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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Engineering a Self-Grown TiO 2 /Ti-MOF Heterojunction with Selectively Anchored High-Density Pt Single-Atomic Cocatalysts for Efficient Visible-Light-Driven Hydrogen Evolution

A photocatalyst TiO 2 /Ti-BPDC-Pt is developed with a self-grown TiO 2 /Ti-metal–organic framework (MOF) heterojunction, i.e., TiO 2 /Ti-BPDC, and selectively anchored high-density Pt single-atomic cocatalysts on Ti-BPDC for photocatalytic hydrogen evolution. This intimate heterojunction, growing from the surface pyrolytic reconstruction of Ti-BPDC, works in a direct Z-scheme, efficiently separating electrons and holes. Pt is selectively anchored on Ti-BPDC by ligands and is found in the form of single atoms with loading up to 1.8 wt %. The selective location of Pt is the electron-enriched domain of the heterojunction, which further enhances the utilization of the separated electrons. This tailored TiO 2 /Ti-BPDC-Pt shows a significantly enhanced activity of 12.4 mmol g -1 h -1 compared to other TiO 2 - or MOF-based catalysts. In conclusion, the structure-activity relationship further proves the balance of two simultaneously exposed domains of heterojunctions is critical to fulfilling this kind of catalyst.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Dense autoencoders, clustering techniques, and semi-supervised learning for HPGe $γ$-spectra

Classifying high-resolution gamma spectra by their isotopic content is an essential task in nuclear forensics and other applications. Traditional analysis methods are often time-intensive, but machine learning (ML) may help analysts quickly process many spectra. Such methods tend to rely on abundant, well-labeled data for training. Historical gamma data exists in various fields but is not uniformly useful for supervised ML due to inconsistent labeling. Here, to address some of these challenges, we present a method to classify and organize unlabeled data from high-purity germanium detectors using an autoencoding neural network (autoencoder). We trained dense autoencoders to compress gamma data into latent representations that enable efficient data characterization. By clustering the encoded spectra or lower-dimensional mappings of them, we identified and removed portions of over-abundant data categories, resulting in a more balanced dataset and improved autoencoder performance. This encoding and clustering pipeline also enabled the organization of spectra into self-consistent categories. Finally, we found that encoded representations showed potential as inputs for semi-supervised learning of nuclide identification (NID) labels, achieving an average F1 score of 0.85 ± 0.03 when mapping encodings to a set of 65 isotope labels.

Autoencoders↗
DOE OSTI2020

A Woven Supramolecular Metal‐Organic Framework Comprising a Ruthenium Bis(terpyridine) Complex and Cucurbit[8]uril: Enhanced Catalytic Activity toward Alcohol Oxidation

Abstract The self‐assembly of a diamondoid woven supramolecular metal–organic framework wSMOF‐1 has been achieved from intertwined [Ru(tpy) 2 ] 2+ (tpy=2,2′,6′,2′′‐terpyridine) complex M1 and cucurbit[8]uril (CB[8]) in water, where the intermolecular dimers formed by the appended aromatic arms of M1 are encapsulated in CB[8]. wSMOF‐1 exhibits ordered pore periodicity in both water and the solid state, as confirmed by a combination of 1 H NMR spectroscopy, UV‐vis absorption, isothermal titration calorimetry, dynamic light scattering, small angle X‐ray scattering and selected area electron diffraction experiments. The woven framework has a pore aperture of 2.1 nm, which allows for the free access of both secondary and primary alcohols and tert ‐butyl hydroperoxide (TBHP). Compared with the control molecule [Ru(tpy) 2 ]Cl 2 , the [Ru(tpy) 2 ] 2+ unit of wSMOF‐1 exhibits a remarkably higher heterogeneous catalysis activity for the oxidation of alcohols by TBHP in n ‐hexane. For the oxidation of 1‐phenylethan‐1‐ol, the yield of acetophenone was increased from 10 % to 95 %.

Zhang, Yun‐Chang↗
DOE OSTI2021

Structure of ice confined in silica nanopores

Observed anomalous thermodynamic properties of confined water such as deviations in the melting point and freezing point motivate the determination of the structure of confined water as a function of pore size and temperature. Here, we investigate the dynamic evolution of the structure of confined ice in SBA-15 porous materials with pore diameters of 4 nm, 6 nm, and 8 nm at temperatures ranging from 183 K to 300 K using in operando Wide-Angle X-Ray Scattering (WAXS) measurements, X-Ray Partial Distribution Function (PDF) measurements, and classical Molecular Dynamics (MD) simulations. Formation of hexagonal ice structures is noted in all the three pore sizes. In silica nanopores with diameters of 4 nm, cubic ice formation is noted in addition to hexagonal ice. Longer lasting hydrogen bonds and longer residence times of the water molecules in the first coordination shell contribute to observed crystalline organization of ice in confinement. Self-diffusion coefficients of confined liquid water, predicted from classical MD simulations, are four orders of magnitude higher compared to ice formed in confinement. These experimental and simulation results provide comprehensive insights underlying the organization of confined water and ice in silica nanopores and the underlying physico-chemical interactions that contribute to the observed structures.

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

Fundamental Processes and Practical Considerations of Lead Chalcogenide Mesocrystals Formed via Self-Assembly and Directed Attachment of Nanocrystals at a Fluid Interface

Significant advances in the synthesis and processing of colloidal nanocrystals have given scientists and engineers access to a vast library of building blocks with precisely defined size, shape, and composition. These materials have inspired exciting prospects to enable bottom-up fabrication of programmable materials with properties by design. Successfully assembling and connecting the building blocks into superstructures in which constituent nanocrystals can purposefully interact requires robust understanding of and control over a complex interplay of dynamic physicochemical processes. Fluid interfaces provide an advantageous experimental workbench to both probe and control these processes. Despite the ostensible simplicity of fabricating nanocrystal assemblies at a fluid interface, sensitivity to processing conditions and limited reproducibility have underscored the complexity of this process. In situ studies have provided mechanistic insights into the competing dynamics of key subprocesses including solvent spreading and evaporation, superlattice formation, ligand detachment kinetics, and nanocrystal attachment. Understanding how these subprocesses influence the complex choreography of self-assembly, structure transformation, and oriented attachment processes presents a rich research challenge. In this context, we present a detailed methodology for self-assembly and attachment of lead chalcogenide nanocrystals at a liquid–gas interface as a model system for the fabrication of mono- and multilayer cubic connected superlattices. We discuss key experimental parameters such as the characteristics of the building blocks and processing conditions and detailed steps from colloidal nanocrystal injection to superlattice transfer. Furthermore, we hope that this Methods/Protocols paper will provide guidance for future advances in the exciting path toward bringing the prospect of nanocrystal-based programmable materials to fruition.

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

Tolerance to allelopathic inhibition by free fatty acids in five biofuel candidate microalgae strains

Contaminating organisms (grazers, pathogens, competitors) and self-inhibition by algae-produced allelopathic chemicals are two issues that may limit the productivity of algal cultivation for bioproducts. One potential solution is to identify algal strains that are not affected by allelopathic inhibition even while undesirable organisms are suppressed. Here we used two experiments to test how sensitivity to allelopathy varies across algae. In the first experiment, we tested the sensitivity of five biofuel candidate green algae strains to two allelopathic compounds (i.e., free fatty acids) and found that the degree of inhibition depends strongly on both the species and specific compound. In the second experiment, we exposed one alga (Chlorella) to the sterile-filtered medium of each species, and found that the concentration of free fatty acids released into the media predicted Chlorella’s growth response. This provides a better understanding of how the production of, and sensitivity to, allelopathic compounds determines algal productivity.

09 BIOMASS FUELS↗
DOE OSTI2023

Controlling the Self-Assembly of DNA Origami Octahedra via Manipulation of Inter-Vertex Interactions

Recent studies have demonstrated novel strategies for the organization of nanomaterials into three-dimensional (3D) ordered arrays with prescribed lattice symmetries using DNA-based self-assembly strategies. In one approach, the nanomaterial is sequestered into DNA origami frames or “material voxels” and then coordinated into ordered arrays based on the voxel geometry and the corresponding directional interactions based on its valency. While the lattice symmetry is defined by the valency of the bonds, a larger-scale morphological development is affected by assembly processes and differences in energies of anisotropic bonds. To facilely model this assembly process, we investigate the self-assembly behavior of hard particles with six interacting vertices via theory and Monte Carlo simulations and exploration of corresponding experimental systems. We demonstrate that assemblies with different 3D crystalline morphologies, but the same lattice symmetry can be formed depending on the relative strength of vertex-to-vertex interactions in orthogonal directions. We observed three distinct assembly morphologies for such systems: cube-like, sheet-like, and cylinder-like. A simple analytical theory inspired by well-established ideas in the areas of protein crystallization, based on calculating the second virial coefficient of patchy hard spheres, captures the simulation results and thus represents a straightforward means of modeling this self-assembly process. To complement the theory and simulations, experimental studies were performed to investigate the assembly of octahedral DNA origami frames with varying binding energies at their vertices. In conclusion, x-ray scattering confirms the robustness of the formed nanoscale lattices for different binding energies, while both optical and electron microscopy imaging validated the theoretical predictions on the dependence of the distinct morphologies of assembled state on the interaction strengths in the three orthogonal directions.

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

Evidence of a Uranium‐Paddlewheel Node in a Catecholate‐Based Metal–Organic Framework

Abstract The interactions between uranium and non‐innocent organic species are an essential component of fundamental uranium redox chemistry. However, they have seldom been explored in the context of multidimensional, porous materials. Uranium‐based metal–organic frameworks (MOFs) offer a new angle to study these interactions, as these self‐assembled species stabilize uranium species through immobilization by organic linkers within a crystalline framework, while potentially providing a method for adjusting metal oxidation state through coordination of non‐innocent linkers. We report the synthesis of the MOF NU‐1700 , assembled from U 4+ ‐paddlewheel nodes and catecholate‐based linkers. We propose this highly unusual structure, which contains two U 4+ ions in a paddlewheel built from four linkers—a first among uranium materials—as a result of extensive characterization via powder X‐ray diffraction (PXRD), sorption, transmission electron microscopy (TEM), and thermogravimetric analysis (TGA), in addition to density functional theory (DFT) calculations.

Knapp, Julia G.↗
DOE OSTI2023

Evidence of a Uranium‐Paddlewheel Node in a Catecholate‐Based Metal–Organic Framework

Abstract The interactions between uranium and non‐innocent organic species are an essential component of fundamental uranium redox chemistry. However, they have seldom been explored in the context of multidimensional, porous materials. Uranium‐based metal–organic frameworks (MOFs) offer a new angle to study these interactions, as these self‐assembled species stabilize uranium species through immobilization by organic linkers within a crystalline framework, while potentially providing a method for adjusting metal oxidation state through coordination of non‐innocent linkers. We report the synthesis of the MOF NU‐1700 , assembled from U 4+ ‐paddlewheel nodes and catecholate‐based linkers. We propose this highly unusual structure, which contains two U 4+ ions in a paddlewheel built from four linkers—a first among uranium materials—as a result of extensive characterization via powder X‐ray diffraction (PXRD), sorption, transmission electron microscopy (TEM), and thermogravimetric analysis (TGA), in addition to density functional theory (DFT) calculations.

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

Designed and biologically active protein lattices

Versatile methods to organize proteins in space are required to enable complex biomaterials, engineered biomolecular scaffolds, cell-free biology, and hybrid nanoscale systems. Here, we demonstrate how the tailored encapsulation of proteins in DNA-based voxels can be combined with programmable assembly that directs these voxels into biologically functional protein arrays with prescribed and ordered two-dimensional (2D) and three-dimensional (3D) organizations. We apply the presented concept to ferritin, an iron storage protein, and its iron-free analog, apoferritin, in order to form single-layers, double-layers, as well as several types of 3D protein lattices. Our study demonstrates that internal voxel design and inter-voxel encoding can be effectively employed to create protein lattices with designed organization, as confirmed by in situ X-ray scattering and cryo-electron microscopy 3D imaging. The assembled protein arrays maintain structural stability and biological activity in environments relevant for protein functionality. The framework design of the arrays then allows small molecules to access the ferritins and their iron cores and convert them into apoferritin arrays through the release of iron ions. The presented study introduces a platform approach for creating bio-active protein-containing ordered nanomaterials with desired 2D and 3D organizations.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Tunable Solid‐State Properties and Anisotropic Charge Mobility in Hydrogen‐Bonded Diketopyrrolopyrrole Polymers via Automated Device Fabrication and Characterization

The optoelectronic properties of semiconducting polymers and device performance rely on a delicate interplay of design and processing conditions. However, screening and optimizing the relationships between these parameters for reliably fabricating organic electronics can be an arduous task requiring significant time and resources. To overcome this challenge, Polybot is developed—a robotic platform within a self‐driving lab that can efficiently produce organic field‐effect transistors (OFETs) from various semiconducting polymers via high‐throughput blade coating deposition. Polybot not only handles the fabrication process but also can conduct characterization tests on the devices and autonomously analyze the data gathered, thus facilitating the rapid acquisition of data on a large scale. This work leverages the capabilities of this platform to investigate the fabrication of OFETs using hydrogen bonding‐containing semiconducting polymers. Through high‐throughput fabrication and characterization, various data trends are analyzed, and large extents of anisotropic charge mobility are observed in devices. The materials are thoroughly characterized to understand the role of processing conditions in solid state and electronic properties of these organic semiconductors. The findings demonstrate the effectiveness of automated fabrication and characterization platforms in uncovering novel structure–property relationships, facilitating refinement of rational chemical design, and processing conditions, ultimately leading to new semiconducting materials.

automated fabrication and characterization↗
DOE OSTI2021

Protein Assembly by Design

Proteins are nature’s primary building blocks for the construction of sophisticated molecular machines and dynamic materials, ranging from protein complexes such as photosystem II and nitrogenase that drive biogeochemical cycles to cytoskeletal assemblies and muscle fibers for motion. Such natural systems have inspired extensive efforts in the rational design of artificial protein assemblies in the last two decades. As molecular building blocks, proteins are highly complex, in terms of both their three-dimensional structures and chemical compositions. To enable control over the self-assembly of such complex molecules, scientists have devised many creative strategies by combining tools and principles of experimental and computational biophysics, supramolecular chemistry, inorganic chemistry, materials science, and polymer chemistry, among others. Owing to these innovative strategies, what started as a purely structure-building exercise two decades ago has, in short order, led to artificial protein assemblies with unprecedented structures and functions and protein-based materials with unusual properties. Furthermore, our goal in this review is to give an overview of this exciting and highly interdisciplinary area of research, first outlining the design strategies and tools that have been devised for controlling protein self-assembly, then describing the diverse structures of artificial protein assemblies, and finally highlighting the emergent properties and functions of these assemblies.

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

Understanding Metal–Organic Framework Nucleation from a Solution with Evolving Graphs

A mechanistic understanding of metal–organic framework (MOF) synthesis and scale-up remains underexplored due to the complex nature of the interactions of their building blocks. In this work, we investigate the collective assembly of building units at the early stages of MOF nucleation, using MIL-101(Cr) as a prototypical example. Using large-scale molecular dynamics simulations, we observe that the choice of solvent (water and N,N-dimethylformamide), the introduction of ions (Na+ and F–) and the relative populations of MIL-101(Cr) half-secondary building unit (half-SBU) isomers have a strong influence on the cluster formation process. Additionally, the shape, size, nucleation and growth rates, crystallinity, and short and long-range order largely vary depending on the synthesis conditions. We evaluate these properties as they naturally emerge when interpreting the self-assembly of MOF nuclei as the time evolution of an undirected graph. Solution-induced conformational complexity and ionic concentration have a dramatic effect on the morphology of clusters emerging during assembly. While pure solvents lead to the rapid formation of a small number of large clusters, the presence of ions in aqueous solutions results in smaller clusters and slower nucleation. This diversity is captured by the key features of the graph representation. Principle component analysis on graph properties reveals that only a small number of molecular descriptors is needed to deconvolute MOF self-assembly. Furthermore, descriptors such as the average coordination number between half-SBUs and fractal dimension are of particular interest as they can be can be followed experimentally by techniques like by time-resolved spectroscopy. Ultimately, graph theory emerges as an approach that can be used to understand complex processes revealing molecular descriptors accessible by both simulation and experiment.

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

Closing the Gap Between Modeling and Experiments in the Self-assembly of Biomolecules at Interfaces and in Solution

Molecular self-assembly is a powerful tool in materials design, wherein non-covalent interactions like electrostatic, hydrophobic, hydrogen bonding, and van der Waals can be exploited to produce supramolecular nanostructures that are functional and highly tunable. Biomolecules are attractive building blocks, as they are biocompatible, biodegradable and adopt a wide array of higher order structures. Moreover, naturally occurring protein systems display a manifold of structures and interactions that can be replicated in synthetic biomolecules. In this perspective, we highlight advances in multiscale simulation techniques across broad spatiotemporal scales that can aid in characterizing self-assembly of hybrid and hierarchical bionanomaterial systems, with an emphasis on physics-based simulation approaches currently employed to study biomolecules at mineral interfaces. The power of these approaches is highlighted across a few recent areas where molecular simulations have advanced our understanding of self-assembly spanning peptides to protein self-assembly. Looking forward, we discuss how in the near future emerging methods in statistical and machine learning will advance this research field in all areas from expanding the capabilities of physics-based simulation methods to enabling new analyses of high throughput experiments. These advances will pave the way for understanding the molecular recognition patterns in systems that are dictated by self-assembly - biomineralizing peptides, hierarchical peptoids, and large protein assemblies, and will aid in the development of a new synthesis science for achieving precise molecular control in materials design

Sampath, Janani↗
DOE OSTI2022

Investigating Deposition Sequence During Synthesis of Pd/Al2O3 Catalysts Modified with Organic Monolayers

Modification of supported metal catalysts with self-assembled monolayers (SAMs) has been shown to improve selectivity and turnover frequencies (TOFs) for many catalytic reactions. However, these benefits are often accompanied by a decrease in overall mass activity due to partial blocking of active sites by the monolayers. Therefore, a potential method for increasing site accessibility is to deposit the active metal (e.g., Pd) after deposition of a SAM modifier on the support material. In this work, Pd/Al2O3 catalysts were synthesized using both a conventional, "metal-first" sequence in which the phosphonic acid (PA) SAM was deposited on Pd/Al2O3 and a "SAM-first" technique in which the ligands were deposited onto the support prior to deposition of the metal. Although metal-first catalysts showed a significant increase in TOF during benzyl alcohol HDO, they exhibited only a modest increase in overall mass activity due to a decrease in the number of active sites. Meanwhile, SAM-first catalysts showed similar improvements in TOF and toluene selectivity but exhibited significantly improved HDO rates compared to metal-first catalysts. The rate increase was attributed to reduced site blocking as evidenced by CO chemisorption measurements. Additionally, analysis of catalysts having high Pd loadings using transmission electron microscopy (TEM) showed that SAM-first catalysts generally resulted in lower average particle sizes than traditionally modified and unmodified catalysts, suggesting that precoating the support surface with PAs changes the way that Pd is deposited during incipient wetness, leading here to improved activity.

catalytic reactions↗
DOE OSTI2020

Probing Self-Assembly in Arginine–Oleic Acid Solutions with Terahertz Spectroscopy and X-ray Scattering

A study of the formation of microstructures in the reaction of oleic acid with arginine elucidates dynamical self-assembly processes at the molecular level. Terahertz spectroscopy combined with density functional calculations reveals the initial hydrogen-bonding motifs in the assembly process, leading to the formation of micelles and vesicles. Small-angle X-ray scattering measurements allow for kinetic analysis of the growth processes of these nanostructures, revealing a prenucleation pathway of vesicles and micelles which lead to spongelike structures. This final stage of the assembly into spongelike aggregates is investigated with optical microscopy. The formed structures only occur at pH > 8 and are resistant to extreme acidic and basic conditions. Here, a mechanistic pathway to the formation of the spongelike aggregates is described.

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

Hierarchical Materials from High Information Content Macromolecular Building Blocks: Construction, Dynamic Interventions, and Prediction

Hierarchical materials that exhibit order over multiple length scales are ubiquitous in nature. Because hierarchy gives rise to unique properties and functions, many have sought inspiration from nature when designing and fabricating hierarchical matter. More and more, however, nature’s own high-information content building blocks, proteins, peptides, and peptidomimetics, are being coopted to build hierarchy because the information that determines structure, function, and interfacial interactions can be readily encoded in these versatile macromolecules. Here, we take stock of recent progress in the rational design and characterization of hierarchical materials produced from high-information content blocks with a focus on stimuli-responsive and “smart” architectures. We also review advances in the use of computational simulations and data-driven predictions to shed light on how the side chain chemistry and conformational flexibility of macromolecular blocks drive the emergence of order and the acquisition of hierarchy and also on how ionic, solvent, and surface effects influence the outcomes of assembly. Furthermore, continued progress in the above areas will ultimately usher in an era where an understanding of designed interactions, surface effects, and solution conditions can be harnessed to achieve predictive materials synthesis across scale and drive emergent phenomena in the self-assembly and reconfiguration of high-information content building blocks.

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

Self-Assembly of Metallo-Supramolecules with Dissymmetrical Ligands and Characterization by Scanning Tunneling Microscopy

Asymmetrical and dissymmetrical structures are widespread and play a critical role in nature and life systems. In the field of metallo-supramolecular assemblies, it is still in its infancy for constructing artificial architectures using dissymmetrical building blocks. Herein, we report the self-assembly of supramolecular systems based on two dissymmetrical double-layered ligands. With the aid of ultra-high-vacuum, low-temperature scanning tunneling microscopy (UHV-LT-STM), we were able to investigate four isomeric structures corresponding to four types of binding modes of ligand LA with two major conformations complexes A. The distribution of isomers measured by STM and total binding energy of each isomer obtained by density functional theory (DFT) calculations suggested that the most abundant isomer could be the most stable one with highest total binding energy. Lastly, through shortening the linker between inner and outer layers and the length of arms, the arrangement of dissymmetrical ligand LB could be controlled within one binding mode corresponding to the single conformation for complexes B.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗