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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 181 records · Page 10

Exploring fingerprints of ultrafast structural dynamics in molecular solutions with an X-ray laser

We apply ultrashort x-ray laser pulses to track optically excited structural dynamics of [Ir 2 (dimen) 4 ] 2+ molecules in solution. In our exploratory study we determine angular correlations in the scattered x-rays, which comprise a complex fingerprint of the ultrafast dynamics. Model-assisted analysis of the experimental correlation data allows us to elucidate various aspects of the photoinduced changes in the excited molecular ensembles. We unambiguously identify that in our experiment the photoinduced transition dipole moments in [Ir 2 (dimen) 4 ] 2+ molecules are oriented perpendicular to the Ir-Ir bond. The analysis also shows that the ground state conformer of [Ir 2 (dimen) 4 ] 2+ with a larger Ir–Ir distance is mostly responsible for the formation of the excited state. We also reveal that the ensemble of solute molecules can be characterized with a substantial structural heterogeneity due to solvent influence. In conclusion, the proposed x-ray correlation approach offers an alternative path for studies of ultrafast structural dynamics of molecular ensembles in the liquid and gas phases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Synergizing human expertise and AI efficiency with language model for microscopy operation and automated experiment design

With the advent of large language models (LLMs), in both the open source and proprietary domains, attention is turning to how to exploit such artificial intelligence (AI) systems in assisting complex scientific tasks, such as material synthesis, characterization, analysis and discovery. Here, we explore the utility of LLMs, particularly ChatGPT4, in combination with application program interfaces (APIs) in tasks of experimental design, programming workflows, and data analysis in scanning probe microscopy, using both in-house developed APIs and APIs given by a commercial vendor for instrument control. We find that the LLM can be especially useful in converting ideations of experimental workflows to executable code on microscope APIs. Beyond code generation, we find that the GPT4 is capable of analyzing microscopy images in a generic sense. At the same time, we find that GPT4 suffers from an inability to extend beyond basic analyses for more in-depth technical experimental design. We argue that an LLM specifically fine-tuned for individual scientific domains can potentially be a better language interface for converting scientific ideations from human experts to executable workflows. Such a synergy between human expertise and LLM efficiency in experimentation can open new doors for accelerating scientific research, enabling effective experimental protocols sharing in the scientific community.

97 MATHEMATICS AND COMPUTING↗

Probing the antiknock effect of anisole through an ignition, speciation and modeling study of its blends with isooctane

In order to unravel the reaction pathways relevant to anisole co-oxidation within a fuel blend, a detailed study of isooctane/anisole blends was performed with the ULille RCM. Ignition delays as well as mole fraction profiles were measured during a two-stage ignition delay using sampling and GC techniques. These results are used to validate a kinetic model developed from ab initio calculations for the most relevant rate constants which included H-atom abstraction reactions from anisole, and reactions on the potential energy surfaces of methoxyphenyl + O 2 and anisyl + O 2 . Pressure dependent rate constants were computed for the methoxyphenyl + O 2 and anisyl + O 2 reactive systems using master equation code analysis. The new kinetic model shows good agreement with the experimental data. Dual brute-force sensitivity analysis was performed, on both first- and second-stages of ignition, allowing the identification of the most important reactions in the prediction of both ignition delays. It was observed that while pure anisole does not show NTC behavior, a 60/40 isooctane/anisole blend displays such behavior, as well as two-stage ignition. This suggests anisole addition may not be as beneficial to knock resistance as expected from its high octane number. The kinetic modeling results demonstrate the importance of H-abstraction reactions both from the methoxy group and from the aryl ring in ortho-position and the addition of the resultant radicals to O2, mostly leading to the formation of polar or non-aromatic products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Physics-guided dual implicit neural representations for source separation

Significant challenges exist in efficient data analysis of most advanced experimental and observational techniques because the collected signals often include unwanted contributions, such as background and signal distortions, that can obscure the physically relevant information of interest. To address this, we have developed a self-supervised machine-learning approach for source separation using a dual implicit neural representation framework that jointly trains two neural networks: one for approximating distortions of the physical signal of interest and the other for learning the effective background contribution. Our method learns directly from the raw data by minimizing a reconstruction-based loss function without requiring labeled data or pre-defined dictionaries. We demonstrate the effectiveness of our framework by considering a challenging case study involving large-scale simulated, as well as experimental, momentum-energy-dependent inelastic neutron scattering data in a four-dimensional parameter space, characterized by heterogeneous background contributions and unknown distortions to the target signal. The method is found to successfully separate physically meaningful signals from a complex or structured background even when the signal characteristics vary across all four dimensions of the parameter space. An analytical approach that informs the choice of the regularization parameter is presented. Our method offers a versatile framework for addressing source separation problems across diverse domains, ranging from superimposed signals in astronomical measurements to structural features in biomedical image reconstructions.

47 OTHER INSTRUMENTATION↗

A physically based mechanical model for Mullins effect in thermoplastic polyurethanes

Despite decades of research, connecting the chemical and physical structure of thermoplastic polyurethanes to their mechanical properties remains highly challenging. Of particular note are their large-deformation and rate-dependent behaviors, which vary greatly with molecular chemistry, including the type and relative content of soft and hard segments. In this work, we develop a physically motivated mechanical theory for predicting the behavior of thermoplastic polyurethanes. The theory incorporates a representation of microstructural evolution during mechanical deformation, which captures the signatures of stress softening over cyclic loading (commonly referred to as the Mullins effect). There are only eight physically motivated fitting parameters, including a direct dependence on the hard segment fraction. The model predicts that increasing the hard segment fraction leads to higher stiffness and greater energy dissipation, in quantitative agreement with published experimental data. Furthermore, we provide a comprehensive analysis of the model and validate its predictions across several independent datasets focused on mechanical characterization. Direct comparisons to experimental data demonstrate its predictive capability on the effect of loading rate, cyclic deformations, and applied tension or compression. Altogether, this work establishes a predictive framework that connects polymer chemistry and microstructure to emergent mechanical behaviors.

36 MATERIALS SCIENCE↗

Bayesian inference analysis of jet quenching using inclusive jet and hadron suppression measurements

The JETSCAPE Collaboration reports a new determination of the jet transport parameter $\hat{q}$ in the quark-gluon plasma (QGP) using Bayesian inference, incorporating all available inclusive hadron and jet yield suppression data measured in heavy-ion collisions at the BNL Relativistic Heavy Ion Collider (RHIC) and the CERN Large Hadron Collider (LHC). This multi-observable analysis extends the previously published JETSCAPE Bayesian inference determination of $\hat{q}$, which was based solely on a selection of inclusive hadron suppression data. jetscape is a modular framework incorporating detailed dynamical models of QGP formation and evolution, and jet propagation and interaction in the QGP. Virtuality-dependent partonic energy loss in the QGP is modeled as a thermalized weakly coupled plasma, with parameters determined from Bayesian calibration using soft-sector observables. This Bayesian calibration of $\hat{q}$ utilizes active learning, a machine-learning approach, for efficient exploitation of computing resources. The experimental data included in this analysis span a broad range in collision energy and centrality, and in transverse momentum. In order to explore the systematic dependence of the extracted parameter posterior distributions, several different calibrations are reported, based on combined jet and hadron data; on jet or hadron data separately; and on restricted kinematic or centrality ranges of the jet and hadron data. Tension is observed in comparison of these variations, providing new insights into the physics of jet transport in the QGP and its theoretical formulation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Fast permeability measurement for tight reservoir cores using only initial data of the one chamber pressure pulse decay test

Here, in this study, a mathematical model for fast determination of the permeabilities of tight rocks using measurements taken from the initial period of the One Chamber Pressure Pulse Decay (OC-PPD) test is presented. The model applies to measurements taken both before and after the pressure pulse front has reached the downstream end of the specimen. The analytical solutions for the pressure decay in the upstream chamber are derived based on a parabolic arc approximation of pore pressure distribution along the test specimen. This approximation allows converting the initial–boundary value problem of fluid diffusion in the specimen, governed by partial differential equations, to a system of ordinary differential equations that can be easily solved by explicit formulae. Thus, an explicit formula for the pressure decay rate is obtained, which enables inverse analysis of the initial experimental data to estimate the rock permeability. The proposed method expedites the pulse decay test as it does not require the system to reach equilibrium. The method is validated with three sets of experimental data of the OC-PPD test using helium as the diffusing fluid, for which the relative error of the permeability is found to be less than 6%. This method is particularly useful if the equilibrium time of the pulse decay test for rock specimens with permeabilities in the range of nano-Darcy takes hours or days.

early-time solution↗

hpMCA: A Python-based Graphical Program for Energy Dispersive X-Ray Diffraction Data Collection and Analysis

Energy-dispersive X-ray diffraction (EDXD) at synchrotron beamlines is commonly used for the study of material properties under high pressure and/or high temperature. Experimenters typically rely on the availability of robust data collection and analysis at a beamline, but this has become increasingly difficult, especially with the introduction of multi-element detectors that generate complex, multi-dimensional data sets. These data sets have energy resolution, and they can also be resolved in relation to sample position, diffraction angle, or different external stimuli. We report a new Python-based graphical program, hpMCA, for EDXD data collection and analysis that streamlines the experimental process for the beamline users. The program features a user-friendly interface, capability for online viewing and analyzing data from multi-element energy-dispersive detectors, and includes features useful for working with samples under high pressure and/or high temperature, such as crystal phase identification, real-time unit cell lattice refinement, and pressure determination based on an equation of state.

data analysis software↗

304L Can Crush Validation Studies

Accurate prediction of ductile behavior of structural alloys up to and including failure is essential in component or system failure assessment, which is necessary for nuclear weapons alteration and life extensions programs of Sandia National Laboratories. Modeling such behavior requires computational capabilities to robustly capture strong nonlinearities (geometric and material), rate- dependent and temperature-dependent properties, and ductile failure mechanisms. This study's objective is to validate numerical simulations of a high-deformation crush of a stainless steel can. The process consists of identifying a suitable can geometry and loading conditions, conducting the laboratory testing, developing a high-quality Sierra/SM simulation, and then drawing comparisons between model and measurement to assess the fitness of the simulation in regards to material model (plasticity), finite element model construction, and failure model. Following previous material model calibration, a J 2 plasticity model with a microstructural BCJ failure model is employed to model the test specimen made of 304L stainless steel. Simulated results are verified and validated through mesh and mass-scaling convergence studies, parameter sensitivity studies, and a comparison to experimental data. The converged mesh and degree of mass-scaling are the mesh discretization with 140,372 elements, and a mass scaling with a target time increment of 1.0e-6 seconds and time step scale factor of 0.5, respectively. Results from the coupled thermal-mechanical explicit dynamic analysis are comparable to the experimental data. Simulated global force vs displacement (F/D) response predicts key points such as yield, ultimate, and kinks of the experimental F/D response. Furthermore, the final deformed shape of the can and field data predicted from the analysis are similar to that of the deformed can, as measured by 3D optical CMM scans and DIC data from the experiment.

36 MATERIALS SCIENCE↗

Doppler Backscattering Data Analysis and Integrated Modeling with OMFIT

One Modeling Framework for Integrated Tasks (OMFIT) is a widely used software tool in the magnetic fusion research community. OMFIT provides magnetic fusion energy researchers with a framework for the development of special-purpose physics modules. This paper describes an OMFIT physics module pertaining to the Doppler Backscattering (DBS) fusion plasma diagnostic. DBS measures density fluctuations and flow velocity through plasma scattering of electromagnetic waves. The OMFIT DBS module was developed to analyze experimental DBS data and facilitate modeling of DBS systems installed on multiple tokamak devices. The OMFIT DBS module is designed to support several analysis workflows: detailed analysis of experimental data, experimental planning, and theory-based synthetic diagnostic modeling. The DBS module uses integrated modeling by leveraging other OMFIT physics modules to perform tasks related to DBS, e.g. ray/beam–tracing simulations, edge-localized mode–synchronized data analysis, magnetic equilibrium reconstruction, and fitting kinetic profile data. Furthermore, this paper describes several supported workflows and serves a reference for the OMFIT DBS module.

Doppler backscattering↗

Measurement bias in self-heating x-ray free electron laser experiments from diffraction studies of phase transformation in titanium

X-ray self-heating is a common by-product of X-ray Free Electron Laser (XFEL) techniques that can affect targets, optics, and other irradiated materials. Diagnosis of heating and induced changes in samples may be performed using the x-ray beam itself as a probe. However, the relationship between conditions created by and inferred from x-ray irradiation is unclear and may be highly dependent on the material system under consideration. Here, we report on a simple case study of a titanium foil irradiated, heated, and probed by a MHz XFEL pulse train at 18.1 keV delivered by the European XFEL using measured x-ray diffraction to determine temperature and finite element analysis to interpret the experimental data. We find a complex relationship between apparent temperatures and sample temperature distributions that must be accounted for to adequately interpret the data, including beam averaging effects, multivalued temperatures due to sample phase transitions, and jumps and gaps in the observable temperature near phase transformations. The results have implications for studies employing x-ray probing of systems with large temperature gradients, particularly where these gradients are produced by the beam itself. Finally, this study shows the potential complexity of studying nonlinear sample behavior, such as phase transformations, where biasing effects of temperature gradients can become paramount, precluding clear observation of true transformation conditions.

Crystallography↗

Exploring the Neutron Substructure with Advanced Polarized Helium-3 Targets (Or: How I Learned to Stop Worrying and Love Spectroscopy)

As we seek to understand the smallest, physical aspects of our universe, we cannot simply rely on our senses to probe the world around us as we did in the past. The smallest physical elements of our universe behave in strange, probabilistic ways and are completely invisible to the naked eye/ear/etc. So, we design clever experiments (such as scattering experiments) to probe these minute realms. Then, just as with the larger, observable world, we devise models and equations to describe what we think is happening. Due to the nature of the physical universe at the quantum scale and with the aid of symmetries such as Lorentz invariance, we can write down equations that describe the scattering, but the expressions contain functions, which we call ?form factors? and ?structure functions?, that we cannot compute from first principles. We can, however, formulate models that make predictions for these functions. By comparing our predictions with the observed data, we can gain insight into the validity of our models and thus a better physical understanding of what is happening at these minuscule scales. Studying the constituents inside of the nucleus of an atom adds another layer of difficulty if we can?t remove those components from the nucleus. This is the case with the neutron. When not bound in the nucleus with protons and other neutrons, the neutron will decay into a proton after about 15 minutes. So, we?re forced to study the neutron while it is still bound in the nucleus of an atom such as helium-3 (3He). For the last 1,000 years (rounding up), our group has developed high quality, polarized 3He targets made of an aluminosilicate glass. These targets are made in order to perform experiments at Jefferson Lab (JLab), experiments which let us determine the form factors and structure functions of the neutron by scattering polarized electrons from polarized neutrons (or rather polarized 3He). The specific experiments reported on in this thesis push the bounds of our understanding of the internal structure of the neutron. Good science is often about pushing experimental techniques to a new level. Toward that goal we study our polarized 3He targets both to advance the technology and to choose the best ones for our experiments. We do this using a process called nuclear magnetic resonance (NMR) to gauge the maximum polarization of a target and how fast the polarization decays with time. While these tests primarily provide us information that make analysis of our experimental scattering data possible, they also let us determine whether or not a target-cell is useful or even, dare I say, of spectacular quality. Our latest targets utilize a novel convection design allowing 3He to be polarized and quickly moved in front of the electron-beam, making it possible to use larger targets with higher electron-beam currents than ever before. This means more electrons scatter and we get more data. And by studying our targets in detail prior to using them in our experiments, we have found techniques to take effects which could have been detrimental to target quality and turn them to our advantage! It?s a real case of making lemonade out of lemons. We also use laser spectroscopy to study the absorption lines of alkali-metals in the target (potassium and rubidium, specifically). We add these alkali-metals to our target to facilitate polarizing the 3He. We can use the measurement of these pressure broadened absorption lines to determine the 3He density inside of the target with great precision. Historically, we understood the width of these lines would be dependent on the temperature of the target. Specifically, if I raise the temperature, the width should get bigger. I found that was not the case, which was very confusing at first, though very exciting now that I realize the data are self-consistent and suggestive of unexpected behavior. This thesis details the development of high quality, glass, polarized 3He targets for the 2020 An 1 /dn 2 and 2023 Gn E experiments, which utilized the first 3He convection targets and broke records in target quality. This thesis also covers the initial development of metal windows for the next-generation of 3He target-cells. Finally, this thesis documents the temperature dependence of the width of potassium (K) and rubidium (Rb) absorption lines as measured with laser spectroscopy.

Jantzi, Christopher↗

Continuous recovery of phosphoric acid and Rare-Earths containing particles from phosphoric acid sludge using a decanter centrifuge

Recovery of rare earth elements (REEs) from various industrial and natural streams currently draws significant attention in efforts to meet the demands of the manufacturing industry. Among many industrial byproducts and waste streams, phosphoric acid sludge could be one of the most economically feasible resources for the recovery of REEs because solid particles in the sludge contain relatively concentrated REEs, up to 3,000 ppm, while the liquid component of the sludge is valuable phosphoric acid (P 2 O 5 ) that can be recovered and returned to the main product. Due to high viscosity and large solids content (e.g., 30–40 %), however, this byproduct stream requires multistep separation and purification processes. In this study, a single-step process involving a continuous-flow decanter centrifuge (CFDC) was employed to investigate its feasibility for continuous solid/liquid separation from real phosphoric acid sludge. High centrifugal forces generated from up to 1500 G gravity acceleration separate solid particles from the sludge, generating a liquid-rich stream and a solids-rich stream at the exit of the CFDC. A single pass of phosphoric-acid sludge through the CFDC yielded 95 % liquid recovery and 90 % recovery of REEs-containing solids from 20 to 34 wt% solids-containing sludge. Finally, a reduced order model developed for the CFDC operation showed good agreement with experimental data, and preliminary technoeconomic analysis revealed potential process feasibility.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Maximizing Marine Carbon Removal by Coupling Electrochemical and Biological Methods

Integrated development of emerging marine decarbonization strategies offers the possibility of lowering CO2 removal costs and enabling their widespread deployment. In this study we examine the feasibility and benefits of coupling electrochemical and biological marine carbon removal strategies. Bipolar membrane electrodialysis (BPMED) is used to generate acid and alkalinity from seawater and electricity, and the alkalinity is returned to the ocean for indirect CO2 removal from the atmosphere, but the acid stream is a waste product. Considering the large-scale of CO2 removal necessary, the acid storage, neutralization, and disposal have prohibitive costs and carbon footprint. Here we investigate the feasibility to valorize the acid stream to enhance the growth and CO2 uptake through photosynthesis in the fast-growing marine phytoplankter Picochlorum celeri. When added to active algae cultures, the BPMED-generated acidified seawater alters the carbonate-bicarbonate equilibrium thereby increasing the bioavailability of CO2 and the observed growth rates. Additions of up to 2 mM H+ from BPMED effluent streams increased algal productivity up to 3-fold. A high-level analysis conducted based on experimental data to estimate the potential of sequestered CO2 emissions when compared to conventional commercial means of acid utilization or disposal, is estimated to be ~30 kgCO2 / kgacid. Through further development and optimization in terms of choice of algal species, growth conditions, acid addition rates, etc. the combined electrochemical-biological approach has the potential to achieve higher net CO2 removal.

carbon dioxide, marine, marine algae↗

Photocatalytic water splitting

With the goal of achieving large-scale H 2 production from renewable resources, water splitting into H 2 and O 2 using semiconductor photocatalysts (sometimes called artificial photosynthesis) has been studied for five decades. Unfortunately, the lack of rigour and reproducibility in the data collection and analysis of experimental results has hindered progress in the field. This Primer provides a comprehensive overview of proper characterization and evaluation of photocatalysts for overall water splitting. In particular, the Primer covers various pitfalls in photocatalysis research, best practices for reproducibility and reliable methods for conducting rigorous experiments. As a result, the recommendations are intended to reduce false positives in the literature and to promote progress towards a practical technology for producing H 2 from water by using sunlight.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Lifetime fatigue response due to wake steering on a pair of utility-scale wind turbines

Quantifying the impacts on turbine loads during wind farm control is an important consideration in assessing power production benefits. Wake steering controls aim to improve total wind farm performance by coordinating the control actions of individual turbines, wherein an upstream turbine is intentionally yawed at an offset angle from the measured wind direction. Consequently, this redirects its wake for improved power production and potentially reduces fatigue loads of the downstream turbines. This paper studies the lifetime fatigue loads associated with wake steering by using utility-scale wind turbine experimental data to conduct an analysis on a pair of wind turbines. This study was part of a large field experiment in which a group of five GE 1.5-MW SLE CWE turbines were selected as targets for conducting wake steering research. A standard loads instrumentation package and data acquisition system were installed on two turbines within the cluster to measure turbine fundamental loads. The time-series databases were used to calculate loads statistics as well as short-term and lifetime damage equivalent loads. Fatigue calculations followed the guidance in Annex H of the International Electrotechnical Commission standard 61400-1, Edition 4. Lifetime fatigue calculation results are presented in this analysis; three methods of assessing lifetime fatigue were used to determine percent difference for blade root moments, main shaft moments, main shaft torque, and tower top torque. For all three fatigue treatments, some components’ lifetime fatigue increases for the controlled turbine; however, the downwind turbine experienced a reduction in lifetime fatigue and combined effect for the turbine pair results in a reduction of fatigue when wake steering controls are applied.

17 WIND ENERGY↗

Consideration of memory of spin and parity in the fissioning compound nucleus by applying the Hauser-Feshbach fission fragment decay model to photonuclear reactions

Prompt and β-delayed fission observables, such as the average number of prompt and delayed neutrons, the independent and cumulative fission product yields, and the prompt γ-ray energy spectra for the photonuclear reactions on 235,238 U and 239 Pu, are calculated with the Hauser-Feshbach fission fragment decay (HF 3 ⁢D) model and compared with available experimental data. Further, in the analysis of neutron-induced fission reactions to the case of photo-induced fission, an excellent reproduction of the delayed neutron yields supports a traditional assumption that the photo fission might be similar to the neutron-induced fission at the same excitation energies regardless of the spin and parity of the fissioning systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗