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721 records · Page 29

Enhancing Coherence Limits in Superconducting Quantum Systems for Computing and Sensing

This talk will highlight recent efforts at the SQMS Center to develop qudit-based quantum computing architectures using superconducting three-dimensional (3D) cavities, as well as the use of these ultra-coherent cavities for quantum sensing. I will present systematic studies of materials and devices aimed at identifying and mitigating the dominant sources of decoherence—including two-level systems (TLS), quasiparticles, and other noise mechanisms—in both transmons and 3D cavities. These investigations include microwave loss characterization of niobium, tantalum, aluminum, their native oxides, and substrate materials such as silicon and sapphire. By combining measurements on qubits and cavities, we disentangle subsystem-specific loss mechanisms and establish a hierarchy of mitigation strategies, leading to transmon coherence times exceeding one millisecond. I will also discuss studies of quasiparticle dynamics, including quasiparticle bursts observed in qubits operated both above ground and at the Gran Sasso underground laboratory, and the observation that applied magnetic fields can suppress temporal T₁ fluctuations. Building on these advances, we demonstrate a record-coherence two-cell cavity-qudit system with coherence times exceeding 20 milliseconds. Leveraging tunable sideband interactions together with error-resilient protocols, including measurement-based error correction and post-selection, we achieve high-fidelity quantum state control, including the preparation of Fock states up to N=20 with fidelities above 95% and the generation of high-fidelity two-mode entangled states. Finally, I will discuss how these ultra-coherent quantum systems are enabling emerging quantum sensing applications, including searches for dark matter and gravitational waves.

Roy, Tanay [Fermilab] (ORCID:000000019442862X)

Chemo‐Mechanical Coupling in Hydrogels: Dynamics in the Diffusion‐Limited Regime

Hydrogels are characterized by substantial volume changes in response to external stimuli, making them promising candidates for developing smart materials with enhanced adaptability and responsiveness. By integrating chemical reactions, hydrogels acquire dynamic and tunable responsiveness to external stimuli through chemo‐mechanical coupling, expanding their potential in emerging applications. However, capturing their transient behavior remains challenging due to the complex interplay of chemical reactions, solvent transport, and polymer network deformation. Classical theories capture equilibrium swelling but fail to describe time‐dependent phenomena. To address this, a time‐dependent continuum model is developed that explicitly couples these processes. Volume phase transition in hydrogels with homogeneous chemical reactions is investigated, then the effects of reaction kinetics on these transitions are analyzed. The coupling of these mechanisms is further explored through a study of transient mechanical instabilities. To illustrate the impact of distinct reaction and diffusion timescales, a photo‐active gripper is studied for robotic applications. Finally, a photo‐active microswimmer that exhibits non‐reciprocal motion is proposed to highlight the solvent diffusion for locomotion at the micro‐ and nano‐ scales. The work establishes that transient dynamics of chemo‐mechanical hydrogels generate functions not accessible by steady state models and provides a predictive platform for designing adaptive materials in emerging applications.

chemo-mechanical coupling

Multiscale aperture synthesis imager

Synthetic aperture imaging has enabled breakthrough observations from radar to astronomy. However, optical implementation remains challenging due to stringent wavefield synchronization requirements among multiple receivers. Here we present the multiscale aperture synthesis imager (MASI), which utilizes parallelism to break complex optical challenges into tractable sub-problems. MASI employs a distributed array of coded sensors that operate independently yet coherently to surpass the diffraction limit of single receiver. It combines the propagated wavefields from individual sensors through a computational phase synchronization scheme, eliminating the need for overlapping measurement regions to establish phase coherence. Light diffraction in MASI naturally expands the imaging field, generating phase-contrast visualizations that are substantially larger than sensor dimensions. Without using lenses, MASI resolves sub-micron features at ultralong working distances and reconstructs 3D shapes over centimeter-scale fields. MASI transforms the intractable optical synchronization problem into a computational one, enabling practical deployment of scalable synthetic aperture systems at optical wavelengths.

electrical and electronic engineering

Theory of the thermionic current beyond the traditional space charge limit enabled by trapped ions in the virtual cathode

We show that trapped ions in virtual cathode potential wells can raise the transmitted current of emitted electrons into a plasma much closer to the full emission than is predicted by cathode sheath theories without trapped ions. The transmitted current is controlled by the well barrier voltage, which must adjust to balance the creation of low-energy ions within the well, and their loss. Our model considers the case of a plasma-facing cathode where trapped ions are created passively via charge-exchange collisions and lost passively via thermal leakage over the well. We quantify these rates and estimate the current in terms of system parameters for thermionic emission into a plasma with several cathode geometries. A general prediction is that the current as a function of emitted flux does not saturate at the traditional space charge limit (the onset of a well) but can reach far higher values until the trapped ion balance breaks down, causing instability. The maximum stable current depends on parameters but in principle can be arbitrarily high if active techniques are used to manipulate the trapped ion balance. We conclude that major improvements in plasma technologies with hot cathodes might be achieved by optimizing the current enhancement enabled by trapped ions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY

Cation-Diffusive Carbon Interlayers Stabilize Na Metal and Double the Current in Na-S Redox-Flow Batteries for Grid-Scale Energy Storage

The sodium-sulfur nonaqueous redox-flow batteries (Na-S NARFBs) using earth-abundant elements are highly attractive due to the low material cost and improved energy density for grid-scale energy storage. However, the low current performance, poor Na0/Na+ redox kinetics, and Na dendrite growth pose severe challenges. We introduce cation-diffusive layers (CDLs): thin and Na+ affinitive interlayers at the Na anode that direct Na+ transport and stabilize Na deposition. Benchmarking three archetypal materials—carbon paper (CP), glass microfiber paper (GF), and foam—across Na-Na and Na-Cu, and Na-S cells identifies CP as the optimum. CP reduces symmetric cell overpotential by more than 70%, achieves 98% Na plating-stripping efficiency, and doubles the Na-S cell current density from 0.5 to 1.0 mA cm−2 without sacrificing capacity or efficiency. Ex situ electrochemical and SEM/XPS analysis, combined with molecular dynamics (MD) studies, reveal that electron-rich carbon fibers disperse supporting salt aggregates, enrich near-surface Na+ density, and create ion transport pathways for fast Na0/Na+ exchange while mitigating membrane degradation. Because of the ion-centric mechanism, CDLs can be generalized to other metal-anode designs. Further, this work establishes CDL design rules—cationic affinity and appropriate micro/nanostructure—as a simple, scalable route to high-current, durable metal-anode flow batteries.

Wu, Wenda [ORNL] (ORCID:000900033307687X)

Iron surface corrosion in supercritical CO2 at atomic scale investigated by molecular dynamics simulations

Understanding the corrosion behavior of steels in supercritical carbon dioxide (S-CO2) is essential for ensuring the safe application of S-CO2 as a heat-transfer fluid in high-temperature energy systems, including advanced nuclear reactors. In this work, molecular dynamics (MD) simulations using ReaxFF potential are performed to explore the atomic-scale corrosion mechanisms of body-centered cubic iron (BCC-Fe) in S-CO2. The results show that CO2 molecules in S-CO2 decompose at the Fe surface, generating free C and O atoms that form Fe-C and Fe-O bonds and subsequently produce oxides and carbides. Concurrently, Fe atoms dissolve from the surface and diffuse into the S-CO2 region, resulting in interdiffusion of Fe, C and O atoms at the interface. The corrosion-layer thickness calculations show that high pressure and temperature induced by S-CO2 have stronger effects than surface orientation on the corrosion process. In addition, surface Fe atoms undergo substantial displacement under S-CO2 exposure, further accelerating corrosion. When a radiation-induced void is introduced near the Fe surface, the corrosion is enhanced. The void-matrix interface expands the reaction surface area and simultaneously induces corrosion reactions inside the bulk, resulting in a deeper penetration of C and O and thicker corrosion layers. All these results indicate that high-temperature, high-pressure and radiation-induced voids can seriously affect the corrosion of Fe in S-CO2, and must be considered to better use S-CO2 in nuclear facilities.

Li, Wenhua

Capturing Secondary Kinetic Instabilities in Three‐Dimensional Dayside Reconnection Using an Improved Gradient‐Based Closure

Magnetic reconnection is a highly dynamic process that excites a wide variety of kinetic waves and instabilities. Transverse current sheet instabilities such as the lower-hybrid drift and secondary drift-kink instabilities in particular have been shown by kinetic simulations to modify the reconnection and introduce significant turbulence and mixing to the reconnection layer. Past studies using the ten-moment fluid model to capture important kinetic physics such as the electron inertia and full representation of the pressure tensor proved advantageous to a two-fluid representation of reconnection, but the model struggled when using a local relaxation closure for the heat flux to replicate the current sheet instabilities and subsequent mixing seen in kinetic simulations. This work uses the Gkeyll software framework to perform simulations of asymmetric reconnection based on the 16 October 2015 MMS crossing of a diffusion region, the Burch event. An improved gradient-based heat flux closure is implemented, showing significant improvement in secondary kinetic instabilities that grow in the current sheet. These instabilities generate turbulence which leads to growth of secondary magnetic islands and flux ropes.

Bradshaw, K. [Princeton University, NJ (United Sta

Large Language Model for Validation, Optical Calibration, and Learning (VOCAL) Distributed Temperature Sensing Interface

Distributed temperature sensing (DTS) using fiber optic sensors (FOS) offers a promising method for temperature measurements in advanced reactors, such as sodium fast reactors and molten salt cooled reactors. To support the calibration and validation of DTS measurements, Argonne National Laboratory developed the Validation, Optical Calibration, and Learning (VOCAL) software package. This report describes the integration of a local large language model (LLM) with a retrieval-augmented generation (RAG) system into the VOCAL interface to serve as an interactive user assistant. The LLM framework enhances the VOCAL platform’s accessibility to users by explaining interface components, clarifying inputs and outputs, and answering user queries dynamically in real-time. The accuracy of the LLM assistant performance was evaluated with 20 queries regarding the interface and its parameters using experimental data from the Thermal Hydraulic Experimental Test Article (THETA) facility. Results demonstrate that the LLM achieved a 95% accuracy rate, with a BERTScore of 0.8816 and SBERT value of 0.7417. Furthermore, validation of the RAG system within the LLM framework showed optimal accuracy with k-values between 1 and 2 using the k-refinement convergence test. The prompt perturbation analysis demonstrated good initial consistency for the RAG system, exhibiting the highest accuracy under punctuation variations and the greatest sensitivity under query reordering. Notably, the model’s errors were limited to data retrieval failures rather than factual hallucinations, reinforcing its baseline reliability. The integration of LLM provides a highly accurate, userfriendly enhancement to the VOCAL platform without disrupting its core computational capabilities for FOS calibration and validation.

Hong, Evan

Self‐Propelling Macroscale Sheets Powered by Enzyme Pumps

Nanoscale enzymes anchored to surfaces act as chemical pumps by converting chemical energy released from enzymatic reactions into spontaneous fluid flow that propels entrained nano‐ and microparticles. Enzymatic pumps are biocompatible, highly selective, and display unique substrate specificity. Utilizing these pumps to trigger self‐propelled motion on the macroscale has, however, constituted a significant challenge and thus prevented their adaptation in macroscopic fluidic devices and soft robotics. Using experiments and simulations, we herein show that enzymatic pumps can drive centimeter‐scale polymer sheets along directed linear paths and rotational trajectories. In these studies, the sheets are confined to the air/water interface. With the addition of appropriate substrate, the asymmetric enzymatic coating on the sheets induces chemically driven, buoyancy flows that controllably propel the sheet's motion on the air/water interface. The directionality and speed of the motion can be tailored by changing the pattern of the enzymatic coating, type of enzyme, and nature and concentration of the substrate. This work highlights the utility of biocompatible enzymes for generating motion in macroscale fluidic devices and robotics and indicates their potential utility for in vivo applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Heavy long-lived dark vector via a gluonic portal

We study a dark gauge boson Z′ that exclusively couples to the QCD gluons through higher dimensional operators. These operators are generated from integrating out of heavy ultraviolet resonances carrying both QCD and dark gauge charges. With SU(3)C gauge invariance, charge and parity symmetries preserved, we find that the leading effective operators are restricted to have the form of Z′GGG and Z′Z′GG at dimension-eight, which can naturally render the Z′ particle long-lived, and serve as a viable dark matter candidate. We investigate the phenomenology of these operators with both collider experiments and cosmological observation, without and with the assumption that this dark gauge boson plays the role of the dominant dark matter component. For an unstable Z′, we show that depending on its lifetime, it can be probed by various observables up to ultraviolet physics scale around 10 9 GeV. For Z′ being dark matter, we find that $m_{Z'}$ ≳ 1 TeV is consistent with the thermal freeze-out scenario. In contrast, in the freeze-in scenario, the extremely small couplings leave the relevant parameter space largely unconstrained by current experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS

Unraveling interphase-driven failure pathways in LiMn0.6Fe0.4PO4/graphite pouch cells

LiMnxFe1−xPO4 (LMFP) is a promising high-voltage, thermally stable, and earth-abundant cathode material, yet its practical application is limited by interphase instability and Mn dissolution. In this work, we systematically evaluate LiMn0.6Fe0.4PO4/graphite pouch cells using three electrolyte formulations including control carbonate electrolyte, control + 2 wt% vinylene carbonate (VC), and control + 2 wt% VC + 1 wt% 1,3,2-dioxathiolane 2,2-dioxide (DTD), to establish how electrolyte composition governs interphase chemistry and long-term degradation. Electrochemical testing shows that both additives are preferentially reduced prior to ethylene carbonate (EC) during cell formation, generating robust cathode-electrolyte interphase (CEI) and solid-electrolyte interphase (SEI) layers that suppress gas evolution and raise the first-cycle coulombic efficiency to 89.3%. Additionally, the dual-additive electrolyte delivers the most stable performance, retaining over 85% capacity after 600 cycles while minimizing impedance growth under long-term cycling at C/3 and 40 °C. Soft X-ray absorption spectroscopy confirms that VC + DTD effectively suppresses electrolyte oxidation at the cathode surface, and micro-X-ray fluorescence shows substantially reduced Mn dissolution and deposition on the graphite anode. Density functional theory simulations further provided insights into the structural and energetic influences of alkoxide species on the cathode surface, proposing a Mn2+ extraction mechanism. The combined experimental and computational findings establish a mechanistic link between electrolyte composition and interphase evolution, highlighting the effectiveness of electrolyte engineering for extending the operational lifetime of LMFP-based lithium-ion batteries.

Chak, Chanmonirath Michael

Bi‐Continuous W‐Rich Refractory High Entropy Alloy‐Cu Composite: Toward Material Innovation of Nuclear Reactor Coolant System

Abstract Refractory high‐entropy alloys (RHEAs) are considered promising candidate materials for next‐generation nuclear reactors due to their superior mechanical strength, irradiation resistance, and thermal stability at high temperatures. However, the significant positive heat of mixing between refractory alloying elements and Cu, commonly used in cooling systems, poses challenges in forming composite structures. This study addresses the issue using a liquid metal dealloying (LMD) process. A precursor alloy (WTaVTi) with a directional dendrite‐interdendrite structure is fabricated and reacted with molten Cu at 1200 °C for 96 h. This approach produced a RHEA‐Cu composite with a stable interface between RHEA (W 31.5 Ta 30.9 V 21.4 Ti 14.3 ) and Cu, featuring a spontaneously formed W‐rich interlayer that enhances interfacial bonding. The composite showed excellent irradiation resistance, with 30% less swelling under α‐ion irradiation than pure W. It also exhibited low thermal conductivity at room temperature, but reached ≈120 W m −1 ·K −1 at ≈650 °C, surpassing pure W. This temperature‐dependent rise in κ, with a positive gradient of +0.075 W m −1 ·K − 2 , is attributed to decreasing diffuse mismatch at elevated temperatures. The large‐scale reaction and stable microstructure achieved through LMD process highlight its industrial potential. This work offers a strategy for developing high‐performance materials by combining RHEA's radiation resistance with Cu's thermal conductivity for extreme environments.

Chemistry

Phase Stability and Electrochemical Performance of La-Site-Doped Li6La3Zr0.5Nb0.5Ta0.5Hf0.5O12 High-Entropy Garnets

We investigate La-site substitution in the high-entropy garnet Li6La3Zr0.5Nb0.5Ta0.5Hf0.5O12 (LLZNTH) using Ba2+, Sr2+, and Sm3+ to elucidate how dopant governs phase stability, Li-site distribution, and electrochemical behavior. X-ray diffraction shows that Sr2+ is incorporated homogeneously into the garnet lattice, whereas the larger Ba2+ and smaller Sm3+ ions partially exceed the structural tolerance, generating secondary phases. Nevertheless, the Sm-doped composition (x = 0.05) exhibits the highest room-temperature ionic conductivity (2.7 × 10–4 S cm–1). Neutron powder diffraction reveals that Sm substitution drives a redistribution of Li+ from the tetrahedral 24 d sites into the higher-mobility 96 h positions, enhancing the connectivity of the three-dimensional Li-ion migration network. A Sm-doping series (x = 0.01–0.05) further shows that only sufficiently high Sm levels induce this redistribution, whereas lower concentrations retain Li arrangements similar to the undoped garnet. Critical current density measurements demonstrate that La-site dopants also influence interfacial stability against Li metal, underscoring a trade-off between bulk transport enhancement and mechanical robustness. Collectively, these findings reveal that in high-entropy garnets improved ionic conductivity can originate not only from phase-pure structures but also from targeted modification of the Li sublattice, even when accompanied by secondary phases, offering a compositional design principle for garnet electrolytes.

Li, Chang [Mechanical Engineering, School of Scien

Boron-Based Neutron Scintillator Screen Characterization with X-Rays and Neutrons

Recent work on boron-based neutron scintillator screens suggests these screens can offer superior performance when compared to commonly used screens. Borated neutron scintillator screens perform well in terms of light output (5-6 times greater than a standard Gadox screen) and detection effi-ciency (larger than standard LiF+ZnS screens). However, previously manu-factured boron-based screens have exhibited non-uniform surface coating and a poor mixture between phosphor and converter particles. The objective of this work was to evaluate newly fabricated scintillator screens to deter-mine if enhanced fabrication methods produced a more homogeneous distribution between neutron converter and scintillation phosphor particles. Uniformity of scintillator material deposition was also inspected. This new iteration of screens appeared more uniform than previous generations with the new coating method improving surface chemistry and scintillator material homogeneity. Additionally, a new methodology for screen characterization, involving the correlation of a neutron image taken with a borated scintillator screen to X-ray computed tomography of that same screen, was demonstrated to elucidate a relationship between scintillator screen thickness and relative light output of the screen under neutron exposure. This method suggested that the ideal thickness of scintillator material was ~150 µm to maximize light output of the screen.

36 - MATERIALS SCIENCE

Proactive Wildfire Management: A Remote Sensing and Multimodal CNN-MLP Architecture for Ignition Risk Forecasting

As the frequency and intensity of wildfires increase, with fire seasons now starting earlier and ending later than they have over the past decades, current monitoring systems, such as lookout towers and satellites, are hindered by cloud cover, low-resolution imagery, and static data gaps that fail to track vegetation moisture levels fast enough to catch rapid pre-ignition changes. This report proposes a Machine Learning-enabled Wildfire Ignition Prediction framework that combines satellite monitoring with dynamic and high-resolution remote sensing from Unmanned Aerial Vehicle (UAV) swarms. The method would use multispectral and thermal data from the Landsat program to create a baseline for vegetation health, calculating a two-band Enhanced Vegetation Index (EVI2) and the moisture content of the vegetation. These inputs will later be fused with microscale UAV weather data, including thermal hotspots found through thick canopies, hyperspectral chemical signatures of pre-visual combustion, and local weather streams. The multispectral satellite, multispectral Light Detection and Ranging (LiDAR), and thermal data would then be processed through a Convolutional Neural Network (CNN), alongside a Multilayer Perceptron (MLP) for the micro-weather telemetry. The outputs of these networks would be fused into a single feature representation and passed through a final prediction network to generate real-time ignition risk scores and hotspot alerts. Model performance would be assessed using standard classification metrics, including a Receiver Operating Characteristic - Area Under the Curve (ROC AUC) and F1 score. This system would allow first responders to identify high-risk zones and intervene before ignition occurs, improving emergency response time compared to current approaches.

machine learning

Novel Zwitterionic Polyurethane-in-Salt Electrolytes with High Ion Conductivity, Elasticity, and Adhesion for High-Performance Solid-State Lithium Metal Batteries

This study presents a novel polymer-in-salt (PIS) zwitterionic polyurethane-based solid polymer electrolyte (zPU-SPE) that offers high ionic conductivity, strong interaction with electrodes, and excellent mechanical and electrochemical stabilities, making it promising for high-performance all solid-state lithium batteries (ASSLBs). The zPU-SPE exhibits remarkable lithium-ion (Li+) conductivity (3.7 × 10⁻⁴ S cm−1 at 25 °C), enabled by exceptionally high salt loading of up to 90 wt.% (12.6 molar ratio of Li salt to polymer unit) without phase separation. It addresses the limitations of conventional SPEs by combining high ionic conductivity with a Li+ transference number of 0.44, achieved through the incorporation of zwitterionic groups that enhance ion dissociation and transport. The high surface energy (338.4 J m−2) and elasticity ensure excellent adhesion to Li anodes, reducing interfacial resistance and ensuring uniform Li+ flux. When tested in Li||zPU||LiFePO₄ and Li||zPU||S/C cells, the zPU-SPE demonstrated remarkable cycling stability, retaining 76% capacity after 2000 cycles with the LiFePO4 cathode, and achieving 84% capacity retention after 300 cycles with the S/C cathode. Molecular simulations and a range of experimental characterizations confirm the superior structural organization of the zPU matrix, contributing to its outstanding electrochemical performance. The findings strongly suggest that zPU-SPE is a promising candidate for next-generation ASSLBs.

Wang, Kun

4D-STEM Mapping of Nanocrystal Reaction Dynamics and Heterogeneity in a Graphene Liquid Cell

Chemical reaction kinetics at the nanoscale are intertwined with heterogeneity in structure and composition. However, mapping such heterogeneity in a liquid environment is extremely challenging. Here, in this work, we integrate graphene liquid cell (GLC) transmission electron microscopy and four-dimensional scanning transmission electron microscopy to image the etching dynamics of gold nanorods in the reaction media. Critical to our experiment is the small liquid thickness in a GLC that allows the collection of high-quality electron diffraction patterns at low dose conditions. Machine learning-based data-mining of the diffraction patterns maps the three-dimensional nanocrystal orientation, groups spatial domains of various species in the GLC, and identifies newly generated nanocrystallites during reaction, offering a comprehensive understanding on the reaction mechanism inside a nanoenvironment. This work opens opportunities in probing the interplay of structural properties such as phase and strain with solution-phase reaction dynamics, which is important for applications in catalysis, energy storage, and self-assembly.

four-dimensional scanning transmission electron mi

High‐Performance Rechargeable Lithium‐Chlorine Batteries with ALD Conformal Starburst Porous Graphene Positive Electrodes

Abstract Rechargeable alkali metal‐chlorine batteries are emerging as a promising high‐energy‐density solution. However, they confront significant challenges, including the primary issue stemming from the weak binding affinity of cathode materials for Cl 2 , which leads to a sluggish and inadequate supply of Cl 2 during the redox reactions, resulting in a shortened cycle life and low Coulombic efficiency (CE), particularly when operating at ultrahigh specific capacity outputs. Herein, an Al 2 O 3 ‐skinned heterostructured starburst porous graphene with conformal metasurfaces (Al 2 O 3 @rGO) is reported, crafted from a hierarchical porous starburst graphene arranged in a unique layered structure by the PTFE microemulsion skin effect, leveraging subsequent fluidized bed atomic layer deposition (FBALD) of Al 2 O 3 groups. Al 2 O 3 @rGO features superhydrophilicity, effective adsorption, fast kinetics from stable dynamic respiratory interface, high electrical and thermal conductivity anisotropy, intelligent thermal management and safe operation over a wide temperature range. Consequently, the Li‐Cl 2 @Al 2 O 3 @rGO battery achieves an ultrahigh discharge specific capacity of 5000 mAh g −1 at ≈100% CE, and even delivers stable cycling over 200 cycles with 2000 mAh g −1 at an average CE of 99.8% under low temperature environment of ‐40 °C. The scalable heterostructure approach offers a sustainable perspective of the development of functionalized metamaterials and metasurfaces for next‐generation safe and energy‐dense batteries and broader applications.

Chemistry