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At least 1,765 records · Page 98

Multi-Task Reinforcement Learning for Distribution System Voltage Control With Topology Changes

This letter proposes a multi-task deep reinforcement learning (DRL) approach for distribution system voltage regulation considering topology changes via PV smart inverter control. The key idea is to encode the topology as an additional state for the DRL and leverage the multi-task learning scheme for joint learning of all task control policies. Unlike other DRL-based methods, our approach is robust to different topologies. Comparison results on the modified IEEE 123-node system demonstrate the enhanced robustness of the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Parametric Comparative Analysis between Virtual Synchronous Generator and Droop-based Inertia for Inverter-Based Microgrids

This paper presents a parametric comparative analysis between the virtual synchronous generator (VSG) method and the droop control method to emulate inertia in the voltage-source inverter (VSI). Droop controllers are commonly used to regulate sharing power in microgrids and distribute power generation proportionally among VSI’s depending on their rated power. Additionally, VSG has been used to regulate the Rate-of-Change-of-Frequency (RoCoF) of the microgrid using virtual inertia. Although both methods can be used to regulate the frequency variation, the influence of each method on the closed loop eigenvalues is not the same. In this work, the transient response of the frequency is analyzed for each method to determine their advantages and disadvantages regarding frequency regulation in microgrid applications. The results were verified by conducting experimental trials using VSI’s. These experiments demonstrated that VSG is more suitable for regulating RoCoF and frequency nadir than droop controllers since it provides inertial support and improves frequency response.

Campo-Ossa, Daniel D.↗

Modeling the spectral modification of lower hybrid wave in the presence of drift-wave type density fluctuation in the scrape-off-layer of the EAST tokamak

In this work, the spectrum change of the lower hybrid (LH) waves caused by a low-frequency density fluctuation in the scrape-off-layer is studied by applying the wave scattering model developed by Bonoli and Ott [Phys. Fluids 25, 359 (1982)] via a Monte Carlo method. A ray-tracing model specific to this purpose is developed to evaluate the probability distribution of both the poloidal refractive index (N θ ) and the parallel refractive index (N ∥ ) of the LH wave at the last closed flux surface (LCFS).The probability distributions of N ∥ and N θ at the LCFS are studied using the EAST parameters as a function of wave frequency, the initial N ∥ , and the polar injection position, which may influence the lower hybrid current drive efficiency.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Molecular beam scattering from flat jets of liquid dodecane and water

Abstract Molecular beam experiments in which gas molecules are scattered from liquids provide detailed, microscopic perspectives on the gas–liquid interface. Extending these methods to volatile liquids while maintaining the ability to measure product energy and angular distributions presents a significant challenge. The incorporation of flat liquid jets into molecular beam scattering experiments in our laboratory has allowed us to demonstrate their utility in uncovering dynamics in this complex chemical environment. Here, we summarize recent work on the evaporation and scattering of Ne, CD 4 , ND 3 , and D 2 O from a dodecane flat liquid jet and present first results on the evaporation and scattering of Ar from a cold salty water jet. In the evaporation experiments, Maxwell–Boltzmann flux distributions with a cos θ angular distribution are observed. Scattering experiments reveal both impulsive scattering (IS) and trapping followed by thermal desorption (TD). Super‐specular scattering is observed for all four species scattered from dodecane and is attributed to anisotropic momentum transfer to the liquid surface. In the IS channel, rotational excitation of the polyatomic scatterers is a significant energy sink, and these species accommodate more readily on the dodecane surface compared to Ne. Our preliminary results on cold salty water jets suggest that Ar atoms undergo some vapor‐phase collisions when evaporating from the liquid surface. Initial scattering experiments characterize the mechanisms of Ar interacting with an aqueous jet, allowing for comparison to dodecane systems. Key Points Molecular beam scattering from flat liquid jets is a powerful technique to elucidate mechanistic detail at the gas–liquid interface. Previous dodecane scattering experiments have uncovered angularly‐resolved thermal desorption fractions and energy transfer at the interface for several small molecule scatterers. Preliminary results on scattering from cold salty water reveal mechanisms of interaction between argon and an aqueous jet.

Yang, Walt↗

Electron and photon structure functions at two loops

We present a fully analytic computation of the complete electron and photon structure functions, or QED lepton parton distribution functions (PDFs) up to two-loop order. Our computation is performed using modern techniques of reduction to Master Integrals and solving them with the differential equation method. We obtain explicit expressions for the electron-in-electron, positron-in-electron, photon-in-electron, electron-in-photon, and photon-in-photon distributions at next-to-next-to-leading order (NNLO). Cross-checks against one-loop results, existing two-loop calculations, and a recent soft-collinear effective theory (SCET) analysis of the electron structure functions are presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Measurement of distribution coefficients on TODGA resin and development of a group separation for mixed activation and fission product samples

Batch equilibrium experiments were performed to determine the distribution coefficients for Sc, Ir, and Ta on N,N,N’,N’tetraoctyl-1,5-diglycolamide (TODGA) resin in various acid matrices. Distribution coefficients were determined in hydrochloric acid (Sc, Ir), nitric acid (Sc, Ta), and a mixture of nitric acid and 0.2M hydrofluoric acid (Sc, Ir, Ta). The distribution coefficients determined through these experiments were then utilized to create a group separation method for activation products, fission products, and environmental constituents.

Louie, Christina A.↗

Anelasticity and Phase Transition During Ramp-Release in Tin

This study examines the qualitative features of an anelasticity model associated with the bowing of dislocations in the presence of phase transition. A simple physically plausible mechanism is introduced to describe the interaction of anelasticity and the transformation. Varying the anelastic parameters results in strong differences in the deviatoric stress response. The model is applied to study the behavior of tin (Sn) and compared to data from ramp driven compression-release experiments. Tin exhibits a complex phase diagram within a relatively accessible range of temperature and pressures and the characterization of its phases is considered an open problem with significant scientific merit. The coupling between anelasticity, plasticity, and phase transformation contributes to release wave features traditionally associated with the phase transition effect alone suggesting the importance of accounting for the effects jointly. Posterior distributions of the plastic and anelastic parameters are computed using Bayesian-inference-based methods, further highlighting the importance of anelasticity in this regime.

36 MATERIALS SCIENCE↗

Non-destructive simulation of node defects in additively manufactured lattice structures

Additive Manufacturing (AM), commonly referred to as 3D printing, offers the ability to not only fabricate geometrically complex lattice structures but parts in which lattice topologies in-fill volumes bounded by complex surface geometries. However, current AM processes produce defects on the strut and node elements which make up the lattice structure. This creates an inherent difference between the as-designed and as-fabricated geometries, which negatively affects predictions (via numerical simulation) of the lattice’s mechanical performance. Although experimental and numerical analysis of an AM lattice’s bulk structure, unit cell and struts have been performed, there exists almost no research data on the mechanical response of the individual as-manufactured lattice node elements. Here we propose a methodology that, for the first time, allows non-destructive quantification of the mechanical response of node elements within an as-manufactured lattice structure. A custom-developed tool is used to extract and classify each individual node geometry from micro-computed tomography scans of an AM fabricated lattice. Voxel-based finite element meshes are generated for numerical simulation and the mechanical response distribution is compared to that of the idealised computer-aided design model. The method demonstrates compatibility with Uncertainty Quantification methods that provide opportunities for efficient prediction of a population of nodal responses from sampled data. Overall, the non-destructive and automated nature of the node extraction and response evaluation is promising for its application in qualification and certification of additively manufactured lattice structures.

36 MATERIALS SCIENCE↗

Hierarchical Bayesian estimation for adsorption isotherm parameter determination

Estimation of isotherm model parameters from experimental data is necessary in adsorption process modeling. To facilitate isotherm modeling, databases that store experimental data exist. Nevertheless, data inconsistency among different researchers must be resolved to find a single set of isotherm parameters from multiple data sets. Herein, we propose a hierarchical Bayesian estimation method to quantify the discrepancy by a multiplicative factor while simultaneously obtaining the probability distributions of a single set of isotherm parameters. This approach also allows us to identify outliers, which are data sets that are not in agreement with other sets. The proposed approach is demonstrated for the case of CO 2 adsorption in the metal-organic framework UiO-66.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine Learning-Driven Solvent Screening for Biobased 2,3-Butanediol Extraction

Biobased 2,3-butanediol (2,3-BDO) is a valuable biomass-derived chemical due to its versatility in being transformed into a wide variety of products. However, the separation and purification of 2,3-BDO from fermentation broth remain a significant challenge owing to its high boiling point and hydrophilic nature. Herein, we developed a machine learning (ML)-based screening workflow that uses molecular calculations as training data and requires only a small number of experimental measurements for validation to identify alternative solvent candidates for the liquid–liquid extraction (LLE) of 2,3-BDO from aqueous solution. In particular, 130 density functional theory (DFT) calculations with the implicit solvation method not only built a correlation between the computational partition coefficient and the experimental distribution coefficient of 2,3-BDO but also parameterized an Extra-Trees ML model to screen the distribution coefficient for a wider range of 6717 organic solvents. The experimental measurements of only 24 solvents were needed to validate the computational results. A list of 50 prioritized solvents was proposed for 2,3-BDO LLE, and seven additional experimental measurements were conducted to further verify our selected solvents. The impact of the extraction temperature and solvent-to-feed ratio was also investigated for selected solvents in experiments. Furthermore, this work suggested alternative solvents for 2,3-BDO LLE and proposed a versatile workflow that requires fewer experiments and can be applied to a broader range of LLE studies.

Extraction↗

Nanoscale Compositional Mapping of Commercial LiNi 0.8 Co 0.15 Al 0.05 O 2 Cathodes Using Atom Probe Tomography

Nickel-rich cathodes provide improved specific capacity that lead to higher gravimetric energy density, critical for electric vehicles. However, poor long-term capacity retention at elevated temperatures/high C-rates (the rate of charge and discharge on a battery) stem from material issues: surface phase changes, corrosive side reactions with the electrolyte, ion dissolution and propagation of cracks. Introducing dopants, developing nanoscale surface coatings and graded core-shell structures have all improved the electrochemical performance of nickel-rich cathodes. However, a material level understanding on the effect of Li composition and distribution in Ni-rich cathodes is limited, due to a lack of characterization methods available that can directly image Li at the nanoscale. Hence, it is critical to establish methods such as atom probe tomography (APT), having both nanometer scale spatial resolution and high compositional sensitivity to quantitatively analyze battery cathodes. To fully realize its potential as a method for quantitative compositional analysis of commercial Li-ion batteries, we provide a comprehensive description of the challenges in sample preparation and analyze the dependency of the analysis parameters, specifically laser pulse energy on the measured stoichiometry of elements in a high Ni content cathode material; LiNi 0.8 Co 0.15 Al 0.05 O 2 (NCA). In this work, our findings show the stoichiometry variations cannot be explained by charge state ratios or Ga implantation damage alone during FIB preparation, indicating that additional factors such as crystallographic orientation may need to be considered to achieve quantitative nanoscale compositional analysis of such battery cathodes using APT.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantitative Imaging of Cobalt Phthalocyanine Distribution on Carbon Nanotubes: A Deep Learning Approach to Catalyst Characterization

Electrochemical reduction of carbon dioxide (CO 2 ) offers a pathway to valuable products, with catalysts playing a crucial role. This study investigates the distribution of cobalt tetraaminophthalocyanine (CoPc-NH 2 ) immobilized on carbon nanotubes (CNTs), utilizing high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) to characterize CoPc-NH 2 distribution. A challenge in the quantitative HAADF-STEM analysis is the introduction of bias from manual Co atom identification. To address this, we developed and trained a convolutional neural network (CNN) using a data set generated from images of CoPc-NH 2 /CNT samples with varying Co loadings. The CNN, implemented in TensorFlow and Keras, facilitated Co atom detections. Analysis of the CNN-generated data confirmed a correlation between Co loading and surface density, consistent with findings from UV–vis spectroscopy. Furthermore, the application of Ripley’s L(d) function highlighted the presence of slight Co atom clustering. Furthermore, this work demonstrates the utility of the combined HAADF-STEM and CNN approach for providing spatially resolved information about catalyst distribution on nonplanar supports, revealing structural details that are typically lost through other characterization methods.

HAADF-STEM↗

Mechanochemically Assisted Synthesis of High-Entropy Layer-Structured Dittmarite Analogues

High-entropy solid-solution materials, especially layered ones incorporating five or more near-equimolar components into single-phase crystal structures, may spark functional synergism toward the electrochemistry area because of their unique antisite disordering structures and the synergistic effect of multiple active sites. Herein, high-entropy dittmarite analogues (HEDAs) were synthesized via a mechanochemistry-assisted hydrothermal method. Furthermore, the as-prepared HEDAs have single dittmarite phases with five homogeneously distributed metal elements, exhibiting enhanced activities in oxygen evolution catalysis compared to the single metal counterparts.

36 MATERIALS SCIENCE↗

Fast wide-field upconversion luminescence lifetime thermometry enabled by single-shot compressed ultrahigh-speed imaging

Photoluminescence lifetime imaging of upconverting nanoparticles is increasingly featured in recent progress in optical thermometry. Despite remarkable advances in photoluminescent temperature indicators, existing optical instruments lack the ability of wide-field photoluminescence lifetime imaging in real time, thus falling short in dynamic temperature mapping. Here, we report video-rate upconversion temperature sensing in wide field using single-shot photoluminescence lifetime imaging thermometry (SPLIT). Developed from a compressed-sensing ultrahigh-speed imaging paradigm, SPLIT first records wide-field luminescence intensity decay compressively in two views in a single exposure. Then, an algorithm, built upon the plug-and-play alternating direction method of multipliers, is used to reconstruct the video, from which the extracted lifetime distribution is converted to a temperature map. Using the core/shell NaGdF 4 :Er 3+ ,Yb 3+ /NaGdF 4 upconverting nanoparticles as the lifetime-based temperature indicators, we apply SPLIT in longitudinal wide-field temperature monitoring beneath a thin scattering medium. SPLIT also enables video-rate temperature mapping of a moving biological sample at single-cell resolution.

47 OTHER INSTRUMENTATION↗

Isolating solvent–solute hydrogen bonding interactions via 2D IR solvation shell spectroscopy

The solvation shell around a solute is a fundamental feature of liquid-phase solutions, determining the behavior and properties of both the solute and the overall solution. Direct experimental measurements of the solvation shell properties are challenging due to the strong signals generated from the bulk solvent, which overwhelm the small contribution of the solvation shell. Here, we use ultrafast two dimensional infrared (2D IR) spectroscopy and intermolecular cross-peaks to isolate the IR absorption spectrum of methanol molecules in the solvation shell surrounding the solute N-methylacetamide. We demonstrate that the intermolecular coupling between the solvent and solute vibrations is indirectly mediated by a low-frequency hydrogen-bonding mode, suggesting an important mechanism for anharmonic coupling induced by hydrogen bonds. From the relative frequency shifts and cross-peak anisotropy, we find that methanol molecules surrounding N-methylacetamide form stronger and distinctly oriented hydrogen bonds than those in the bulk solvent. Here, we also compare these results with the solvent spectra of the solute N,N-dimethylacetamide to investigate how solute structural changes alter the solvation shell and the contribution of N–H hydrogen bond donation. Our results are supported by molecular dynamics simulations, which provide detailed insights into the hydrogen-bonding distributions. Through these results, we demonstrate 2D solvation shell spectroscopy to be a valuable method for investigating solvation structures and dynamics without interference from the bulk solvent.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Impossibility of obtaining time-independent, three-dimensional, spherically symmetric densities of confined systems of relativistically moving constituents

The quantum-mechanical definition of probability, the uncertainty principle, and Poincaré invariance provide strong basic restrictions on the ability to define spatial densities associated with form factors describing the properties of confined systems of relativistically moving constituents. Despite this, many papers ignore one or more of these restrictions. Here I show how to obtain time-independent , two-dimensional densities that are consistent with the stated restrictions. This is done using the light-front, infinite momentum frame formalism. Two-dimensional density interpretations of the axial-vector form factor and all three gravitational form factors is obtained. The resulting mass radius is smaller than the charge radius. Additionally, an expression of a two-dimensional mass density related to the trace of the energy momentum tensor is obtained. I also show that all known methods for finding three-dimensional densities—using the Breit frame, Abel transformations, Wigner distributions, and spherically symmetric wave packets with vanishing spatial extent—violate the basic restrictions in different ways. Furthermore, the use of the latter leads to densities that vanish almost everywhere in space as time increases from an initial value.

form factors↗

Halo effective field theory analysis of one-neutron knockout reactions of Be 11 and C 15

Background: One-nucleon knockout reactions provide insightful information on the single-particle structure of nuclei. When applied to one-neutron halo nuclei, they are purely peripheral, suggesting that they could be properly modeled by describing the projectile within a halo effective field theory (halo-EFT). Purpose: We reanalyze the one-neutron knockout measurements of 11 Be and 15 C —both one-neutron halo nuclei—on beryllium at about 60 MeV/nucleon. We consider halo-EFT descriptions of these nuclei which already provide excellent agreement with breakup and transfer data. Method: Here we include a halo-EFT description of the projectile within an eikonal-based model of the reaction and compare its outcome to existing data. Results: Excellent agreement with experiment is found for both nuclei. The asymptotic normalization coefficients inferred from this comparison confirm predictions from ab initio nuclear-structure calculations and values deduced from transfer data. Conclusions: Halo-EFT can be reliably used to analyze one-neutron knockout reactions measured for halo nuclei and test predictions from state-of-the-art nuclear structure models on these experimental data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Constraints on dark matter from dynamical heating of stars in ultrafaint dwarfs. II. Substructure and the primordial power spectrum

There is a large and growing interest in observations of small-scale structure in dark matter. We propose a new way to probe dark matter structures in the ∼ 10 – 10 8 M ⊙ range. This allows us to constrain the primordial power spectrum over shorter distances scales than possible with direct observations from the CMB. For k in the range ∼ 10 – 1000 Mpc − 1 our constraints on the power spectrum are orders of magnitude stronger than previous bounds. We also set some of the strongest constraints on dark matter isocurvature perturbations. Our method relies on the heating effect such dark matter substructures would have on the distribution of stars in an ultrafaint dwarf galaxy. Many models of inflation produce enhanced power at these short distance scales and can thus be constrained by our observation. Further, many dark matter models such as axion dark matter, self-interacting dark matter and dissipative dark matter, produce dense structures which could be constrained this way. Published by the American Physical Society 2024

Graham, Peter W. (ORCID:0000000216001601)↗