, inflammation reduction, and reducing the risk of cancer. Selectively harvesting these phytochemicals, such as lycopene, from tomatoes through the adsorption method is cost‐effective and energy efficient. In this work, a templated synthesis of 3D‐printed crosslinked cyclodextrin polymers featuring nanotubular structures for highly selective lycopene harvesting is reported. Polypseudorotaxanes formed by triethoxysilane‐based telechelic polyethylene glycols and α‐cyclodextrins (α‐CDs) are designed as the template to (1) synthetically access urethane‐based nanotubular structures at the molecular level, and (2) construct 3D‐printed architectures with designed macroscale voids. The polypseudorotaxane hydrogels showed good rheological properties for direct ink writing, and the 3D‐printed hydrogels were converted to the desired α‐CD polymer network through a three‐step postprinting transformation. The obtained urethane‐crosslinked α‐CD monoliths possess nanotubular structures and 3D‐printed voids. They selectively adsorb lycopene from raw tomato juice, protecting lycopene from photo‐ or thermo‐degradations. This work highlights the hierarchically templated synthesis approach in developing functional 3D‐printing materials by connecting the bottom‐up molecular assembly and synthesis with the top‐down 3D architecture control and fabrication.

Chemistry↗
DOE OSTI2020

Design of functional composite and all-inorganic nanostructured materials via infiltration of polymer templates with inorganic precursors

Robust and efficient approaches for the synthesis of materials with structure, porosity, and composition controlled at the nanoscale are highly important for a wide range of applications. Polymer templates are promising platforms to achieve such control. The self-assembly process of polymers provides access to diverse structures that can serve as templates for the deposition of inorganic materials. By infiltrating metal precursors from gas or liquid phases, using sequential infiltration synthesis (SIS) or swelling-based infiltration (SBI), respectively, into the polymer templates, one can create finely-tuned texturing of the surface films and bulk materials. In this review, we outline the specifics and dynamics of the polymer infiltration process and characterize the structure and properties of the synthesized materials. Finally, we highlight recent progress in implementing polymer infiltration-based nanoporous ceramics for many applications, including sensors, antireflective coatings, oil-absorbing foams, nanolithographic patterns, and catalytic materials.

Berman, Diana↗
DOE OSTI2020

Template-Assisted, Seed-Mediated Synthesis of Hierarchically Mesoporous Core–Shell UiO-66: Enhancing Adsorption Capacity and Catalytic Activity through Iterative Growth

A hierarchically mesoporous (HM) UiO-66-F 4 shell with ~8 nm mesopores can be iteratively grown on top of UiO-66 nanoparticle (NP) seeds over several cycles templated by Pluronic F-127 micelles. Presumably, the Pluronic micelles that were formed in water can surround UiO-66 NPs to facilitate the overgrowth of an HM-UiO-66-F 4 shell in the presence of Zr IV precursors and BDC-F 4 linkers. The UiO-66 NP seeds play an important role in directing the continuous growth of the HM-UiO-66-F 4 shell, as only a nonporous phase was obtained in their absence. Furthermore, this template-assisted, seed-mediated method can be extended to produce other UiO-66-X (X = (OH) 2 , (COOH) 2 , etc.) shells, demonstrating its generality for the UiO-66 family of metal–organic frameworks. Notably, the incorporation of mesopores into the thrice-overgrown UiO-66@HM|3rd-UiO-66-F 4 materials leads to impressive enhancements in the per-mass uptake capacity of Direct Blue 86, a large anionic dye: 320% better than the parent UiO-66 seeds and 150% better than that for a [UiO-66 + UiO-66-F 4 ] physical mixture at the same mass proportion. Similar enhancements were also observed in the catalyzed oxidation of thioanisole.

36 MATERIALS SCIENCE↗
DOE OSTI2021

INBOUND APPOINTEE PUBLICATION Importance of Substrate-Particle Repulsion for Protein-Templated Assembly of Metal Nanoparticles

We study the protein-directed assembly of colloidal gold nanoparticles on de novo designed protein nanofiber templates. Using sequential assembly on glass substrates, we attach of positively-charged gold nanoparticles to protein nanofibers engineered to have a high density of negatively-charged surface residues. Using a combination of electron and optical microscopy, we measure the density of particle attachment and characterize binding specificity. By varying nanoparticle size and pH of the solution, we explore the importance of charge-dependent particle-fiber and particle-substrate interactions. We find an inverse correlation between particle size and attachment density to the protein nanofibers, attributed to the balance between size-dependent electrostatic particle-fiber attraction and particle-substrate repulsion. We show pH-dependent particle attachment density and binding specificity in relation to the protonation fraction of each assembly layer. Finally, we employ hyperspectral scattering microscopy to draw conclusions about particle density and interparticle spacings of optically-observable particle assemblies.

Guye, Kathryn N.↗
DOE OSTI2020

Data-Driven Template Discovery Using Graph Convolutional Neural Networks

Modeling adversarial activities is a critical component of developing high-con?dence indicators of efforts to acquire, fabricate, proliferate, and/or deploy weapons of mass terror (WMTs). Current approaches to generating representative patterns of interest (a.k.a templates) from the real-world domains involve a Subject Matter Expert (SME)-guided manual process. The goal of Data-Driven Template Discovery (DDTD) is to use a (potentially small) set of SME generated templates to discover other previously unknown and interesting templates in an attributed graph. A template is an activity pattern describing a set of interactions among a group of nodes in the graph. The motivation behind DDTD is to expand the original set of templates, without having SMEs craft all the templates by hand. DDTD also provides seed templates to SMEs, to help them construct larger, high-?delity, and scenario-oriented templates. In these cases, obtaining a larger set of templates that are related (contain similar signals) to the original set is of great value. In this work, we propose to use Graph Convolutional Neural Networks (GCNs) to discover new templates that are heavily related to the original set. GCNs are a family of Neural Network (NN) architectures especially designed to work directly on graphs. In contrast to the traditional NNs, that require considerable amounts of labeled data, GCNs do not require a big labeled training set because they can directly leverage the graph structure instead. This property makes GCNs the perfect tool for creating activity templates.

Joaristi, Mikel↗
DOE OSTI2021

Recent Advances in Functional Materials through Cellulose Nanofiber Templating

Advanced templating techniques have enabled delicate control of both nano- and microscale structures and have helped thrust functional materials into the forefront of society. Cellulose nanomaterials are derived from natural polymers and show promise as a templating source for advanced materials. Use of cellulose nanomaterials in templating combines nanoscale property control with sustainability, an attribute often lacking in other templating techniques. Use of cellulose nanofibers for templating has shown great promise in recent years, but previous reviews on cellulose nanomaterial templating techniques have not provided extensive analysis of cellulose nanofiber templating. Cellulose nanofibers display several unique properties, including mechanical strength, porosity, high water retention, high surface functionality, and an entangled fibrous network, all of which can dictate distinctive aspects in the final templated materials. Many applications exploit the unique aspects of templating with cellulose nanofibers that help control the final properties of the material, including, but not limited to, applications in catalysis, batteries, supercapacitors, electrodes, building materials, biomaterials, and membranes. A detailed analysis on the use of cellulose nanofibers templating is provided, addressing specifically how careful selection of templating mechanisms and methodologies, combined toward goal applications, can be used to directly benefit chosen applications in advanced functional materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

The Transactive Energy Network Template Metamodel

While transactive energy, which is defined as an allocation of electricity based on dynamically discovered values or prices, has been extensively studied, its uptake and use has been slow. This report describes a tool, the transactive network template, which should hasten the creation and uptake of transactive energy networks. Some basic principles of transactive energy are familiar from existing wholesale electricity markets. Locational prices are calculated today for zones within bulk electric transmission systems. Locational prices differ while accounting for the locational costs of electricity generation and the losses and constraints incurred when electricity is transmitted from generators and distributed to consumers. A transactive energy network might include these transmission zones. However, current research strives to apply transactive energy also in electricity distribution circuits, buildings, and even for individual generating and consuming devices. At the same time, researchers explore how to apply transactive energy in real time during increasingly shorter time intervals. Automated computational agents become necessary as transactive energy becomes applied to smaller circuit zones and at faster dynamic timescales. A transactive energy network is an example of a multi-agent system. Each zone in the network is represented by its transactive agent, which makes decisions for and acts on behalf of a business entity that is responsible for and manages one of the circuit regions. A transactive energy network is also an example of a decentralized, distributed control system. Control decisions and responsibilities are distributed among the network’s transactive agents. The transactive agents are independent; that is, there typically is no centralized authority or oversight function. Instead, transactive agents exchange transactive signals and thereby negotiate the prices and quantities of electricity that they will exchange. Initially, the circuit regions and responsibilities of transactive agents appear to be very dissimilar. Each circuit region may comprise transmission, distribution, or building-level circuits. Each has a unique position and electrical connectivity within the transactive energy network. Each possesses unique assets that either generate or consume electricity, and these (e.g., renewable energy generator, diesel generator, aggregate utility load, building load, space conditioning, refrigerator, etc.) may further differ in their price flexibility and in their strategies for responding to dynamic electricity prices. Given such diversity, an implementer’s first inclination might be to start from scratch to define all these devices and to engineer their seemingly unique interactions. Given that each implementer’s perspective may be narrow within a transactive energy network, it is unlikely that uniquely engineered systems would interact well. This is where the transactive network template is applicable. The transactive network template is a metamodel that has been developed to guide implementers as they configure their own transactive agent within a network of such agents. The object-oriented design of the transactive network template provides basic code object types that may be used and extended by implementers to represent each of the assets in their circuit region. These objects further facilitate the transactive agent’s necessary computations, which are divided among responsibilities to schedule power usage, balance electric supply and demand, and coordinate the exchange of electricity with the other transactive agents. This report addresses the conceptual transactive network template design. Implementers are directed to more formal design documents and reference implementations. A Python™-based1 reference implementation of the transactive network template has been coded, and three implementations have been configured to represent a national laboratory and two university campuses. Version 2 of the transactive node template generalizes the market class and its methods to facilitate multiple, and more diverse market coordination mechanisms than were facilitated by and demonstrated using Version 1. Version 3 includes new Appendix B, which addresses the designs of methods that would make dynamic prices track approved electricity rates. In the future, the author wishes to make the transactive network template more generally applicable to networks that require more accurate power flow. Development of the transactive network template is jointly funded by the U.S. Department of Energy (DOE) Energy Efficiency and Renewable Energy and the DOE Office of Electricity. In late 2015, one of the first projects to be funded by the DOE Grid Laboratory Modernization Laboratory Consortium was the Clean Energy and Transactive Campus project, led by Pacific Northwest National Laboratory. DOE funds were matched by an investment by the Washington Department of Commerce through its Clean Energy Fund. The transactive network template was developed to guide the implementation of transactive energy networks within this project’s scope.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Templated synthesis enhances the cobalt adsorption capacity of a porous organic polymer

Divalent transition metals such as Co(II) are important targets for removal from water sources, due to their potential toxicity as well as their high value. In this study, we found that a series of porous organic polymers based on amide-linked tetraphenylmethane units are effective Co(II) ion adsorbents in aqueous solution. To increase the density of Co(II) binding sites, we then developed a templated synthesis in which the branched, rigid monomers are pre-assembled around Co(II) ions prior to polymerization. Furthermore, after polymer formation, the Co(II) template ions are removed to yield a material rich in Co(II) binding sites. Ion adsorption isotherms show that the Co(II)-templated material has an ion adsorption capacity significantly greater than those of the non-templated materials, highlighting the utility of a templated synthetic route. SEM and TEM images show the morphology of the templated polymer to be dramatically different from the non-templated polymers and to be similar in size and shape to the Co(II)–monomer precursors, emphasizing the role of the template ions in directing the formation of the resulting polymer. This guest-templated approach requires no functionalization of the generic monomer and represents a promising synthetic route to high-capacity ion adsorbents for water purification and aqueous separations.

36 MATERIALS SCIENCE↗
DOE OSTI2026

SPT-3G D1: Foreground-Robust Lensing Templates for Primordial Gravitational Wave Searches

Gravitational lensing of the cosmic microwave background (CMB) generates B-mode polarization that acts as a source of contamination to searches for B modes generated by primordial gravitational waves (PGWs). The strongest constraint on PGW B modes is already significantly limited by lensing B modes, as shown in the most recent BICEP result. In this work, we present CMB lensing B-mode templates constructed using SPT-3G and Planck data, which characterize the lensing B modes and can be used to improve PGW B-mode searches. We use SPT-3G data from the 2019 and 2020 observing seasons for the E modes and the CMB-reconstructed lensing potential, and a cosmic infrared background (CIB) map from Planck as an external lensing tracer. To test for extragalactic foreground biases in the lensing template, we consider CMB lensing reconstruction variants with different levels of foreground immunity: the standard and profile-hardened global minimum variance (GMV) quadratic estimators, and a polarization-only quadratic estimator. We validate the template construction using Gaussian simulations and Agora simulations with realistic non-Gaussian foregrounds. From simulations, we find that foreground-induced biases are strongly suppressed for the template constructed with the profile-hardened GMV + CIB tracer, with residual bias below 10% of the statistical uncertainty on the template power spectrum. Data difference tests on this template similarly show no evidence for significant foreground contamination. This foreground-immune lensing template achieves delensed residual BB power of $A_{\rm lens}^{\rm res} \simeq 0.48$ averaged over $20 \leq \ell \leq 200$, the highest delensing efficiency lensing template to date. These results demonstrate and validate a method to construct foreground-robust lensing templates which will be used in upcoming delensed PGW B-mode analyses of BICEP data.

Nakato, Y. [Stanford U.]↗