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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 235 records · Page 13

Disordered TiO x –SiO x Nanocatalysts Using Bioinspired Synthetic Routes

Metal oxide nanomaterials have increasing significance and broad applications in catalysis, ranging from support materials to active catalysts. Here, we have demonstrated a facile synthetic strategy to create disordered, high-surface-area metal oxide nanomaterials using biomineralization-inspired methods. Using protamine as a protein template, a range of TiO x –SiO x nanomaterials were synthesized and implemented for catalytic CO 2 thermal reduction reactions. The modularity of synthetic options afforded via biomineralization enables increases in surface area, which are ideally suited for subsequent modification to regulate catalytic performance. All materials were thoroughly characterized using a suite of synchrotron scattering and spectroscopic methods. Through these techniques, we have demonstrated that protamine-induced biomineralization results in largely disordered materials with changes in the local atomic structure dependent on the applied synthetic conditions. Protamine removal with treatment under acidic conditions greatly increased material surface area while causing measurable changes in the structure as revealed by X-ray absorption spectroscopy. Upon subsequent hydrogenation, Ti- and Si-based defects were induced in the materials while the disordered nature of the material was still largely retained. Furthermore, we found that the incorporation of Si into TiO x was able to mitigate the known anatase to rutile phase change during the reaction while stabilizing the defect sites. The synthetic strategies described in this work are expected to be translatable to other metal oxide nanomaterial chemical structures, providing a means to control catalytic properties using benign synthetic strategies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Technical Lignin Fractionation: A Powerful Tool for Lignin Structure Homogenization and Its Application

Extracted lignin as a by-product of pulping and bio-refining processes is the main available bio-phenolic polymer. The structural complexity, polydispersity, and black color of lignin are the main limiting factors for its application. Preparation of lignin with lower structural complexity and polydispersity through lignin fractionation is one of the primary solutions to engineer lignin into a value-added material. Sequential lignin fractionation was developed based on pH reduction from alkaline to acidic using mineral acids and was recently optimized using carbon dioxide as a pH controller. The partial solubility of lignin in organic solvents is another promising method for lignin fractionation. Organic solvents with different polarity and solubility factors are able to fractionate lignin, yielding a more homogeneous chemical structure. As a modification of the lignin fractionation process, the use of solvents, water/organic solvent mixtures, such as alcohols, and acetic acid from room to high temperature has been proposed as a greener method for lignin fractionation. Using membrane technology is another promising method and current results indicate its good potential for lignin recovery and fractionation.

Sadeghifar, Hasan↗

HypoRiPPAtlas as an Atlas of hypothetical natural products for mass spectrometry database search

Abstract Recent analyses of public microbial genomes have found over a million biosynthetic gene clusters, the natural products of the majority of which remain unknown. Additionally, GNPS harbors billions of mass spectra of natural products without known structures and biosynthetic genes. We bridge the gap between large-scale genome mining and mass spectral datasets for natural product discovery by developing HypoRiPPAtlas, an Atlas of hypothetical natural product structures, which is ready-to-use for in silico database search of tandem mass spectra. HypoRiPPAtlas is constructed by mining genomes using seq2ripp, a machine-learning tool for the prediction of ribosomally synthesized and post-translationally modified peptides (RiPPs). In HypoRiPPAtlas, we identify RiPPs in microbes and plants. HypoRiPPAtlas could be extended to other natural product classes in the future by implementing corresponding biosynthetic logic. This study paves the way for large-scale explorations of biosynthetic pathways and chemical structures of microbial and plant RiPP classes.

60 APPLIED LIFE SCIENCES↗

From Pyrolysis Oil to Advanced Biographite Anode: Unravelling Biocoke Structural Evolution and Delayed Coking Effects

Catalytic graphitization of biomass-derived carbon offers a promising route to produce biographite as a sustainable alternative to petroleum-based synthetic graphite for lithium-ion battery (LIB) anodes. This study investigates the physicochemical properties of biocokes produced from pyrolysis oil at carbonization temperatures ranging from 150 degrees C to 500 degrees C. Using an iron (Fe) catalyst, graphitization was performed at 1500 degrees C, significantly lower than the ~3000 degrees C required for conventional synthetic graphite. The effects of introducing an intermediate-temperature hold (400 degrees C-600 degrees C) prior to graphitization were evaluated, simulating a "delayed coking" process to enable the coproduction of sustainable aviation fuels (SAFs). Chemical structure evolution during biocoke formation was analyzed, and proposed mechanisms are presented. Biographites produced via the delayed coking pathway exhibited high crystallinity and excellent electrochemical performance in both half-cell and full-cell LIB configurations. The full cells exhibited an initial discharge capacity close to the theoretical capacity of the NMC622 cathode (175 mAh/g at 4.2 V), and high capacity retention (~88%) after 150 cycles. Notably, the graphitic and electrochemical properties remained stable across the range of intermediate hold temperatures. These findings provide a foundation for optimizing temperature parameters in delayed coking systems to enable scalable, integrated production of biographite and SAFs from pyrolysis oil.

09 BIOMASS FUELS↗

Combining artificial intelligence and physics-based modeling to directly assess atomic site stabilities: from sub-nanometer clusters to extended surfaces

The performance of functional materials is dictated by chemical and structural properties of individual atomic sites. In catalysts, for instance, the thermodynamic stability of constituting atomic sites is a key descriptor from which more complex properties, such as molecular adsorption energies and reaction rates, can be derived. In this study, we present a widely applicable machine learning (ML) approach to instantaneously compute the stability of individual atomic sites in structurally and electronically complex nano-materials. Conventionally, we determine such site stabilities using computationally intensive first-principles calculations. With our approach, we predict the stability of atomic sites in sub-nanometer metal clusters of 3–55 atoms with mean absolute errors in the range of 0.11–0.14 eV. To extract physical insights from the ML model, we introduce a genetic algorithm (GA) for feature selection. This algorithm distills the key structural and chemical properties governing the stability of atomic sites in size-selected nanoparticles, allowing for physical interpretability of the models and revealing structure–property relationships. The results of the GA are generally model and materials specific. In the limit of large nanoparticles, the GA identifies features consistent with physics-based models for metal–metal interactions. By combining the ML model with the physics-based model, we predict atomic site stabilities in real time for structures ranging from sub-nanometer metal clusters (3–55 atom) to larger nanoparticles (147 to 309 atoms) to extended surfaces using a physically interpretable framework. Finally, we present a proof of principle showcasing how our approach can determine stable and active nanocatalysts across a generic materials space of structure and composition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ferromagnetic liquid droplets with adjustable magnetic properties

Significance Structured functional liquids combine mechanical versatility of fluids with solid-state properties, such as ferromagnetism, and offer a route to synthesize and control magnetic liquids for adaptive liquid robotics. Studies on these intriguing materials are only in their nascent state, and a profound understanding of the physical state is still lacking. We use hydrodynamics experiments to probe how the magnetization of ferromagnetic liquid droplets, governed by the assembly and jamming of magnetic nanoparticles at liquid–liquid interfaces, and their response to external stimuli can be tuned by chemical, structural, and magnetic means. Our results highlight the leading role of structural short-range order on magnetic properties, which provide a path toward nano-patterning structured liquids.

36 MATERIALS SCIENCE↗

Building workflows for an interactive human-in-the-loop automated experiment (hAE) in STEM-EELS

Exploring the structural, chemical, and physical properties of matter on the nano- and atomic scales has become possible with the recent advances in aberration-corrected electron energy-loss spectroscopy (EELS) in scanning transmission electron microscopy (STEM). However, the current paradigm of STEM-EELS relies on the classical rectangular grid sampling, in which all surface regions are assumed to be of equal a priori interest. However, this is typically not the case for real-world scenarios, where phenomena of interest are concentrated in a small number of spatial locations, such as interfaces, structural and topological defects, and multi-phase inclusions. One of the foundational problems is the discovery of nanometer- or atomic-scale structures having specific signatures in EELS spectra. Herein, we systematically explore the hyperparameters controlling deep kernel learning (DKL) discovery workflows for STEM-EELS and identify the role of the local structural descriptors and acquisition functions in experiment progression. In agreement with the actual experiment, we observe that for certain parameter combinations the experiment path can be trapped in the local minima. We demonstrate the approaches for monitoring the automated experiment in the real and feature space of the system and knowledge acquisition of the DKL model. Based on these, we construct intervention strategies defining the human-in-the-loop automated experiment (hAE). This approach can be further extended to other techniques including 4D STEM and other forms of spectroscopic imaging. The hAE library is available on Github at https://github.com/utkarshp1161/hAE/tree/main/hAE.

Pratiush, Utkarsh [Univ. of Tennessee, Knoxville, ↗

Enhancing the metal–insulator transition in VO 2 heterostructures with graphene interlayers

In this work, studies were conducted on epitaxial VO 2 thin films to assess to the effect of remote epitaxy on the metal–insulator transition (MIT). The epitaxial VO 2 heterostructures were synthesized on both bare Al 2 O 3 (0001) substrates and Al 2 O 3 substrates coated with two monolayer-thick graphene. While both systems exhibit the MIT, the film grown by remote epitaxy on graphene demonstrates improved transport properties. Electrical transport measurements show that the on/off ratio is enhanced by a factor of ~7.5 and the switching temperature window is narrower for VO 2 thin films grown on graphene. By characterizing the heterostructures with a suite of structural, chemical, and spectroscopic tools, we find that the graphene interlayer inhibits oxygen vacancy diffusion from Al 2 O 3 (0001) during the VO 2 growth, resulting in improved electrical behavior at the MIT.

36 MATERIALS SCIENCE↗

A Significant Increase in Detection of High-resolution Emission Spectra Using a Three-dimensional Atmospheric Model of a Hot Jupiter

High-resolution spectroscopy has opened the way for new, detailed study of exoplanet atmospheres. There is evidence that this technique can be sensitive to the complex, three-dimensional (3D) atmospheric structure of these planets. In this work, we perform cross-correlation analysis of high-resolution (R ∼ 100,000) CRIRES/VLT emission spectra of the hot Jupiter HD 209458b. We generate template emission spectra from a 3D atmospheric circulation model of the planet, accounting for temperature structure and atmospheric motions—winds and planetary rotation—missed by spectra calculated from one-dimensional models. In this first-of-its-kind analysis, we find that using template spectra generated from a 3D model produces a more significant detection (6.9σ) of the planet’s signal than any of the hundreds of one-dimensional models we tested (maximum of 5.1σ). We recover the planet’s thermal emission, its orbital motion, and the presence of CO in its atmosphere at high significance. Additionally, we analyzed the relative influences of 3D temperature and chemical structures in this improved detection, including the contributions from CO and H{sub 2}O, as well as the role of atmospheric Doppler signatures from winds and rotation. This work shows that the hot Jupiter’s 3D atmospheric structure has a first-order influence on its emission spectra at high resolution and motivates the use of multidimensional atmospheric models in high-resolution spectral analysis.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Surface structure of linear nanopores in amorphous silica: Comparison of properties for different pore generation algorithms

In this work, we compare the surface structure of linear nanopores in amorphous silica (a-SiO 2 ) for different versions of “pore drilling” algorithms (where the pores are generated by the removal of atoms from the preformed bulk a-SiO 2 ) and for “cylindrical resist” algorithms (where a-SiO 2 is formed around a cylindrical exclusion region). After adding H to non-bridging O, the former often results in a moderate to high density of surface silanol groups, whereas the latter produces a low density. The silanol surface density for pore drilling can be lowered by a final dehydroxylation step, and that for the cylindrical resist approach can be increased by a final hydroxylation step. In this respect, the two classes of algorithms are complementary. We focus on the characterization of the chemical structure of the pore surface, decomposing the total silanol density into components corresponding to isolated and vicinal mono silanols and geminal silanols. The final dehyroxylation and hydroxylation steps can also be tuned to better align some of these populations with the target experimental values.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Identifying Performance Advantaged Biobased Chemicals Utilizing Bioprivileged Molecules

Two technology areas were advanced; a) novel molecules with improved performance in the end use application of organic corrosion inhibitors and flame retardant nylon polymers and b) development of a systematic process for identifying biomass-derived molecules with improved performance in end use applications. In total 17 novel organic corrosion inhibitors were identified that had significantly better performance than the commercial reference organic corrosion inhibitor and 7 novel nylons were synthesized with improved flame retardant properties relative to standard nylon-6,6. While an end-to-end systematic process for identifying biomass-derived molecules with improved end use performance was not completed, important progress was made computational tools for mining chemical structures from the literature and databases as well as establishing reaction network generation algorithms to aid in the discovery of novel molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Influence of Coordination Environment of Anchored Single-Site Cobalt Catalyst on CO 2 Hydrogenation

Heterogeneous catalysts generally have a variety of active-site structures due to the innate heterogeneity of the surface,resulting in complicated correlations between activity and active-site structure. Single site heterogeneous cobalt catalysts with a uniform catalytic surface were utilized as a platform to probe surface sensitive reactions; in this case CO 2 hydrogenation. It was found that atomically isolated cobalt single sites, which exist solely in the tetrahedral Co 2+ coordination, exclusively form CO under typical CO 2 methanation conditions,while cobalt clusters yielded the highest rate of CO 2 reactionand began to form methane. Utilizing the principles of Ostwald Ripening to probe the ensemble effects for CO 2 hydrogenation, the transition from atomic isolation to small clusters of atoms to nanoparticles was explored. Furthermore, the chemical structure of the cobalt was elucidated primarily via X-Ray Absorption Spectroscopy (XANES/EXAFS) and X-Ray Photoelectron Spectroscopy (XPS).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Predicting Volume of Distribution in Humans: Performance of In Silico Methods for a Large Set of Structurally Diverse Clinical Compounds

Volume of distribution at steady state (V D,ss ) is one of the key pharmacokinetic parameters estimated during the drug discovery process. Despite considerable efforts to predict V D,ss , accuracy and choice of prediction methods remain a challenge, with evaluations constrained to a small set (<150) of compounds. To address these issues, a series of in silico methods for predicting human V D,ss directly from structure were evaluated using a large set of clinical compounds. Machine learning (ML) models were built to predict V D,ss directly and to predict input parameters required for mechanistic and empirical V D,ss predictions. In addition, log D, fraction unbound in plasma (fup), and blood-to-plasma partition ratio (BPR) were measured on 254 compounds to estimate the impact of measured data on predictive performance of mechanistic models. Furthermore, the impact of novel methodologies such as measuring partition (Kp) in adipocytes and myocytes (n = 189) on V D,ss predictions was also investigated. In predicting V D,ss directly from chemical structures, both mechanistic and empirical scaling using a combination of predicted rat and dog V D,ss demonstrated comparable performance (62%–71% within 3-fold). The direct ML model outperformed other in silico methods (75% within 3-fold, r 2 = 0.5, AAFE = 2.2) when built from a larger data set. Scaling to human from predicted V D,ss of either rat or dog yielded poor results (<47% within 3-fold). Measured fup and BPR improved performance of mechanistic V D,ss predictions significantly (81% within 3-fold, r 2 = 0.6, AAFE = 2.0). Adipocyte intracellular Kp showed good correlation to the V D,ss but was limited in estimating the compounds with low V D,ss .

59 BASIC BIOLOGICAL SCIENCES↗

Lignin as a bioactive polymer and heavy metal absorber- an overview

As a pulping and bio-refinery by-product with phenolic chemical structure, lignin indicated high potential as natural antioxidant activity, UV blocker, antibacterial and toxic material absorbent properties. Presence of phenolic hydroxyl groups in lignin structure plays the main role of its antioxidant activity. However, lignin antioxidant power can change depending on its other structural features and functional groups like ortho-methoxy groups, –OCH 3 groups, the α-CH 2 groups, the aliphatic carbonyl groups, and the size of π-conjugated systems. Lignin in mixture with synthetic polymers, improved their thermal stability. Lignin has high UV light absorbing potential in broad-spectrum (UVA, UVB). Adding 1–5% of lignin into hand cream indicated excellent range of sun protection factor (SPF) with more than 95% UV light absorption. Lignin also indicated strong UV light protection when applied in different transparent film and protect paint, oil, and varnish from UV degradation. Further, lignosulfonate and other modified lignin including chemically modification, nano-particles and lignin hydrogel indicated high potential as heavy metal absorber.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Approaching disorder-tolerant semiconducting polymers

Doping has been widely used to control the charge carrier concentration in organic semiconductors. However, in conjugated polymers, n-doping is often limited by the tradeoff between doping efficiency and charge carrier mobilities, since dopants often randomly distribute within polymers, leading to significant structural and energetic disorder. Here, we screen a large number of polymer building block combinations and explore the possibility of designing n-type conjugated polymers with good tolerance to dopant-induced disorder. We show that a carefully designed conjugated polymer with a single dominant planar backbone conformation, high torsional barrier at each dihedral angle, and zigzag backbone curvature is highly dopable and can tolerate dopant-induced disorder. With these features, the designed diketopyrrolopyrrole (DPP)-based polymer can be efficiently n-doped and exhibit high n-type electrical conductivities over 120 S cm -1 , much higher than the reference polymers with similar chemical structures. This work provides a polymer design concept for highly dopable and highly conductive polymeric semiconductors.

36 MATERIALS SCIENCE↗

A Proxy Method to Bridge LCA Data Gaps Using Automated Material Classification and Probabilistic Under-Specification

Life cycle assessments (LCAs) are essential for understanding the environmental impacts of material production. However, gaps in life cycle inventory (LCI) data for material and chemical inputs present a key challenge for LCA practitioners, especially in the early design stages. Strategies for filling in these gaps require additional time and expertise, which can hinder the LCA’s completion. This study combined automatic material classification and probabilistic under-specification to create a time-efficient method to fill material LCI data gaps. To illustrate the proposed method, proxy environmental impact distributions were generated using publicly available material LCI data classified into the ChemOnt chemical taxonomy using the open-source chemical classification software ClassyFire. Input materials with data gaps were then classified into the same taxonomy, where proxy environmental impact values could be selected from the available distributions to quickly fill in any data gaps. Although these methods were applied to classify material production processes available in the Federal LCA Commons and Ecoinvent databases, they can be applied to any LCA database. This study shows that classifying materials by their chemical structure produces taxonomies with increased granularity relative to industrial classification, improving the ability of under-specified proxy data to be used for differentiating the environmental impacts of competing designs.

biological databases↗

Thermal Stability of Quasi-1D NbS 3 Nanoribbons and Their Transformation to 2D NbS 2 : Insights from in Situ Electron Microscopy and Spectroscopy

Here in situ electron microscopy imaging and spectroscopy enabled us to study the evolution of quasi-1D NbS 3 -IV nanoribbons with respect to morphology and chemical structure at temperatures between room temperature and 1000 °C. Scanning transmission electron microscopy (STEM) experiments included imaging in the secondary electron, (transmitted) bright field, and high-angle annular dark-field modes while operating in the low kV regime. The results showed that NbS 3 -IV samples transform dramatically from smooth nanoribbons into highly textured configurations featuring polyhedral divots and steps. Similar in situ heating experiments conducted with aberration-corrected STEM revealed that bilayers of NbS 3 -IV chains convert topotactically into aligned 2H-NbS 2 sheets upon loss of sulfur. Atomic resolution imaging, fast Fourier transform analysis, and electron energy loss spectroscopy confirmed these chemical changes, from which we propose an atomistic mechanism for the NbS 3 -IV → 2H-NbS 2 conversion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Building Structure-Property Relationships of Cycloalkanes in Support of Their Use in Sustainable Aviation Fuels

In 2018 13.7 EJ of fuel were consumed by the global commercial aviation industry. Worldwide, demand will increase into the foreseeable future. Developing Sustainable Aviation Fuels (SAFs), with decreased CO 2 and soot emissions, will be pivotal to the on-going mitigation efforts against global warming. Minimizing aromatics in aviation fuel is desirable because of the high propensity of aromatics to produce soot during combustion. Because aromatics cause o-rings to swell, they are important for maintaining engine seals, and must be present in at least 8 vol% under ASTM-D7566. Recently, cycloalkanes have been shown to exhibit some o-ring swelling behavior, possibly making them an attractive substitute to decrease the aromatic content of aviation fuel. Cycloalkanes must meet specifications for a number of other physical properties to be compatible with jet fuel, and these properties can vary greatly with the cycloalkane chemical structure, making their selection difficult. Building a database of structure-property relationships (SPR) for cycloalkanes greatly facilitates their furthered inclusion into aviation fuels. The work presented in this paper develops SPRs by building a data set that includes physical properties important to the aviation industry. The physical properties considered are energy density, specific energy, melting point, density, flashpoint, the Hansen solubility parameter, and the yield sooting index (YSI). Further, our data set includes cycloalkanes drawn from the following structural groups: fused cycloalkanes, n-alkylcycloalkanes, branched cycloalkanes, multiple substituted cycloalkanes, and cycloalkanes with different ring sizes. In addition, a select number of cycloalkanes are blended into Jet-A fuel (POSF-10325) at 10 and 30 wt%. Comparison of neat and blended physical properties are presented. One major finding is that ring expanded systems, those with more than six carbons, have excellent potential for inclusion in SAFs. Our data also indicate that polysubstituted cycloalkanes have higher YSI values.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗