A generalized poroelastic model using FEniCS with insights into the Noordbergum effect
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Haagenson, Ryan↗
SEARCH · Engineering Papers
Results for “gradient methods”
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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Controlling Molecular Structure and Spin with Multiconfigurational Quantum Chemistry (Final Technical Report)
For many first-row transition metal complexes, structure-property relationships can be obtained from high-level molecular geometry optimizations and subsequent electronic structure studies. The project funded under this award utilized newly implemented fully internally contracted (FIC) nuclear gradients for extended multi-state (XMS) complete active space second-order multireference perturbation theory (CASPT2) to explore geometry changes in first-row transition metal coordination complexes. At the start of the project, only one full geometry optimization using FIC-CASPT2 analytical gradients had been reported (J. Chem. Theory Comput., 2016, 12 (8), 3781), and many open-questions regarding the performance and achievable accuracy in applying such computations to larger complexes persisted. Key deliverables in the report include the implementation of the numerical Hessian and subsequent vibrational analysis in the BAGEL program package. This includes both full Hessian vibrational analysis (FHVA) and a partial Hessian vibrational analysis (PHVA). The latter of which allows us to reduce the significant cost of computing the vibrational frequencies in a large molecule by focusing on the modes of highest interest. The gradient code also proved useful in the development of an approach to improve the Hubbard-U correction by removing bias in predicting spin-splitting in Fe(II) complexes via plane-wave density functional theory (DFT). Finally, we showed for three families of complexes (spin-crossover (SCO) complexes, metallocorroles complexes, and those with metal-metal bonds) that CASPT2 can result in good molecular geometries and established best practices in undertaking this work. We are now using this approach in collaborative projects with experimental groups, which would not have been possible at the start of this project. A common theme also arose through this work that static and dynamic correlation must be recovered in a balanced way to yield quantitative results. By systematically varying how both effects were included, we were able to make key chemical insights. This work supported the training of two postdoctoral scholars, one graduate student, and one undergraduate student in applying high-level wavefunction based methods to challenging systems.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Role of Intermolecular Interactions in Deep Eutectic Solvents for CO 2 Capture: Vibrational Spectroscopy and Quantum Chemical Studies
Recent research and reviews on CO 2 capture methods, along with advancements in industry, have highlighted high costs and energy-intensive nature as the primary limitations of conventional direct air capture and storage (DACS) methods. In response to these challenges, deep eutectic solvents (DESs) have emerged as promising absorbents due to their scalability, selectivity, and lower environmental impact compared to other absorbents. However, the molecular origins of their enhanced thermal stability and selectivity for DAC applications have not been explored before. Therefore, the current study focuses on a comprehensive investigation into the molecular interactions within an alkaline DES composed of potassium hydroxide (KOH) and ethylene glycol (EG). Combining Fourier transform infrared (FT-IR) and quantum chemical calculations, the study reports structural changes and intermolecular interactions induced in EG upon addition of KOH and its implications on CO 2 capture. Experimental and computational spectroscopic studies confirm the presence of noncovalent interactions (hydrogen bonds) within both EG and the KOH-EG system and point to the aggregation of ions at higher KOH concentrations. Additionally, molecular electrostatic potential (MESP) surface analysis, natural bond orbital (NBO) analysis, quantum theory of atoms-in-molecules (QTAIM) analysis, and reduced density gradient-noncovalent interaction (RDG-NCI) plot analysis elucidate changes in polarizability, charge distribution, hydrogen bond types, noncovalent interactions, and interaction strengths, respectively. Evaluation of explicit and hybrid models assesses their effectiveness in representing intermolecular interactions. This research enhances our understanding of molecular interactions in the KOH-EG system, which are essential for both the absorption and desorption of CO 2 . The study also aids in predicting and selecting DES components, optimizing their ratios with salts, and fine-tuning the properties of similar solvents and salts for enhanced CO 2 capture efficiency.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Toward predictive permeabilities: Experimental measurements and multiscale simulation of methanol transport in Nafion
A polymer membrane's permeability to solutes determines its suitability for various applications: a permeability value is essential for predicting performance in diverse contexts. Using aqueous methanol permeation through Nafion as an example, we describe a methodology for determining membrane permeability that accounts for boundary layer effects and the possibility of swelling. For the materials and apparatus used herein, analysis of a permeance measurement and computational fluid dynamics simulations show that the mass transfer boundary layer is on the order of ones to tens of microns. Additionally, the data are used to develop and validate a multiscale model describing solute permeation through a hydrated membrane as a series of physical mechanistic steps: reversible adsorption from solution at the membrane interface, diffusion driven by a concentration gradient within the membrane, and reversible desorption into solution at the opposite membrane interface. The validated model is used to predict methanol transport across a solar-driven CO 2 reduction device and to assess the impact of polymer changes on the measured value. The approach of combining experimental data, computational fluid dynamics, and the mechanistic multiscale model is expected to provide more accurate analysis of membrane permeation data in cases with polymer swelling or unusual device geometries, among others.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Tokamak ITG-KBM transition benchmarking with the mixed variables/pullback transformation electromagnetic gyrokinetic scheme
Electromagnetic gyrokinetic simulation of high temperature plasma is required to predict confinement in magnetic fusion devices and has posed challenges for existing codes. In this paper, we demonstrate successful global gyrokinetic simulation of the ion temperature gradient-driven mode-kinetic ballooning mode transition in a toroidal fusion plasma test case using the mixed variables/pullback transformation (MV/PT) scheme with the particle-in-cell codes XGC and ORB5, and compare to results from a conventional continuum code from the literature. Furthermore, the MV/PT scheme combines explicit time integration with mitigation of the well-known electromagnetic gyrokinetic “cancelation problem.” We calculate eigenmodes in the electrostatic and parallel vector potentials, and find good agreement in growth rate, real frequency, and the normalized plasma pressure of mode transition.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
In-situ thermomechanical measurements during burst testing of Zr claddings using digital image correlation and infrared thermography techniques
Burst testing has long been a relied-on method for assessing fuel cladding materials in light-water reactoraccident scenarios. However, burst testing historically provided minimal in-situ observations beyond a few thermocouple readings, pressure from transducers, and post-test deformation measurements. Acquisition of full cladding thermomechanical data throughout a burst test would be invaluable to fuel system qualification, material model development and fuel performance code validation, such as the BISON fuel performance code. Recently, methodologies for simultaneously applying 2-dimensional digital image correlation and infrared thermography techniques to quantify the relationship between temperature, internal cladding pressure, and deformation during burst testing were developed. This work details results from the application of these techniques to burst testing of Zircaloy-4 cladding segments subjected to loss-of-coolant accident transients in an air environment. Two types of tests were performed with: (a) cladding segments connected to a fixed pressure reservoir as well as (b) closed systems where internal pressure increased during transients. In-situ thermomechanical measurements including strain and thermal gradient data are presented, demonstrating the effectiveness of applying combined surface measurement techniques to burst testing
Bell, Sam↗
The impact of habitat fragmentation on domatia-dwelling mites and a mite-plant-fungus tritrophic interaction
Abstract Context Habitat fragmentation is a leading threat to biodiversity, yet the impacts of fragmentation on most taxa, let alone interactions among those taxa, remain largely unknown. Objectives We studied how three consequences of fragmentation—reduced patch connectivity, altered patch shape, and edge proximity—impact plant-dwelling mite communities and mite-plant-fungus interactions within a large-scale habitat fragmentation experiment. Methods We sampled mite communities from the leaves of Quercus nigra (a plant species that has foliar domatia which harbor fungivorous and predacious mites) near and far from edge within fragments of varying edge-to-area ratio (shape) and connectivity via corridors. We also performed a mite-exclusion experiment across these fragmentation treatments to test the effects of mite presence and fungal hyphal abundance on leaf surfaces. Results Habitat edges influenced the abundance and richness of leaf-dwelling mites; plants closer to the edge had higher mite abundance and species richness. Likewise, hyphal counts were higher on leaves near patch edges. Despite both mite and fungal abundance being higher at patch edges, leaf hyphal counts were not impacted by mite abundance on those leaves. Neither patch shape nor connectivity influenced mite abundance, mite species richness, or the influence of mites on leaf surface fungal abundance. Conclusion Our results suggest that mites and foliar fungi may be independently affected by edge-structured environmental gradients, like temperature, rather than trophic effects. We demonstrate that large-scale habitat fragmentation and particularly edge effects can have impacts on multiple levels of microscopic communities, even in the absence of cascading trophic effects.
60 APPLIED LIFE SCIENCES↗
Linking international technical specifications for acoustic characterization of marine energy converter sounds with environmental compliance criteria
As new ocean energy technologies emerge and are deployed for testing and operations, sound emissions are a potential concern for environmental effects to marine life. Consistent acoustic measurement and data analysis methods can help promote comparisons of technologies and transferability between project sites. In 2022, acoustic emissions from a prototype scale wave energy converter (WEC) were characterized for a range of environmental conditions and power generation states in the coastal waters off southern California using a set of international technical specifications. Results from the international technical specification analyses were applied to United States regulatory threshold criteria for acoustic impacts to marine mammals and examined in the context of European underwater noise monitoring guidelines. Weighted 24 hour cumulative sound exposure levels SEL24h calculated from the highest power generation state WEC sound pressure levels were often more than 20 dB below threshold criteria for temporary threshold shifts in five relevant marine mammal hearing groups. Following European Union recommendations for analyses and reporting, WEC sound characterization in third octave bands centered at 63 Hz and 125 Hz show clear spatial decay of WEC-generated noise, with more pronounced attenuation at 63 Hz, and a less marked but still detectable gradient at 125 Hz, collectively suggesting a relatively confined acoustic footprint under the observed conditions. The value of the international technical specification approach is highlighted by the isolation of WEC sounds from the surrounding soundscape. This allows for a robust characterization of acoustic emissions through a range of device power generation and sea states. Furthermore, in threshold-based regulatory contexts like the U.S., this facilitates direct evaluation of source contributions, while in broader monitoring frameworks used in the E.U. it provides a reproducible foundation for assessing the contribution of emerging ocean energy technologies to the underwater acoustic environment.
Haxel, Joseph H. (ORCID:0000000273864761)↗
Convergence of variational Monte Carlo simulation and scale-invariant pre-training
We provide theoretical convergence bounds for the variational Monte Carlo (VMC) method as applied to optimize neural network wave functions for the electronic structure problem. Here, we study both the energy minimization phase and the supervised pre-training phase that is commonly used prior to energy minimization. For the energy minimization phase, the standard algorithm is scale-invariant by design, and we provide a proof of convergence for this algorithm without modifications. The pre-training stage typically does not feature such scale-invariance. We propose using a scale-invariant loss for the pretraining phase and demonstrate empirically that it leads to faster pre-training.
97 MATHEMATICS AND COMPUTING↗
Microscopic subsurface characterization of layered magnetic materials using magnetic resonance force microscopy
This project resulted in the following accomplishments: 1) The invention of scanned probe ferromagnetic resonance microscopy. Upon implementation and refinement this approach was used to measure static and dynamic magnetic resonance properties of ferromagnets with an unprecedented combination of spectral and spatial resolution. 2) Demonstration and study of spin pumping in a pristine ferromagnet across a boundary defined entirely by a magnetic field gradient, and so free of materials discontinuities. 3) First demonstrated highly efficient dynamic spin injection from Y 3 Fe 5 O 12 (YIG) into NiO, an antiferromagnetic (AF) insulator and robust spin propagation in AF NiO over distances up to 100-nm thickness; both spin injection and spin transport are mediated by the AF spin correlations. 4) Demonstration of exceptionally high efficiency conversion of spin current to charge current achieved in spin pumping from the dynamic magnetization of a ferromagnetic insulator into a variety of adjacent metal films. 5) Seminal study of the nature of spin-orbit coupling in d-electron metals that revealed the dominant sensitivity of the d-orbital moment to the d-electron count and revealing the important roles of both d-electron configuration and atomic number in the physics of the spin Hall effect. 6) Demonstration of observation of FMR by means of optically-detected NV diamond relaxometry that provided a highly sensitive, spatially resolved FMR detection method and revealed spin pumping across 100-nm length scales by means of dipolar coupling. 7) Using magnetic field localization, developed for FMR imaging, demonstrated a novel approach to discretizing spin wave modes to improve the characteristics of auto-oscillators driven by pure spin currents produced by the spin Hall effect. 8) We demonstrated large spin pumping signals from propagating high wavevector spinwaves in thin film YIG find that the spin pumping efficiency was insensitive to wavevector thus emphasizing the promise of thin YIG films for spinwave-based spintronics by allowing for predictable down-scaling of device dimensions and enabling a broad range of operational frequencies.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
A scalable compressible volume of fluid solver using a stratified flow model
Here, in this paper, a Volume of Fluid method which uses a Stratified Flow model for flux calculation is proposed to solve a compressible multiphase flow in a way that has high parallel efficiency. The solver is part of an open-source computing tool to study fuel entrainment and combustion in the application of paraffin-based hybrid rocket motors. This paper focuses on the compressible Volume of Fluid solver for the liquid and gaseous phases in this environment. This solver uses perfect gas and stiffened gas models for equation of state, with the ability to easily add other models as desired. Additionally a comparison of a Riemann solver versus an AUSM+up scheme is conducted, showing improvement with the later in the solution of multiphase flows. This solver successfully reproduces shock tube cases with the expected accuracy, as well as simulating two-dimensional shear and gravity-driven flows. Results also show that the code is able to utilize a Stratified Flow model to evaluate shear flow without the need for interface reconstruction or gradient calculations. Finally, it is shown that the solver has near-ideal scaling under strong scaling tests as well as good performance in static scaling, giving improved performance over current options and implying future advancement of high-performance computing efficiency for multiphase flow solvers.
97 MATHEMATICS AND COMPUTING↗
Modelling of electrostatic ion-scale turbulence in divertor tokamaks with the gyrokinetic code $\mathrm{COGENT}$
Here, continuum gyrokinetic simulations of electrostatic ion scale turbulence are presented for the case of a diverted (single-null) tokamak geometry. The simulation model, implemented in the finite-volume code COGENT, solves the long-wavelength limit of the full-F gyrokinetic equation for ion species coupled to a vorticity equation for electrostatic potential variations, where a fluid model is used for an electron response. The model describes the ion scale ion temperature gradient (ITG) and resistive drift modes as well as neoclassical ion physics effects. Different turbulence regimes are observed depending on the plasma profiles, and the roles of a self-consistent background electric field and an X-point geometry are explored. In particular, increasing the pedestal density gradient and the corresponding radial electric field is demonstrated to suppress the ITG turbulence, whereas the same edge plasma background can still be destabilized by the resistive modes when the plasma resistivity is increased. The effects of X-point geometry are assessed by comparing cross-separatrix simulations with counterpart calculations performed for a toroidal annulus geometry. For the simulation parameters considered, similar global behaviour is observed in both cases, whereas strong local suppression of turbulence fluctuations is demonstrated near the X-point for the case of a single-null geometry.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Manifold Sampling for Optimizing Nonsmooth Nonconvex Compositions
Here we propose a manifold sampling algorithm for minimizing a nonsmooth composition $f= h\circ F$, where we assume $h$ is nonsmooth and may be inexpensively computed in closed form and $F$ is smooth but its Jacobian may not be available. We additionally assume that the composition $h\circ F$ defines a continuous selection. Manifold sampling algorithms can be classified as model-based derivative-free methods, in that models of $F$ are combined with particularly sampled information about $h$ to yield local models for use within a trust-region framework. We demonstrate that cluster points of the sequence of iterates generated by the manifold sampling algorithm are Clarke stationary. We consider the tractability of three particular subproblems generated by the manifold sampling algorithm and the extent to which inexact solutions to these subproblems may be tolerated. Numerical results demonstrate that manifold sampling as a derivative-free algorithm is competitive with state-of-the-art algorithms for nonsmooth optimization that utilize first-order information about $f$.
97 MATHEMATICS AND COMPUTING↗
LABQ3: Bayesian method for quantification of mineral compositions and nano-scale elemental mapping of 3D synchrotron XCT data
Quantitative analysis of mineral compositions is essential in understanding geochemical, mineralogical and environmental processes. Fine-resolution 3D imaging is widely done using synchrotron X-ray computed tomography (XCT), but existing analyses are limited to visualization and segmentation. This paper presents a new method, Linear Attenuation Bayesian Quantitative 3D-mapper (LABQ3), based on the linearity of X-ray attenuation with respect to elemental concentrations. To address the random variability in attenuation measurements, LABQ3 employs Bayesian decision theory to minimize classification error, using reference attenuation distributions from scans of pure mineral standards. To demonstrate LABQ3 and test its performance, we studied precipitated carbonate samples. XCT scans were done at multiple energies using the transmission X-ray microscope (TXM) at beamline 32-ID-C of the Advanced Photon Source at Argonne National Laboratory. The reconstructed 3D images have a voxel size of 20 nm. Analyses revealed rich nano-scale compositional heterogeneity within individual particles. A mixture of calcium and cadmium produced an overall stoichiometric composition of (Ca 0.78 ,Cd 0.22 )CO 3 , with some voxels containing nearly pure CdCO 3 . The addition of zinc led to an overall stoichiometric composition of 33% Ca, 28% Cd, 39% Zn, with a nearly pure CaCO 3 core and compositional zonation through the rim. These compositional gradients are related to temporal sequences of carbonate mineral formation where Cd precipitated at the beginning in (Ca,Cd)CO 3 , while Cd and Zn precipitated at the end in (Ca, Cd,Zn)CO 3 . Results differ from bulk analyses using Inductively Coupled Plasma-Mass Spectrometry (ICP-MS), showing that LABQ3 provides particle-specific insights. LABQ3 distinguishes itself by quantifying chemical compositions along a continuum, making it different from XCT analyses based on segmentation. LABQ3 allows simultaneous acquisition of morphology and chemical composition in 3D, facilitating the interpretation of chemical gradients of trace elements, quantification of solid solution compositions, inferences about temporal sequences of mineral precipitation, and addressing other concerns about solid-phase chemistry.
58 GEOSCIENCES↗
Continuous Fly-Through High-Temperature Synthesis of Nanocatalysts
Conventional thermal treatment system, such as muffle and tube furnaces, typically feature low ramping and cooling rates, which lead to steep thermal gradients during bulk material synthesis that generate inefficient, non-uniform reaction conditions and result in nanoparticle aggregation. Herein, we demonstrate a continuous fly-through material synthesis approach using a novel high-temperature reactor design based on the emerging thermal-shock technology. By facing two sheets of carbon paper with a small distance apart (1–3 mm), we are able to generate uniform, ultra-high temperatures that can reach up to 3200 K within 50 ms by simply applying a voltage of 15 V. We can control this high-temperature to enable ultrafast chemical reactions by continuously feeding raw materials through the device from one end to the other, allowing the final products to be rapidly collected. As a proof-of-concept demonstration, we synthesized Pt nanocatalysts ~4 nm in size anchored to carbon black via this fly-through high-temperature reactor at ~1400 K. Furthermore, we find these supported Pt nanoparticles feature excellent electrocatalytic activities toward methanol oxidation reaction. Compared to existing heating methods, this continuous fly-through high temperature reactor offers a new and highly efficient platform for the synthesis of nanomaterials at high temperatures.
Qiao, Yun↗
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↗
Toward a Holistic Performance Evaluation of Large Language Models Across Diverse AI Accelerators
Artificial intelligence (AI) methods have become critical in scientific applications to help accelerate scientific discovery. Large language models (LLMs) are being considered a promising approach to address some challenging problems because of their superior generalization capabilities across domains. The effectiveness of the models and the accuracy of the applications are contingent upon their efficient execution on the underlying hardware infrastructure. Specialized Al accelerator hardware systems have recently become available for accelerating Al applications. However, the comparative performance of these AI accelerators on large language models has not been previously studied. In this paper, we systematically study LLMs on multiple AI accelerators and GPUs and evaluate their performance characteristics for these models. We evaluate these systems with (i) a micro-benchmark using a core transformer block, (ii) a GPT-2 model, and (iii) an 1,I,M-driven science use case, GenSLM. We present our findings and analyses of the models' performance to better understand the intrinsic capabilities of AI accelerators. Furthermore, our analysis takes into account key factors such as sequence lengths, scaling behavior, and sensitivity to gradient accumulation steps.
Emani, Murali↗