Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “predictive synthesis”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Design and Synthesis of PtPdNiCoMn High‐Entropy Alloy Electrocatalyst for Enhanced Alkaline Hydrogen Evolution Reaction: A Theoretically Supported Predictive Design Approach

Electrocatalytic hydrogen generation requires a multifunctional electrocatalyst with abundant active sites to drive multielectron transfer reactions. High entropy alloys (HEA) are five or more-elements with high configurational entropy are considered unique materials for next-generation electrocatalysts. Here, in this work, based on new screening guidelines for catalyst selections that combine density-functional theory calculated Gibbs formation-enthalpy with bond length and electronegativity variance, a novel HEA electrocatalyst consisting of five elements, namely, Pt, Pd, Ni, Co, and Mn has been designed. By simple room temperature electrodeposition, the designed catalyst is prepared and its hydrogen evolution reaction (HER) is explored and validated through experimental and theoretical approaches. The HEA demonstrated a superior HER activity with an overpotential of 22.6 mV at -10 mA cm -2 which outperforms Pt/C commercial catalyst. No evident degradation of the material is detected even after 100 hours of continuous operation under high current density. Moreover, the HEA has shown exceptional performance in harsh electrolyte conditions such as in simulated seawater and actual seawater. Remarkably, the density-functional theory calculated Gibbs formation-enthalpy is small (≈0 eV) compared to Pt/C placing the new HEA near the apex of Trasatti's model of Volcano plot, which is also suggestive of superior HER activity.

36 MATERIALS SCIENCE↗
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 OSTI2023

Phase-field modeling of solid-state metathesis reactions with the charge neutrality constraint

In this work, we present a phase-field model that captures the evolution of ionic concentrations and phase fractions during solid-state metathesis (SSM) reactions where diffusion limits the rate of transformation. The evolution of the mole fraction of each ion is obtained via governing equations that describe the reduction of a free energy, which includes an energy landscape with local minima located at compositions corresponding to stable products. We utilized two Lagrange multipliers to impose constraints of electroneutrality as well as on the sum of mole fractions, which were then eliminated to derive set of two partial differential equations that describe the dynamics of the mole fraction evolution. From these governing equations, the expressions for effective mobilities for the cations and the anions were obtained. We first study the effect of mobilities of ions on the reaction kinetics, using a simple model considering the ions with an identical absolute value of charge numbers. The simulation results show that the overall characteristic mobility, defined as the sum of the two effective ionic mobilities, provides an excellent measure of the rate at which reaction progresses and that the ratio of the effective mobilities of the anions and the cations signifies the manner by which the reaction progresses. We then generalize the model to consider ions with different charge numbers and tuned the mobility of ions based on their diffusion coefficients reported in the literature and experimental data from a thin-film experiment for the synthesis of FeS 2 to demonstrate the capability of the model to predict the phase evolution during SSM reactions. In particular, the simulation predicts nonplanar phase evolution, which is recently observed in thin-film reactions for the synthesis of FeS 2 via transmission electron microscopy. The approach can serve as a basis for models for phase transformations in other multiphase ionic mixtures, such as in all-solid-state batteries and in ionic liquids.

36 MATERIALS SCIENCE↗
NASA NTRS1990

Vector adaptive predictive coder for speech and audio

A real-time vector adaptive predictive coder which approximates each vector of K speech samples by using each of M fixed vectors in a first codebook to excite a time-varying synthesis filter and picking the vector that minimizes distortion. Predictive analysis for each frame determines parameters used for computing from vectors in the first codebook zero-state response vectors that are stored at the same address (index) in a second codebook. Encoding of input speech vectors s.sub.n is then carried out using the second codebook. When the vector that minimizes distortion is found, its index is transmitted to a decoder which has a codebook identical to the first codebook of the decoder. There the index is used to read out a vector that is used to synthesize an output speech vector s.sub.n. The parameters used in the encoder are quantized, for example by using a table, and the indices are transmitted to the decoder where they are decoded to specify transfer characteristics of filters used in producing the vector s.sub.n from the receiver codebook vector selected by the vector index transmitted.

Chen, Juin-Hwey↗
DOE OSTI2020

Predicting Morphological Evolution during Coprecipitation of MnCO 3 Battery Cathode Precursors Using Multiscale Simulations Aided by Targeted Synthesis

The performance of lithium-ion batteries is intimately linked to both the structure and the morphology of the cathode material, which in turn is critically linked to the synthesis conditions. However, few studies focus on understanding synthesis, especially during the coprecipitation of metal oxide precursors, a process that largely determines the final morphology of the material. In this paper, we go beyond the typical equilibrium particle shape analysis conducted in the literature and incorporate kinetic aspects of morphology evolution. We perform these studies using controlled synthesis on a well-defined metal salt system (MnCO 3 ) combined with multiscale simulations and high-resolution microscopy. Results show that with increasing metal concentration, the particles transition from rhombohedral to cubic to spherical shapes. Computational analysis using density functional theory (DFT) reveals that rhombohedral shaped particles evolve under equilibrium conditions. Phase field techniques indicate that at higher metal concentrations, fast growth kinetics of the precipitates result in the transition to cubic and, subsequently, spherical shapes, accompanied by a decrease in particle size. This study, while limited to the one metal salt system, provides an approach to shed light on the synthesis process of mixed transition metal salts, gradient materials, and other cathode materials of interest to the battery community.

25 ENERGY STORAGE↗
DOE OSTI2022

Composite Correlated Molecular Orbital Theory Calculations of Ring Strain for Use in Predicting Polymerization Reactions

Strained ring systems play an important role in synthesis and can be characterized by the ring strain energy (RSE). The RSE of 3, 4, 5, and 6 membered saturated and unsaturated ring systems containing N, O, P, and S heteroatoms and H, F, SiMe 3 , and SO 2 Me substituents were calculated at the G3(MP2) composite correlated molecular orbital theory level using up to 5 models to predict the RSE. Generally, the RSE decreased as ring size increased with a substantial decrease from 4 to 5 membered rings. Replacement of a ring CH 2 with P or S reduced the RSE, consistent with less angle strain. The RSE for unsaturated systems were generally greater than for saturated systems due to increased angle strain. No general trends were found with respect to substituent effects. In conclusion, the RSE values suggest that 3-pyrroline and 2-pyrroline and their derivatives may be able to support ring opening metathesis polymerization and warrant further study.

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

Trends in Carbon, Oxygen, and Nitrogen Core in the X-ray Absorption Spectroscopy of Carbon Nanomaterials: A Guide for the Perplexed

Successful deployment of carbon nanomaterials in many applications, such as sensing, energy storage, and catalysis, relies on the selection, synthesis, and tailoring of the surface properties. Predictive analysis of the behavior is difficult without detailed knowledge of the differences between various carbon nanomaterials and their surface functionalization, thus leaving the selection process to traditional trial-and-error work. The present characterization fills this knowledge gap for carbon nanomaterial surface properties with respect to chemical states and functionalization. We present an overview of the chemical trends that can be extracted from soft X-ray absorption spectroscopy (XAS) spectra on an extended set of nonideal carbon nanomaterials as a function of sp 2 bonded carbon and bond ordering. In particular, the surface chemical state, the presence of long-range order in the carbon matrix, and a qualitative estimation of the amount of oxygen and nitrogen and their respective functional group formation on the material surface, together with the detailed material fabrication parameters, are reported. The results expand our understanding of carbon nanomaterial functionalization, which can support material selection in practice, provided that the specifications of the application are known.

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

Accelerated discovery of a large family of quaternary chalcogenides with very low lattice thermal conductivity

The development of efficient thermal energy management devices such as thermoelectrics and barrier coatings often relies on compounds having low lattice thermal conductivity (κ l ). Here, we present the computational discovery of a large family of 628 thermodynamically stable quaternary chalcogenides, AMM'Q 3 (A = alkali/alkaline earth/post-transition metals; M/M' = transition metals, lanthanides; Q = chalcogens) using high-throughput density functional theory (DFT) calculations. We validate the presence of low κ l in these materials by calculating κ l of several predicted stable compounds using the Peierls–Boltzmann transport equation. Our analysis reveals that the low κ l originates from the presence of either a strong lattice anharmonicity that enhances the phonon-scatterings or rattler cations that lead to multiple scattering channels in their crystal structures. Our thermoelectric calculations indicate that some of the predicted semiconductors may possess high energy conversion efficiency with their figure-of-merits exceeding 1 near 600 K. Our predictions suggest experimental research opportunities in the synthesis and characterization of these stable, low κ l compounds.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Solvation and oxidation effects on the crystal structure and morphology of tetraoxolene-based materials

Owing to their rich redox behavior and strong metal chelating ability, tetraoxolene ligands have been established as one of the foundational building blocks for multifunctional metal–organic materials. Here, we show how simple and often overlooked synthetic parameters can be used to control the structures of transition metal and lanthanide-based metal–tetraoxolene materials across multiple length scales. Through the synthesis of twelve new compounds, we provide a comprehensive survey detailing how the choice of solvent, initial ligand redox state, and in situ oxidant impact the local coordination geometry and chain architecture, as well as the crystal size and shape (e.g., rods vs. platelets). This work represents an important step towards the synthesis of new metal–tetraoxolene materials with predictable architectures and, therefore, targeted functionality.

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

Resolving local ordering and structure in Mn x Ge 1- x Te alloys through thermodynamic ensembles of pair distribution functions

Characterizing local bonding environments in complex materials is essential for understanding and optimizing their properties. Equally as important is the ability to predict local motifs as a function of synthesis conditions, enhancing chemists’ ability to design properties into materials. In this study, we present an approach to leverage statistical mechanics to generate temperature- and energy-informed ensemble averaged pair distribution functions (PDFs). This method, which we have named Thermodynamic Ensemble Averages of PDFs for Ordering and Transformations (TEAPOT), utilizes density functional theory (DFT) to relax supercells while incorporating energetic penalties for local order, enabling accurate and computationally efficient analysis of local structure. We apply this method to the neutron PDF measurements of the pseudobinary MnTe–GeTe (MGT) alloy, demonstrating its capability to resolve complex local distortions and chemical ordering. Our results reveal detailed insights into phase transformations and local distortions driven by Mn substitution. For compositions that globally present as rock salt, our analysis reveals that Ge coordination geometry is heavily impacted by synthesis temperature. We propose that high temperature synthesis conditions promote a lowered Ge polyhedra distortion, promoting high charge carrier mobility due to the alignment of local and global structure. Incorporating statistical mechanics and computation into experimental analysis thus guides synthesis of tailored local structure.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Molecular beam epitaxy of PdO on MgO (001)

PdO, widely used in catalysis in powder form for decades, has been predicted recently to be a Dirac semimetal. Synthesis of high-quality single crystals of this material is thus of great interest. Here, by using ozone-assisted molecular beam epitaxy, PdO thin films were grown on a MgO (001) substrate. X-ray diffraction and transmission electron microscopy indicate the film is a / b axis oriented, with the c axis lying in plane. Fully oxygenated PdO films have a low density of holelike carriers, and are insulating at the lowest temperatures. Our density functional theory calculations using the Heyd-Scuseria-Ernzerhof exchange-correlation functional suggest a ~1.0 eV band gap at the M point, where the gap can be reduced by tensile strain along the c axis and the bands begin to invert when the tensile strain is as high as 18%. Although tensile strain of this magnitude is experimentally not viable using epitaxy, electrons can be doped by oxygen reduction. Finally, our results emphasize the need for careful consideration of electron correlation effects and stoichiometry in ab initio modeling of topological semimetals involving transition metal oxides.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Plant diversity and functional identity drive grassland rhizobacterial community responses after 15 years of CO 2 and nitrogen enrichment

Abstract Improved understanding of bacterial community responses to multiple environmental filters over long time periods is a fundamental step to develop mechanistic explanations of plant–bacterial interactions as environmental change progresses. This is the first study to examine responses of grassland root‐associated bacterial communities to 15 years of experimental manipulations of plant species richness, functional group and factorial enrichment of atmospheric CO 2 (eCO 2 ) and soil nitrogen (+N). Across the experiment, plant species richness was the strongest predictor of rhizobacterial community composition, followed by +N, with no observed effect of eCO 2 . Monocultures of C 3 and C 4 grasses and legumes all exhibited dissimilar rhizobacterial communities within and among those groups. Functional responses were also dependent on plant functional group, where N 2 ‐fixation genes, NO 3− ‐reducing genes and P‐solubilizing predicted gene abundances increased under resource‐enriched conditions for grasses, but generally declined for legumes. In diverse plots with 16 plant species, the interaction of eCO 2 +N altered rhizobacterial composition, while +N increased the predicted abundance of nitrogenase‐encoding genes, and eCO 2 +N increased the predicted abundance of bacterial P‐solubilizing genes. Synthesis : Our findings suggest that rhizobacterial community structure and function will be affected by important global environmental change factors such as eCO 2 , but these responses are primarily contingent on plant species richness and the selective influence of different plant functional groups.

Revillini, Daniel↗
NASA NTRS1988

Characterization of damped structural connections for multi-component systems

The inability to model connections adequately has historically limited the ability to predict overall system dynamic response. Connections between structural components are often mechanically complex and difficult to accurately model analytically. Improved analytical models for connections are needed to improve system dynamic predictions. This study explores combining Component Mode Synthesis methods for coupling structural components with Parameter Identification procedures for improving the analytical modeling of the connections. Improvements in the connection stiffness and damping properties are computed in terms of physical parameters so the physical characteristics of the connections can be better understood, in addition to providing improved input for the system model.

Lawrence, Charles↗
NASA NTRS1989

Characterization of damped structural connections for multi-component systems

The inability to model connections adequately has historically limited the ability to predict overall system dynamic response. Connections between structural components are often mechanically complex and difficult to accurataely model analytically. Improved analytical models for connections are needed to improve system dynamic predictions. This study explores combining Component Mode Synthesis methods for coupling structural components with Parameter Identification procedures for improving the analytical modeling of the connections. Improvements in the connection stiffness and damping properties are computed in terms of physical parameters so the physical characteristics of the connections can be better understood, in addition to providing improved input for the system model.

Lawrence, Charles↗
NASA NTRS1993

Interferometry of Cyg A and Cas A - Source noise at 327 MHz

Interferometric observations of Cyg A and Cas A at 327 MHz confirm predictions for the characteristics of noise in synthesis images of very bright sources. On a single baseline, the noise variances of the real and imaginary components of the complex visibility are not equal. The noise in an image is larger for positions on-source than off-source. The on-source noise is scattered into the off-source region by the sidelobes of the synthesized beam. Part of this contribution to the off-source noise can be removed by judicious deconvolution.

Mccullough, Peter R.↗
NASA NTRS2020

A Census of Ultraluminous X-ray Sources in the Local Universe

Using the Chandra Source Catalog 2.0and a newly compiled catalogue of galaxies in the local Universe, we deliver a census of ultraluminous X-ray source (ULX) populations in nearby galaxies. We find 629 ULX candidates in 309 galaxies with distance smaller than 40 Mpc. The foreground/background contamination is∼20 per cent. The ULX populations in bona fide star-forming galaxies scale on average with star formation rate and stellar mass (M) such that the number of ULXs per galaxy is 0.45+0.06−0.09×SFRMyr−1+3.3+3.8−3.2×MM. The scaling depends strongly on the morphological type. This analysis shows that early spiral galaxies contain an additional population of ULXs that scales with Mstar. We also confirm the strong anticorrelation of the ULX rate with the host galaxy’s metallicity. In the case of early-type galaxies, we find that there is a non-linear dependence oft he number of ULXs with Mstar which is interpreted as the result of star formation history differences. Taking into account age and metallicity effects, we find that the predictions from X-ray binary population synthesis models are consistent with the observed ULX rates in early-type galaxies, as well as spiral/irregular galaxies.

K Kovlakas↗
DOE OSTI2021

BETO 2021 Peer Review - Advanced Catalyst Synthesis and Characterization (ACSC) Project WBS 2.5.4.304; 303; 305

The Advanced Catalyst Synthesis and Characterization (ACSC) project, in close collaboration with the Chemical Catalysis for Bioenergy (ChemCatBio) Consortium enabling projects, CatCost, and the Engineering of Catalyst Scale-Up project, (1) provides fundamental insight into working catalysts leading to actionable recommendations for all of the ChemCatBio catalysis projects, (2) addresses overarching catalysis challenges central to the ChemCatBio Consortium, and (3) adapts and applies new synthesis methodologies and in situ/operando characterization capabilities to meet the evolving needs of the catalysis projects. The outcome is a transition from empirical catalyst development to rational design through the prediction of materials with targeted properties based on advanced characterization combined with computational modeling, and the synthesis of next generation catalysts with predicted structures that yield demonstrated improvements in catalytic performance. In FY18, the ACSC helped to demonstrate the utility of the complete catalyst and process development cycle for dimethyl ether to high-octane gasoline over metal-modified zeolite catalysts for the Upgrading of C1 Building Blocks project, and in FY21 will leverage capabilities, expertise, and computational models established for this effort to target next-generation catalysts for ethanol to distillates for the Upgrading of C2 Intermediates project with enhanced performance in half the time.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Direct Ab Initio Simulation of the Synthesis of BaZrO 3 and the Microstructure Impacts on Proton Transport

Controlling and predicting the processing-structure-performance relationship in functional materials is a grand challenge in materials science, with important implications for a wide range of emerging applications; a high fidelity understanding of the performance impact of microstructures formed under synthesis conditions is required to develop advanced materials, such as solid-state fuel cells and electrolyzers. Using the ceramic BaZrO 3 as a case study, we directly simulate the synthesis and investigate how proton transport is dictated by microstructures. We develop a framework that couples density functional theory (DFT), machine-learning interatomic potential (MLIP) driven molecular dynamics, and grand canonical Monte Carlo to perform large-scale, microstructure-resolved, atomistic simulations of proton transport in experimentally representative polycrystalline structures. Our fully ab initio approach, using a MLIP as a proxy for DFT, allows us to quantify the competition between two distinct diffusion mechanisms: one associated with grain-boundary regions and another within grains. When the impacts of grain boundaries are taken into account, proton transport exhibits substantial deviation from the bulk oxide limit. This addresses long-standing discrepancies between theory and experiments. Our integrated approach provides atomistic insight into microstructure-dependent proton pathways in BaZrO 3 and establishes a general protocol for predicting processing-structure-performance relationships.

organic↗