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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Nanomaterial Synthesis Insights from Machine Learning of Scientific Articles by Extracting, Structuring, and Visualizing Knowledge

Nanomaterials of varying compositions and morphologies are of interest for many applications from catalysis to optics, but the synthesis of nanomaterials and their scale-up are most often time-consuming and Edisonian processes. Information gleaned from the scientific literature can help inform and accelerate nanomaterials development, but again, searching the literature and digesting the information are time-consuming manual processes for researchers. To help address these challenges, here we developed scientific article-processing tools that extract and structure information from the text and figures of nanomaterials articles, thereby enabling the creation of a personalized knowledgebase for nanomaterials synthesis that can be mined to help inform further nanomaterials development. Starting with a corpus of ~35k nanomaterials-related articles, we developed models to classify articles according to the nanomaterial composition and morphology, extract synthesis protocols from within the articles’ text, and extract, normalize, and categorize chemical terms within synthesis protocols. We demonstrate the efficiency of the proposed pipeline on an expert-labeled set of nanomaterials synthesis articles, achieving 100% accuracy on composition prediction, 95% accuracy on morphology prediction, 0.99 AUC on protocol identification, and up to a 0.87 F1-score on chemical entity recognition. In addition to processing articles’ text, microscopy images of nanomaterials within the articles are also automatically identified and analyzed to determine the nanomaterials’ morphologies and size distributions. To enable users to easily explore the database, we developed a complementary browser-based visualization tool that provides flexibility in comparing across subsets of articles of interest. We use these tools and information to identify trends in nanomaterials synthesis, such as the correlation of certain reagents with various nanomaterial morphologies, which is useful in guiding hypotheses and reducing the potential parameter space during experimental design.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Synthesis of α,β‐ and β‐Unsaturated Acids and Hydroxy Acids by Tandem Oxidation, Epoxidation, and Hydrolysis/Hydrogenation of Bioethanol Derivatives

Abstract We report a reaction platform for the synthesis of three different high‐value specialty chemical building blocks starting from bio‐ethanol, which might have an important impact in the implementation of biorefineries. First, oxidative dehydrogenation of ethanol to acetaldehyde generates an aldehyde‐containing stream active for the production of C 4 aldehydes via base‐catalyzed aldol‐condensation. Then, the resulting C 4 adduct is selectively converted into crotonic acid via catalytic aerobic oxidation (62 % yield). Using a sequential epoxidation and hydrogenation of crotonic acid leads to 29 % yield of β‐hydroxy acid (3‐hydroxybutanoic acid). By controlling the pH of the reaction media, it is possible to hydrolyze the oxirane moiety leading to 21 % yield of α,β‐dihydroxy acid (2,3‐dihydroxybutanoic acid). Crotonic acid, 3‐hydroxybutanoic acid, and 2,3‐dihydroxybutanoic acid are archetypal specialty chemicals used in the synthesis of polyvinyl‐co‐unsaturated acids resins, pharmaceutics, and bio‐degradable/ ‐compatible polymers, respectively.

Santhanaraj, Daniel↗
DOE OSTI2020

Synthesis of α,β‐ and β‐Unsaturated Acids and Hydroxy Acids by Tandem Oxidation, Epoxidation, and Hydrolysis/Hydrogenation of Bioethanol Derivatives

Abstract We report a reaction platform for the synthesis of three different high‐value specialty chemical building blocks starting from bio‐ethanol, which might have an important impact in the implementation of biorefineries. First, oxidative dehydrogenation of ethanol to acetaldehyde generates an aldehyde‐containing stream active for the production of C 4 aldehydes via base‐catalyzed aldol‐condensation. Then, the resulting C 4 adduct is selectively converted into crotonic acid via catalytic aerobic oxidation (62 % yield). Using a sequential epoxidation and hydrogenation of crotonic acid leads to 29 % yield of β‐hydroxy acid (3‐hydroxybutanoic acid). By controlling the pH of the reaction media, it is possible to hydrolyze the oxirane moiety leading to 21 % yield of α,β‐dihydroxy acid (2,3‐dihydroxybutanoic acid). Crotonic acid, 3‐hydroxybutanoic acid, and 2,3‐dihydroxybutanoic acid are archetypal specialty chemicals used in the synthesis of polyvinyl‐co‐unsaturated acids resins, pharmaceutics, and bio‐degradable/ ‐compatible polymers, respectively.

Santhanaraj, Daniel↗
DOE OSTI2024

Template-independent enzymatic synthesis of RNA oligonucleotides

Abstract RNA oligonucleotides have emerged as a powerful therapeutic modality to treat disease, yet current manufacturing methods may not be able to deliver on anticipated future demand. Here, we report the development and optimization of an aqueous-based, template-independent enzymatic RNA oligonucleotide synthesis platform as an alternative to traditional chemical methods. The enzymatic synthesis of RNA oligonucleotides is made possible by controlled incorporation of reversible terminator nucleotides with a common 3′-O-allyl ether blocking group using new CID1 poly(U) polymerase mutant variants. We achieved an average coupling efficiency of 95% and demonstrated ten full cycles of liquid phase synthesis to produce natural and therapeutically relevant modified sequences. We then qualitatively assessed the platform on a solid phase, performing enzymatic synthesis of severalN + 5 oligonucleotides on a controlled-pore glass support. Adoption of an aqueous-based process will offer key advantages including the reduction of solvent use and sustainable therapeutic oligonucleotide manufacturing.

Biotechnology & Applied Microbiology↗
DOE OSTI2025

Modeling MTS pyrolysis and SiC deposition kinetics using principal component analysis and neural networks

Accurate chemical kinetics modeling is crucial for improving the efficiency of chemical processing and synthesis of ceramic matrix composites. Detailed kinetic models are computationally expensive due to the large number of transported chemical species, while the simplified physics-based models, such as single-step global mechanisms, are efficient but often overlook key chemical intermediates and pathways. Recent deep learning approaches promise accurate and cost-effective models. Yet, they require additional closures for the transported nonlinear latent variables, complicating integration with existing solvers. In this work, we develop a hybrid linear—nonlinear reduced model for silicon carbide deposition from methyltrichlorosilane precursor by combining principal component analysis (PCA) and autoencoder (AE) neural network (NN) approaches. PCA is used to identify a smaller set of linear transport variables, enabling direct reuse of conventional transport solvers. NNs then reconstruct the full chemical state from these reduced variables. We demonstrate the method on a chemical vapor deposition reactor—comprising a gas-phase pyrolysis plug flow reactor and a heterogeneous surface reactor—over a wide range of temperatures, pressures, and residence times. Our PCA–AE model achieves high accuracy with only five transported scalars, achieving an eightfold cost reduction compared to detailed mechanisms, in both a priori (using data from the test set only) and a posteriori (coupled with a differential equation solver). In conclusion, notable errors arise primarily near training domain boundaries and for long residence times, indicating the need for domain shift indicators and better long-horizon predictions in future reduced chemistry model development.

autoencoder neural networks↗
DOE OSTI2024

Tuning Surface, Phase, and Magnetization of Superparamagnetic Magnetite by Ionic Liquids: Single-Step Microwave-Assisted Synthesis

Achieving colloidal and chemical stability in ferrofluids by surface modification requires multiple steps, including purification, ex situ modification steps, and operation at high temperatures. In this study, a single-step microwave-assisted methodology is developed for iron oxide nanoparticle (IONP) synthesis utilizing a series of imidazolium-based ionic liquids (ILs) with chloride, bis(trifluoromethylsulfonyl)imide, and pyrrolide anions as the reaction media, thus eliminating the use of volatile organics while enabling rapid synthesis at 80 °C as well as in situ surface functionalization. The characterized surface functionality, hydrodynamic particle size, magnetization, and colloidal stability of the IONPs demonstrate a strong dependence on the IL structure, ion coordination strength, reactivity, and hydrophilicity. The IONPs present primarily a magnetite (Fe 3 O 4 ) phase with superparamagnetism with the highest saturation magnetization at 81 and 73 emu/g at 10 and 300 K, respectively. Depending on the IL coating, magnetization and exchange anisotropy decrease by 20 and 2–3 emu/g (at 35 wt % IL), respectively, but still represent the highest magnetization achieved for coated IONPs by a coprecipitation method. Further, the surface-functionalized superparamagnetic magnetite nanoparticles show good dispersibility and colloidal stability in water and dimethyl sulfoxide at 0.1 mg/mL concentration over the examined 3 month period. This study reports on the intermolecular and chemical interactions between the particle surface and the ILs under synthetic conditions as they relate to the magnetic and thermal properties of the resulting IONPs that are well suited for a variety of applications, including separation and catalysis.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Fabrication, oxidation, and combustion of nanoscale magnesium diboride and tetraboride

The difficult ignition of boron decreases the combustion efficiency of boron-loaded, fuel-rich propellants. One approach to solving this problem involves the use of magnesium diboride (MgB2), which ignites easier than boron. Magnesium tetraboride (MgB4) offers greater energy density owing to its higher boron content. However, the effect of B/Mg ratio on the ignition and combustion is unknown. Additionally, while nanoscale MgB₂ particles and quasi-2D structures were recently recognized as promising energetic additives, the oxidation and combustion properties of nanoscale MgB₄ have not been explored. The objectives of the present work included synthesis, purification, and high-energy ball milling of MgB2 and MgB4 powders as well as investigation of their thermal decomposition, oxidation, and combustion. The MgB2 and MgB4 powders were fabricated by combustion synthesis in the chemical oven mode and by heating Mg/B mixtures in a tube furnace. The latter method was superior in the synthesis of MgB4. Oxide impurities in the synthesized powders were removed by acid leaching. Nanoscale powders were obtained by high-energy ball milling. Thermal decomposition and oxidation of the obtained MgB₂ and MgB₄ powders were investigated by conducting non-isothermal thermogravimetric analysis (TGA) at temperatures up to 1550 °C in argon and oxygen flows. Combustion of B, MgB₂, and MgB₄ powders with oxygen at atmospheric pressure was studied in a windowed chamber using laser ignition and high-speed video recording. The TGA has shown multi-step decomposition of both magnesium borides in an argon environment. The maximum oxidation rate of MgB4 in oxygen was observed at a much lower temperature than in the case of MgB2. In the combustion experiments, both magnesium borides burned much faster than submicron boron. Ball milling of the borides further increased their burning rates. It has been concluded that nanoscale magnesium tetraboride is a promising ingredient for fuel-rich propellants owing to its high energy density, efficient oxidation, and rapid combustion.

Molina, Andre [The University of Texas at El Paso]↗
DOE OSTI2025

Combinatorial investigation of the Mn–Ge–N chemical system containing ternary nitrides Mn 3 GeN and MnGeN 2

By changing nitrogen chemical potential during synthesis of Mn–Ge–N ternary nitrides, both wurtzite MnGeN 2 and antiperovskite Mn 3 GeN ternary phases are prepared. Antiperovskite films are optically opaque and conductive, while wurtzite films with Mn/(Mn + Ge) ≤ 0.5 transmit light above ~ 2 eV. Alloys of Mn 3 GeN with Si and Al are also investigated. Mn 3 (Ge 1−x Al x )N alloys with 0.07 ≤ x ≤ 0.16 exhibit a cubic (rather than tetragonal) structure. Mn 3 (Ge 1−x Si x )N with x ≤ 0.05 maintains the tetragonal structure but becomes cubic when x > 0.05. This study shows that care must be taken in the synthesis of Mn–Ge–N and similar nitrides, especially when materials are integrated into devices not amenable to structural and chemical probing.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A graph-based network for predicting chemical reaction pathways in solid-state materials synthesis

Abstract Accelerated inorganic synthesis remains a significant challenge in the search for novel, functional materials. Many of the principles which enable “synthesis by design” in synthetic organic chemistry do not exist in solid-state chemistry, despite the availability of extensive computed/experimental thermochemistry data. In this work, we present a chemical reaction network model for solid-state synthesis constructed from available thermochemistry data and devise a computationally tractable approach for suggesting likely reaction pathways via the application of pathfinding algorithms and linear combination of lowest-cost paths in the network. We demonstrate initial success of the network in predicting complex reaction pathways comparable to those reported in the literature for YMnO 3 , Y 2 Mn 2 O 7 , Fe 2 SiS 4 , and YBa 2 Cu 3 O 6.5 . The reaction network presents opportunities for enabling reaction pathway prediction, rapid iteration between experimental/theoretical results, and ultimately, control of the synthesis of solid-state materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Predicting Energetics Materials’ Crystalline Density from Chemical Structure by Machine Learning

To expedite new molecular compound development, a long-sought goal within the chemistry community has been to predict molecules’ bulk properties of interest a priori to synthesis from a chemical structure alone. In this work, we demonstrate that machine learning methods can indeed be used to directly learn the relationship between chemical structures and bulk crystalline properties of molecules, even in the absence of any crystal structure information or quantum mechanical calculations. We focus specifically on a class of organic compounds categorized as energetic materials called high explosives (HE) and predicting their crystalline density. An ongoing challenge within the chemistry machine learning community is deciding how best to featurize molecules as inputs into machine learning models—whether expert handcrafted features or learned molecular representations via graph-based neural network models—yield better results and why. We evaluate both types of representations in combination with a number of machine learning models to predict the crystalline densities of HE-like molecules curated from the Cambridge Structural Database, and we report the performance and pros and cons of our methods. Our message passing neural network (MPNN) based models with learned molecular representations generally perform best, outperforming current state-of-the-art methods at predicting crystalline density and performing well even when testing on a data set not representative of the training data. However, these models are traditionally considered black boxes and less easily interpretable. Here, to address this common challenge, we also provide a comparison analysis between our MPNN-based model and models with fixed feature representations that provides insights as to what features are learned by the MPNN to accurately predict density.

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

Chemical Kinetics in Microdroplets

Micrometer-sized compartments play significant roles in driving heterogeneous transformations within atmospheric and biochemical systems as well as providing vehicles for drug delivery and novel reaction environments for the synthesis of industrial chemicals. Many reports now indicate that reaction kinetics are accelerated under microconfinement, for example, in sprays, thin films, droplets, aerosols, and emulsions. These observations are dramatic, posing a challenge to our understanding of chemical reaction mechanisms with potentially significant practical consequences for predicting the complex chemistry in natural systems. Here we introduce the idea of kinetic confinement, which is intended to provide a conceptual backdrop for understanding when and why microdroplet reaction kinetics differ from their macroscale analogs.

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

Defining the Minimal Set of Microbial Genes Required for Valorization of Lignin Biomass (Final Report)

Project Goals: Lignin is the second most abundant biopolymer on earth and represents a critically underutilized biomass resource for hydrocarbon feedstocks. Despite substantial effort, there is still no efficient process to convert lignin to useable carbon-based platform chemicals and materials. The goal of this project is identify a minimal set of microbial enzymes necessary for lignin breakdown and sufficient for the synthesis of valuable chemical intermediates from lignin isolated as a byproduct of lignocellulosic ethanol production. These genes will be then used to engineer functional whole cell biocatalysts for tunable lignin metabolism. To date, although a number of enzymes have been associated with lignin degradation, most have been tested in isolation (as individual enzymes) and on drastically different substrates -- often dyes that are not related to lignin. In contrast, lignin utilization in nature likely occurs by microbial consortia with multiple enzymes acting synergistically. We propose to examine two separate stages of lignin breakdown carried out by the microbes that do it best: (1) early breakdown of native polymeric lignin into soluble fragments by a set of sequenced wood-rotting fungal species, and (2) downstream metabolism of these soluble lignin fragments to useful chemical intermediates by a panel of sequenced soil saprophytes. Our approach involves testing sets of genes that will be assayed combinatorially in the context of a heterologous expression host. The resulting engineered strains will be systematically assayed using soluble lignin fragments, synthetic defined polymeric lignin, and finally lignin directly sourced from lignocellulosic processing streams. In addition to resulting in a functional whole cell biocatalyst for lignin utilization, we anticipate that this approach will allow us to address key unanswered questions about lignin metabolism in nature, including: (1) Why does the Trametes versicolor genome contain 25 different class II peroxidases? (2) What is the role of laccases in lignin metabolism? Why do some aggressive lignin degraders have many laccases (e.g. >7 in T. versicolor) while others have none (e.g. P. chrysosporium)? (3) How is peroxide provided in a controlled manner to drive peroxidase activity without causing the enzyme inhibition that is so often observed in vitro? (4) What strategies do microbial lignin degraders use to avoid the problem of repolymerization during active lignin degradation? and (5) Can microbial lignin metabolism be diverted for high level production of defined aromatics? A final critical question is whether combining key minimal sets of enzymes from a wide range of organisms will result in engineered strains capable of highly efficient, streamlined pathways for lignin utilization that can be tuned for a specific carbon output. This effort will leverage DOE investments in microbial genome sequencing, and secure a critical channel for lignin biomass utilization that will also help to render lignocellulosic a viable feedstock for the production of renewable liquid biofuels.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Chemical preintercalation of magnesium ions into ⍺-MoO 3 structure for improved electrochemical stability in Li-ion cells

Chemical preintercalation of layered materials, used as electrodes in intercalation-based energy storage devices, represents a promising strategy to enhance electrochemical stability and extend cycle life. However, standardized synthesis approaches for the chemical preintercalation of diverse ions into various layered materials are lacking, necessitating the development of specific synthesis routes for each ion and layered phase combination. In this study, we present the first successful demonstration of Mg 2+ ion chemical preintercalation into the interlayer region of α-MoO 3 , revealing its stabilizing effect during cycling in non-aqueous Li-ion cells. Using ethanol during hydrothermal treatment facilitated molybdenum reduction, which was critical for Mg 2+ ion preintercalation. Interestingly, we found that Mg preintercalation was accompanied by the incorporation of water. Mg-preintercalated α-MoO 3 exhibited enhanced charge storage capacity, electrochemical stability, and power capability compared to pristine α-MoO 3 electrodes. This improved performance is attributed to the structural stabilization provided by Mg 2+ pillars, which prevent undesirable phase transformations during repeated Li intercalation/deintercalation, and increased Li + ion diffusion due to the shielding of electrostatic interactions between electrochemically cycled ions and the α-MoO 3 lattice, enabled by structural water. In conclusion, our study offers new insights into developing chemical preintercalation synthesis approaches that can be broadly applied to a wide range of pillaring ions and layered material hosts.

25 ENERGY STORAGE↗
DOE OSTI2020

Engineering lithium-ion battery cathodes for high-voltage applications using electromagnetic excitation

Microwave radiation (MWR), a type of electromagnetic excitation source, reduces the synthesis temperature and processing time for chemical reactions compared to traditional synthesis methods. Recently, we demonstrated that MWR can engineer ceramics with different crystal phases compared to traditional methods [ Journal of Materials Chemistry A 5 , 35 (2017)]. Here, we further apply the MWR-assisted technique to improve the electrochemical performance of LiCoO 2 cathodes by engineering TiO 2 and ZrO 2 ceramic coatings. Electrochemical tests suggest that the TiO 2 coating improves the rate capability of the LiCoO 2 electrode. Both TiO 2 and ZrO 2 coatings improve the high-voltage (4.5 V) cycling stability of LiCoO 2 . The capacity remaining is improved from 52.8 to 84.4% and 81.9% by the TiO 2 coating and the ZrO 2 coating, respectively, after 40 cycles. We compare these results with existing studies that apply traditional methods to engineer TiO 2 /ZrO 2 on LiCoO 2 , and find that the MWR-assisted method shows better performance improvement. X-ray photoelectron spectroscopy measurements suggest that the improved cycling stability arises from the formation of metal fluorides that protect the electrode from side reactions with electrolytes. This mechanism is further supported by the reduced Co dissolution from TiO 2 /ZrO 2 -coated LiCoO 2 electrode after cycling. This study provides a new toolbox facilitating the integration of many delicate, low melting point materials like polymers into battery electrodes.

25 ENERGY STORAGE↗
DOE OSTI2021

Towards synthetic L 1 0 -FeNi: Detecting the absence of cubic symmetry in Laser-Ablated Fe-Ni nanoparticles

The L 1 0 crystal structure underlines an important class of chemically ordered alloys that exhibits uniaxial magnetocrystalline anisotropy. The near-equiatomic L 1 0 -FeNi extracted from meteorites has demonstrated intriguing magnetic properties for permanent magnet applications. However, the synthesis of this chemically ordered non-cubic structure has been a longstanding challenge. Here, in this work, we demonstrate the absence of cubic symmetry in near-equiatomic Fe-Ni nanoparticles synthesized by picosecond-pulsed laser ablation in liquids. The non-cubic phase detected in these particles can only be L 1 0 -FeNi or hexagonal close-packed (HCP) FeNi, and the absence of cubic symmetry was unequivocal. The orientation relationship between the non-cubic phase and the adjacent cubic phase was characterized by a series of transmission electron microscopy (TEM) techniques, which consistently suggests that the formation of the non-cubic phase involves a martensitic transformation process.

36 MATERIALS SCIENCE↗
NASA NTRS2004

New Material for Surface-Enhanced Raman Spectroscopy

A chemical method of synthesis and application of coating materials that are especially suitable for surface-enhanced Raman spectroscopy (SERS) has been developed. The purpose of this development is to facilitate the utilization of the inherently high sensitivity of SERS to detect chemicals of interest (analytes) in trace amounts, without need for lengthy sample preparation. Up to now, the use of SERS has not become routine because the methods available have not been able to reproduce sampling conditions and provide quantitative measurements. In contrast, the coating materials of the present method enable analysis with minimum preparation of samples, and SERS measurements made using these materials are reproducible and reversible. Moreover, unlike in methods investigated in prior efforts to implement SERS, sampling is not restricted to such specific environments as electrolytes or specific solvents. The coating materials of this method are porous glasses, formed in sol-gel processes, that contain small particles of gold or silver metal. Materials of this type can be applied to the sample-contact surfaces of a variety of sampling and sensing devices, including glass slides, glass vials, fiber-optic probes, and glass tubes. Glass vials with their insides coated according to this method are particularly convenient for SERS to detect trace chemicals in solutions: One simply puts a sample solution containing the analyte(s) into a vial, then puts the vial into a Raman spectrometer for analysis. The chemical ingredients and the physical conditions of the sol-gel process have been selected so that the porous glass formed incorporates particles of the desired metal with size(s) to match the wavelength(s) of the SERS excitation laser in order to optimize the generation of surface plasmons. The ingredients and processing conditions have further been chosen to tailor the porosity and polarity of the glass to optimize the sample flow and the interaction between the analyte(s) and the plasmon field that generates Raman photons. The porous silica network of a sol-gel glass creates a unique environment for stabilizing SERS-active metal particles. Relative to other material structures that could be considered for SERS, the porous silica network offers higher specific surface area and thus greater interaction between analyte molecules and metal particles. Efforts to perform SERS measurements with the help of sampling devices coated by this method have been successful. In tests, numerous organic and inorganic chemicals were analyzed in several solvents, including water. The results of the tests indicate that the SERS measurements were reproducible within 10 percent and linear over five orders of magnitude. One measure of the limits of detectability of chemicals in these tests was found to be a concentration of 300 parts per billion. Further development may eventually make it possible to realize the full potential sensitivity of SERS for detecting some analytes in quantities as small as a single molecule.

Farquharson, Stuart↗
NASA NTRS1980

Studies of the chemical basis of the origin of protein synthesis Initiation and direction of peptide growth

The data presented in this paper show that the ease of nonenzymatic activation of carboxylic acids by ATP at pH 5 varies directly with the pKa of the carboxyl group, and is consistent with the idea that it is the protonated form of the carboxyl group which participates in the activation reaction. Consequently, since most N-blocked amino acids have higher pKas than do their unblocked forms, they are activated more readily, and it has been demonstrated that this principle applies to peptides as well, which are activated more rapidly than single amino acids. It is proposed that this fact may be partly responsible for the origin of two important features still observed in contemporary protein synthesis: (1) initiation in prokaryotes is accomplished with an N-blocked amino acid, and (2) elongation in all living systems occurs at the carboxyl end of the growing peptide.

Mullins, D. W., Jr.↗