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At least 811 records · Page 45

All sources NASA NTRS DOE OSTI

DOE OSTI2020

TAILORED BIOBLENDSTOCKS WITH LOW ENVIRONMENTAL IMPACT TO OPTIMIZE MCCI ENGINES

The overall objective of the project is to develop and demonstrate a microalgae bio-blendstock with greater than 60% greenhouse gas reduction potential relative to petroleum diesel, that can reduce sooting propensity, increase cetane number and improve engine thermal efficiency relative to a baseline diesel engine operating on conventional fuel. Specific objectives include: (1) development of a new framework for both LCA and TEA that explicitly considers temporal variation in productivity and the frequency of crop loss; (2) determination of how fuel compounds that can be produced from the algal biomass can be ‘bio-tailored’ based on the species composition and biological production process, and subsequent processing via HTL to biocrude, and upgrading of the biocrude; (3) execution of a feedback loop (algae production  biocrude refining  combustion optimization  feedback to refining stage), for optimization of fuels for MCCI combustion; (4) optimization of MCCI combustion and emissions performance, accounting first for the biological processes that dictate the chemical composition of biocrude oil, and second for the subsequent chemical processes that comprise mixing controlled compression ignition combustion; (6) simulation of MCCI engine combustion processes to demonstrate the incorporation of relevant fuel chemistry that captures the specific impacts of optimized algal fuels.

09 BIOMASS FUELS↗

DOE OSTI2020

Tailored Bioblendstocks with Low Environmental Impact to Optimize MCCI Engines

09 BIOMASS FUELS↗

DOE OSTI2020

A critical examination of compound stability predictions from machine-learned formation energies

Machine learning has emerged as a novel tool for the efficient prediction of material properties, and claims have been made that machine-learned models for the formation energy of compounds can approach the accuracy of Density Functional Theory (DFT). The models tested in this work include five recently published compositional models, a baseline model using stoichiometry alone, and a structural model. By testing seven machine learning models for formation energy on stability predictions using the Materials Project database of DFT calculations for 85,014 unique chemical compositions, we show that while formation energies can indeed be predicted well, all compositional models perform poorly on predicting the stability of compounds, making them considerably less useful than DFT for the discovery and design of new solids. Most critically, in sparse chemical spaces where few stoichiometries have stable compounds, only the structural model is capable of efficiently detecting which materials are stable. The nonincremental improvement of structural models compared with compositional models is noteworthy and encourages the use of structural models for materials discovery, with the constraint that for any new composition, the ground-state structure is not known a priori. This work demonstrates that accurate predictions of formation energy do not imply accurate predictions of stability, emphasizing the importance of assessing model performance on stability predictions, for which we provide a set of publicly available tests.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Selective modifiers for composite material property enhancement

A laminate comprising a first ply, a second ply, and a plurality of interfacial modifiers arranged between opposing faces of the first ply and the second ply. A chemical composition of an interfacial modifier of the plurality of interfacial modifiers can be selected based on a resulting bond strength between the interfacial modifier of the plurality of interfacial modifiers and at least one of the first ply or the second ply. The plurality of interfacial modifiers can be arranged in a pattern to selectively modify toughness of a portion of the laminate based on the bond strength of the interfacial modifier of the plurality of interfacial modifiers.

Briggs, Timothy↗

NASA NTRS1994

Composition, Chemistry, and Climate of the Atmosphere. 2: Mean properties of the atmosphere

The atmosphere can be defined as the relatively thin gaseous envelope surrounding the entire planet Earth. It possesses a number of properties related to its physical state and chemical composition, and it undergoes a variety of internal processes and external interactions that can either maintain or alter these properties. Whereas descriptions of the atmosphere's chemical properties form much of the remaining chapters of this book, the present chapter will highlight the atmosphere's gases, and these define its temperature structure. In contrast, the larger-scale motions comprise the winds, the global organization of which is often referred to as the general circulation. The framework of the dynamical and thermodynamical laws, including the three principles of conversation of mass, momentum, and energy, are fundamental in describing both the internal processes of the atmosphere and its external interactions. The atmosphere is not a closed system, because it exchanges all three of these internally conservative quantities across the atmosphere's boundary below and receives input from regions outside it. Thus surface fluxes of moisture, momentum, and heat occur to and from the underlying ocean and land. The atmosphere exchanges very little mass and momentum with space, though it absorbs directly a portion of the solar radiational energy received from above.

Singh, Hanwant B.↗

DOE OSTI2024

Composition-Nanoarchitecture-Performance Analysis of High Energy Density Electrodeposited Silicon for Lithium-Ion Battery Anodes

Electrodeposition of silicon (Si) was previously demonstrated as a promising method for fabricating 3D-structured lithium-ion battery anodes. However, the relationship between the electrochemical performance and chemical composition of the relatively impure electrodeposited silicon is not well understood. Here, we report the electrodeposition of a Si-dominant active material (EDEP-Si) onto 3D-structured nickel (Ni) scaffolds and systematically compare the electrochemical properties, elemental composition, atomistic Si coordination, and molecular structure of EDEP-Si with high-purity amorphous Si grown via static chemical vapor deposition. Despite the considerable amount of carbon (9–11 at %) and oxygen (42–44 at %) present in EDEP-Si, the cycling stability and high reversible specific capacity are remarkably similar to those of CVD-Si on a silicon basis (~2400 mA h/g-Si after 100 cycles). The primary difference is that EDEP-Si exhibits reduced cycling efficiency over the first 10–20 cycles. Reactions between carbon and, more importantly, oxygen in EDEP-Si with lithium are likely responsible for the reduced early cycle performance and lower capacity of the total deposit. Finally, our observations suggest ultrapure Si is not necessary for high electrochemical access to reversible charge storage, although limiting the presence of incorporated impurity species would improve energy density and first cycle efficiency.

25 ENERGY STORAGE↗

DOE OSTI2025

Fully‐Printed Ion Sensor Arrays for Measuring Agricultural Nitrogen and Potassium Concentrations Using Nernstian and AI Models

Abstract The chemical composition of growing media is a key factor for plant growth, impacting agricultural yield and sustainability. However, there is a lack of affordable chemical sensors for ubiquitous nutrient ion monitoring in agricultural applications. This work investigates using fully printed ion‐sensor arrays to measure the concentrations of nitrate, ammonium, and potassium in mixed‐electrolyte media. Ion sensor arrays composed of nitrate, ammonium, and potassium ion‐selective electrodes and a printed silver‐silver chloride (Ag/AgCl) reference electrode are fabricated and characterized in aqueous solutions in a range of concentrations that encompass what is typical for agricultural growing media (0.01 m m –1 m ). The sensors are also tested in mixed‐electrolyte solutions of NaNO 3 , NH 4 Cl, and KCl of varying concentrations, and the recorded potentials are input into Nernstian and artificial neural network models to compare the prediction accuracy of the models against ground truth. The artificial neural network models demonstrated higher accuracy over the Nernstian model, and the model using only ion‐sensor inputs is 7.5% more accurate than the Nernstian model under the same conditions. By enabling more precise and efficient fertilizer application, these sensor arrays coupled to computational models can help increase crop yields, optimize resource use, and reduce environmental impact.

Goodrich, Payton [University of California Berkele↗

DOE OSTI2024

Precision Plant Biomass Characterization in Agriculture: Harnessing Machine Learning and Hyperspectral Imaging [Slides]

Efficient Biomass Separation Object detection of anatomical parts (Cob, Stalk, Husk) in IR images enables precise separation, improving preprocessing (e.g., drying, grinding) for biofuel production. Detailed Biomass Characterization with Hyperspectral Data Hyperspectral imaging captures spectral signatures of biomass, allowing for the identification of specific traits like moisture content, lignin levels, and nutrient composition, leading to optimized treatments for each biomass part. Enhanced Feedstock Quality By leveraging hyperspectral data, feedstock can be processed based on its chemical composition, improving conversion efficiency and biofuel yield. Automation for Large-Scale Operations Automated object detection and hyperspectral data analysis reduce manual labor, ensuring accurate sorting and faster processing, making large-scale biofuel production more efficient. Maximized Biomass Utilization Accurate identification of biomass properties minimizes waste and ensures that each part is processed according to its highest biofuel potential.

09 BIOMASS FUELS↗

NASA NTRS1981

The moon

The principal scientific results from the Apollo Program are reviewed. Data on the nature of the moon, including the surface, interior, and composition, are discussed. Attention is also given to problems of lunar age determination, and to certain unanswered questions concerning the moon (e.g., the chemical composition of the whole moon and the moon's asymmetry). A number of illustrative photographs are presented.

French, B. M.↗

NASA NTRS2006

Comets, Asteroids, Meteorites, and the Origin of the Biosphere

During the past few decades, the delivery of water, organics, and prebiotic chemicals to the Biosphere of Earth during the Hadean (4.5-3.8 Ga) period of heavy bombardment by comets and asteroids has become more widely accepted. Comets are still largely regarded as frigid, pristine bodies of protosolar nebula material that are devoid of liquid water and therefore unsuitable for life. Complex organic compounds have been observed in comets and on the water-rich asteroid 1998 KY26 and near IR observations have indicated the presence of crystalline water ice and ammonia hydrate on the large Kuiper Belt object (50000) Quaoar that has resurfacing suggesting cryovolcanic outgassing. Spacecraft observations of the chemical compositions and characteristics of the nuclei of several comets (Halley, Borrelly, Wild 2, and Tempel 1) have shown that comets contain complex organic chemicals; that water is the predominant volatile; and that extremely high temperatures (approx. 350-400 K) can be reached on the surfae of the very black (albedo approx. 0.03) nuclei of comets when they approach the Sun. Impact craters and pinnacles observed on comet Wild 2 suggest a thick crust. Episodic outbursts and jets from the nuclei of several comets indicate that localized regimes of liquid water and water vapor can periodically exist beneath the comet crust. The Deep Impact mission found the temperature of the nucleus of comet Tempel 1 at 1.5 AU varied from a minimum of 280 plus or minus 8 K the 330K (57 C) on the sunlit side. In this paper it is argued that that pools and films of liquid water exist (within a wide range of temperatures) in cavities and voids just beneath the hot, black crust. The possibility of liquid water existing over a wide range of temperatures significantly enhances the possibility that comets might contain niches suitable for the growth of microbial communities and ecosystems. These regimes would be ideal for the growth of psychrophilic, mesophilic, and thermophilic photoautotrophs and chemolithotrophs such as the motile filamentous cyanobacteria (e.g., Calothrix, Oscillatoria, Phormidium, and Spirulina) that grow in geothermal springs and geysers of Earth at temperatures ranging fiom 320K to 345K and are also found growing in cold polar desert soils. The mineralized remains of morphotypes of all of these cyanobacteria have also been found in the Orgueil CI1 and the Murchison CN2 carbonaceous meteorites that may derive from cometary parent bodies. Observational results that support the hypothesis that liquid water can in active regions just beneath the surface of comets and that comets, carbonaceous meteorites, and asteroids may have played a significant role in the origin and evolution of the Biosphere and in the distribution of microbial life throughout the Solar System.

Hoover, Richard B.↗

NASA NTRS2016

Role of Atmospheric Chemistry in the Climate Impacts of Stratospheric Volcanic Injections

The climate impact of a volcanic eruption is known to be dependent on the size, location and timing of the eruption. However, the chemistry and composition of the volcanic plume also control its impact on climate. It is not just sulfur dioxide gas, but also the coincident emissions of water, halogens and ash that influence the radiative and climate forcing of an eruption. Improvements in the capability of models to capture aerosol microphysics, and the inclusion of chemistry and aerosol microphysics modules in Earth system models, allow us to evaluate the interaction of composition and chemistry within volcanic plumes in a new way. These modeling efforts also illustrate the role of water vapor in controlling the chemical evolution, and hence climate impacts, of the plume. A growing realization of the importance of the chemical composition of volcanic plumes is leading to a more sophisticated and realistic representation of volcanic forcing in climate simulations, which in turn aids in reconciling simulations and proxy reconstructions of the climate impacts of past volcanic eruptions. More sophisticated simulations are expected to help, eventually, with predictions of the impact on the Earth system of any future large volcanic eruptions.

Disrupting↗

DOE OSTI2022

Trends in Microbial Community Composition and Function by Soil Depth

Microbial communities play important roles in soil health, contributing to processes such as the turnover of organic matter and nutrient cycling. As soil edaphic properties such as chemical composition and physical structure change from surface layers to deeper ones, the soil microbiome similarly exhibits substantial variability with depth, with respect to both community composition and functional profiles. However, soil microbiome studies often neglect deeper soils, instead focusing on the top layer of soil. Here, we provide a synthesis on how the soil and its resident microbiome change with depth. We touch upon soil physicochemical properties, microbial diversity, composition, and functional profiles, with a special emphasis on carbon cycling. In doing so, we seek to highlight the importance of incorporating analyses of deeper soils in soil studies.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Predicting the synthesizability of crystalline inorganic materials from the data of known material compositions

Abstract Reliably identifying synthesizable inorganic crystalline materials is an unsolved challenge required for realizing autonomous materials discovery. In this work, we develop a deep learning synthesizability model ( SynthNN ) that leverages the entire space of synthesized inorganic chemical compositions. By reformulating material discovery as a synthesizability classification task, SynthNN identifies synthesizable materials with 7× higher precision than with DFT-calculated formation energies. In a head-to-head material discovery comparison against 20 expert material scientists, SynthNN outperforms all experts, achieves 1.5× higher precision and completes the task five orders of magnitude faster than the best human expert. Remarkably, without any prior chemical knowledge, our experiments indicate that SynthNN learns the chemical principles of charge-balancing, chemical family relationships and ionicity, and utilizes these principles to generate synthesizability predictions. The development of SynthNN will allow for synthesizability constraints to be seamlessly integrated into computational material screening workflows to increase their reliability for identifying synthetically accessible materials.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

Results of the Preliminary Analyses of Asteroid Ryugu Regolith Samples Returned by the Hayabusa2 Mission

The Hayabusa2 spacecraft returned 5.5g of regolith material from asteroid 162173 Ryugu in December 2021. The samples were maintained in near-vacuum conditions up to and even during many analyses, a factor that was critical for comparisons of Ryugu lithologies to meteorites because of ubiquitous terrestrial alteration of the latter. Observations of asteroid Ryugu by the Hayabusa2 spacecraft found that it is spinning, top-shaped rubble pile, formed from re-accretion of a (probably) small subset of fragments from a disrupted parent asteroid. Samples retrieved from Ryugu by the spacecraft during two brief touchdowns were expected to contain a record of this history, including the formation and early evolution of the parent body, its subsequent impact destruction and partial re-accretion, and later space weathering. The composition of Ryugu was expected to be similar to that of naturally-heated Ivuna-type carbonaceous chondrite meteorites (CI chondrites), based on ground- and spacecraft-based spectroscopy. Six preliminary examination teams investigated the formation history of Ryugu through laboratory analysis of the returned samples over the past 18 months. Specifically, we sought to determine (1) when and where in the Solar System the parent asteroid of Ryugu formed; (2) the original mineralogy, bulk elemental abundances, and chemical compositions of the accreted materials; (3) how these materials evolved through chemical and physical processing of the parent asteroid; and (4) how the parent asteroid was disrupted during impact and reaccumulated into Ryugu. This brief report mainly summarizes results from the mineralogy and petrology subteams, although results of the composition and isotope subteams are also mentioned. To address these issues, we analyzed numerous Ryugu particles up to ~8 mm in size.

Michael Zolensky↗

DOE OSTI2025

Measurement and analysis of the Doppler broadened energy spectra of gamma radiation originating from the annihilation of positrons incident on clean and adsorbate-covered surfaces

We present measurements and theoretical modeling demonstrating the capability of coincidence Doppler broadened (CDB) annihilation gamma spectroscopy to provide element-specific information from the topmost atomic layer of surfaces. Our measurements show that the energy spectra of Doppler-shifted annihilation gamma photons emitted following the annihilation of positrons from the topmost atomic layers of clean and adsorbate covered surfaces of gold (Au), silver (Ag) and copper (Cu) differ significantly. The shape of the Doppler-broadened gamma spectrum, as analyzed using ratio curves, indicates that the elemental composition of the surface can still be identified despite contributions from positronium annihilation and a significant reduction in core electron annihilation. We estimate the chemical composition of the various probed surfaces by modeling the ratios of the measured Doppler spectra with respect to the Doppler spectra from a clean Cu surface using a linear combination of calculated ratio curves. The fitting of the experimental ratio curves was used to obtain an estimate of the elemental composition of Cu surfaces with sulfur segregation, oxygen adsorption, a thin film of Selenium (Se), and a single layer of graphene (SLG). A similar analysis was performed on the Ag surface with environmental adsorbates, the same surface after argon ion sputtering, as well as a sputter cleaned Au surface. The surface compositions obtained from the analysis of the CDB data were compared to the compositions obtained using positron annihilation induced Auger electron spectroscopy (PAES). Our results show that CDB can detect, identify, and quantify, sub-monolayer adsorbates and a single atomic layer deposited on metal substrates.

Lotfimarangloo, Sima [Univ. of Texas, Arlington, T↗

DOE OSTI2025

Large language model-driven database for thermoelectric materials

Thermoelectric materials have the ability to convert waste heat into electricity, offering a valuable solution for energy harvesting. However, their widespread use is hindered by low conversion efficiency, the reliance on expensive rare earth elements, and the environmental and regulatory concerns associated with lead-based materials. A fast and cost-effective way to identify highly efficient thermoelectric materials is through data-driven methods. These approaches rely on robust and comprehensive datasets to train models. Although there are several databases on thermoelectric materials, there is still a need to collect and integrate experimental data from peer-reviewed research articles to capture diverse compositions and properties of materials. Here, in this work, we developed a comprehensive database of 7,123 thermoelectric compounds, containing key information such as chemical composition, structural detail, seebeck coefficient, electrical and thermal conductivity, power factor, and figure of merit (ZT). We used the GPTArticleExtractor workflow, powered by large language models (LLM), to extract and curate data automatically from the scientific literature published in Elsevier journals. This process enabled the creation of a structured database that addresses the challenges of manual data collection. The open access database could stimulate data-driven research and advance thermoelectric material analysis and discovery.

Database↗

DOE OSTI2024

Defect Properties, Anion Ordering, and Photochromic Mechanism in Yttrium Oxyhydride

Yttrium oxyhydride (YHO) undergoes a reversible photochromic transition when exposed to ultraviolet light. However, the mechanism for this transformation is not fully understood, and the structure and precise chemical composition of YHO remain under debate. Here, we use first-principles density functional theory calculations with a hybrid functional to study the structure, chemical stability, and point defect properties of YHO. As experiments have shown, we find that YHO prefers a cubic structure, with H and O anions present in equal concentrations and located on tetrahedral sites. Stoichiometric and ordered YHO is chemically stable, but it has a wide band gap of 5.01 eV, considerably larger than that measured in experiments (2.4–3.8 eV). On the other hand, Y4H10O has a smaller band gap of 2.97 eV and also has a region of chemical stability; thus, the actual material may include some fraction of this H-rich structure. The defect chemistry of YHO is dominated by anionic antisite species (H O and O H ), with hydrogen interstitials (H i ) and vacancies (V H ) also present in reasonably high concentrations. We show that antisite disorder lowers the band gap relative to the perfectly ordered structure, bringing the magnitude of the gap into closer agreement with experiment. Based on our calculations of defect migration and the positions of defect states relative to the band edges, we link the onset of photochromic behavior to the reaction H O – → V O 0 + H i – , which follows photoexcitation of a H O + defect. H i – can subsequently migrate away and be trapped by additional H O + defects, contributing to the persistence of the reaction, while the resultant oxygen vacancy, V O 0 , introduces an occupied defect state that leads to optical absorption at visible wavelengths. Our results can explain reported discrepancies between experimental and computational results for YHO, and they allow us to propose specific atomic-scale processes that can lead to photochromism. In conclusion, understanding these mechanisms is key for unlocking YHO’s application in devices ranging from smart windows and optoelectronics to electrochemical synapses for neural networks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Enhanced Hanford Low-Activity Waste Glass Property Data Development: Phase 2

This report summarizes and analyzes the data collected on a second test matrix of 42 low-activity waste (LAW) glass compositions intended to expand the LAW glass composition region over which glass property-composition models are valid. The 42 LAW glass compositions were selected using a statistical layered experimental design approach to explore a new glass composition region that overlaps and expands beyond the previously explored LAW glass composition region. The layered design of 42 LAW glasses consisted of 21 outer-layer glasses, 15 inner-layer glasses, a center glass (three replicates), and two glasses previously tested at another laboratory. The outer-layer glass compositions include extrema based on current projections of the LAW feeds and melter operating temperatures. One of the outer-layer compositions was eliminated due to the inability to form a glass. Therefore, only 41 glasses were analyzed. The analyses performed on these glasses include chemical composition (for target compositional verification), density, viscosity, electrical conductivity, crystal fraction, canister centerline cooling with crystal identification, the Product Consistency Test, sulfur solubility, and the Vapor Hydration Test. This report discusses the results obtained from this testing.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗