Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “model compounds”

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 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Circadian Effects on Simple Components of Complex Task Performance

The goal of this study was to advance understanding and prediction of the impact of circadian rhythm on aspects of complex task performance during unexpected automation failures, and subsequent fault management. Participants trained on two tasks: a process control simulation, featuring automated support; and a multi-tasking platform. Participants then completed one task in a very early morning (circadian night) session, and the other during a late afternoon (circadian day) session. Small effects of time of day were seen on simple components of task performance, but impacts on more demanding components, such as those that occur following an automation failure, were muted relative to previous studies where circadian rhythm was compounded with sleep deprivation and fatigue. Circadian low participants engaged in compensatory strategies, rather than passively monitoring the automation. The findings and implications are discussed in the context of a model that includes the effects of sleep and fatigue factors.

circadian effects↗
DOE OSTI2020

Frequency-domain hot-wire sensor and 3D model for thermal conductivity measurements of reactive and corrosive materials at high temperatures

High temperature solids and liquids are becoming increasingly important in next-generation energy and manufacturing systems that seek higher efficiencies and lower emissions. Accurate measurements of thermal conductivity at high temperatures are required for the modeling and design of these systems, but commonly employed time-domain measurements can have errors from convection, corrosion, and ambient temperature fluctuations. Here, we describe the development of a frequency-domain hot-wire technique capable of accurately measuring the thermal conductivity of solid and molten compounds from room temperature up to 800 °C. Therefore, by operating in the frequency-domain, we can lock into the harmonic thermal response of the material and reject the influence of ambient temperature fluctuations, and we can keep the probed volume below 1 µl to minimize convection. The design of the microfabricated hot-wire sensor, electrical systems, and insulating wire coating to protect against corrosion is covered in detail. Furthermore, we discuss the development of a full three-dimensional multilayer thermal model that accounts for both radial conduction into the sample and axial conduction along the wire and the effect of wire coatings. The 3D, multilayer model facilitates the measurement of small sample volumes important for material development. A sensitivity analysis and an error propagation calculation of the frequency-domain thermal model are performed to demonstrate what factors are most important for thermal conductivity measurements. Finally, we show thermal conductivity measurements including model data fitting on gas (argon), solid (sulfur), and molten substances over a range of temperatures.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

National Energy Water Treatment & Speciation (NEWTS): A Water & Critical Mineral Database and Dashboard

The scarcity of water resources, the need for beneficial water reuse, and the challenges of wastewater treatment are becoming increasingly pressing in economic, social, and environmental domains. Addressing these concerns requires effective treatment strategies to manage wastewater streams and tackle environmental and economic issues. Furthermore, the recovery of critical minerals from the waste streams associated with energy production holds the promise of offsetting treatment costs and securing local sources of valuable minerals. However, relevant data on these waste streams are dispersed and challenging to locate. The process of ingesting such data into modeling software often involves multiple steps, requiring data restructuring to meet software-input requirements. The non-standardized reporting of water data makes data aggregation and reformatting a time-consuming process. Additionally, essential attributes necessary for modeling water treatment and mineral scale formation are frequently missing. Moreover, data gaps vary depending on the region of interest. Consequently, there is a pressing need for high-quality energy-water composition data that can be easily imported into water chemistry modeling software. To address this need, the National Energy Technology Laboratory has created the National Energy Water Treatment and Speciation (NEWTS) Database and Dashboard—a free online tool catering to community leaders and water researchers. NEWTS facilitates a comprehensive understanding of the composition of energy-related wastewater streams in the United States. The datasets provide detailed concentrations and speciation of major and minor aqueous compounds in energy-related wastewater streams, including power plant leachate, acid mine drainage, brackish water, and oil and gas produced water across the United States. Many of the aqueous species are critical minerals (Li, REEs) in high demand to modernize the world’s energy infrastructure. Many of the datasets also contain volumetric flow-rates needed to model the treatment and reuse scenarios in advanced aqueous chemistry software programs. The NEWTS Database and Dashboard offer public access to hitherto challenging-to-access datasets, presented in a standardized format that is tailored for easy input into aqueous chemistry modeling software. By performing the work needed to transform dispersed, disparate data sources into unified, model-ready datasets, NEWTS serves as an essential resource in advancing water treatment research and sustainable water resource management.

produced water management↗
DOE OSTI2024

Chemical Differences between Phenolic Secondary Organic Aerosol Formed through Gas-Phase and Aqueous-Phase Reactions

Phenolic compounds, which are significant emissions from biomass burning (BB), undergo rapid photochemical reactions in both gas and aqueous phases to form secondary organic aerosol, namely, gasSOA and aqSOA, respectively. The formation of gasSOA and aqSOA involves different reaction mechanisms, leading to different product distributions. In this study, we investigate the gaseous and aqueous reactions of guaiacol a representative BB phenol to elucidate the compositional differences between phenolic aqSOA and gasSOA. Aqueous-phase reactions of guaiacol produce higher SOA yields than gas-phase reactions (e.g., roughly 60 vs 30% at one half-life of guaiacol). These aqueous reactions involve more complex reaction mechanisms and exhibit a more gradual SOA evolution than their gaseous counterparts. Initially, gasSOA forms with high oxidation levels (O/C > 0.82), while aqSOA starts with lower O/C (0.55–0.75). However, prolonged aqueous-phase reactions substantially increase the oxidation state of aqSOA, making its bulk chemical composition closer to that of gasSOA. Additionally, aqueous reactions form a greater abundance of oligomers and high-molecular-weight compounds, alongside a more sustained production of carboxylic acids. AMS spectral signatures representative of phenolic gasSOA have been identified, which, together with tracer ions of aqSOA, can aid in the interpretation of field observation data on aerosol aging within BB smoke. The notable chemical differences between phenolic gasSOA and aqSOA highlighted in this study also underscore the importance of accurately representing both pathways in atmospheric models to better predict the aerosol properties and their environmental impacts.

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

Accelerating Computational Materials Discovery with Machine Learning and Cloud High-Performance Computing: from Large-Scale Screening to Experimental Validation

High-throughput computational materials discovery has promised significant acceleration of the design and discovery of new materials for many years. Despite a surge in interest and activity, the constraints imposed by large-scale computational resources present a significant bottleneck. Furthermore, examples of large-scale computational discovery carried through experimental validation remain scarce, especially for materials with product applicability. In this paper, we demonstrate how this vision became reality by first combining state-of-the-art artificial intelligence (AI) models and traditional physics-based models on cloud high performance computing (HPC) resources to quickly navigate through more than 32 million candidates and predict around half a million potentially stable materials. Focusing on solid-state electrolytes for battery applications, our discovery pipeline further identified 18 promising candidates with new compositions and rediscovered a decade’s worth of collective knowledge in the field as a byproduct. By employing around one thousand virtual machines in the cloud, this process took less than 80 hours. We then synthesized and experimentally characterized the structures and conductivities of our top candidates, the Na x Li 3-x YCl 6 (0.5 ≤ x ≤ 2.5) series, demonstrating the potential of these compounds to serve as solid electrolytes. Additional candidate materials are currently under experimental investigation that could offer more examples of the computational discovery of new phases of Li- and Na-conducting solid electrolytes. We believe this unprecedented approach of synergistically integrating AI models and cloud HPC not only accelerates materials discovery but also showcases the potency of AI-guided experimentation in unlocking transformative scientific breakthroughs with real-world applications.

36 MATERIALS SCIENCE↗
DOE OSTI2023

HT Model Dataset

This website contains the dataset that was used for writing the manuscript "HT Model: Using the Molecular Transformer for predicting hydrotreating reactions" (PNNL-SA-186589) The dataset includes a collection of hydrotreating reactions compiled from 41 peer-reviewed literature sources. These sources contain experimental data related to hydrotreating reactions. These reactions involve the reaction of chemical compounds with hydrogen gas in the presence of a catalyst to remove heteroatoms or to convert specific functional groups. The dataset contains reactions both with and without reaction conditions. Reaction conditions refer to the specific parameters under which the reaction takes place, such as temperature and pressure. For each reaction, the dataset includes both SMILES and SELFIES representations. SMILES (Simplified Molecular Input Line Entry System) and SELFIES (SELF-referencIng Embedded Strings) are two popular notations used to represent chemical structures in a compact and standardized format. The dataset was created with the aim of training a predictive model, specifically using the Molecular Transformer architecture.

bioprocessing, hydrotreating, deep learning algori↗
DOE OSTI2023

Oxamniquine derivatives overcome Praziquantel treatment limitations for Schistosomiasis

Human schistosomiasis is a neglected tropical disease caused by Schistosoma mansoni, S. haematobium, and S. japonicum. Praziquantel (PZQ) is the method of choice for treatment. Due to constant selection pressure, there is an urgent need for new therapies for schistosomiasis. Previous treatment of S. mansoni included the use of oxamniquine (OXA), a drug that is activated by a schistosome sulfotransferase (SULT). Guided by data from X-ray crystallography and Schistosoma killing assays more than 350 OXA derivatives were designed, synthesized, and tested. We were able to identify CIDD-0150610 and CIDD-0150303 as potent derivatives in vitro that kill (100%) of all three Schistosoma species at a final concentration of 71.5 μM. We evaluated the efficacy of the best OXA derivates in an in vivo model after treatment with a single dose of 100 mg/kg by oral gavage. The highest rate of worm burden reduction was achieved by CIDD -150303 (81.8%) against S. mansoni, CIDD-0149830 (80.2%) against S. haematobium and CIDD-066790 (86.7%) against S. japonicum. We have also evaluated the ability of the derivatives to kill immature stages since PZQ does not kill immature schistosomes. CIDD-0150303 demonstrated (100%) killing for all life stages at a final concentration of 143 μM in vitro and effective reduction in worm burden in vivo against S. mansoni. To understand how OXA derivatives fit in the SULT binding pocket, X-ray crystal structures of CIDD-0150303 and CIDD-0150610 demonstrate that the SULT active site will accommodate further modifications to our most active compounds as we fine tune them to increase favorable pharmacokinetic properties. Treatment with a single dose of 100 mg/kg by oral gavage with co-dose of PZQ + CIDD-0150303 reduced the worm burden of PZQ resistant parasites in an animal model by 90.8%. Therefore, we conclude that CIDD-0150303, CIDD-0149830 and CIDD-066790 are novel drugs that overcome some of PZQ limitations, and CIDD-0150303 can be used with PZQ in combination therapy.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Predictive Design of Hybrid Improper Ferroelectric Double Perovskite Oxides

The computational design of suitable multiferroic double perovskite oxides requires finding materials that exhibit sizable polarization, magnetization, and coupling between them. Oxides with the chemical formula of AA'BB'O 6 with building blocks of ABO 3 single perovskite oxides in centrosymmetric Pnma symmetry are strong candidates that have been reported to satisfy such criteria. The system lowers to noncentrosymmetric, polar P2 1 symmetry if A/A' layered and B/B' rocksalt cation orderings are imposed. A detailed compositional search over a variety of chemical spaces followed by evaluating their polarization may lead to the identification of more of these compounds with ferroelectric ordering. The standard density functional theory practices to estimate polarization within the Berry phase formalism require the systems to be perfectly insulating. The number of compounds that can be evaluated using this method is therefore limited. In this work, we introduce a predictive learning strategy based on importance sampling to build a series of machine learning models using results from first-principles simulations to predict polarization and the corresponding switching barrier. The geometry-driven features related to charge states and cationic radii play key roles in predicting the switching barrier with complementary contributions from the key structural mode-based order parameters. These modes become important to draw reasonable predictions of polarization components from machine learning models. In conclusion, our predictive models identify candidates with high polarizations and low switching barriers from a pool of double perovskite oxides, suitable for future investigation for their potential applications in spintronic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Machine learned synthesizability predictions aided by density functional theory

Abstract A grand challenge of materials science is predicting synthesis pathways for novel compounds. Data-driven approaches have made significant progress in predicting a compound’s synthesizability; however, some recent attempts ignore phase stability information. Here, we combine thermodynamic stability calculated using density functional theory with composition-based features to train a machine learning model that predicts a material’s synthesizability. Our model predicts the synthesizability of ternary 1:1:1 compositions in the half-Heusler structure, achieving a cross-validated precision of 0.82 and recall of 0.82. Our model shows improvement in predicting non-half-Heuslers compared to a previous study’s model, and identifies 121 synthesizable candidates out of 4141 unreported ternary compositions. More notably, 39 stable compositions are predicted unsynthesizable while 62 unstable compositions are predicted synthesizable; these findings otherwise cannot be made using density functional theory stability alone. This study presents a new approach for accurately predicting synthesizability, and identifies new half-Heuslers for experimental synthesis.

Lee, Andrew (ORCID:0000000153014295)↗
DOE OSTI2021

Measurement of Local Magnetic Fields in Actinide Tetrafluorides

Fluorine-19 magnetic shielding tensors have been measured in a series of actinide tetrafluorides (AnF4) by solid state nuclear magnetic resonance (NMR) spectroscopy. Tetravalent actinide centers with 0 to 8 valence electrons can form tetrafluorides with the same unit cell, making these compounds an attractive choice for a systematic study of the variation in electronic structure across the 5f row of the Periodic Table. Pronounced deviations from predictions based on localized valence electron models have been detected by these experiments, which suggests that this approach may be used as a quantitative probe of electronic correlations.

Walter, Eric D.↗
DOE OSTI2020

Elucidating algal-bacterial community interactions by tracking volatile biomarkers (Final Report)

This feasibility study project aimed to lay further groundwork for studying and understanding how microorganisms interact with each other at the molecular level using model algal-bacterial co-cultures. A better understanding of such interactions is critical to optimizing and operating biotic platforms for a number of applications, including bioenergy, algal bioproducts and agriculture, and carbon capture. Here we explored the feasibility of characterizing and following these interactions by identifying and tracking volatile metabolites and biomarkers in the complex gaseous headspace of such cultures. We set up an experimental platform using a co-culture of Phaeodactylum tricornutum and Marinobacter subspecies 3-2 as a model system, used solid-phase microextraction fibers for volatile collection at various time points throughout culture growth, and employed gas chromatography mass spectrometry-based instrumentation available at LLNL for compound identification and quantification. We found that it is feasible to determine volatile profiles from the growth of Phaeodactylum tricornutum and Marinobacter subspecies 3-2 using our methodology and monitor profile changes over time. We also observed that volatiles distinguishing between cultures of the individual species and the co-cultures could be detected. We expect that results of this project will feed into the ongoing LLNL’s DOE BER funded Biofuels Scientific Focus Area (SFA) on algal-bacterial interactions and pave the way for future expanded volatile studies supported by DOE. The approach and technologies developed here would also be applicable and transferable to other microbial communities under study, such as cyanobacteria, rhizosphere communities and biofilms.

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

Bacterial Membranes Are More Perturbed by the Asymmetric Versus Symmetric Loading of Amphiphilic Molecules

Characterizing the biophysical properties of bacterial membranes is critical for understanding the protective nature of the microbial envelope, interaction of biological membranes with exogenous materials, and designing new antibacterial agents. Presented here are molecular dynamics simulations for two cationic quaternary ammonium compounds, and the anionic and nonionic form of a fatty acid molecule interacting with a Staphylococcus aureus bacterial inner membrane. The effect of the tested materials on the properties of the model membranes are evaluated with respect to various structural properties such as the lateral pressure profile, lipid tail order parameter, and the bilayer’s electrostatic potential. Conducting asymmetric loading of molecules in only one leaflet, it was observed that anionic and cationic amphiphiles have a large impact on the Staphylococcus aureus membrane’s electrostatic potential and lateral pressure profile as compared to a symmetric distribution. Nonintuitively, we find that the cationic and anionic molecules induce a similar change in the electrostatic potential, which points to the complexity of membrane interfaces, and how asymmetry can induce biophysical consequences. Finally, we link changes in membrane structure to the rate of electroporation for the membranes, and again find a crucial impact of introducing asymmetry to the system. Understanding these physical mechanisms provides critical insights and viable pathways for the rational design of membrane-active molecules, where controlling the localization is key.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1983

Studies of the mechanisms of turbine fuel instability

The formation of insoluble deposits in a Jet A, a Diesel, and a model fuel (1/10 v/v tetralin/dodecane) was studied. Experiments were conducted using glass containers at 394 K with an air/fuel ratio of 14/1. The effects of addition of ppm levels of various compounds on deposit formation were evaluated. Nitrogen heterocycles were shown to produce a basicity dependent acceleration of deposition. Thiols and thiophene were shown to increase deposition while sulfides and disulfides act as inhibitors. Copper metal and its salts also promote deposition. Results of various instrumental analyses of deposits and development of a high performance liquid chromatographic method for monitoring deposit precursors are discussed.

Daniel, S. R.↗
NASA NTRS1985

Origin of life

The pathways of organic chemical synthesis, the chemical evolution on the early Earth leading to life was constrained by the development of the planet by accretion and core formation. The accretion and differentiation into the core-mantle-crust-atmosphere system strongly influenced the temperature and composition of the atmosphere, surface, and interior; but large gaps persist in our understanding of these processes. The time-span over which Earth acquired its volatiles, the composition of these volatiles, and the conditions under which outgassing of volatiles occurred to form the atmosphere, are unknown. Uncertainties in existing models for Earth accretion and early planetary development allows a wide range of possible prebiotic atmospheric compositions at the time and temperature when liquid water appeared and thermally-labile organic compounds could survive. These compositions range from strongly reducing atmospheres to mildly reducing ones.

Chang, S.↗
NASA NTRS1992

A novel directly coupled gradostat

The original bidirectional compound chemostat (gradostat) described by Lovitt and Wimpenny has been simplified by making a more compact apparatus in which chemical gradients are established by diffusion between adjacent culture chambers. The experimental model (diffusion coupled (DC) gradostat) consisted of five chambers whose contents could be agitated by turbines rotating in the horizontal plane on a common shaft. Two biological experiments were designed to reveal the value of the DC gradostat. A methylotroph (Methylophilus methylotrophus) grown in a methanol gradient showed expected changes in cell viability as a function of position in the five vessel array. Cells of two species of photosynthetic bacteria (Rhodobacter capsulata and Rhodopseudomonas marina/agilis) with different salt sensitivities could be mixed and subsequently separated by the DC gradostat operating with a NaCl gradient of 0-3% w/v.

NASA Discipline Exobiology↗
DOE OSTI2023

Effective Lanthanide Diffusivity through U-Zr Metallic Fuel

Fuel-cladding chemical interaction (FCCI) is one of the main concerns for the performance of U-Zr metallic fuels. Although FCCI results in complex phase transformations and morphological changes in both the fuel and cladding sides of the interface, the formation of a brittle layer in the cladding side of the interface (sometimes referred to as wastage) has one of the most significant impacts on the cladding mechanical integrity. This brittle layer is associated with the formation of intermetallic compounds between the cladding constituents Fe, Cr and the lanthanide fission product species. The formation of this cladding wastage layer has been the focus of recent efforts to develop a mechanistic modeling framework, including production of lanthanides in the fuel, transport through the fuel to the fuel-cladding interface, and phase transformation to form intermetallic phases. To calculate the rate of transport of lanthanides through the fuel, a multi-scale computational approach has been used. Atomistic calculations have been performed to determine the diffusivities of Nd, the most prevalent lanthanide species, through the solid fuel matrix and along pore surfaces. These diffusivities have been used as input parameters for a mesoscale model to determine an effective diffusion coefficient that accounts for the formation of porosity, its interconnection, and infiltration with bond sodium from the fuel-cladding gap. The effective diffusivity has been used in engineering-scale simulations using the BISON fuel performance code, and BISON simulations have been compared to representative validation cases from the EBR-II reactor.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Experimental evaluation of the stabilization of the COT orbitals by 4f orbitals in COT 2 Ce using a Hubbard model

Significant orbital mixing is rare in lanthanide complexes because of the limited radial extent of the 4f orbitals, which results in a generally small stabilization due to 4f orbital interactions. Nevertheless, even a small amount of additional stabilization could enhance lanthanide separations. One lanthanide complex in which orbital mixing has been extensively studied both experimentally and computationally is cerocene, COT 2 Ce, where COT is cyclooctatetraene. This compound has a singlet ground state with a low-lying, triplet excited state. Previous fluorescence studies on trimethylsilyl-substituted cerocenes indicate the triplet state is 0.4 eV higher in energy than the singlet state. In addition, computational studies predict that the triplet is 0.3 to 1 eV higher in energy than the singlet. The synthesis of highly pure COT 2 Ce by Walter and Andersen allowed its physical properties to be accurately measured. Using these measurements, we evaluate the stabilization of the 4f orbitals using two, independent approaches. A Hubbard model is used to evaluate the stabilization of the ground state due to orbital mixing. This stabilization, which is also the singlet–triplet gap, is –0.29 eV using this model. Furthermore, this gap was also from the temperature independent paramagnetism of COT 2 Ce, which yielded a value of –0.32 eV.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗