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Results for “Henry’s constant”

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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Coupled Interfacial and Bulk Kinetics Govern the Timescales of Multiphase Ozonolysis Reactions

Chemical transformations in aerosols impact the lifetime of particle phase species, the fate of atmospheric pollutants, and both climate- and health-relevant aerosol properties. Timescales for multiphase reactions of ozone in atmospheric aqueous phases are governed by coupled kinetic processes between the gas phase, the particle interface, and its bulk, which respond dynamically to reactive consumption of O 3 . However, models of atmospheric aerosol reactivity often do not account for the coupled nature of multiphase processes. Herein, to examine these dynamics, we use new and prior experimental observations of aqueous droplet reaction kinetics, including three systems with a range of surface affinities and ozonolysis rate coefficients ( trans -aconitic acid (C 6 H 6 O 6 ), maleic acid (C 4 H 4 O 4 ), and sodium nitrite (NaNO 2 )). Using literature rate coefficients and thermodynamic properties, we constrain a simple two-compartment stochastic kinetic model which resolves the interface from the particle bulk and represents O 3 partitioning, diffusion, and reaction as a coupled kinetic system. Our kinetic model accurately predicts decay kinetics across all three systems, demonstrating that both the thermodynamic properties of O 3 and the coupled kinetic and diffusion processes are key to making accurate predictions. An enhanced concentration of adsorbed O 3 , compared to gas and bulk phases is rapidly maintained and remains constant even as O 3 is consumed by reaction. Multiphase systems dynamically seek to achieve equilibrium in response to reactive O 3 loss, but this is hampered at solute concentrations relevant to aqueous aerosol by the rate of O 3 arrival in the bulk by diffusion. As a result, bulk-phase O 3 becomes depleted from its Henry's law solubility. This bulk-phase O 3 depletion limits reaction timescales for relatively slow-reacting organic solutes with low interfacial affinity (i.e., trans-aconitic and maleic acids, with k rxn ≈ 10 3 -10 4 M -1 s -1 ), which is in contrast to fast-reacting solutes with higher surface affinity (i.e., nitrite, with k rxn ≈ 10 5 M -1 s -1 ) where surface reactions strongly impact the observed decay kinetics.

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

Looking at supersymmetric black holes for a very long time

We study correlation functions for extremal supersymmetric black holes. It is necessary to take into account the strongly coupled nature of the boundary supergraviton mode. We consider the case with {\cal N}=2 supercharges which is the minimal amount of supersymmetry needed to give a large ground state degeneracy, separated from the continuum. Using the exact solution for this theory we derive formulas for the two point function and we also give integral expressions for any n n -point correlator. These correlators are time independent at large times and approach constant values that depend on the masses and couplings of the bulk theory. We also explain that in the non-supersymmetric case, the correlators develop a universal time dependence at long times. This paper is the longer companion paper of arXiv:2207.00407.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Metal stack templates for suppressing secondary grains in sca1n

A metal stack for templating the growth of AlN and ScAlN films is disclosed. The metal stack comprises one, two, or three layers of metal, each of which is compatible with CMOS post-processing. The metal stack provides a template that promotes the growth of highly textured c-axis {002} AlN and ScAlN films. The metal stacks include one or more metal layers with each metal layer having either a hexagonal {002} orientation or a cubic {111} orientation. If the metal stack includes two or more metal layers, the layers can alternate between hexagonal {002} and cubic {111} orientations. The use of ScAlN results in a higher piezoelectric constant compared to that of AlN for ScAlN alloys up to approximately 44% Sc. The disclosed metal stacks resulted in ScAlN films having XRD FWHM values of less than approximately 1.1° while significantly reducing the formation of secondary grains in the ScAlN films.

Esteves, Giovanni↗
DOE OSTI2020

Effect of gap size on composition and structure of regeneration 19 years after harvest in a southeastern bottomland forest, USA

Following timber harvests in bottomland mixed-oak (Quercus L.) stands, desirable oak advance regeneration can be overgrown by shade-intolerant pioneer species. We investigated the effects of group selection opening size on composition of tree regeneration 19 years postharvest in an oak-dominated bottomland forest and compared results with earlier findings to evaluate development trends. In response to six opening sizes (7–40 m radii), we evaluated regeneration density and dominance of four tree species groups: conifers, hard mast, shade-intolerant hardwoods, and shade-tolerant hardwoods. Our objectives were to determine the optimum gap size for regenerating oaks and test the delayed oak dominance hypothesis, in which oaks slowly gain dominance as pioneer species undergo self-thinning. Opening size influenced conifer regeneration but minimally affected hardwoods. Hard mast species density was less than that of either intolerant or tolerant species regardless of opening size. Future stem density trends suggest increasing intolerant species and constant mast and tolerant species. Modeled future height trends suggest increasing mast species dominance over intolerant pioneers after 30 years. Furthermore, our results suggest that gap-based silviculture can be used to regenerate bottomland hardwood stands with desirable species including oaks; larger gaps favor conifers but there was no optimum size to enhance oak regeneration.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Feasibility of measuring the speed of sound of the quark-gluon plasma from the multiplicity and mean 𝑝 𝑇 of ultracentral heavy-ion collisions

The mean transverse momentum ⟨𝑝 𝑇 ⟩ of hadrons has been observed experimentally and in numerical simulations to have a power-law dependence on the hadronic multiplicity 𝑁 in ultracentral relativistic heavy-ion collisions: ⟨𝑝 𝑇 ⟩∝𝑁 𝑏 UC . It has been put forward that this exponent 𝑏 UC is the speed of sound of quark-gluon plasma measured at a temperature determined from ⟨𝑝 𝑇 ⟩. We study step by step the connection between (i) the energy and entropy of hydrodynamic simulations and (ii) experimentally measurable observables. We show that an argument based on energy and entropy should yield an exponent equal to the pressure over energy density 𝑃/ɛ, rather than the speed of sound 𝑐$_s^2$; however, we also observe that ⟨𝑝 𝑇 ⟩ and 𝑁 are not sufficiently accurate proxies for the energy and entropy to make this possible in practice. From simulations, we find that the exponent 𝑏 UC is significantly different whether the “effective volume” is strictly constant or not, a condition that cannot be enforced experimentally. Additional tests using a modified equation of state find that the exponent 𝑏 UC exhibits a variable degree of correlations with the speed of sound and with 𝑃/ɛ, but is not an accurate measurement of either quantity in general.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Cosmological structure formation and soliton phase transition in fuzzy dark matter with axion self-interactions

Herein we investigate cosmological structure formation in fuzzy dark matter (FDM) with the attractive self-interaction (SI) with numerical simulations. Such a SI would arise if the FDM boson were an ultra-light axion, which has a strong CP symmetry-breaking scale (decay constant). Although weak, the attractive SI may be strong enough to counteract the quantum ‘pressure’ and alter structure formation. We find in our simulations that the SI can enhance small-scale structure formation, and soliton cores above a critical mass undergo a phase transition, transforming from dilute to dense solitons.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Machine Learning a Simple Interpretable Short-Range Potential for Silica

A wide array of models, spanning from computationally expensive ab initio methods to a spectrum of force-field approaches, have been developed and employed to probe silica polymorphs and understand growth processes and atomic-level dynamical transitions in silica. However, the quest for a model capable of making accurate predictions with high computational efficiency for various silica polymorphs is still ongoing. Recent developments in short-range machine-learned models, such as GAP and NNPScan, have shown promise in providing reasonable descriptions of silica, but their computational cost remains high compared to force fields such as BKS which are based on simple interpretable functional forms. Here, in this study, we build on the recent success of our reinforcement learning (RL) workflow to derive a new set of optimal parameters for a promising short-range BKS-based model proposed by Soules. We use RL to navigate the eight-dimensional parameter space of the Soules potential using an experimental training data set that includes both local and global structural features from approximately 21 experimentally realized silica polymorphs, including high density phases and porous zeolites. We compare the performance of our machine-learned ML-Soules model with other high quality models including our recent machine-learned parametrization of BKS (ML-BKS), a machine-learned potential (GAP), as well as predictions of ab initio calculations with the highly fidelity SCAN functional. The ML-Soules accurately captures the relative energetic ordering of various polymorphs as well as their structural features at a significantly reduced computational expense. The ML-Soules model also reasonably captures the structure, density, and elastic constants of quartz, as well as metastable silica polymorphs. We further discuss the limitations of the Soules functional form and propose potential enhancements, including the incorporation of additional three-body terms and/or the utilization of different short-ranged functional forms to achieve greater accuracy for both global and local features in the modeling of silica while retaining low computational cost.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Hierarchical Reinforcement Learning of a Short-Range Bond-Order Potential for Silica: Analytic Embedding of Coordination with Classical Efficiency

Reinforcement learning (RL) has recently emerged as a data-efficient strategy to parametrize short-range interatomic potentials. Building on our past RL optimization of pairwise silica models, we extend the framework to a bond-order (Tersoff-type) potential that provides an analytic embedding of local coordination through a three-body term. A hierarchical RL workflow combining continuous-action Monte Carlo Tree Search and property-based rewards efficiently explores the 26-dimensional parameter space, sequentially optimizing lattice parameters, densities, angles, and cohesive energies of 21 silica polymorphs. The resulting models, Q-Tersoff and ML-Tersoff, reproduce the energetic ordering of low-energy phases and capture the angular correlations and amorphous structure factors of silica with improved fidelity over pairwise force fields, while remaining orders of magnitude faster than high-dimensional machine-learned potentials. Both models underperform for elastic constants and high-energy frameworks, delineating the limits of the current analytic form. The approach establishes a general and interpretable route to angle-aware, short-range potentials that bridge physics-based and machine-learned descriptions of silicate materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The atmospheric importance of methylamine additions to Criegee intermediates

We report that Criegee intermediates are important targets for study in atmospheric chemistry because of their capacity to oxidize airborne species. Among these species, ammonia has received critical attention for its presence in polluted agricultural or industrial areas and its role in forming particulate matter and condensation nuclei. Although methylamine has been given less attention than ammonia, both theoretical and experimental studies have demonstrated that the additional methyl substitution on the ammonia derivatives increases the rate constants for some systems. This suggests that the methylamine addition to Criegee intermediates could be more significant to atmospheric processes. In this work, geometries are optimized at the DF-CCSD(T)/ANO1 level for the methylamine addition reactions to the simplest Criegee intermediate and the anti- and syn-methylated Criegee intermediates. Energies for each stationary point were computed at the CCSD(T)/CBS level with corrections from the CCSDT(Q) method. Rate constants are obtained for each reaction using canonical transition state theory. Although methylamine addition proved to be a more favorable reaction relative to ammonia addition, the significantly lower concentration of atmospheric methylamine limits the prevalence of these reactions, even in the most optimal conditions. It is unlikely that the methylamine addition to Criegee intermediates will contribute significantly to the consumption of Criegee intermediates in the atmosphere.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

A theoretical kinetic study of ĊH 3 + ṄH 2 : From electronic structure to NH 3 /CH 4 combustion modelling implications

Carbon–nitrogen interaction reactions play an important role in governing the reactivity of ammonia blended fuels. However, there remains uncertainties regarding their detailed reaction pathways and rate constants, hampering the development of high-fidelity chemical kinetic models. In this study, the kinetics of ĊH 3 + ṄH 2 , a key C–N interaction reaction in ammonia/methane blend combustion have been investigated. The potential energy surface has been explored using the high-level ANL0F method, yielding highly accurate stationary point energies that agree with ATcT values within 0.1 kcal mol –1 . Variable reaction coordinate transition state theory is used to treat the barrierless association and decomposition reaction channels, based on directly sampled radical-radical interaction energies at the CASPT2-F12(2e,2o)/cc-pVTZ-F12 level of theory. The minimum transitional mode numbers of states obtained are then coupled with the RRKM/master equation to calculate temperature- and pressure-dependent rate constants. Our a priori calculations capture available experimental measurements from the literature very well. The calculated rate constants have been incorporated into an NH 3 /CH 4 chemical kinetic model currently under development at the University of Galway. The effect of the updated kinetic data for ĊH 3 + ṄH 2 on model predicted NH 3 /CH 4 fuel reactivity is elucidated.

ab initio↗
DOE OSTI2022

Multi-reward Reinforcement Learning Based Bond-Order Potential to Study Strain-Assisted Phase Transitions in Phosphorene

Here, we introduce a multi-reward reinforcement learning (RL) approach to train a flexible bond-order potential (BOP) for 2D phosphorene based on ab initio training data sets. Our approach is based on a continuous action space Monte Carlo tree search algorithm that is general and scalable and presents an efficient multiobjective optimization scheme for high-dimensional materials design problems. As a proof-of-concept, we deploy this scheme to parametrize multiple structural and dynamical properties of 2D phosphorene polymorphs. Our RL-trained BOP model adequately captures the structure, energetics, transformation barriers, equation of state, elastic constants, and phonon dispersions of various 2D P polymorphs. We use this model to probe the impact of temperature and strain rate on the phase transition from black (α-P) to blue phosphorene (β-P) through molecular dynamics simulations. A decrease in critical strain for this phase transition with increase in temperature is observed, and the underlying atomistic mechanisms are discussed.

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

Mucin and Agitation Shape Predation of Escherichia coli by Lytic Coliphage

The ability of bacteriophage (phage), abundant within the gastrointestinal microbiome, to regulate bacterial populations within the same micro-environment offers prophylactic and therapeutic opportunities. Bacteria and phage have both been shown to interact intimately with mucin, and these interactions invariably effect the outcomes of phage predation within the intestine. To better understand the influence of the gastrointestinal micro-environment on phage predation, we employed enclosed, in vitro systems to investigate the roles of mucin concentration and agitation as a function of phage type and number on bacterial killing. Using two lytic coliphage, T4 and PhiX174, bacterial viability was quantified following exposure to phages at different multiplicities of infection (MOI) within increasing, physiological levels of mucin (0–4%) with and without agitation. Comparison of bacterial viability outcomes demonstrated that at low MOI, agitation in combination with higher mucin concentration (>2%) inhibited phage predation by both phages. However, when MOI was increased, PhiX predation was recovered regardless of mucin concentration or agitation. In contrast, only constant agitation of samples containing a high MOI of T4 demonstrated phage predation; briefly agitated samples remained hindered. Our results demonstrate that each phage–bacteria pairing is uniquely influenced by environmental factors, and these should be considered when determining the potential efficacy of phage predation under homeostatic or therapeutic circumstances.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Demonstrating resonant ultrasound spectroscopy as a viable technique to characterize thermally conditioned high explosive materials

We present results of resonant ultrasound spectroscopy (RUS) measurements applied to granular high explosive materials at different bulk pressing densities and degree of thermal conditioning. The material chosen in this study is a ubiquitously used explosive material known as pentaerythritol tetranitrate (PETN), which is used commercially in civil and defense applications both as a binderized plastic bonded explosive material and an unbinderized neat material. However, changes in granular PETN bulk elastic properties due to thermal conditioning, which could have implications for better understanding environmental aging-related effects, have not been well studied even though it is believed that elasticity may play an important role in explosive material initiation mechanisms. Furthermore, monitoring elastic property changes in granular explosive pressings has not yet been demonstrated using RUS, which is an appealing non-destructive characterization tool that requires only dry point contact with the explosive material. To this end, we report the first study using RUS to quantify the elastic properties of binderized and neat PETN pressings as well as to quantify changes in elastic properties as a function of both thermal conditioning and bulk pressing density. Elastic stiffness coefficients, sometimes more commonly referred to as elastic constants, calculated from the RUS measurements on the different PETN-based materials show a significant increase for the post-conditioned samples compared to the pre-conditioned samples. This trend of increasing elastic properties with thermal conditioning was consistent for different density pressings, different thermal exposure conditions, and even different neat PETN pressings of differing average crystal sizes and/or specific surface areas.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Cost Estimation of a Permanent Magnet Synchronous Machine for Use in Adjustable Speed-Pumped Storage Hydropower

Electric machine design has become an easier process with the availability of computers in recent decades. However, the interest in electric machine design among students has declined. University-level design courses must compete with courses perceived as more desirable by the potential job market. Hence, the power system engineers with this expertise are very few and are nearing retirement. Contrarily, renewable energy has been picking up in the past few decades. The indeterminacy and variation of renewable energy sources require a balancing mechanism to maintain the constant voltage and frequency of the grid. Adjustable-Speed Pumped-Storage Hydropower plants are considered the contender for future energy storage, providing large capacity and fast-acting response. Large-scale hydropower applications depend on the natural characteristics of each project site, making less expensive, off-the-shelf generators unfeasible. This work gives a shortcut to estimate the cost of constructing a permanent magnet generator for low-volume manufacturing.

13 HYDRO ENERGY↗
DOE OSTI2023

Improved ion heating in fast ignition by pulse shaping

The fast ignition paradigm for inertial fusion offers increased gain and tolerance of asymmetry by compressing fuel at low entropy and then quickly igniting a small region. Because this hotspot rapidly disassembles, the ions must be heated to ignition temperature as quickly as possible, but most ignitor designs directly heat electrons. A constant-power ignitor pulse, which is generally assumed, is suboptimal for coupling energy from electrons to ions. Using a simple model of a hotspot in isochoric plasma, a novel pulse shape to maximize ion heating is presented in analytical form. Bounds are derived on the maximum ion temperature attainable by electron heating only. Moreover, arranging for faster ion heating allows a smaller hotspot, improving fusion gain. As a result, under representative conditions, the optimized pulse can reduce ignition energy by over 20%.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Machine learning prediction of self-diffusion in Lennard-Jones fluids

In this work, different machine learning (ML) methods were explored for the prediction of self-diffusion in Lennard-Jones (LJ) fluids. Using a database of diffusion constants obtained from the molecular dynamics simulation literature, multiple Random Forest (RF) and Artificial Neural Net (ANN) regression models were developed and characterized. The role and improved performance of feature engineering coupled to the RF model development was also addressed. The performance of these different ML models was evaluated by comparing the prediction error to an existing empirical relationship used to describe LJ fluid diffusion. It was found that the ANN regression models provided superior prediction of diffusion in comparison to the existing empirical relationships.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Multi-reward reinforcement learning based development of inter-atomic potential models for silica

Abstract Silica is an abundant and technologically attractive material. Due to the structural complexities of silica polymorphs coupled with subtle differences in Si–O bonding characteristics, the development of accurate models to predict the structure, energetics and properties of silica polymorphs remain challenging. Current models for silica range from computationally efficient Buckingham formalisms (BKS, CHIK, Soules) to reactive (ReaxFF) and more recent machine-learned potentials that are flexible but computationally costly. Here, we introduce an improved formalism and parameterization of BKS model via a multireward reinforcement learning (RL) using an experimental training dataset. Our model concurrently captures the structure, energetics, density, equation of state, and elastic constants of quartz (equilibrium) as well as 20 other metastable silica polymorphs. We also assess its ability in capturing amorphous properties and highlight the limitations of the BKS-type functional forms in simultaneously capturing crystal and amorphous properties. We demonstrate ways to improve model flexibility and introduce a flexible formalism, machine-learned ML-BKS, that outperforms existing empirical models and is on-par with the recently developed 50 to 100 times more expensive Gaussian approximation potential (GAP) in capturing the experimental structure and properties of silica polymorphs and amorphous silica.

36 MATERIALS SCIENCE↗
DOE OSTI2021

X-ray diffraction and in situ pressurization of dentine apatite reveals nanocrystal modulus stiffening upon carbonate removal

Bone-like materials comprise carbonated-hydroxyapatite nanocrystals (c-Ap) embedding a fibrillar collagen matrix. The mineral particles stiffen the nanocomposite by tight attachment to the protein fibrils creating a high strength and toughness material. The nanometer dimensions of c-Ap crystals make it very challenging to measure their mechanical properties. Mineral in bony tissues such as dentine contains 2~6 wt.% carbonate with possibly different elastic properties as compared with crystalline hydroxyapatite. Here we determine strain in biogenic apatite nanocrystals by directly measuring atomic deformation in pig dentine before and after removing carbonate. Transmission electron microscopy revealed the platy 3D morphology while atom probe tomography revealed carbon inside the calcium rich domains. High-energy X-ray diffraction in combination with in situ hydrostatic pressurization quantified reversible c-Ap deformations. Additionally, crystal strains differed between annealed and ashed (decarbonated) samples, following 1 or 10 h heating at 250 °C or 550 °C respectively. Measured bulk moduli (K) and a-/c-lattice deformation ratios (η) were used to generate synthetic K syn and ηsyn identifying the most likely elastic constants C 33 and C 13 for c-Ap. These were then used to calculate the nanoparticle elastic moduli. For ashed samples, we find an average E 11 =107 GPa and E 33 =128 GPa corresponding to ~5% and ~17% stiffening of the a-/c-axes of the nanocrystals as compared with the biogenic nanocrystals in annealed samples. Ashed samples exhibit ~10% lower Poisson's ratios as compared with the 0.25~0.36 range of carbonated apatite. Carbonate in c-Ap may therefore serve for tuning local deformability within bony tissues.

36 MATERIALS SCIENCE↗