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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

The ACS LCID project. X. the star formation history of IC 1613: Revisiting the over-cooling problem

We present an analysis of the star formation history (SFH) of a field near the half-light radius in the Local Group dwarf irregular galaxy IC 1613 based on deep Hubble Space Telescope Advanced Camera for Surveys imaging. Our observations reach the oldest main sequence turn-off, allowing a time resolution at the oldest ages of ∼1 Gyr. Our analysis shows that the SFH of the observed field in IC 1613 is consistent with being constant over the entire lifetime of the galaxy. These observations rule out an early dominant episode of star formation in IC 1613. We compare the SFH of IC 1613 with expectations from cosmological models. Since most of the mass is in place at early times for low-mass halos, a naive expectation is that most of the star formation should have taken place at early times. Models in which star formation follows mass accretion result in too many stars formed early and gas mass fractions that are too low today (the 'over-cooling problem'). The depth of the present photometry of IC 1613 shows that, at a resolution of ∼1 Gyr, the star formation rate is consistent with being constant, at even the earliest times, which is difficult to achieve in models where star formation follows mass assembly.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

THE RELATION BETWEEN STAR FORMATION RATE AND STELLAR MASS FOR GALAXIES AT 3.5 ≤ z ≤ 6.5 IN CANDELS

Distant star-forming galaxies show a correlation between their star formation rates (SFRs) and stellar masses, and this has deep implications for galaxy formation. Here, we present a study on the evolution of the slope and scatter of the SFR-stellar mass relation for galaxies at 3.5 ≤ z ≤ 6.5 using multi-wavelength photometry in GOODS-S from the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS) and Spitzer Extended Deep Survey. We describe an updated, Bayesian spectral-energy distribution fitting method that incorporates effects of nebular line emission, star formation histories that are constant or rising with time, and different dust-attenuation prescriptions (starburst and Small Magellanic Cloud). From z = 6.5 to z = 3.5 star-forming galaxies in CANDELS follow a nearly unevolving correlation between stellar mass and SFR that follows SFR ∼ M{sub ⋆}{sup a} with a =0.54 ± 0.16 at z ∼ 6 and 0.70 ± 0.21 at z ∼ 4. This evolution requires a star formation history that increases with decreasing redshift (on average, the SFRs of individual galaxies rise with time). The observed scatter in the SFR-stellar mass relation is tight, σ(log SFR/M {sub ☉} yr{sup –1}) < 0.3-0.4 dex, for galaxies with log M {sub *}/M {sub ☉} > 9 dex. Assuming that the SFR is tied to the net gas inflow rate (SFR ∼ M-dot {sub gas}), then the scatter in the gas inflow rate is also smaller than 0.3–0.4 dex for star-forming galaxies in these stellar mass and redshift ranges, at least when averaged over the timescale of star formation. We further show that the implied star formation history of objects selected on the basis of their co-moving number densities is consistent with the evolution in the SFR-stellar mass relation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

An analytical model for galaxy metallicity: What do metallicity relations tell us about star formation and outflow?

We develop a simple analytical model that tracks galactic metallicities governed by star formation and feedback to gain insight from the observed galaxy stellar mass–metallicity relations over a large range of stellar masses and redshifts. The model reveals the following implications of star formation and feedback processes in galaxy formation. First, the observed metallicity relations provide a stringent upper limit for the averaged outflow mass-loading factors of local galaxies, which are ∼20 for M{sub ∗}∼10{sup 9} M{sub ⊙} galaxies and monotonically decrease to ∼1 for M{sub ∗}∼10{sup 11} M{sub ⊙} galaxies. Second, the inferred upper limit for the outflow mass-loading factor sensitively depends on whether the outflow is metal-enriched with respect to the interstellar medium metallicity. If half of the metals ejected from supernovae leave the galaxy in metal-enriched winds, the outflow mass-loading factor for galaxies at any mass can barely be higher than ∼10, which puts strong constraints on galaxy formation models. Third, the relatively lower stellar-phase to gas-phase metallicity ratio for lower-mass galaxies indicates that low-mass galaxies are still rapidly enriching their metallicities in recent times, while high-mass galaxies are more settled, which seems to show a downsizing effect in the metallicity evolution of galaxies. The analysis presented in the paper demonstrates the importance of accurate measurements of galaxy metallicities and the cold gas fraction of galaxies at different redshifts for constraining star formation and feedback processes, and demonstrates the power of these relations for constraining the physics of galaxy formation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

FORMATION OF CLOSE IN SUPER-EARTHS AND MINI-NEPTUNES: REQUIRED DISK MASSES AND THEIR IMPLICATIONS

Recent observations by the Kepler space telescope have led to the discovery of more than 4000 exoplanet candidates consisting of many systems with Earth- to Neptune-sized objects that reside well inside the orbit of Mercury around their respective host stars. How and where these close-in planets formed is one of the major unanswered questions in planet formation. Here, we calculate the required disk masses for in situ formation of the Kepler planets. We find that if close-in planets formed as isolation masses, then standard gas-to-dust ratios yield corresponding gas disks that are gravitationally unstable for a significant fraction of systems, ruling out such a scenario. We show that the maximum width of a planet's accretion region in the absence of any migration is 2v {sub esc}/Ω, where v {sub esc} is the escape velocity of the planet and Ω is the Keplerian frequency, and we use it to calculate the required disk masses for in situ formation with giant impacts. Even with giant impacts, formation without migration requires disk surface densities in solids at semi-major axes of less than 0.1 AU of 10{sup 3}-10{sup 5} g cm{sup –2}, implying typical enhancements above the minimum-mass solar nebular (MMSN) by at least a factor of 20. Corresponding gas disks are below but not far from the gravitational stability limit. In contrast, formation beyond a few AU is consistent with MMSN disk masses. This suggests that the migration of either solids or fully assembled planets is likely to have played a major role in the formation of close-in super-Earths and mini-Neptunes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

The Milky Way’s bulge star formation history as constrained from its bimodal chemical abundance distribution

ABSTRACT We conduct a quantitative analysis of the star formation history (SFH) of the Milky Way’s (MW) bulge by exploiting the constraining power of its stellar [Fe/H] and [Mg/Fe] distribution functions. Using Apache Point Observatory Galactic Evolution Experiment survey data, we confirm the previously established bimodal [Mg/Fe]–[Fe/H] distribution within 3 kpc of the inner Galaxy. To fit the chemical bimodal distribution, we use a simple but flexible star formation framework, which assumes two distinct stages of gas accretion and star formation, and systematically evaluate a wide multidimensional parameter space. We find that the data favour a three-phase SFH that consists of an initial starburst, followed by a rapid star formation quenching episode, and a lengthy, quiescent secular evolution phase. The metal-poor, high-α bulge stars ([Fe/H] < 0.0 and [Mg/Fe] > 0.15) are formed rapidly (<2 Gyr) during the early starburst. The density gap between the high- and low-α sequences is due to the quenching process. The metal-rich, low-α population ([Fe/H] > 0.0 and [Mg/Fe] < 0.15) then accumulates gradually through inefficient star formation during the secular phase. This is qualitatively consistent with the early SFH of the inner disc. Given this scenario, a notable fraction of young stars (age <5 Gyr) is expected to persist in the bulge. Combined with extragalactic observations, these results suggest that a rapid star formation quenching process is responsible for bimodal distributions in both the MW’s stellar populations and in the general galaxy population and thus plays a critical role in galaxy evolution.

Lian, Jianhui↗
DOE OSTI2023

Assessment of exchange-correlation functionals on oxygen vacancy formation energies of metal oxides

Oxygen vacancies are a common defect in oxides and play vital roles in many technological applications such as oxygen separation, catalytic reactors, solid oxide fuel cells, and solar thermochemical water splitting. The oxygen vacancy formation energy is directly related to the oxide reduction enthalpy and the vacancy concentration and, therefore, is a key quantity underlying these applications. The complexity of measuring oxygen vacancy formation energies experimentally suggests the utility of calculations based on density functional theory (DFT). However, the calculated results are strongly dependent on the exchange-correlation functionals and other parameters such as the Hubbard U . In this work, we compare the performance of the meta-GGA strongly constrained and appropriately normed (SCAN) functional and the commonly used semilocal generalized gradient approximation (GGA) functionals with experimental values of structural parameters, band gaps, magnetic structures, and oxygen vacancy formation energies for six representative oxides, i.e., CaMnO 3 , SrMnO 3 , LaMnO 3 , YMnO 3 , LaFeO 3 , and CeO 2 . Further, our results show that SCAN usually has better agreement with the experimental lattice constants and band gaps and larger magnetic moments than the commonly used GGA functionals. Although SCAN overestimates the oxygen vacancy formation energies of transition metal oxides and therefore requires unusually large Hubbard U values to reproduce the experimental reduction enthalpies, it does predict the correct oxygen vacancy formation energy of CeO 2 , which challenges the commonly used GGA and hybrid functionals. Our results underscore the challenges that exist in describing these complex oxides by DFT and may shed light on developing more accurate exchange-correlation functionals for oxygen vacancy formation energy calculations.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Oxygen vacancy formation energies in PbTiO 3 / SrTiO 3 superlattice

The defect stability in a prototypical perovskite oxide superlattice consisting of ${\mathrm{SrTiO}}_{3}$ and ${\mathrm{PbTiO}}_{3}$ (STO/PTO) is determined by using first principles density functional theory calculations. Specifically, the oxygen vacancy formation energies ${E}_{\mathrm{v}}$ in the paraelectric and ferroelectric phases of a superlattice with four atomic layers of STO and four layers of PTO (4STO/4PTO) are determined and compared. The effects of charge state, octahedral rotation, polarization, and interfaces on ${E}_{\mathrm{v}}$ are examined in this paper. The formation energies vary layer by layer in the superlattices, with ${E}_{\mathrm{v}}$ being higher in the ferroelectric phase than that in the paraelectric phase. The two interfaces constructed in these oxide superlattices, which are symmetrically equivalent in the paraelectric systems, exhibit very different formation energies in the ferroelectric superlattices and this can be seen to be driven by the coupling of ferroelectric and rotational modes. At equivalent lattice sites, ${E}_{\mathrm{v}}$ of charged vacancies is generally lower than that of neutral vacancies. Octahedral rotations $({\mathrm{a}}^{0}{\mathrm{a}}^{0}{\mathrm{c}}^{{-}})$ in the superlattices have a significant effect on ${E}_{\mathrm{v}}$, increasing the formation energy of vacancies located near the interface but decreasing the formation energy of the oxygen vacancies located in the bulk-like regions of the STO and PTO constituent parts. The formation-energy variations among different layers are found to be primarily caused by the difference in the local relaxation at each layer. Finally, these fundamental insights into the defect stability in perovskite superlattices can be used to tune defect properties by controlling the constituent materials of superlattices and interface engineering.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Global distribution, formation and fate of mineral‐associated soil organic matter under a changing climate: A trait‐based perspective

Abstract Soil organic matter (SOM) is the largest actively cycling reservoir of terrestrial carbon (C), and the majority of SOM in Earth's mineral soils (~65%) is mineral‐associated organic matter (MAOM). Thus, the formation and fate of MAOM can exert substantial influence on the global C cycle. To predict future changes to Earth's climate, it is critical to mechanistically understand the processes by which MAOM is formed and decomposed, and to accurately represent this process‐based understanding in biogeochemical and Earth system models. In this review, we use a trait‐based framework to synthesize the interacting roles of plants, soil micro‐organisms, and the mineral matrix in regulating MAOM formation and decomposition. Our proposed framework differentiates between plant and microbial traits that influence total OM inputs to the soil (‘feedstock traits’) versus traits that influence the proportion of OM inputs that are ultimately incorporated into MAOM (‘MAOM formation traits’). We discuss how these feedstock and MAOM formation traits may be altered by warming, altered precipitation and elevated carbon dioxide. At a planetary scale, these feedstock and MAOM formation traits help shape the distribution of MAOM across Earth's biomes, and modulate biome‐specific responses of MAOM to climate change. We leverage a global synthesis of MAOM measurements to provide estimates of the total amount of MAOM‐C globally (~840–1540 Pg C; 34%–51% of total terrestrial organic C), and its distribution across Earth's biomes. We show that MAOM‐C concentration is highest in temperate forests and grasslands, and lowest in shrublands and savannas. Grasslands and croplands have the highest proportion of soil organic carbon (SOC) in the MAOM fraction (i.e. the MAOM‐C:SOC ratio), while boreal forests and tundra have the lowest MAOM‐C:SOC ratio. Drawing on our trait framework, we then review experimental data and posit the effects of climate change on MAOM pools in different biomes. We conclude by discussing how MAOM is integrated into soil C models, and how feedstock and MAOM formation traits may be included in these models. We also summarize the projected fate of MAOM under climate change scenarios (Representative Concentration Pathways 4.5 and 8.5) and discuss key model uncertainties. Read the free Plain Language Summary for this article on the Journal blog.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Reconstruction of limnology and microbialite formation conditions from carbonate clumped isotope thermometry

Abstract Quantitative tools for deciphering the environment of microbialite formation are relatively limited. For example, the oxygen isotope carbonate‐water geothermometer requires assumptions about the isotopic composition of the water of formation. We explored the utility of using ‘clumped’ isotope thermometry as a tool to study the temperatures of microbialite formation. We studied microbialites recovered from water depths of 10–55 m in Pavilion Lake, and 10–25 m in Kelly Lake, spanning the thermocline in both lakes. We determined the temperature of carbonate growth and the 18 O/ 16 O ratio of the waters that microbialites grew in. Results were then compared to current limnological data from the lakes to reconstruct the history of microbialite formation. Modern microbialites collected at shallow depths (11.7 m) in both lakes yield clumped isotope‐based temperatures of formation that are within error of summer water temperatures, suggesting that clumped isotope analyses may be used to reconstruct past climates and to probe the environments in which microbialites formed. The deepest microbialites (21.7–55 m) were recovered from below the present‐day thermoclines in both lakes and yield radioisotope ages indicating they primarily formed earlier in the Holocene. During this time, pollen data and our reconstructed water 18 O/ 16 O ratios indicate a period of aridity, with lower lake levels. At present, there is a close association between both photosynthetic and heterotrophic communities, and carbonate precipitation/microbialite formation, with biosignatures of photosynthetic influences on carbonate detected in microbialites from the photic zone and above the thermocline (i.e., depths of generally <20 m). Given the deeper microbialites are receiving <1% of photosynthetically active radiation ( PAR ), it is likely these microbialites primarily formed when lower lake levels resulted in microbialites being located higher in the photic zone, in warm surface waters.

Petryshyn, V. A.↗
DOE OSTI2018

Study of the Formation Time of a Self-Sustained Subnanosecond Discharge at High and Ultrahigh Gas Pressures

The formation times of self-sustained subnanosecond discharges in nitrogen at pressures of 1‒40 atm and in hydrogen at pressures of 1–60 atm are analyzed in terms of the avalanche model. In experiments, a subnanosecond voltage pulse with an amplitude of 102 ± 2 kV was applied to a 0.5-mm-long discharge gap with a uniformly distributed electric field (the curvature radii of both the cathode and anode ends were 1 cm). The rise time of the voltage pulse from 0.1 to 0.9 of its amplitude value was about 250 ps. Breakdown occurred at the leading edge of the pulse. The discharge formation time was measured at different gas pressures with a step of 5–10 atm. Analysis of the experimental results shows that, in nitrogen at pressures of 10–40 atm and in hydrogen at pressures of 20–50 atm, breakdown occurs earlier than the electron avalanche reaches its critical length and that the critical avalanche length lies in the range of (2–8) × 10{sup –2} mm, which is one order of magnitude shorter than the discharge gap length. This means that the avalanche–streamer model is inapplicable in this case. The fast formation of a conducting channel under these conditions can be explained by ionization of gas by runaway electrons. In this case, the conducting column develops as a result of simultaneous development of a large number of electron avalanches in the gas volume. An increase in the hydrogen pressure from 50 to 60 atm leads to an abrupt increase in the discharge formation time by about 50%. As a result, the growth time of the electron avalanche to its critical length becomes shorter than the discharge formation time. In this case, the electrons cease to pass into the runaway regime and the discharge is initiated from the cathode due to field emission from microinhomogeneities on its surface. Under these conditions, the discharge formation time is well described by the avalanche–streamer model.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Characterization of Most Promising Sequestration Formations in the Rocky Mountain Region

The project Characterization of Most Promising Sequestration Formations in the Rocky Mountain Region is one of 9 site characterization projects that were implemented as part of ARRA (American Recovery and Reinvestment Act). Data from this project was used to improve resolution of data in NATCARB in the area of study. Data related to this study has already been incorporated in NATCARB Atlas. The Rocky Mountain Carbon Capture and Storage (RMCCS) project investigated multiple geologic formations and characterized a local site on the Colorado Plateau for future CCS opportunities. The RMCCS project focused on the Cretaceous Dakota, Jurassic Entrada, and Pennsylvanian Weber Sandstones, the three largest regional formations. All formations in this project are potential CO2 storage resources for future power plants, natural gas processing plants, cement plants, and oil shale development projects. The area adjacent to Craig, Colorado, (Sand Wash Basin) was the area selected for detailed geologic characterization on the RMCCS project. The basin was selected in part because the geology can be extrapolated to other sites on the Colorado Plateau. Field mapping and seismic surveys were conducted to identify and evaluate the basin's structural configuration. A 9,745-foot deep characterization well was drilled to collect 131 feet of core and a suite of geophysical well log data. Petrophysical tests on samples of core were used to calibrate geophysical log data, which can be used to obtain storage resource estimates and evaluate associated uncertainty as well as simulate the hydrologic behavior of injected CO2. A detailed analysis of the primary formations (Dakota, Entrada and Weber sandstones) yielded a more accurate CO2 storage resource assessment for these formations within the Colorado Plateau; RMCCS estimates indicate a total CO2 storage resource of more than 38,000 million metric tons. The characterization of the Sand Wash Basin (2-D seismic surveys, multiple well logs and lithological, petrophysical and geochemical analyses) allowed for a detailed 3-D model to be constructed. The model served as the framework for analyses ranging from CO2 storage resource, injectivity, and subsurface flow to uncertainty estimates to evaluation of risk.

2-D seismic↗
DOE OSTI2014

Subtask 2.17 - CO 2 Storage Efficiency in Deep Saline Formations

As the field of carbon capture and storage (CCS) continues to advance, and large-scale implementation of geologic carbon dioxide (CO 2 ) storage progresses, it will be important to understand the potential of geologic formations to store meaningful amounts of CO 2 . Geologic CO 2 storage in deep saline formations (DSFs) has been suggested as one of the best potential methods for reducing anthropogenic CO 2 emission to the atmosphere, and as such, updated storage resource estimation methods will continue to be an important component for the widespread deployment of CCS around the world. While there have been several methodologies suggested in the literature, most of these methods are based on a volumetric calculation of the pore volume of the DSF multiplied by a storage efficiency term and do not consider the effect of site-specific dynamic factors such as injection rate, injection pattern, timing of injection, pressure interference between injection locations, and overall formation pressure buildup. These volumetric methods may be excellent for comparing the potential between particular formations or basins, but they have not been validated through real-world experience or full-formation injection simulations. Several studies have also suggested that the dynamic components of geologic storage may play the most important role in storing CO 2 in DSFs but until now have not directly compared CO 2 storage resource estimates made with volumetric methodologies to estimates made using dynamic CO 2 storage methodologies. In this study, two DSFs, in geographically separate areas with geologically diverse properties, were evaluated with both volumetric and dynamic CO 2 storage resource estimation methodologies to compare the results and determine the applicability of both approaches. In the end, it was determined that the dynamic CO 2 storage resource potential is timedependent and it asymptotically approaches the volumetric CO 2 storage resource potential over very long periods of time in the two systems that were evaluated. These results indicate that the volumetric assessments can be used as long as the appropriate storage efficiency terms are used and it is understood that it will take many wells over very long periods of time to fully realize the storage potential of a target formation. This subtask was funded through the Energy & Environmental Research Center (EERC)– U.S. Department of Energy (DOE) Joint Program on Research and Development for Fossil Energy-Related Resources Cooperative Agreement No. DE-FC26-08NT43291. Nonfederal funding was provided by the IEA Greenhouse Gas R&D Programme.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

High-Burnup-Structure (HBS): Model Development in MARMOT for HBS Formation and Stability Under Radiation and High Temperature

A detailed phase field model for the formation of High Burnup Structure (HBS) was developed and implemented in MARMOT. The model treats the HBS formation as an irradiation-induced recrystallization. The model takes into consideration the stored energy associated with dislocations formed under irradiation. The accumulation of radiation damage, hence, increases the system free energy and triggers recrystallization. The increase in the free energy due to the formation of new grain boundaries is offset by the reduction in the free energy by creating dislocation-free grains at the expense of the deformed grains. The model was first used to study the growth of recrystallized flat and circular grains. The model reults were shown to agree well with theorrtical predictions. The case of HBS formation in UO2 was then investigated. It was found that a threshold dislocation density of (or equivalently a threshold burn-up of 33-40 GWd/t) is required for HBS formation at 1200K, which is in good agrrement with theory and experiments. In future studies, the presence of gas bubbles and their effect on the formation and evolution of HBS will be considered.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Navy Flight Testing Environmental Data Transfer Format Standard

This document outlines key elements of a data format standard for transferring Navy environmental flight test data between members of the Collaborative Environments Characterization Working Group (CECWG). The plan applies to measured data as well as analyzed or processed data. This plan is intended to foster a more productive collaboration between CECWG members by providing a common interface format such that each agency only has to receive and transmit data in one common format. Ideally, each agency is thus only responsible for translating formats between the native format of each agency’s respective database of flight measurements and this common data transfer format.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

A simple json format for storing and exchanging code calculation and experimental results

Calculation codes and code systems give their results in a plethora of different formats and/or files. For instance, MCNP gives a user the MCNP specific output file, the mctal file, the ptrac file, etc. while PARTISN has a PARTISN specific output file and a number of binary files with various kinds of information about the calculation. However, the results we are interested in are always the same. These can be single values such as the effective multiplication factor k eff or the effective delayed neutron fraction β eff . It can be histogram data (such as particle spectra, reaction rates, sensitivity profiles, etc.) or even pointwise data (for example the nuclide composition as a function of time, etc.). It is also worthwhile to note that this would also apply to experimental data that we may wish to compare with as well. Calculation and experimental results can basically be split into two components: attributes (or metadata) and the actual result itself. Attributes represent information about the result that are not necessarily required for its’ interpretation but that are still good to have. Often, these attributes are what we will want to filter results on. This means that these attributes are often the answer to specific questions we may have about the result. The following is a non exhaustive list of such basic questions: what type of result is it: e.g. the effective multiplication factor k eff , the effective delayed neutron fraction β eff , etc.; which case does it relate to: e.g. a specific ICSBEP case such as PU-MET-FAST-001-001; which code and version produced this result: e.g. MCNP 6.2, etc.; which nuclear data library was used to obtain the result: e.g. ENDF/B-VIII.0 or JEFF 3.3; which nuclide and reaction does it apply to (for reaction rates and sensitivity profiles); which volume in the geometry was it calculated in? The second component of the calculation or experimental result is the actual numerical data of the result. It is this data that we want to compare, exchange, plot, interpret, etc. It consists of values with optional uncertainties and units. It also includes the underlying structure (if any structure is required to interpret the result). Depending on the type of result, it may be a single value (e.g. the effective multiplication factor), an array of values (e.g. a reaction rate or particle spectrum) or even a multidimensional array. In order to exchange results between different organisations, for instance for benchmarking, people often resort to spreadsheets or custom text files that need to be filled out. While this approach works well if little information is to be exchanged, it can become cumbersome when dealing with large amounts of data (like for instance particle spectra for thousands of cases). In addition, such an approach does not always capture the metadata we may be interested in to allow for automated processing of these files. The purpose of this report is to propose a standardised json structure to store any type of result and present an associated python interface to interact with these results directly. For such a structure to be useful, it must fulfill a specific set of functional requirements that we try to meet with this proposal. The format must allow for the calculation result to stand by itself. This means that we should not have to look in multiple places to be able to understand it. For example, if the result relates to a particle spectrum, the group structure in which the result is given should be stored with it. The format should be code agnostic. This means that we do not need to know where it came from to understand it. The format should be result type agnostic. This means that the format must be generic enough so that we can even use it for results we have not thought of yet. The format should be relatively easy to interact with through different scripting or programming languages (i.e. the machine interface) while still providing a clean structure that can be used directly by any human.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Elucidating the formation mechanisms of zeolites using data-driven modelling and in-situ characterization

Zeolites are the main solid catalysts used by the chemical industry. The use of zeolites in separations and as shape selective catalysts requires control of the width and connectivity of their pores. 235 distinct zeolite frameworks have been synthesized to date, of over 2 million that have been proposed. Recent work indicates that the limitation is in large part kinetic: new synthetic pathways are required to access new zeolites. Organic cations are used to direct the synthesis towards specific zeolites. However, the molecular mechanisms by which cations direct the nucleation towards specific zeolites is not known. Elucidating these mechanisms is key to realize new zeolites for catalysis and separations, and is the focus of this project. This project developed and implemented a synergistic, data-driven computational and experimental approach to resolve the molecular pathways of nucleation, growth, and polymorph selection of zeolites and the role of organic cations in directing their formation. The project developed computationally efficient and accurate models for the study of the nucleation and growth of pure silica zeolites in molecular simulations, using machine learning with data from experiments. Simulations with these models were integrated with scanning tunneling electron microscopy, computer vision, and deep learning to unveil the molecular pathways of formation of a zeolite. Of particular interest in this project was to elucidate the role of amorphous precursors in the nucleation of the zeolite. Previous experiments indicate that zeolites are born within non-crystalline aggregates in which the silicates and organic cations have local and medium range order similar to that of the zeolite. The organic cations that direct the formation of zeolites and those that direct the formation of ordered mesoporous silicas are similar. We hypothesized that the frustrated attraction that for large organic cations leads to the formation of stable mesophases that direct the synthesis of mesoporous silicas, could promote the formation of metastable mesophases that can assist in the nucleation and polymorph selection of zeolites. The simulations resolved how structure directing agents build crystalline order and showed that mesoscopic pre-ordering occurs is not required to facilitate the nucleation of zeolites, because the synthesis occurs at high driving forces, where the barriers for nucleation are negligible. This project unveiled that polymorph selection in zeolite synthesis occurs after nucleation, opening a distinct area of control through the kinetics of growth and not through nucleation barriers.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Investigating Kinetic Mechanisms of Soot Formation in Plasma Pyrolysis of Methane via Active Learning (Final Technical Report)

Plasma pyrolysis of methane is an effective route for zero-carbon hydrogen production. Yet, soot generated from pyrolysis of hydrocarbons is detrimental to the climate and human health. There is ample experimental and theoretical evidence that suggests polycyclic aromatic hydrocarbons (PAHs) are the molecular precursors to soot particles. The reaction pathways of PAH formation are intricately dependent on a multitude of process parameters, whose kinetic mechanisms are not well-understood in plasma pyrolysis. This project aims to leverage advances in the kinetic modeling of soot formation in combustion, as well as in surrogate modeling and active learning, to systematically investigate the effects of process parameter on the kinetics of PAH formation in plasma pyrolysis of methane. To this end, we propose to use the PAH formation kinetics model developed by the PPPL/PU group based on the well-established ABF and HACA mechanisms, coupled with low-temperature plasma models. We will develop an active learning (AL) framework based on Bayesian optimization to systematically and data-efficiently explore the complex and multivariable parameter space of plasma pyrolysis in order to quantify the effects of plasma and feed parameters on the ABF and HACA kinetic pathways. AL is the branch of machine learning concerned with systematically querying samples from a system (experimental or computational) to train a data-driven model that maps design parameters to a performance criterion. We will use the data generated via AL to perform global sensitivity analysis, combined with uncertainty quantification, to elucidate the impact of different reaction pathways on minimizing formation of soot precursors. This study will result in an improved understanding of kinetics of PAH formation in plasma pyrolysis and can pave the way for more advanced mechanistic studies (e.g., soot nucleation mechanisms). Additionally, the findings will be useful for establishing practical strategies for increasing the pyrolysis efficiency and producing high-grade carbon for synthesis of nanomaterials.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Accelerating CO2 Storage Site Characterization through a New Understanding of Favorable Formation Properties and the Impact of Core-Scale Heterogeneities

CO2 sequestration in deep geologic formations can permanently reduce atmospheric CO2 emissions and help to abate climate change. Target formations must undergo a time- and resource-intensive site evaluation process, assessing storage capacity, environmental safety, and suitability for CO2 trapping via reactive transport models based on data from a limited number of core samples. As such, simulations are often simplified and omit heterogeneities in formation properties that may be significant but are not well understood. To facilitate more rapid site assessment, this work first defines the aquifer properties of favorable storage formations through the analysis of promising and active storage sites. Data show quartz is the most prevalent formation mineral with carbonate minerals, highly reactive with injected CO2, present in over 75% of formations. Porosity and permeability data are highly clustered at 10–30% and 10–1000 mD. Field-scale reactive transport simulations are then constructed and used to analyze CO2 trapping efficiency. The models consider porosity and carbonate mineral heterogeneity as well as the impacts of typical temperature gradients. Simulated sequestration efficiencies are compared to results from a comparable homogenous model to understand the implications of aquifer non-uniformities. The results show a lower sequestration efficiency in the homogeneous model during the injection phase. During the post-injection phase, the homogenization of porosity and carbonate mineralogy results in a higher sequestration efficiency. Incorporating the temperature gradient also increases the sequestration efficiency. Importantly, the maximum deviation between the homogeneous and heterogeneous simulations at the end of the 50-year study period is only ~10%. Larger impacts may be incurred for properties outside the defined, promising ranges suggested here.

Environmental Sciences & Ecology↗