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At least 559 records · Page 31

Pore2Chip: All-in-one python tool for soil microstructure analysis and micromodel design

The Pore2Chip Python package is designed to create 2D micromodels using extracted data from 3D X-ray computed tomography (XCT) images. This package helps analyze soil structure and function, allowing for the investigation of hydro-biogeochemical processes that impact mineral extraction and reactivity, oxygen concentrations, and nutrient availability in disturbed or managed soils. Key metrics encompass pore size distributions, pore throat size distributions, and connectivity (pore coordination numbers). The final output is a 2D scalable SVG design representing a core or aggregate. Designs can be fabricated with methods such as laser etching, 3D printing, and photolithography.

lab-on-chip↗

Full 3D Kinetic Modeling and Quantification of Positive Streamer Evolution in an Azimuthally Swept Pin-to-Plane Wedge Geometry

Cathode-directed streamer evolution in near atmospheric air is modeled in 3D pin-to-plane geometries using a 3D kinetic Particle-In-Cell (PIC) code that simulates particle-particle collisions via the Direct Simulation Monte Carlo (DSMC) method. Due to the computational challenges associated with a complete 360° volumetric domain, a practical alternative was achieved using a wedge domain and a range of azimuthal angles was explored (5°, 15°, 30°, and 45°) to study possible effects on the streamer growth and propagation due to the finite wedge angle. A DC voltage of 6 kV is administered to a hemispherical anode of radius 100 μm, with a planar cathode held at ground potential, generating an over-volted state with an electric field of 4 MV/m across a 1500 μm gap. The domain is seeded with an initial ion and electron density of 10 18 m -3 at 1 eV temperature confined to a spherical region of radius 100 μm centered at the tip of the anode. The air chemistry model [1] includes standard Townsend breakdown mechanisms (electron-neutral elastic, excitation, ionization, attachment, and detachment collision chemistry and secondary electron emission) as well as streamer mechanisms (photoionization and ion-neutral collisions) via tracking excited state neutrals which can then either quench via collisions or spontaneously emit a photon based on specific Einstein-A coefficients [2, 3]. In this work, positive streamer dynamics are formally quantified for each wedge angle in terms of electron velocity and density as temporal functions of coordinates r, Φ, and z. Applying a random plasma seed for each simulation, particles of interest are tracked with near femtosecond temporal resolution out to 1.4 ns and spatially binned. This process is repeated six times and results are averaged. Prior 2D studies have shown that the reduced electric field, E/n, can significantly impact streamer evolution [4]. We extend the analysis to 3D wedge geometries, to limit computational costs, and examine the wedge angle’s effect on streamer branching, propagation, and velocity. Results indicate that the smallest wedge angle that produced an acceptably converged solution is 30°. The potential effects that a mesh, when under-resolved with respect to the Debye length, can impart on streamer dynamics and numerical heating were not investigated, and we explicitly state here that the smallest cell size was approximately 10 times the minimum λ D in the streamer channel at late times. This constraint on cell size was the result of computational limitations on total mesh count.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

SigTime: Learning and Visually Explaining Time Series Signatures

Understanding and distinguishing temporal patterns in time series data is essential for scientific discovery and decision-making. For example, in biomedical research, uncovering meaningful patterns in physiological signals can improve diagnosis, risk assessment, and patient outcomes. However, existing methods for time series pattern discovery face major challenges, including high computational complexity, limited interpretability, and difficulty in capturing meaningful temporal structures. Here, to address these gaps, we introduce a novel learning framework that jointly trains two Transformer models using complementary time series representations: shapelet-based representations to capture localized temporal structures and traditional feature engineering to encode statistical properties. The learned shapelets serve as interpretable signatures that differentiate time series across classification labels. Additionally, we develop a visual analytics system—SigTime—with coordinated views to facilitate exploration of time series signatures from multiple perspectives, aiding in useful insights generation. We quantitatively evaluate our learning framework on eight publicly available datasets and one proprietary clinical dataset. Additionally, we demonstrate the effectiveness of our system through two usage scenarios along with the domain experts: one involving public ECG data and the other focused on preterm labor analysis.

97 MATHEMATICS AND COMPUTING↗

Direct Observation of Alternating Octahedral and Prismatic Sodium Layers in O3-Type Transition Metal Oxides

The oxygen stacking of O3-type layered sodium transition metal oxides (O3-NaTMO 2 ) changes dynamically upon topotactic Na extraction and reinsertion. While the phase transition from octahedral to prismatic Na coordination that occurs at intermediate desodiation by transition metal slab gliding is well understood, the structural evolution at high desodiation, crucial to achieve high reversible capacity, remains mostly uncharted. In this work, the phase transitions of O3-type layered NaTMO 2 at high voltage are investigated by combining experimental and computational approaches. An OP2-type phase that consists of alternating octahedral and prismatic Na layers is directly observed by in situ X-ray diffraction and high-resolution scanning transmission electron microscopy. The origin of this peculiar phase is explained by atomic interactions involving Jahn–Teller active Fe 4+ and distortion tolerant Ti 4+ that stabilize the local Na environment. Finally, the path-dependent desodiation and resodiation pathways are also rationalized in this material through the different kinetics of the prismatic and octahedral layers, presenting a comprehensive picture about the structural stability of the layered materials upon Na intercalation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Access to Ru(IV)–Ru(V) and Ru(V)–Ru(VI) Redox in Layered Li 7 RuO 6 via Intercalation Reactions

The push to increase the capacity of oxides to store charge as Li-ion battery cathodes has challenged our knowledge of the boundaries of redox chemistry and its relationship to the atomic structure. Layered phases with Ru are now classical models in the quest for refined theories. Current understanding dictates that the highest formal state that can be reached in them is Ru(V), after which activity centered at the oxide anions is triggered. Yet, this picture is challenged by this investigation of the intercalation chemistry of Li 7 RuO 6 . Coupling structural and spectroscopic analysis with computational simulations, we show that Li 7 RuO 6 is capable of highly reversible lithiation to Li 8 RuO 6 through the Ru(V)/Ru(IV) redox couple. Further, Li 7 RuO 6 can also undergo anodic Li deintercalation, showing clear evidence of the reversible formation of Ru(VI) with octahedral coordination, an unusual state that is not accessible in other layered oxides. The results highlight the versatility of the Ru-O bond to undergo distinct redox transitions depending on the specific layered arrangements. They enrich our understanding of redox chemistry in solids while underscoring the need for descriptions of charge compensation that reflect the nuance of covalent interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Accurate Prediction of Voltage of Battery Electrode Materials Using Attention-Based Graph Neural Networks

Performing first-principles calculations to discover electrodes’ properties in the large chemical space is a challenging task. While machine learning (ML) has been applied to effectively accelerate those discoveries, most of the applied methods ignore the materials’ spatial information and only use predefined features: based only on chemical compositions. Here, we propose two attention-based graph convolutional neural network techniques to learn the average voltage of electrodes. Our proposed methods, which combine both atomic composition and atomic coordinates in 3D-space, improve the accuracy in voltage prediction significantly when compared to composition-based ML models. The first model directly learns the chemical reaction of electrodes and metal ions to predict their average voltage, whereas the second model combines electrodes’ ML predicted formation energy (E form ) to compute their average voltage. Our E form -based model demonstrates improved accuracy in transferability from our subset of learned Li ions to Na ions. Moreover, we predicted the theoretical voltage of 10 Na x MPO 4 F (M = Ti, Cr, Fe, Cu, Mn, Co, and Ni) fluorophosphate battery frameworks, which are unavailable in the Material Project database. It could be shown that we can expect average voltages higher than 3.1 V from those Na battery frameworks except from the NaTiPO 4 F and TiPO 4 F pair of electrodes, which offer an average voltage of 1.32 V.

25 ENERGY STORAGE↗

Strategy for distributed controller defence: Leveraging controller roles and control support groups to maintain or regain control in cyber-adversarial power systems

Distributed controllers play a prominent role in electric power grid operation. The coordinated failure or malfunction of these controllers is a serious threat, where the resulting mechanisms and consequences are not yet well-known and planned against. If certain controllers are maliciously compromised by an adversary, they can be manipulated to drive the system to an unsafe state. The authors present a strategy for distributed controller defence (SDCD) for improved grid tolerance under conditions of distributed controller compromise. The work of the authors’ first formalises the roles that distributed controllers play and their control support groups using controllability analysis techniques. With these formally defined roles and groups, the authors then present defence strategies for maintaining or regaining system control during such an attack. A general control response framework is presented here for the compromise or failure of distributed controllers using the remaining, operational set. The SDCD approach is successfully demonstrated with a 7-bus system and the IEEE 118-bus system for single and coordinated distributed controller compromise; the results indicate that SDCD is able to significantly reduce system stress and mitigate compromise consequences.

97 MATHEMATICS AND COMPUTING↗

High-field/high-frequency electron spin resonances of Fe-doped β − Ga 2 O 3 by terahertz generalized ellipsometry: Monoclinic symmetry effects

We demonstrate detection and measurement of electron paramagnetic spin resonances (EPR) of iron defects in β − Ga 2 O 3 utilizing generalized ellipsometry at frequencies between 110 and 170 GHz. The experiments are performed on an Fe-doped single crystal in a free-beam configuration in reflection at 45 ∘ and magnetic fields between 3 and 7 T. In contrast with low-field, low-frequency EPR measurements, we observe all five transitions of the s = 5 / 2 high-spin state Fe 3 + simultaneously. We confirm that ferric Fe 3 + is predominantly found at octahedrally coordinated Ga sites. We obtain the full set of fourth-order monoclinic zero-field splitting parameters for both octahedrally and tetrahedrally coordinated sites by employing measurements at multiple sample azimuth rotations. The capability of high-field EPR allows us to demonstrate that simplified second-order orthorhombic spin Hamiltonians are insufficient, and fourth-order terms as well as consideration of the monoclinic symmetry are needed. These findings are supported by computational approaches based on density-functional theory for second-order and on ligand-field theory for fourth-order parameters of the spin Hamiltonian. Terahertz ellipsometry is a way to measure spin resonances in a cavity-free setup. Its possibility of varying the probe frequency arbitrarily without otherwise changing the experimental setup offers unique means of truly disentangling different components of highly anisotropic spin Hamiltonians. Published by the American Physical Society 2024

Materials Science↗

Structural organization of the spongy mesophyll

Summary Many plant leaves have two layers of photosynthetic tissue: the palisade and spongy mesophyll. Whereas palisade mesophyll consists of tightly packed columnar cells, the structure of spongy mesophyll is not well characterized and often treated as a random assemblage of irregularly shaped cells. Using micro‐computed tomography imaging, topological analysis, and a comparative physiological framework, we examined the structure of the spongy mesophyll in 40 species from 30 genera with laminar leaves and reticulate venation. A spectrum of spongy mesophyll diversity encompassed two dominant phenotypes: first, an ordered, honeycomblike tissue structure that emerged from the spatial coordination of multilobed cells, conforming to the physical principles of Euler’s law; and second, a less‐ordered, isotropic network of cells. Phenotypic variation was associated with transitions in cell size, cell packing density, mesophyll surface‐area‐to‐volume ratio, vein density, and maximum photosynthetic rate. These results show that simple principles may govern the organization and scaling of the spongy mesophyll in many plants and demonstrate the presence of structural patterns associated with leaf function. This improved understanding of mesophyll anatomy provides new opportunities for spatially explicit analyses of leaf development, physiology, and biomechanics.

3D↗

High- and Mid-Fidelity Modeling Comparison for a Floating Marine Turbine System

There is a lack of suitable numerical tools, particularly open-source tools, that can be used for designing and optimizing marine turbine systems. The National Renewable Energy Laboratory has added features to their widely used mid-fidelity wind turbine modeling code, OpenFAST, to enable modeling of axial-flow marine turbines. This necessitated the addition of several physical effects relevant to marine turbines that are neglected for wind turbines. These include buoyancy, added mass and inertial loads, wave-current superposition, and changes to the coordinate systems. This updated version of OpenFAST allows for the modeling of both fixed and floating marine turbines at a speed comparable to real time. While efficient for large sets of load cases and design studies, mid-fidelity codes make simplifying assumptions that may impact their accuracy. High-fidelity computational fluid dynamics (CFD) simulations can capture more flow effects with fewer assumptions and provide detailed body pressure mapping and flow-field information. It is important to compare predictions between mid-fidelity and high-fidelity codes, both to verify the models and to understand the limitations. A floating marine turbine system was modeled both with OpenFAST and with the commercial CFD code STAR-CCM+. The CFD model used a three-dimensional unsteady Reynolds-averaged Navier-Stokes solver for a volume-of-fluid numerical wave and current tank. The blade-resolved simulations used the sliding-interface technique for the spinning rotor and an overset grid to accommodate the rigid-body motion of the floating system. The mooring system was modeled with a custom coupling of the CFD solver with the open-source code MoorDyn. This improves upon the existing quasi-static catenary solver in STAR-CCM+, which lacks seabed contact or line-to-line connections. Simulation results for a floating marine turbine are compared between OpenFAST and CFD, highlighting the capabilities of the mid-fidelity code and identifying the areas where a high-fidelity approach is needed.

CFD↗

An MLCommons Scientific Benchmarks Ontology

Scientific machine learning research spans diverse domains and data modalities, yet existing benchmark efforts remain siloed and lack standardization. This makes novel and transformative applications of machine learning to critical scientific use-cases more fragmented and less clear in pathways to impact. This paper introduces an ontology for scientific benchmarking developed through a unified, community-driven effort that extends the MLCommons ecosystem to cover physics, chemistry, materials science, biology, climate science, and more. Building on prior initiatives such as XAI-BENCH, FastML Science Benchmarks, PDEBench, and the SciMLBench framework, our effort consolidates a large set of disparate benchmarks and frameworks into a single taxonomy of scientific, application, and system-level benchmarks. New benchmarks can be added through an open submission workflow coordinated by the MLCommons Science Working Group and evaluated against a six-category rating rubric that promotes and identifies high-quality benchmarks, enabling stakeholders to select benchmarks that meet their specific needs. The architecture is extensible, supporting future scientific and AI/ML motifs, and we discuss methods for identifying emerging computing patterns for unique scientific workloads. The MLCommons Science Benchmarks Ontology provides a standardized, scalable foundation for reproducible, cross-domain benchmarking in scientific machine learning. A companion webpage for this work has also been developed as the effort evolves: https://mlcommons-science.github.io/benchmark/

Hawks, Ben [Fermilab] (ORCID:0000000157000288)↗

Expanding the Material Search Space for Multivalent Cathodes

Multivalent batteries are an energy storage technology with the potential to surpass lithium-ion batteries; however, their performance have been limited by the low voltages and poor solid-state ionic mobility of available cathodes. A computational screening approach to identify high-performance multivalent intercalation cathodes among materials that do not contain the working ion of interest has been developed, which greatly expands the search space that can be considered for material discovery. This approach has been applied to magnesium cathodes as a proof of concept, and four resulting candidate materials [NASICON V 2 (PO 4 ) 3 , birnessite NaMn 4 O 8 , tavorite MnPO 4 F, and spinel MnO 2 ] are discussed in further detail. In examining the ion migration environment and associated Mg 2+ migration energy in these materials, local energy maxima are found to correspond with pathway positions where Mg 2+ passes through a plane of anion atoms. While previous studies have established the influence of local coordination on multivalent ion mobility, these results suggest that considering both the type of the local bonding environment and available free volume for the mobile ion along its migration pathway can be significant for improving solid-state mobility.

25 ENERGY STORAGE↗

General approaches for shear-correcting coordinate transformations in Bragg coherent diffraction imaging. Part II

X-ray Bragg coherent diffraction imaging (BCDI) has been demonstrated as a powerful 3D microscopy approach for the investigation of sub-micrometre-scale crystalline particles. The approach is based on the measurement of a series of coherent Bragg diffraction intensity patterns that are numerically inverted to retrieve an image of the spatial distribution of the relative phase and amplitude of the Bragg structure factor of the diffracting sample. This 3D information, which is collected through an angular rotation of the sample, is necessarily obtained in a non-orthogonal frame in Fourier space that must be eventually reconciled. To deal with this, the approach currently favored by practitioners (detailed in Part I) is to perform the entire inversion in conjugate non-orthogonal real- and Fourier-space frames, and to transform the 3D sample image into an orthogonal frame as a post-processing step for result analysis. In this article, which is a direct follow-up of Part I, two different transformation strategies are demonstrated, which enable the entire inversion procedure of the measured data set to be performed in an orthogonal frame. The new approaches described here build mathematical and numerical frameworks that apply to the cases of evenly and non-evenly sampled data along the direction of sample rotation ( i.e. the rocking curve). The value of these methods is that they rely on the experimental geometry, and they incorporate significantly more information about that geometry into the design of the phase-retrieval Fourier transformation than the strategy presented in Part I. Finally, two important outcomes are (1) that the resulting sample image is correctly interpreted in a shear-free frame and (2) physically realistic constraints of BCDI phase retrieval that are difficult to implement with current methods are easily incorporated. Computing scripts are also given to aid readers in the implementation of the proposed formalisms.

36 MATERIALS SCIENCE↗

Electrochemical Oxidation in Garnet-Type Solid Electrolyte by Formation of Point Defects

All-solid-state batteries hold greater promise for improving safety and energy density over conventional battery technology employing organic liquid electrolytes. One of the required features of a Li + conducting solid electrolyte is electrochemical stability, attained thermodynamically or kinetically, within the targeted operating voltage and temperature ranges. Therefore, understanding of the oxidative or reductive degradation mechanism is important to allow the design of stable solid electrolyte materials. This work contributes to building an understanding of the oxidative degradation mechanism in lithium solid electrolytes at cell operating conditions. Here, we have focused on resolving the oxidative decomposition mechanism of Al-doped lithium garnet Li 6.28 Al 0.24 La 3 Zr 2 O 12 (LLZO) as a state-of-the-art inorganic ceramic electrolyte. By combining experimental and computational analyses, we show that oxidation of LLZO occurs by simultaneous loss of oxygen and lithium from the structure, resulting in substoichiometric LLZO, at a moderate temperature (80 °C) and a high electrode potential (4.3 V vs Li/Li + ). Based on X-ray absorption and diffraction analyses, we find that the zirconium coordination shells in LLZO contract while the crystal structure experiences positive chemical strain upon electrochemical oxidation. The results from ex situ structural characterization of both the local structure and crystal symmetry are supported by a substoichiometric LLZO with lithium and oxygen vacancies, modeled by density functional theory (DFT) calculations. These chemical and structural changes in LLZO suppress effective lithium-ion conductivity by an order of magnitude. Formation of lithium and oxygen vacancies in LLZO upon electrochemical oxidation is different from prior thermodynamic predictions of phase decomposition of LLZO. The difference here is that the experiments were conducted at near-room temperature, which can hinder the kinetics of phase separation, and thus, the resultant LLZO solid electrolyte is still single-phase but substoichiometric in Li and O. In conclusion, these findings contribute an important degradation mechanism of the electrolyte, relevant for practical operational conditions of solid-state batteries.

36 MATERIALS SCIENCE↗

Complexation of Lanthanides and Heavy Actinides with Aqueous Sulfur-Donating Ligands

The separation of trivalent lanthanides and actinides is challenging because of their similar sizes and charge densities. S-donating extractants have shown significant selectivity for trivalent actinides over lanthanides, with single-stage americium/ lanthanide separation efficiencies for some thiol-based extractants reported at >99.999%. While such separations could transform the nuclear waste management landscape, these systems are often limited by the hydrolytic and radiolytic stability of the extractant. Progress away from thiol-based systems is limited by the poorly understood and complex interactions of these extractants in organic phases, where molecular aggregation and micelle formation obfuscates assessment of the metal–extractant coordination environment. Because S-donating thioethers are generally more resistant to hydrolysis and oxidation and the aqueous phase coordination chemistry is anticipated to lack complications brought on by micelle formation, we have considered three thioethers, 2,2'-thiodiacetic acid (TDA), (2R,5S)- tetrahydrothiophene-2,5-dicarboxylic acid, and 2,5-thiophenedicarboxylic acid (TPA), as possible trivalent actinide selective reagents. Formation constants, extended X-ray absorption fine structure spectroscopy, and computational studies were completed for thioether complexes with a variety of trivalent lanthanides and actinides including Nd, Eu, Tb, Am, Cm, Bk, and Cf. TPA was found to have moderately higher selectivity for the actinides because of its ability to bind actinides in a different manner than lanthanides, but the utility of TPA is limited by poor water solubility and high rigidity. While significant competition with water for the metal center limits the efficacy of aqueous-based thioethers for separations, the characterization of these solution-phase, S-containing lanthanide and actinide complexes is the most comprehensively available in the literature to date. Here, this is due to the breadth of lanthanides and actinides considered as well as the techniques deployed and serves as a platform for the further development of Scontaining reagents for actinide separations. Additionally, this paper reports on the first bond lengths for Cf and Bk with a neutral S donor.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ion-Electron Coupling-Driven Redox Behavior in Metal–Organic Frameworks

Redox-active metal–organic frameworks (MOFs) have long been proposed as electronic transport platforms, yet the microscopic origin of their conductivity remains debated. A theoretical demonstration reveals charge transport in a Zn(pyrazole–naphthalene diimide (NDI)) MOF arising not from delocalized band-like states but from redox hopping between discrete linker sites. Using ab initio molecular dynamics simulations combined with electronic structure analysis, we established a direct link among electron injection, structural reorganization, and transport. Electron accumulation proceeds sequentially and site-selectively from imide and carbonyl groups of the NDI core progressively involving pyrazole N atoms at higher reduction states, through a hierarchy of redox-active sites. In contrast, Zn nodes remain essentially redox-inactive, which confirms their structural role. Density-of-states analysis corroborates a transport regime dominated by linker-centered states with evolving p-character upon reduction, resulting in dynamically reconfigured conduction networks. Real-time trajectories reveal anisotropic linker-to-linker electron transfer modulated by counterion coordination. This cooperative ion–electron regime emerges from potential energy surface collapse into a single low-barrier transition (ΔG ‡ ≈ 45 meV), where ionic and electronic motions evolve adiabatically on the same free-energy landscape. Elucidating redox conductivity in Zn(pyrazole–NDI) MOFs provides a theoretical framework for use in neuromorphic computing and related technologies.

Charge transfer↗

An exact inversion method for extracting orientation ordering by small-angle scattering

Here, we outline a nonparametric inversion strategy for determining the orientation distribution function (ODF) of sheared interacting rods using small-angle scattering techniques. With the presence of direct inter-rod interaction and fluid mechanical forces, the scattering spectra are no longer characterized by the azimuthal symmetry in the coordinates defined by the principal directions of simple shear conditions, which severely compounds the reconstruction of ODFs based on currently available methods developed for dilute systems. Using a real spherical harmonic expansion scheme, the real-space ODFs are uniquely determined from the anisotropic scattering spectra and their numerical accuracy is verified computationally. Our method can be generalized to extract ODFs of uniaxially anisotropic objects under different flow conditions in a properly transformed reference frame with suitable basis vectors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Augmented Kalman filter with a reduced mechanical model to estimate tower loads on a land-based wind turbine: a step towards digital-twin simulations

This article presents an application of the Kalman filtering technique to estimate loads on a wind turbine. The approach combines a mechanical model and a set of measurements to estimate signals that are not available in the measurements, such as wind speed, thrust, tower position, and tower loads. The model is severalfold faster than real time and is intended to be run online, for instance, to evaluate real-time fatigue life consumption of a field turbine using a digital twin, perform condition monitoring, or assess loads for dedicated control strategies. The mechanical model is built using a Rayleigh–Ritz approach and a set of joint coordinates. We present a general method and illustrate it using a 2-degrees-of-freedom (DOF) model of a wind turbine and using rotor speed, generator torque, pitch, and tower-top acceleration as measurement signals. The different components of the model are tested individually. The overall method is evaluated by computing the errors in estimated tower-bottom-equivalent moment from a set of simulations. From this preliminary study, it appears that the tower-bottom-equivalent moment is obtained with about 10 % accuracy. The limitation of the model and the required steps forward are discussed.

17 WIND ENERGY↗