Accurate ZVS Analysis of a Full-Bridge T-Type Resonant Converter for a 20-kW Unfolding-Based AC-DC Topology
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GURUDIWAN, SHUBHANGI↗
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Exploring the Effects of Node Topology, Connectivity, and Metal Identity on the Binding of Nerve Agents and Their Hydrolysis Products in Metal–Organic Frameworks
Recent studies have shown that metal–organic frameworks (MOFs) built from hexanuclear M(IV) oxide cluster nodes are effective catalysts for nerve agent hydrolysis, where the properties of the active sites on the nodes can strongly influence the reaction energetics. The connectivity and metal identity of these M6 nodes can be easily tuned, offering extensive opportunities for computational screening to predict promising new materials. Thus, we used density functional theory (DFT) to examine the effects of node topology, connectivity, and metal identity on the binding energies of multiple nerve agents and their corresponding hydrolysis products. By computing an optimization metric based on the relative binding strengths of key hydrolysis reaction species (water, agent, and bidentate-bound products), we predicted optimal M6 nodes for hydrolyzing specific nerve agent and simulant molecules, where our results are in qualitative agreement with observed experimental trends. This analysis highlighted the notion that no single metal or node topology is optimal for all possible organophosphates, suggesting that MOFs should be selected based on the agent of interest. Using the large amount of data generated from our DFT calculations, we then derived quantitative structure–activity relationship (QSAR) models to help explain the complex trends observed in the binding energies. Through linear regression, we identified the most important descriptors for describing the binding of nerve agents and their hydrolysis products to M6 nodes. These results suggested that both molecular and node properties, including both structural and chemical features, collectively contribute to the binding energetics. By performing a thorough statistical analysis, we showed that our QSAR models are capable of making quantitatively accurate binding energy predictions for nerve agents and their hydrolysis products in a wide variety of M(IV)-MOFs. In conclusion, the insights gained herein can be used to guide future experiments for the synthesis of MOFs with enhanced catalytic activity for organophosphate hydrolysis.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Linear and nonlinear optical responses in the chiral multifold semimetal RhSi
Chiral topological semimetals are materials that break both inversion and mirror symmetries. They host interesting phenomena such as the quantized circular photogalvanic effect (CPGE) and the chiral magnetic effect. In this work, we report a comprehensive theoretical and experimental analysis of the linear and nonlinear optical responses of the chiral topological semimetal RhSi, which is known to host multifold fermions. We show that the characteristic features of the optical conductivity, which display two distinct quasi-linear regimes above and below 0.4 eV, can be linked to excitations of different kinds of multifold fermions. The characteristic features of the CPGE, which displays a sign change at 0.4 eV and a large non-quantized response peak of around 160 μA/V 2 at 0.7 eV, are explained by assuming that the chemical potential crosses a flat hole band at the Brillouin zone center. Our theory predicts that, in order to observe a quantized CPGE in RhSi, it is necessary to increase the chemical potential as well as the quasiparticle lifetime. More broadly, our methodology, especially the development of the broadband terahertz emission spectroscopy, could be widely applied to study photogalvanic effects in noncentrosymmetric materials and in topological insulators in a contact-less way and accelerate the technological development of efficient infrared detectors based on topological semimetals.
Materials Science↗
Level-set topology optimization with PDE generated conformal meshes
This paper presents a level-set topology optimization approach that uses conformal meshes for the analysis of the displacement field. The structure’s boundary is represented by the iso-contour of a level-set field discretized on a fixed background design mesh. The conformal mesh is updated for each design iteration via a PDE based mesh morphing process that identifies the set of facets in the background mesh that are homeomorphic to the boundary and relaxes the homeomorphic mesh to conform to the structure’s boundary and ensure high element quality. The conformal mesh allows for a more accurate computation of the response versus density and some level-set based methods which interpolate material properties using the volume fraction. Numerical examples illustrate the proposed approach by optimizing linear-elastic two- and three-dimensional structures, wherein insight into the performance of the mesh morphing process is provided. The examples also highlight the scalability of the approach.
42 ENGINEERING↗
Leveraging Topological Events in Tracking Graphs for Understanding Particle Diffusion
Abstract Single particle tracking (SPT) of fluorescent molecules provides significant insights into the diffusion and relative motion of tagged proteins and other structures of interest in biology. However, despite the latest advances in high‐resolution microscopy, individual particles are typically not distinguished from clusters of particles. This lack of resolution obscures potential evidence for how merging and splitting of particles affect their diffusion and any implications on the biological environment. The particle tracks are typically decomposed into individual segments at observed merge and split events, and analysis is performed without knowing the true count of particles in the resulting segments. Here, we address the challenges in analyzing particle tracks in the context of cancer biology. In particular, we study the tracks of KRAS protein, which is implicated in nearly 20% of all human cancers, and whose clustering and aggregation have been linked to the signaling pathway leading to uncontrolled cell growth. We present a new analysis approach for particle tracks by representing them as tracking graphs and using topological events – merging and splitting, to disambiguate the tracks. Using this analysis, we infer a lower bound on the count of particles as they cluster and create conditional distributions of diffusion speeds before and after merge and split events. Using thousands of time‐steps of simulated and in‐vitro SPT data, we demonstrate the efficacy of our method, as it offers the biologists a new, detailed look into the relationship between KRAS clustering and diffusion speeds.
McDonald, T.↗
On exact-WKB analysis, resurgent structure, and quantization conditions
There are two well-known approaches to studying nonperturbative aspects of quantum mechanical systems: saddle point analysis of the partition functions in Euclidean path integral formulation and the exact-WKB analysis based on the wave functions in the Schrödinger equation. In this work, based on the quantization conditions obtained from the exact-WKB method, we determine the relations between the two formalism and in particular show how the two Stokes phenomena are connected to each other: the Stokes phenomenon leading to the ambiguous contribution of different sectors of the path integral formulation corresponds to the change of the “topology” of the Stoke curves in the exact-WKB analysis. We also clarify the equivalence of different quantization conditions including Bohr-Sommerfeld, path integral and Gutzwiller’s ones. In particular, by reorganizing the exact quantization condition, we improve Gutzwiller’s analysis in a crucial way by bion contributions (incorporating complex periodic paths) and turn it into an exact result. Furthermore, we argue the novel meaning of quasi-moduli integral and provide a relation between the Maslov index and the intersection number of Lefschetz thimbles.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Magnetic crystalline-symmetry-protected axion electrodynamics and field-tunable unpinned Dirac cones in EuIn 2 As 2
Knowledge of magnetic symmetry is vital for exploiting nontrivial surface states of magnetic topological materials. EuIn 2 As 2 is an excellent example, as it is predicted to have collinear antiferromagnetic order where the magnetic moment direction determines either a topological-crystalline-insulator phase supporting axion electrodynamics or a higher-order-topological-insulator phase with chiral hinge states. Here, we use neutron diffraction, symmetry analysis, and density functional theory results to demonstrate that EuIn 2 As 2 actually exhibits low-symmetry helical antiferromagnetic order which makes it a stoichiometric magnetic topological-crystalline axion insulator protected by the combination of a 180° rotation and time-reversal symmetries: $C_2 × \mathcal{T} =$ 2'. Surfaces protected by 2' are expected to have an exotic gapless Dirac cone which is unpinned to specific crystal momenta. All other surfaces have gapped Dirac cones and exhibit half-integer quantum anomalous Hall conductivity. We predict that the direction of a modest applied magnetic field of $μ_0H ≈$ 1 to 2 T can tune between gapless and gapped surface states.
36 MATERIALS SCIENCE↗
Design of an alumina forming coating for Nb-base refractory alloys
Refractory multi-principal element alloys (RMPEAs) promise to significantly enhance gas turbine engine efficiency, but their poor oxidation performance inhibits their implementation. Alumina-forming bond coat alloys can provide oxidation protection, but discovering suitable chemistries remains a challenge. We employed a design methodology that screens for alumina-formation capability using Al activity and phase constitution predictions from CalPhaD (Thermo-Calc). Alloy down-selection from approximately 7,800 alloys in the Nb-Si-Ti-Al-Hf system was conducted via analysis of calculated thermodynamic properties with number-density topology style maps. This approach is validated by creating and testing the composition Nb 12 Si 23 Ti 24 Al 36 Hf 5 , which forms protective alumina scales up to 1400 °C and resists pesting at 800 °C. Further, the alloy has an average coefficient of thermal expansion of ~10.1 ppm/K, making it well matched to Nb-based refractory alloys. The methodology will be useful for the design of coatings for RMPEAs, enabling their implementation and significant efficiency benefits sooner.
36 MATERIALS SCIENCE↗
Procedures for Assessing the Stability of Proposed Topological Materials
Here, we investigate the stability of MnPb 2 Bi 2 Te 6 (MPBT), which is predicted to be a magnetic topological insulator (TI), using density functional theory calculations. Our analysis includes various measures such as enthalpies of formation, Helmholtz free energies, defect formation energies, and dynamical stability. Our thermodynamic analysis shows that the phonon contribution to the energy gain from finite temperature is estimated to be less than 10 meV/atom, which may not be sufficient to stabilize MPBT at high temperatures, even with the most favorable reactions starting from binaries. While MPBT is generally robust against the formation of various defects, we find that the anti-site defect formation of MnPb is the most likely to occur, with a corresponding energy less than 60 meV. This can be attributed to the significant energy cost from compressive strain at the PbTe layer. Our findings suggest that MPBT is on the brink of stability in terms of thermodynamics and defect formation, underscoring the importance of conducting systematic analyses of the stability of proposed TIs, including MPBT, for their practical utilization. This study offers valuable insights into the design and synthesis of desirable magnetic TI materials with robust stabilities.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Magnetic structure and spin dynamics of the quasi-two-dimensional antiferromagnet Zn-doped copper pyrovanadate
We report magnetic properties of the antiferromagnet Zn x Cu 2-x V 2 O 7 (ZnCVO) with x ≈ 0.06 have been thoroughly investigated on powder and single-crystal samples. The crystal structure determination using powder x-ray and neutron diffraction confirms that our ZnCVO samples are isostructural with β-Cu 2 V 2 O 7 (β-CVO) with a small deviation in the lattice parameters. Macroscopic magnetic property measurements also confirm the similarity between the two compounds. The Cu 2+ spins were found to align along the crystallographic c axis, antiparallel to their nearest neighbors connected by the leading exchange interaction J 1 . Spin dynamics reveals a typical symmetric spin-wave dispersion with strong interactions in the bc plane and weak interplane coupling. The exchange interaction analysis indicates that the spin network of ZnCVO is topologically consistent with the previous DFT prediction but the values of leading exchange interactions are contradictory. Furthermore, rather than the predicted 2D honeycomb structure, the spin network in ZnCVO could be better described by the anisotropic 2D spin network composed of J 1 , J 5 , and J 6 interactions, four bonds per one spin site, coupled by weak interplane interactions.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Neutrino-nucleus CC 0 π cross-section tuning in GENIE v3
This article summarizes the state of the art of v μ and $\bar{v}_μ$ CC0π cross-section measurements on carbon and argon and discusses the relevant nuclear models, parametrizations and uncertainties in GENIE v3. The CC0π event topology is common in experiments at a few-GeV energy range. Although its main contribution comes from quasi-elastic interactions, this topology is still not well understood. The GENIE global analysis framework is exploited to analyze CC0π datasets from MiniBooNE, T2K and MINERvA. A partial tune for each experiment is performed, providing a common base for the discussion of tensions between datasets. The results offer an improved description of nuclear CC0π datasets as well as data-driven uncertainties for each experiment. This work is a step towards a GENIE global tune that improves our understanding of neutrino interactions on nuclei. It follows from earlier GENIE work on the analysis of neutrino scattering datasets on hydrogen and deuterium.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Uncovering Structure–Conductivity Relationships in Anion Exchange Membranes (AEMs) Using Interpretable Machine Learning
Anion exchange membranes (AEMs) play a vital role in the performance of water electrolyzers and fuel cells, yet their discovery and optimization remain challenging due to the complexity of structure–property relationships. In this study, we introduce a machine learning framework that leverages conditional graph neural networks (cGNNs) and descriptor-based models and a hybrid graph neural network (HGARE) to predict and interpret ionic conductivity. The descriptor-based pipeline employs principal component analysis (PCA), ablation, and SHAP analysis to identify factors governing anion conductivity, revealing electronic, topological, and compositional descriptors as key contributors. Beyond prediction, dimensionality reduction and clustering are performed by employing t-SNE and KMeans as well as SOM, which reveal distinct membranes clusters, some of which were enriched with high anion conductivity. Among graph-based approaches, the graph convolutional (GCN) achieved strong predictive performance, while the Hybrid Graph Autoencoder-Regressor Ensemble (HGARE) achieved the highest accuracy. Additionally, atom-level saliency maps from GCN provide spatial explanations for conductive behavior, revealing the importance of polarizable and flexible regions. This work contributes to the accelerated and data-driven design of high-performance AEMs.
Naghshnejad, Pegah [Department of Chemical Enginee↗
Creating a system for the geological exploitation of satellite images: Automatic mapping and geophysical data comparison
A method is presented for integrating satellite images into a geophysical data interpretation system. Aspects of the method include: an attempt to automatically interpret images by structural, mainly topological, methods for the mapping of geological contours; an analysis of the position relation of the contours gives a skeleton stratigraphy (order of succession); and a system combining some of the extracted elements with geographic data to make an objective search for an interpretation hypothesis. Some examples are presented.
Braconne, S.↗
Formulation and application of Russell's method
It is shown that the numerical technique of Russell's momentum approach can be derived by using Hamilton's principle and Vance's numerical scheme. It results in a set of first order differnce equations for solving the angular velocities. The numerical examples show that the method is reliable. The algorithm is modified next to perform the analysis of N-body systems with closed loop topology. To increase the formulation flexibility, the equations of motion are represented by using Cartesian coordinates and Lagrange multipliers. The algorithm consists of two parts, Vance's scheme and an unconstrained minimization. The Vance's scheme is used to find the angular velocities, and the unconstrained minimization is applied to provide the correct angular displacements. The proposed scheme is further extended to find the design sensitivity of an N-body system with closed loop configuration, and to carry out the design optimization as well. The numerical example of a small-scaled mechanical system is presented to verify the proposed formulation.
Hou, J. W.↗
Comparison Between Path Lengths Traveled by Solar Electrons and Ions in Ground-Level Enhancement Events
We have examined the Wind/3DP/SST electron and Wind/EPACT/LEMT ion data to investigate the path length difference between solar electrons and ions in the ground-level enhancement (GLE) events in solar cycle 23. Assuming that the onset time of metric type II or decameter-hectometric (DH) type III radio bursts is the solar release time of non-relativistic electrons, we have found that within an error range of plus or minus 10% the deduced path length of low-energy (approximately 27 keV) electrons from their release site near the Sun to the 1 AU observer is consistent with the ion path length deduced by Reames from the onset time analysis. In addition, the solar longitude distribution and IMF topology of the GLE events examined are in favor of the coronal mass ejection-driven shock acceleration origin of observed non-relativistic electrons.We have also found an increase of electron path lengths with increasing electron energies. The increasing rate of path lengths is correlated with the pitch angle distribution (PAD) of peak electron intensities locally measured, with a higher rate corresponding to a broader PAD. The correlation indicates that the path length enhancement is due to the interplanetary scattering experienced by first arriving electrons. The observed path length consistency implies that the maximum stable time of magnetic flux tubes, along which particles transport, could reach 4.8 hr.
electrons↗
Design of an Electric Propulsion System for SCEPTOR
The rise of electric propulsion systems has pushed aircraft designers towards new and potentially transformative concepts. As part of this effort, NASA is leading the SCEPTOR program which aims at designing a fully electric distributed propulsion general aviation aircraft. This article highlights critical aspects of the design of SCEPTOR's propulsion system conceived at Joby Aviation in partnership with NASA, including motor electromagnetic design and optimization as well as cooling system integration. The motor is designed with a finite element based multi-objective optimization approach. This provides insight into important design tradeoffs such as mass versus efficiency, and enables a detailed quantitative comparison between different motor topologies. Secondly, a complete design and Computational Fluid Dynamics analysis of the air breathing cooling system is presented. The cooling system is fully integrated into the nacelle, contains little to no moving parts and only incurs a small drag penalty. Several concepts are considered and compared over a range of operating conditions. The study presents trade-offs between various parameters such as cooling efficiency, drag, mechanical simplicity and robustness.
SCEPTOR↗
Short-range magnetic order and planar anisotropy in the topological ferrimagnet Mn 3 Si 2 Te 6
Mn 3 Si 2 Te 6 is a ferrimagnetic topological nodal-line semiconductor that exhibits unconventional colossal magnetoresistance behavior, with short-range spin fluctuations being potentially intimately linked to the emergent properties. Here we determine the short-range magnetic order and anisotropy through total neutron scattering and polarized neutron powder diffraction measurements on polycrystalline Mn 3 Si 2 Te 6 . Strong in-plane anisotropy is quantified on the Mn ions through extraction of the local site susceptibility tensor. Here, the real-space local spin structure is determined through the application of magnetic pair distribution function analysis covering a wide temperature range. Short-range order over a locally frustrated trimer of three nearest neighbors is found to exist well above the long-range ferrimagnetic transition.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Double-differential Measurements of Mesonless Charged-current Muon Neutrino Interactions on Argon with Final-State Protons using the MicroBooNE Detector
This note reports the first double-differential measurements of charged-current $ν_µ$ scattering on argon leading to final states containing zero mesons and one or more protons. This event topology (hereafter abbreviated as CC0$πNp$) is the most common at the neutrino energies typically produced by the Fermilab Booster Neutrino Beam. A detailed understanding of neutrino-argon scattering in the CC0$πNp$ channel is therefore crucial for the success of the precision neutrino oscillation analyses planned for the Short-Baseline Neutrino (SBN) program. This remains true for the upcoming Deep Underground Neutrino Experiment (DUNE), but the higher mean neutrino energy used there will ensure that more inelastic reaction modes, such as single pion production, will also play a major role. The analysis described in this note builds on a previous MicroBooNE study of the CC0$πNp$ channel which obtained the first single-differential cross-section measurements on an argon target. Since that foundational work, significant improvements have been made to MicroBooNE’s simulation software, event reconstruction algorithms, and procedure for calculating systematic uncertainties. When combined with a larger dataset (corresponding to a beam exposure of 6.79 × 10 20 protons-on-target versus 1.60 × 10 20 in Ref. [3]), these enhancements allow the important CC0$πNp$ channel to be studied in more detail. This note begins with a description of the data and simulation samples used as input to the analysis. Section 3 then defines the CC0$πNp$ signal event topology, and Section 4 describes a set of selection criteria designed to identify these events in MicroBooNE data. Binning schemes are then defined in Section 5 for two double-differential measurements of event rates. The first of these considers the momentum and scattering cosine of the outgoing muon, while the second reports the same observables for the leading proton, i.e., the final-state proton with the largest momentum. After a discussion of systematic uncertainties in Section 6, the note concludes by comparing the predictions of MicroBooNE Monte Carlo (MC) simulations to the measured double-differential distributions. These results will form the basis for a future extraction of flux-averaged double-differential CC0$πNp$ cross sections that will be immediately comparable to the theoretical predictions of multiple neutrino event generators. The selection described herein may also be used to study various other observables in CC0$πNp$ events, including those which are sensitive to correlations between leptonic and hadronic kinematics in the final state.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗