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Mesh-based multiphysics coupling acceleration for fusion neutronics through clustering for fusion blanket applications

Accurate modeling of particle transport within fusion blankets is essential for predicting performance metrics such as heat deposition and the tritium breeding ratio (TBR). However, high-fidelity coupling of thermal fluids from computational fluid dynamics (CFD) to neutronics simulations often incurs significant computational costs due to the complexity of surface intersection calculations in Monte Carlo codes. This paper presents an accelerated multiphysics coupling method for neutronics that utilizes hierarchical agglomerative clustering to map complex material property distributions to a neutronics model. Implemented within the fusion reactor design and assessment (FREDA) framework, the method leverages existing Python packages to automate the creation of clustered geometries for OpenMC. The approach is demonstrated on a sector model of an ARC-class tokamak with an immersion molten salt blanket, and an simple geometry with varying isotopic concentrations. Results show that the clustering method significantly reduces computational burden without compromising fidelity, providing a foundation for agile iteration of neutronics simulations involving multiple coupled material properties.

Bae, Jin Whan [ORNL] (ORCID:0000000326548907)

Improving Ionic Conformality Across Polymer Electrolyte|Electrode Interfaces

Maintaining uniform ionic transport at electrode|electrolyte interfaces, i.e., ionic conformality, remains challenging in polymer electrolyte (PE)-based solid-state batteries. Morphological conformality does not necessarily imply ionic conformality. In PEs, which typically consist of a mechanically supporting component and distinct ionically conductive components, the rearrangement or depletion of mobile ion-conductive domains at interfaces can disrupt ionic transport pathways. Such localized ionic depletion contributes to interfacial instability and capacity degradation in high-voltage lithium-metal batteries. Herein, an electrolyte design approach aimed at minimizing interfacial heterogeneities is demonstrated through compositional adjustments, characterized by spatially resolved structural and chemical X-ray techniques and NMR diffusometry to elucidate ion transport dynamics. This approach improves ionic conformality at electrode interfaces, enhancing cycling stability in Li||LiNi 0.8 Co 0.1 Mn 0.1 O 2 (NMC811) coin and pouch cells cycled at high voltages. These results contribute to understanding interfacial behaviors in multiphase PEs and inform strategies for improving stability across solid-state battery interfaces.

36 MATERIALS SCIENCE

HydraGNN_Predictive_GFM_2026 - Ensemble of predictive graph foundation models for atomistic materials modeling

This release contains data and parameters of HydraGNN-based graph foundation models trained as a result of the work published in the pre-print "Exascale Multi-Task Graph Foundation Models for Imbalanced, Multi-Fidelity Atomistic Data" by M. Lupo Pasini et al. (https://arxiv.org/abs/2604.15380). We jointly train on 16 open first-principles datasets (544+ million structures covering 85+ elements) using a multi-task architecture with per-dataset heads and a scalable ADIOS2/DDStore data pipeline. On Frontier, we execute six large-scale DeepHyper hyperparameter optimization campaigns in FP64 and promote the top-performing message-passing models to sustained 2,048-node training, yielding a PaiNN-based lead model. The version of HydraGNN used to generate the outputs provided in this release is HydraGNN v5.0 (https://github.com/ORNL/HydraGNN/releases/tag/v5.0) The list of datasets used for the training of the graph foundation model is the following: 1) Alexandria [1] 2) ANI1x [2] 3) MPTrj [3] 4) Open Catalyst 2020 (OC20) [4] 5) Open Catalyst 2022 (OC22) [5] 6) Open Catalyst 2025 (OC25) [6] 7) Open Direct ir Capture 2023 (ODAC23) [7] 8) Open Materials 2024 (OMat24) [8] 9) Open Molecules 2025 (OMol25) [9] 10) OMol25-neutral (subset of OMol25 that contains only molecules with zero total charge) 11) OMol25-non-neutral (subset of OMol25 that contains only molecules with non-zero total charge) 12) Open Polymers 2026 (OPoly2026) [10] 13) Nabla2DFT [11] 14) QCML [12] 15) QM7X [reference 13] 16) transition1x [14] Dataset references: [1] J. Schmidt et al., “A dataset of 175k stable and metastable materials calculated with the PBEsol and SCAN functionals,” Scientific Data, vol. 9, p. 64, 2022. [2] J. S. Smith et al., “The ANI-1ccx and ANI-1x data sets, coupled-cluster and density functional theory properties for molecules,” Scientific Data, vol. 7, p. 134, 2020. [Online]. Available: https: //www.nature.com/articles/s41597-020-0473-z [3] A. Jain et al., “Commentary: The Materials Project: A materials genome approach to accelerating materials innovation,” APL Materials, vol. 1, no. 1, p. 011002, 07 2013. [Online]. Available: https://doi.org/10.1063/1.4812323 [4] L. Chanussot et al., “Open catalyst 2020 (oc20) dataset and community challenges,” ACS Catalysis, vol. 11, no. 10, pp. 6059–6072, 2021. [Online]. Available: https://doi.org/10.1021/acscatal.0c04525 [5] K. Tran et al., “Open catalyst 2022 (oc22) dataset and challenges for oxidation electrocatalysts,” ACS Catalysis, vol. 13, no. 5, pp. 3066–3084, 2023. [Online]. Available: https://doi.org/10.1021/acscatal.2c05426 [6] S. J. Sahoo et al., “The open catalyst 2025 (oc25) dataset and models for solid-liquid interfaces,” arXiv preprint arXiv:2509.17862, 2025. [Online]. Available: https://arxiv.org/abs/2509.17862 [7] A. Sriram et al., “The open DAC 2023 dataset and challenges for sorbent discovery in direct air capture,” ACS Central Science, vol. 10, no. 5, pp. 923–941, 2024. [8] L. Barroso-Luque et al., “Open materials 2024 (omat24) inorganic materials dataset and models,” 2024. [Online]. Available: https://arxiv.org/abs/2410.12771 [9] D. S. Levine et al., “The open molecules 2025 (OMol25) dataset, evaluations, and models,” 2025. [Online]. Available: https://arxiv.org/abs/2505.08762 [10] D. S. Levine et al., The open polymers 2026 (OPoly26) dataset and evaluations,” arXiv preprint arXiv:2512.23117, 2025. [Online]. Available: https://arxiv.org/abs/2512.23117 [11] K. Khrabrov et al., “Nabla2dft: A universal quantum chemistry dataset of drug-like molecules and a benchmark for neural network potentials,” in NeurIPS 2024 Datasets and Benchmarks Track, 2024. [Online]. Available: https://openreview.net/forum?id=ElUrNM9U8c [12] S. Ganscha et al., “The QCML dataset, quantum chemistry reference data from 33.5M DFT and 14.7B semi-empirical calculations,” Scientific Data, vol. 12, p. 406, 2025. [13] J. Hoja et al., “QM7-X, a comprehensive dataset of quantum-mechanical properties spanning the chemical space of small organic molecules,” Scientific Data, vol. 8, p. 43, 2021. [Online]. Available: https://www.nature.com/articles/s41597-021-00812-2 [14] M. Schreiner et al., “Transition1x - a dataset for building generalizable reactive machine learning potentials,” Scientific Data, vol. 9, p. 779, 2022. The folder "datasets_ADIOS2_format" contains the set of pre-processed datasets in Adaptable I/O System (ADIOS) format (https://www.exascaleproject.org/research-project/adios/) that have been used for the development and training of GFMs in this work. The "datasets_ADIOS2_format" directory contains 2 sub-directories, one for the version "v1" of the datasets and one for the version "v2" of the datasets. The version "v1" of the datasets provides values of the total energy as they are extracted from the original data as it was released by the respective institutions. The version "v2" of the datasets provides values of the energy that have been realigned. The realignment was performed by training a linear regression model that predicts the total energy as a function of the chemical composition of the atomistic structure, and then subtract such prediction from the original value of the total energy. Both folders "v1" and "v2" contain 16 sub-directories, each corresponding to an ADIOS2-formatted dataset The folder "DeepHyper-results" contains the configurational files and model's parameters for all the 186 HPO trials that were successfully completed by the scalable hyperparameter optimization (HPO) runs on Frontier. The content of the folder "DeepHyper-results" I structured as follows: 1) task-list.txt: list of mpnn name, jobid, and deephyper task id 2) gfm_${MPNN}_${JOBID}_0.${TASKID}: run directory with checkpoint files 3) gfm_${MPNN}: deephyper summary directory (*.csv) for each specific MPNN type 4) deephyper-experiment-${JOBID}: output and error logs for each job The file "deephyper-sorted.csv" contains the details of each HydraGNN model built and tested by HPO, obtained by merging the (*.csv) filed from each HPO run executed. Out of all the HPO trials, we selected 10 to continue the training of the respective HydraGNN models. Due to limited computational budget available in the LRN070 allocation we could not complete the training till convergence for all these 10 selected models. The folder "models" contains multiple sub-folders, one per each HydraGNN model trained. Each model sub-folder contains the parameters of each HydraGNN model, with multiple checkpoint-restarts. The list of sub-folders are as follows: 1) multidataset_hpo-BEST1-fp64 2) multidataset_hpo-BEST2-fp64 3) multidataset_hpo-BEST3-fp64 4) multidataset_hpo-BEST4-fp64 5) multidataset_hpo-BEST5-fp64 6) multidataset_hpo-BEST6-fp64 7) multidataset_hpo-BEST7-fp64 8) multidataset_hpo-BEST8-fp64 9) multidataset_hpo-BEST9-fp64 10) multidataset_hpo-BEST10-fp64 Within each one of these folders, additional auxiliary log files are provided with descriptions about how the training proceeded. The lead PaiNN-model is contained inside "multidataset_hpo-BEST6-fp64". The file "mlp_branch_weights" contains the parameters of the multi-layer perceptron (MLP) used to reconcile the predictions of the 16 output decoding heads of the HydragNN architectures. The MLP takes in input the chemical composition of the atomistic structure and predicts averaging weights to linearly mix the predictions of each output decoding head toward consolidating them into a single one. The folder "1.1billion-structure-inference" contains 1.1 billion atomistic structures randomly generated. Each structures is associated with energy and forces predicted with the lead-PaiNN model combined with the MLP model for reconciliation of the multi-branch predictions generated by the 16 output decoding heads. The folder "1.1billion-structure-inference" contains 9,300 (*.tar.gz) subdirectories, one per Frontier compute node used to execute the inference at exascale. Once uncompressed, each (*.tar.gz) subdirectory contains an ADIOS2 (*.bp) file container, where each atomistic structure is stored as a PyTorch-Geometric Data object. The file "export_dataset_environment_variables.sh" contains the environment variables that need to be set before running the HydraGNN code to reproduce the results provided in this dataset release. The code that can be used to load the ADIOS2 files, load HydraGNN models, and run inference is available at: https://github.com/ORNL/HydraGNN/releases/tag/v5.0

36 MATERIALS SCIENCE

Characterizing and modeling the mechanical behavior of an anion exchange membrane for carbon capture applications

A new direct air capture (DAC) technology uses a moisture swing (MS) process with anion exchange membranes, potentially offering a more energy-efficient way to remove CO₂ from the air. In this MS process, the membrane absorbs CO₂ as it dries and releases it when water is added. Understanding the mechanical behavior of these membranes is essential for improving the design and efficiency of DAC systems and prolonging sorbent lifetime. This study tested one anion exchange membrane, Fumasep’s FAA-3, under mechanical loading and various temperature and humidity conditions to measure its swelling, stiffness, strength, plastic deformation, and stress relaxation. Experimental results were used to identify a mechanical model for FAA-3 that can be used to predict the material’s nonlinear viscous behavior under various loads and environments. Unlike prior studies that assumed linear elastic behavior, this work incorporates humidity-dependent swelling, thermal expansion, and nonlinear viscoelasticity of FAA-3 in both the experiments and the model.

Direct air capture

Future Projection of Tropical Upper-Tropospheric Troughs and Implications for Tropical Cyclone Activity

Summertime tropical upper-tropospheric troughs (TUTTs) provide a unified framework to better understand how extratropical and tropical forcings jointly modulate basin-scale tropical cyclone (TC) activity. In this study, we examine future changes in TUTTs and their implications for TC activity. Multimodel ensemble-mean projections from 45 Coupled Model Intercomparison Project phase 6 (CMIP6) models suggest a contraction of the Pacific TUTT and an expansion of the Atlantic TUTT as the climate warms. Consistently, future changes in environment-based TC indices indicate that the large-scale conditions will become more favorable for TC genesis and intensification over the central North Pacific but less favorable over the tropical North Atlantic and Gulf of Mexico. Utilizing a TC-permitting large-ensemble dataset [i.e., the Database for Policy Decision-Making for Future Climate Change (d4PDF)] that adequately captures the observed interannual TUTT–TC relationships, we further confirm the impacts of projected TUTT changes on the TC activity in a warmer climate. In contrast, the TUTT–TC relationship is poorly represented in most CMIP6 High-Resolution Model Intercomparison Project (HighResMIP) models; such deficiencies call for caution when assessing future TC risk based on explicitly tracked TCs in these models. Additionally, CMIP6 projections show large intermodel spread in TUTT changes, implying uncertainty in projected TC activity, especially over the central-to-eastern Pacific and the North Atlantic. This intermodel spread is associated with interhemispheric sea surface temperature warming asymmetry, which leads to a meridional shift of the intertropical convergence zone (ITCZ) and the simultaneous weakening or strengthening of TUTTs in the North Pacific and North Atlantic. The potential contributions of anthropogenic aerosol forcing and oceanic circulation to this interhemispheric warming asymmetry are briefly examined.

Climate Change

Chiral edge state control of thermoelectric effects

Thermoelectric responses in two-dimensional electron gases subjected to magnetic fields have the potential to provide unique information about quasiparticle statistics. In this study, we show that chiral edge states play a key role in thermoelectric Hall bar measurements by completely controlling the direction of the internal thermal gradient. To this end, we perform measurements of the magnetothermoelectric responses of cadmium arsenide quantum wells. The magnetothermoelectric responses in the quantum Hall regime agree with theoretical predictions if one considers the role of chiral edge states, which flow in opposite directions on either side of the Hall bar and establish an internal temperature gradient that is perpendicular to the externally applied thermal gradient. We show that the results are self-consistent within this picture under different measurement conditions. We discuss potential applications of the findings, such as in nanoscale control of local temperature gradients and thermoelectric effects along with the characterization of other topological systems with chiral edges states.

Science & Technology - Other Topics

The SPT-deep Cluster Catalog: Sunyaev–Zel’dovich Selected Clusters from Combined SPT-3G and SPTpol Measurements over 100 Square Degrees

We present a catalog of 500 galaxy cluster candidates in the SPT-Deep field: a 100 deg$^{2}$ field that combines data from the SPT-3G and SPTpol surveys to reach noise levels of 3.0, 2.2, and 9.0 μK-arcmin at 95, 150, and 220 GHz, respectively. Candidates are selected via the thermal Sunyaev–Zel’dovich (SZ) effect with a minimum significance of ξ = 4.0, resulting in a catalog of purity ∼89%. Optical data from the Dark Energy Survey and infrared data from the Spitzer Space Telescope are used to confirm 442 cluster candidates. The clusters span 0.12 < z ≲ 1.8 and 1.0 × 10$^{14}$M$_{⊙}$/h$_{70}$ < M$_{500c}$ < 8.7 × 10$^{14}$M$_{⊙}$/h$_{70}$. The sample’s median redshift is 0.74, and the median mass is 1.7 × 10$^{14}$M$_{⊙}$/h$_{70}$; these are the lowest median mass and highest median redshift of any SZ-selected sample to date. We assess the effect of infrared emission from cluster member galaxies on cluster selection by performing a joint fit to the infrared dust and tSZ signals by combining measurements from SPT and overlapping submillimeter data from Herschel/SPIRE. We find that at high redshift (z > 1), the tSZ signal is reduced by $17.9_{−3.2}^{+3.8}$%$(3.8_{−0.7}^{+0.9}$%$)$ at 150 GHz (95 GHz) due to dust contamination. We repeat our cluster finding method on dust-nulled SPT maps and find the resulting catalog is consistent with the nominal SPT-Deep catalog, suggesting dust contamination does not significantly impact the SPT-Deep selection function; we attribute this lack of bias to the inclusion of the SPT 220 GHz band.

79 ASTRONOMY AND ASTROPHYSICS

Rethinking 𝛼−RuCl 3 : Parameters, models, and phase diagram

RuCl 3 was likely the first ever deliberately synthesized ruthenium compound, following the discovery of the 44 Ru element in 1844. For a long time it was known as an oxidation catalyst, with its physical properties being discrepant and confusing, until a decade ago when its allotropic form 𝛼−RuCl 3 rose to exceptional prominence. This “rediscovery” of 𝛼−RuCl 3 has not only reshaped the hunt for a material manifestation of the Kitaev spin liquid, but it has opened the floodgates of theoretical and experimental research in the many unusual phases and excitations that the anisotropic-exchange magnets as a class of compounds have to offer. Given its importance for the field of Kitaev materials, it is astonishing that the low-energy spin model that describes this compound and its possible proximity to the much-desired spin-liquid state is still a subject of significant debate ten years later. In the present study, we argue that the existing key phenomenological observations put strong natural constraints on the effective microscopic spin model of 𝛼−RuCl 3 , and specifically on its spin-orbit-induced anisotropic-exchange parameters that are responsible for the nontrivial physical properties of this material. These constraints allow one to focus on the relevant region of the multidimensional phase diagram of the 𝛼−RuCl 3 model, suggest an intuitive description of it via a different parametrization of the exchange matrix, offer a unifying view on the earlier assessments of its parameters, and bring closer together several approaches to the derivation of anisotropic-exchange models. We explore extended phase diagrams relevant to the 𝛼−RuCl 3 parameter space using quasiclassical, Luttinger-Tisza, exact diagonalization, and density-matrix renormalization-group methods, demonstrating a remarkably close quantitative accord between them on the general structure and hierarchy of the phases, with the zigzag, ferromagnetic, and incommensurate phases that are proximate to each other. As a result, one of the highlights is the detailed agreement on the nature of the incommensurate phases that realize two distinct counterrotating helical states.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND

SPT clusters with DES and HST weak lensing. II. Cosmological constraints from the abundance of massive halos

We present cosmological constraints from the abundance of galaxy clusters selected via the thermal Sunyaev-Zel’dovich (SZ) effect in South Pole Telescope (SPT) data with a simultaneous mass calibration using weak gravitational lensing data from the Dark Energy Survey (DES) and the Hubble Space Telescope (HST). The cluster sample is constructed from the combined SPT-SZ, SPTpol ECS, and SPTpol 500d surveys, and comprises 1,005 confirmed clusters in the redshift range 0.25–1.78 over a total sky area of 5200 deg 2 . We use DES Year 3 weak-lensing data for 688 clusters with redshifts 𝑧 < 0.95 and HST weak-lensing data for 39 clusters with 0.6 < 𝑧 < 1.7. The weak-lensing measurements enable robust mass measurements of sample clusters and allow us to empirically constrain the SZ observable-mass relation without having to make strong assumptions about, e.g., the hydrodynamical state of the clusters. For a flat Λ⁢ CDM cosmology, and marginalizing over the sum of massive neutrinos, we measure Ω m = 0.286 ± 0.032, 𝜎 8 = 0.817 ± 0.026, and the parameter combination 𝜎 8 ⁢(Ω m /0.3) 0.25 = 0.805 ± 0.016. Our measurement of 𝑆 8 ≡ 𝜎 8 ⁢$\sqrt{Ω_{m}/0.3}$ = 0.795 ± 0.029 and the constraint from Planck CMB anisotropies (2018 TT, TE, EE+lowE) differ by 1.1⁢𝜎. In combination with that Planck dataset, we place a 95% upper limit on the sum of neutrino masses ∑𝑚 𝜈 < 0.18 eV. When additionally allowing the dark energy equation of state parameter 𝑤 to vary, we obtain 𝑤 = −1.45 ± 0.31 from our cluster-based analysis. In combination with Planck data, we measure 𝑤 =−1.3⁢4$^{+0.22}_{−0.15}$, or a 2.2⁢𝜎 difference with a cosmological constant. We use the cluster abundance to measure 𝜎8 in five redshift bins between 0.25 and 1.8, and we find the results to be consistent with structure growth as predicted by the Λ⁢ CDM model fit to Planck primary CMB data.

79 ASTRONOMY AND ASTROPHYSICS

Extreme confinement of hydrogen gas within fullerenelike nanoporous carbon

Nanoporous carbons and carbon nanostructures can store hydrogen at cryogenic temperatures but lack the volumetric and gravimetric capacity to be industrially significant. Recent inelastic neutron scattering experiments suggest a highly dense phase of hydrogen at temperatures well above the melting point of solid hydrogen. However, it remains unclear how pore geometry and intermolecular interactions enable these dense phases to exist, with dispersion (van der Waals) or electrostatic/induction suggested to be the key effects in slit and curved pores but their relative contributions have yet to be quantified. In this paper, we perform benchmark electronic structure calculations allowing the interactions between planar and curved aromatic molecules with hydrogen to be accurately determined. Dispersion was found to dominate over electrostatic and inductive effects with some many-body charge transfer (Dobson type-A) effects needed to capture the most highly curved structures. Density functional methods that include type-A many-body effects were found to accurately describe the intermolecular interactions at a fraction of the cost of coupled-cluster simulations and these approaches were used to calculate the energies inside large carbon bowl and slit pores. The interaction energies inside the bowl pores were found to depend on the orientation of the hydrogen molecule. This rotational barrier, modeled as a quantum hindered rotor, could reproduce the peak splitting observed in inelastic neutron scattering experiments, with weak splitting arising from bowl-like fullerene pores and strong splitting from highly confining nanotubelike pores. Increasing the fraction of such curved pores in nanoporous carbons may therefore offer a pathway to enhance their hydrogen-storage capacity. Moreover, the preferential adsorption of ortho hydrogen on nanotubelike pores could enable the storage of high-density hydrogen without the need to remove heat produced during the ortho-para hydrogen conversion.

36 MATERIALS SCIENCE

Systematic Construction of Time-Dependent Hamiltonians for Microwave-Driven Josephson Circuits

Time-dependent electromagnetic drives are fundamental for controlling complex quantum systems, including superconducting Josephson circuits. In these devices, accurate time-dependent Hamiltonian models are imperative for predicting their dynamics and designing high-fidelity quantum operations. Existing numerical methods, such as black-box quantization (BBQ) and energy-participation ratio (EPR), excel at modeling the static Hamiltonians of Josephson circuits. However, these techniques do not fully capture the behavior of driven circuits stimulated by external microwave drives, nor do they include a generalized approach to account for the inevitable noise and dissipation that enter through microwave ports. Here, we introduce numerical techniques that leverage classical microwave simulations, efficiently executable in finite-element solvers, to obtain the time-dependent Hamiltonian of microwave-driven superconducting circuits with arbitrary geometries under charge, flux, or mixed electromagnetic modulation. Importantly, our techniques do not rely on a lumped-element description of the superconducting circuit, in contrast to previous approaches to tackling this problem. We demonstrate the versatility of our approach by characterizing the driven properties of realistic circuit devices in complex electromagnetic environments, including coherent dynamics due to charge and flux modulation, as well as drive-induced relaxation and dephasing. Our techniques offer a powerful toolbox for optimizing circuit designs and advancing practical applications in superconducting quantum computing.

Lu, Yao [Yale U.; Yale U. (main); Fermilab] (ORCID

Nuclear Safety [Vol. 29, No. 1, January-March 1988]

Nuclear Safety is a review journal that covers significant developments in the field of nuclear safety. Its scope includes the analysis and control of hazards associated with nuclear energy, operations involving fissionable materials, and the products of nuclear fission and their effects on the environment. Primary emphasis is on safety in reactor design, construction, and operation; however, the safety aspects of the entire fuel cycle, including fuel fabrication, spent-fuel processing, nuclear waste disposal, handling of radioisotopes, and environmental effects of these operations, are also treated. Table of Contents for this issue follows. THE CHERNOBYL ACCIDENT: 1 Core History and Nuclide Inventory of the Chernobyl Core at the Time of Accident by Gerald Kirchner and Cornelius C. Noack; GENERAL SAFETY CONSIDERATIONS: 6 Nonprescriptive Nuclear Safety Regulation: The Example of Loss of Offsite Power by M. W. Golay, V. P. Manno, and C. Vlahoplus, Jr., 20 Nuclear Power Safety Goals in Light of the Chernobyl Accident by C. Whipple and C. Starr; ACCIDENT ANALYSIS: 29 Containment Loads from Severe Accidents—U.S. Program by W. Kerr and M. K. Dey; PLANT SAFETY FEATURES: 36 Safety Characteristics of Modern High-Temperature Reactors: Focus on German Designs by W. Kröger, H. Nickel, and R. Schulten; ENVIRONMENTAL EFFECTS: 49 Radiation Hormesis and Nuclear Safety by C. C. Congdon; OPERATING EXPERIENCES: 58 Evaluation of Nonradiological Water Chemistry at Power Reactors by Harvey Zibulsky, James J. Kottan, Walter J. Pasciak, Mary Ann Castrogivanni, and Sujit Banerjee, 64 Reactor Shutdown Experience Compiled by J. W. Cletcher, 67 Operating U.S. Power Reactors Compiled by E. G. Silver; RECENT DEVELOPMENTS: 85 General Administrative Activities Compiled by E. G. Silver, 94 Reports, Standards, and Safety Guides by D. S. Queener, 100 Status of Power-Reactor Projects Undergoing Licensing Review Compiled by E. G. Silver, 103 Proposed Rule Changes as of Sept. 30, 1987; ANNOUNCEMENTS: 5 Northwestern University Short Course on Radiation Safety, 28 International Approach to Nuclear Safety (After Three-Mile Island and Chernobyl), 57 RPI Short Course on Modern Developments in Boiling Heat Transfer and Two-Phase Flow, 107 20th DOE/NRC Nuclear Air Cleaning Conference, 110 Third International Topical Meeting on Nuclear Power Plant Thermal Hydraulics and Operations, 108 The Authors, 111 Indexes to Nuclear Safety, Volume 28.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS

A Reductively Stable Electrolyte Realizes Deep Cycling Behavior in Anode‐free Sodium Batteries

For anode‐free sodium batteries to achieve practical consideration, highly reversible chemistries require exceptional ≥99.95% coulombic efficiencies that maintain over prolonged cycling periods. To do so, consumption of this severely limited sodium inventory must be restricted while metal nucleation processes that comprise the in situ formed metal anode are improved. Herein, we describe a fluorine‐free carborane electrolyte that satisfies these criteria by emphasizing reductive stability and weakly coordinating anion behavior as design principles. We find this approach promotes the development of a thin, robust SEI chemistry rich in both organic speciation and boron. The electrolyte described herein exhibits ideal metal nucleation behavior on one‐micron thin carbonaceous current collector surfaces and achieves a metal deposition/stripping efficiency near parity for 400 cycles. This novel anode chemistry is introduced to anode‐free full cell configurations where 87% of the initial discharge capacity is retained after 1000 cycles at 2.0 C. In conclusion, post‐test characterization of deep‐cycled anode‐free cells reveals suppressed capacity fade in these systems is attributed to the chemical stability of the carborane anion.

anode-free

Nonlinear nanoelectrodynamics of a Weyl metal

Chiral Weyl fermions with linear energy-momentum dispersion in the bulk accompanied by Fermi-arc states on the surfaces prompt a host of enticing optical effects. While new Weyl semimetal materials keep emerging, the available optical probes are limited. In particular, isolating bulk and surface electrodynamics in Weyl conductors remains a challenge. We devised an approach to the problem based on near-field photocurrent imaging at the nanoscale and applied this technique to a prototypical Weyl semimetal TaIrTe 4 . As a first step, we visualized nano-photocurrent patterns in real space and demonstrated their connection to bulk nonlinear conductivity tensors through extensive modeling augmented with density functional theory calculations. Notably, our nanoscale probe gives access to not only the in-plane but also the out-of-plane electric fields so that it is feasible to interrogate all allowed nonlinear tensors including those that remained dormant in conventional far-field optics. Surface- and bulk-related nonlinear contributions are distinguished through their “symmetry fingerprints” in the photocurrent maps. Robust photocurrents also appear at mirror-symmetry breaking edges of TaIrTe 4 single crystals that we assign to nonlinear conductivity tensors forbidden in the bulk. Here, nano-photocurrent spectroscopy at the boundary reveals a strong resonance structure absent in the interior of the sample, providing evidence for elusive surface states.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC

On-chip terahertz emission from Floquet-Bloch states [Invited]

Floquet engineering uses time-periodic electromagnetic fields to modify the electronic properties of quantum materials via the creation of Floquet-Bloch states. These photon-dressed states inherit features from both the material and the driving field, enabling the exploration and control of quantum phenomena in light-matter hybrid systems. In non-centrosymmetric materials, shift currents can arise from the quantum geometric properties of electronic wavefunctions. However, shift currents from Floquet-Bloch states remain experimentally unexplored. Here, we employ an on-chip optoelectronic circuit to detect intrinsic terahertz emission from Floquet-Bloch states in T d -WTe 2 under intense optical driving. We observe strong edge-localized terahertz emission that scales linearly with the driving field, consistent with the theoretical prediction for shift currents generated by Floquet-Bloch states. The results advance our understanding of strongly driven quantum materials and provide insights for developing efficient, bias-free terahertz sources for future optoelectronic technologies.

Li, Xinyu [Max Planck Institute for the Structure

Prospects of Nanoscience with Nanocrystals: 2025 Edition

Abstract Nanocrystals (NCs) of various compositions have made important contributions to science and technology, with their impact recognized by the 2023 Nobel Prize in Chemistry for the discovery and synthesis of semiconductor quantum dots (QDs). Over four decades of research into NCs has led to numerous advancements in diverse fields, such as optoelectronics, catalysis, energy, medicine, and recently, quantum information and computing. The last 10 years since the predecessor perspective “Prospect of Nanoscience with Nanocrystals” was published in ACS Nano have seen NC research continuously evolve, yielding critical advances in fundamental understanding and practical applications. Mechanistic insights into NC formation have translated into precision control over NC size, shape, and composition. Emerging synthesis techniques have broadened the landscape of compounds obtainable in colloidal NC form. Sophistication in surface chemistry, jointly bolstered by theoretical models and experimental findings, has facilitated refined control over NC properties and represents a trusted gateway to enhanced NC stability and processability. The assembly of NCs into superlattices, along with two-dimensional (2D) photolithography and three-dimensional (3D) printing, has expanded their utility in creating materials with tailored properties. Applications of NCs are also flourishing, consolidating progress in fields targeted early on, such as optoelectronics and catalysis, and extending into areas ranging from quantum technology to phase-change memories. In this perspective, we review the extensive progress in research on NCs over the past decade and highlight key areas where future research may bring further breakthroughs.

Chemistry

Numerical simulation of frost formation and heat transfer on fin-and-tube heat exchangers in turbulent cross-flow

Frost formation in fin-and-tube heat exchangers in turbulent cross-flow presents significant challenges in industrial refrigeration applications, affecting heat transfer efficiency and operational reliability. The purpose of this work is to investigate frost deposition and growth on a staggered bank of a fin-and-tube freezer coil under turbulent forced convection conditions. The focus here is on investigating conditions that closely replicate real-world scenarios in large walk-in industrial freezers. Using a direct numerical simulation approach, we examine the flow dynamics and thermal behaviour in the presence of frost, considering turbulent regimes characterized by a Reynolds number in the range 1050 ≤ R e D , avg ≤ 4800 , with the characteristic length being the outer diameter of the tube and the velocity being the bulk fluid velocity between the plates (fins). Computational fluid dynamics simulations are employed to resolve the interactions between turbulent airflow and the frost layer. Our approach incorporates a modified immersed boundary method and a slow-time acceleration technique to address the complex dynamic interface between the continuously evolving frost layer and the flowing air stream. Our findings indicate that frost forms more on the sides of the finned surfaces (plates) and less on the tubes themselves. This article is part of the theme issue ‘Heat and mass transfer in frost and ice’.

Science & Technology - Other Topics

Single‐photon emitters in PECVD‐grown silicon nitride films: from material growth to photophysical properties

Abstract Silicon nitride (SiN) is a key material for quantum photonics due to its wide transparency window, high refractive index, low optical losses, and semiconductor foundry compatibility. We study the formation of single‐photon emitters in SiN films grown by plasma‐enhanced chemical vapor deposition (PECVD), exploring their photophysical properties and dependence on growth conditions. Emitters were observed across the entire range of nitrogen‐to‐silicon precursor ratios, from silicon‐rich to nitrogen‐rich conditions, enabled by the low background fluorescence. We demonstrate single‐photon emitters in SiN films with a higher refractive index (1.8–1.9) compared to our previous reports (∼1.7). Notably, nitrogen‐rich, thinner films yield particularly bright emitters with shorter emission lifetimes, likely due to more efficient annealing. Silicon‐rich SiN films exhibit red‐shifted emission, suggesting that composition may provide a mechanism for wavelength tuning. These findings establish the feasibility of emitters formation in foundry standard PECVD tools, advancing the scalability and lab‐to‐fab transition of SiN‐based quantum photonic technologies.

Materials Science