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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records

High magnetic field response of superconductivity dome in quantum artificial high−⁢𝑇 𝐶 superlattices with variable geometry

It is known that cuprate artificial high-𝑇 𝐶 superlattices (AHTS) with period 𝑑, composed of quantum wells confining interface space charge in stoichiometric Mott insulator layers (𝑆), with thickness 𝐿, at the interface with overdoped normal metallic cuprate layers (𝑁) show a superconducting dome by tuning the geometric 𝐿 over 𝑑 ratio of the SNSN superlattice with the top predicted by quantum material design engineering quantum size effects. Here we report high-field magnetotransport measurements up to 41 Tesla of AHTS across the entire superconducting dome. The results show the universal upward-concave behavior of the temperature-dependent upper critical magnetic field in low-𝑇 𝐶 samples at the rising edge and drop edge of the dome, providing strong evidence consistent with two-band superconductivity in agreement with multigap theory used for quantum design of the SNSN superlattices. The measured superconducting coherence length demonstrates that atomic-scale engineering controls not only the critical temperature but also the intrinsic pair size at Fano-Feshbach resonances physics paving the way toward next-generation quantum devices and shedding light on unconventional superconductivity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND

Reimagining Disassembly Interfaces With Visualization: Combining Instruction Tracing and Control Flow With DisViz

In applications where efficiency is critical, developers may examine their compiled binaries, seeking to understand how the compiler transformed their source code and what performance implications that transformation may have. This analysis is challenging due to the vast number of disassembled binary instructions and the many-to-many mappings between them and the source code. These problems are exacerbated as source code size increases, giving the compiler more freedom to map and disperse binary instructions across the disassembly space. Interfaces for disassembly typically display instructions as an unstructured listing or sacrifice the order of execution. Here, we design a new visual interface for disassembly code that combines execution order with control flow structure, enabling analysts to both trace through code and identify familiar aspects of the computation. Central to our approach is a novel layout of instructions grouped into basic blocks that displays a looping structure in an intuitive way. We add to this disassembly representation a unique block-based mini-map that leverages our layout and shows context across thousands of disassembly instructions. Finally, we embed our disassembly visualization in a web-based tool, DisViz, which adds dynamic linking with source code across the entire application. DizViz was developed in collaboration with program analysis experts following design study methodology and was validated through evaluation sessions with ten participants from four institutions. Participants successfully completed the evaluation tasks, hypothesized about compiler optimizations, and noted the utility of our new disassembly view. Our evaluation suggests that our new integrated view helps application developers in understanding and navigating disassembly code.

Computer science

Pathways for Nucleation and Growth in Confined Spaces and at Interfaces

Mineral crystallization is central to myriad natural processes from the formation of snowflakes to stalagmites, but the molecular-scale mechanisms are often far more complex than models reflect. Feedbacks between the hydro-, bio-, and geo-spheres drive complex crystallization processes that challenge our ability to observe and quantify them, motivating an expansion of crystallization theories. Here, in this article, we discuss how the driving forces and timescales of nucleation are influenced by factors ranging from simple geometric confinement to distinct interfacial solution structures involving solvent organization, electrical double layers, and surface charging effects. Taken together, these ubiquitous natural phenomena can preserve metastable intermediates, drive precipitation of undersaturated phases, and modulate crystallization in time and space.

biosphere

Latent space dynamics identification for interface tracking with application to shock-induced pore collapse

Capturing sharp, evolving interfaces remains a central challenge in reduced-order modeling, especially when data is limited and the system exhibits localized nonlinearities or discontinuities. Here, we propose LaSDI-IT (Latent Space Dynamics Identification for Interface Tracking), a data-driven framework that combines low-dimensional latent dynamics learning with explicit interface-aware encoding to enable accurate and efficient modeling of physical systems involving moving material boundaries. At the core of LaSDI-IT is a revised autoencoder architecture that jointly reconstructs the physical field and an indicator function representing material regions or phases, allowing the model to track complex interface evolution without requiring detailed physical models or mesh adaptation. The latent dynamics are learned through linear regression in the encoded space and generalized across parameter regimes using Gaussian process interpolation with greedy sampling. We demonstrate LaSDI-IT on the problem of shock-induced pore collapse in high explosives, a process characterized by sharp temperature gradients and dynamically deforming pore geometries. The method achieves relative prediction errors below 9% across the parameter space, accurately recovers key quantities of interest such as pore area and hot spot formation, and matches the performance of dense training with only half the data. This latent dynamics prediction was 10 6 times faster than the conventional high-fidelity simulation, proving its utility for multi-query applications. These results highlight LaSDI-IT as a general, data-efficient framework for modeling discontinuity-rich systems in computational physics, with potential applications in multiphase flows, fracture mechanics, and phase change problems.

Gaussian process

Space charge studies on strong hadron cooler energy recovery linac

An Energy Recovery Linac (ERL) based cooler, using Coherent electron Cooling (CeC) is being designed for cooling hadron beams of the Electron-Ion Collider (EIC). The ERL design utilizes highcurrent, high-brightness electron beams with low emittance and a uniform longitudinal distribution for efficient hadron cooling. This is designed to operate in two modes to accommodate cooling requirements for hadron bunches at 100 GeV and 275 GeV, each with an average current of 100 mA and 1 nC bunch charge. With these parameters, the space charge effects become significant in this ERL design due to the low beam energy and high beam current. In this paper, we discuss strategies for including space charge effects in the optics design and implementation of an interface for space charge dominated and non-dominated regions of this ERL lattice.

Accelerator Physics

Optimizing Grain Boundary Structures with LAMMPS Using Evolutionary Algorithms

Grain boundary structure optimization is an important part of materials modeling. Current methods for grain boundary structure optimization involve inefficient, time-consuming processes that do not fully explore the interface parameter space. Evolutionary algorithms have recently been demonstrated to be effective at determining both stable and metastable grain boundary interface structures. In this work, we demonstrate the use of GBOpt, a grain boundary structure optimization software designed to use the Large-scale Atomic/Molecular Massively Parallel Simulation (LAMMPS) software to efficiently determine grain boundary structures. We demonstrate that a only a few manipulations, namely atom insertion, atom removal, and relative grain displacement, are sufficient to explore much of the grain boundary structure parameter space. The efficacy of this approach is demonstrated on an FCC Ni system, and a BCC Fe system. The computational cost is compared against the gamma-surface sampling approach to demonstrate performance improvement.

Evolutionary algorithms

VUV Photoionization Dynamics and Reactivity of Heterogeneous Water Clusters

This feature focuses on bridging isolated water and bulk water studies. It assembles experiments and theory on water clusters, mainly probed by vacuum ultraviolet (VUV) radiation, and summarizes what the effects are of intermolecular interactions on both the spectroscopy and the VUV-induced processes in water. In particular, it highlights studies of heterogeneous water clusters─those incorporating other molecular species such as naphthalene, methane, formic acid, and glycerol─which serve as model systems to investigate the fundamental roles of water in hydrogen bonding networks, proton transfer, and astrochemical processes. These mixed clusters provide a platform to revisit the stability of protonated water clusters and compile observations of ionization-induced structural rearrangements and fragmentation, especially in systems involving hydroxyl-rich cosolvents. This feature then explores energy transfer mechanisms in molecular clusters, following VUV photoexcitation. It concludes with potential future directions. First, we investigate excited-state dynamics in molecular clusters through direct probing, complementing the synchrotron studies discussed here. Second, exploring gas-phase molecule evaporation from confined spaces and interfaces using advanced spectroscopic techniques sheds light on these ubiquitous, yet currently debated, molecular processes.

Cluster chemistry

An on-chip phased array for non-classical light

Abstract Quantum science and technology can offer fundamental enhancements in sensing, communications and computing. The expansion from wired to wireless links is an exciting prospect for quantum technologies. For classical technologies, the advent of phased arrays enabled directional and adaptive wireless links by manipulating electromagnetic waves over free space. Here we demonstrate a phased array system on a chip that can receive, image and manipulate non-classical light over free space. We use an integrated photonic-electronic system with more than 1000 functional components on-chip to detect squeezed light. By integrating an array of 32 sub-wavelength engineered metamaterial antennas, we demonstrate a direct free-space-to-chip interface for reconfigurable quantum links. On the same chip, we implement a large-scale array of quantum-limited coherent receivers that can resolve non-classical signals simultaneously across 32 channels. With coherent readout and manipulation of these signals, we demonstrate 32-pixel imaging and spatially configurable reception of squeezed light over free space. Our work advances wireless quantum technologies that could enable practical applications in quantum communications and sensing.

Science & Technology - Other Topics

Understanding LIB Battery Electrodes Through Classical Electrochemical Interface Theory

Classical models of the electrochemical interface can be applied to complex and dynamic electrodes to understand important mechanisms that are relevant to device-level phenomena like calendar aging or cycle life. Here, we show that negative alloy electrodes with wide electrochemical windows cannot be assumed to have static interfaces throughout all states of charge. Under high states of charge, the interface -including the solid electrolyte interphase - has characteristics that resemble a highly polarized electrode far from the point of zero charge. Under these conditions, the interface can be understood through the Helmholtz model. At lower states of charge, the interface capacitance decreases and the space charge layer length increases. This transformation resembles a metal electrode approaching the point of zero charge which is understood through the Gouy-Chapman-Stern-Grahame model of the electrochemical interface. This transformation happens at both silicon and carbon-coated silicon interfaces. From voltage-limited cycling experiments, in the limit of the diffuse double layer, the silicon electrode impedance rises significantly in the first few cycles. This rise is related to the continuous electrochemical reduction of electrolyte components from an interface that is not electronically screened from the electrolyte. In other words, an electrode interface for batteries should resemble a 'Helmholtz-like' structure.

anode

Quantitative Analysis of the Semiconductor–Electrolyte Interface Using Cyclic Voltammetry Measurements

Small changes in the chemical potential at a semiconductor interface can result in dramatic changes to the space-charge layer that underpins applications in the electronic and photovoltaic industries as well as in photoelectrochemical cells for fuel production. There has hence been great interest in techniques that directly probe the space-charge layer, yet many fail at the semiconductor–electrolyte interface due to the potential drop in the electric double-layer region of the electrolyte. This article demonstrates that photovoltages, obtained from straightforward cyclic voltammetry measurements, provide an experimental and quantitative approach for characterizing the semiconductor–electrolyte interface. Key parameters accessible through this approach include the flat-band potential ( E fb ), the fraction of the total potential that drops across the space-charge layer (γ sc ) and the electric double layer, as well as the surface recombination lifetime (τ s ). Here, we report photovoltage measurements for p -type Si(111) photoelectrodes in contact with electrolytes containing redox-active species with a range of known reduction potentials that exceed the 1.1 eV bandgap. In tetrabutylammonium [NBu 4 ] + electrolyte, the flat-band potential determined for hydrogen-terminated ( p -Si–H), methyl-terminated ( p -Si–CH 3 ), and chemically oxidized ( p -Si–cSiO x ) surfaces were −0.02, −0.31, and 0.30 V vs Fc +/0 , respectively, agreeing well with expected shifts arising from surface dipole modifications. The quantitative analysis also reveals that 67% of the applied bias drops across the space-charge layer for p -Si–H, 73% for p -Si–CH 3 , and only 44% for p -Si–cSiO x . The remaining potential drop is attributed to the interfacial surface layer, which consists of a molecular dipole or oxide overlayer, and the Helmholtz layer within the electrolyte. When the larger [NBu 4 ] + electrolyte was replaced with Li + , the flat-band position showed minimal changes, but the fraction of the potential drop across the space-charge layer increased significantly, consistent with the small cation altering the structure of the electric double layer.

electrolytes

Enhanced Performance of Silicon Anodes through Hybrid Surface Engineering

Silicon (Si) is a promising anode material for nextgeneration lithium-ion batteries (LIBs) due to its high theoretical capacity. However, Si-containing anodes typically suffer from unacceptably short lives because of the unrestricted growth of the solid electrolyte interphase (SEI). Here, in this study, hybrid surface coatings are developed to stabilize the SEI in high loading pure Si anodes using atomic and molecular layer deposition. The coatings, consisting of LiF paired with lithicone, create an ionically conductive surface that enhances the capacity retention, rate performance, and longevity. Careful binder selection helps demonstrate the full utility of the coatings by enabling high loading electrodes to cycle continuously at current densities of 1200 mA/g Si . Uncoated controls, in comparison, fail within just 10 cycles at lower loadings. X-ray photoelectron spectroscopy and electrochemical impedance spectroscopy are used to provide supporting evidence of the coating composition and efficacy. The data indicate that our lithicone coating is converted to Li 2 CO 3 upon cycling contributing to favorable LiF/Li 2 CO 3 interfaces that enhance the space-charge effect at the active material’s surface. When applied to electrodes made with thermally stable binders and increasingly higher loadings (approaching 5 mAh/cm 2 ), ion transport through the bulk electrode, rather than SEI growth, is shown to be the limiting factor. Furthermore, data suggests a favorable interaction between lithicone precursors and poly(acrylic acid) binders mitigates thermal decomposition at higher temperatures. The work presented here represents the successful realization of composite coatings containing LiF/Li 2 CO 3 components to stabilize high-loading Si anodes. This work helps inform advanced surface engineering strategies to achieve highly reversible, high-capacity Si anodes capable of fast charging for high-performance LIBs.

atomic layer deposition

MOSAIC-CONUS: A Multimodal, Multi-Temporally Paired Dataset for Earth Sciences

Earth embeddings—vector representations of geographic locations indexed in space and time—are emerging as a unifying interface for geospatial AI. However, their quality depends not only on model design, but on how multimodal Earth observation (EO) data are spatially indexed, temporally aligned, and cross-modally associated during pretraining. We introduce MOSAIC-CONUS (Multimodal Observations with Spatially Aligned Imagery, Urban Points of Interest, In-Situ Measurements and Text Captions), a large-scale EO dataset over the contiguous United States, organized around 250,000 stratified point indices that serve as stable spatial keys across seven modalities: active radar, passive optical imagery, lidar-derived elevation, land cover, functional context, hydrometeorological measurements, and textual summaries. Unlike existing EO datasets, MOSAIC-CONUS introduces four contributions not jointly addressed in prior work: 1. an open-source, large-scale multimodal EO corpus structured around point-indexed data designed to support Earth embedding learning; 2. explicit radar-optical pairing tables spanning twelve temporal alignment regimes, formalizing cross-sensor alignment as a controllable variable for analyzing how temporal mismatch across modalities influences learned embeddings quality; 3. a benchmark suite spanning cross-modal retrieval, annual nightlights regression, and basin-held-out streamflow prediction, positioning MOSAIC-CONUS as a benchmark-ready resource for multimodal AI systems; and 4. a language-based embedding layer through co-registered textual summaries, enabling Earth embeddings to function as a queryable interface for agentic AI systems. The dataset and pairing protocols are publicly released.

54 ENVIRONMENTAL SCIENCES

A New Phase for Space Weather

As we move into the declining phase of solar cycle 25, the sunspot number is going down but space weather impacts are not disappearing. Solar energetic particle events, large x-ray flares, and geomagnetic storms are still happening and the declining phase will bring a different balance of hazards. The need for space weather science, space weather applications, and an interface between research, application, and stakeholder communities has not passed. Observations and insights from solar cycle 25 will continue to help us prepare for solar cycle 26, so that we approach the next solar maximum with better predictions, better understanding of outcomes, and a stronger community enabling more confident mitigation and clearer outreach.

99 GENERAL AND MISCELLANEOUS

Electrical readout of topological spin order in ultrathin insulators with small magnetization

Probing magnetic order in insulators with small magnetization is particularly challenging in the ultrathin limit, where magnetometry and diffraction lose sensitivity. Here, in this study, we show that topological spin order with vanishingly small magnetization can be electrically detected through an interfacial topological Hall effect in heavy-metal/magnetic-insulator heterostructures. Using Pt coupled to the canted antiferromagnetic insulator hexagonal LuFe⁢O 3 (h-LuFe⁢O 3 ) we observe an unusually large and robust Hall response arising from the transfer of real-space spin topology across the interface via magnetic proximity effect (MPE). This interfacial signal enables detection of magnetic order in h-LuFe⁢O 3 with an extremely small net magnetization (0.025 𝜇 B /Fe), corresponding to Hall-conductivity-magnetization ratio ≈ 2 V −1 , which is one to two orders of magnitude large than other MPE-induced Hall effects and anomalous Hall effects of conducting magnets. This high sensitivity allows detection of magnetic order in h-LuFe⁢O 3 down to a thickness of only 1.5 unit cells. Our results establish an interfacial Hall-based approach for electrically probing topological spin structures in ultrathin insulators and the related interfaces, enabling access to magnetic order in regimes where conventional probes fail.

Topological Hall Effect

Algebraic Multigrid with Filtering: An Efficient Preconditioner for Interior Point Methods in Large-Scale Contact Mechanics Optimization

Large-scale contact mechanics simulations are crucial in many engineering fields such as structural design and manufacturing. In the frictionless case, contact can be modeled by minimizing an energy functional; however, these problems are often nonlinear, nonconvex, and increasingly difficult to solve as mesh resolution increases. In this work, we employ a Newton-based interior-point (IP) filter line-search method, an effective approach for large-scale constrained optimization. While this method converges rapidly, each iteration requires solving a large saddle-point linear system that becomes ill-conditioned as the optimization process converges, largely due to IP treatment of the contact constraints. Such ill-conditioning can hinder solver scalability and increase iteration counts with mesh refinement. Here, to address this, we introduce a novel preconditioner, algebraic multigrid with filtering (AMGF), tailored to the Schur complement of the saddle-point system. Building on the classical AMG solver, commonly used for elasticity, we augment it with a specialized subspace correction that filters near null space components introduced by contact interface constraints. Through theoretical analysis and numerical experiments on a range of linear and nonlinear contact problems, we demonstrate that the proposed solver achieves mesh independent convergence and maintains robustness against the ill-conditioning that notoriously plagues IP methods. These results indicate that AMGF makes contact mechanics simulations more tractable and broadens the applicability of Newton-based IP methods in challenging engineering scenarios. More broadly, AMGF is well suited for problems, optimization or otherwise, where solver performance is limited by a low-dimensional subspace, such as those arising from localized constraints, interface conditions, or model heterogeneities. This makes the method widely applicable beyond contact mechanics and constrained optimization.

Mathematics and Computing

An Open-Source Framework for Rapid Validation of Scientific ASICs

Spacely is an open-source framework for the post-silicon validation of analog, digital, and mixed-signal ASICs (Application-Specific Integrated Circuits) which maximizes the reuse of hardware and software, reducing the time taken to achieve meaningful test results. Spacely specifically addresses the needs of small, flexible ASIC design teams commonly found in academia or research institutions which benefit most from sharing the overhead of test stand creation between many unique ASIC designs. Spacely is a set of software, firmware, and design practices. It targets two primary hardware platforms (NI-PXI and Caribou) as well as offering extensible support for bench instruments. Spacely provides a high-level Python interface to all test hardware for accessibility, while also giving more sophisticated teams the opportunity to integrate custom test firmware. The design principles of Spacely are presented in brief. Current documentation is available at https://github.com/SpacelyProject/spacely-docs.

Quinn, Adam [Fermilab]

HPC Network Simulation Tuning via Automatic Extraction of Hardware Parameters

Popular HPC network interconnection simulators such as SST/macro provide a variety of configurable parameters to explore the design space of hardware components such as network interface cards (NIC), switches, and links among them. While such knobs provide flexibility to explore design trade-offs for novel hardware, manually configuring simulations for matching configurations of the existing hardware to focus on topology exploration can be cumbersome and error-prone, leading to widely inaccurate simulations. This challenge is compounded when specifications of various (proprietary) technologies are not readily available or intentionally omitted. In this work, we propose a framework to autotune the multiple network models’ simulation configurations within SST/macro using Tree-structured Parzen Estimator-based Bayesian optimization to observe the effect on simulation accuracy across different message regimes. These regimes consist of small to large message sizes and latency to bandwidth-bound messages. We provide a detailed analysis of the simulation error for four representative HPC systems. Our Bayesian optimization based autotuning framework for network models achieves a maximum of 5x improvement in accuracy over best-effort manual configurations based on available hardware specifications.

Simulation, autotuning

Beyond the eutectic paradigm: nanolamellar patterns in a rapidly solidified peritectic alloy

Peritectic transformations are central to many structural alloys, yet pattern formation remains poorly understood due to complex growth dynamics and limited three-dimensional data. Here, we report an unusual two-phase microstructure in a Zn–Ag peritectic alloy subjected to rapid solidification by laser surface remelting. Synchrotron X-ray nanotomography reveals a lamellar structure of primary 𝜀-AgZn 3 and peritectic Zn with ∼700 nm spacing. Although resembling a eutectic morphology, this pattern forms without a eutectic reaction through non-steady coupled growth from the liquid. SEM and TEM-EDS confirm interface shapes and phase compositions. These findings expand the design space of peritectics for refined microstructural control.

36 MATERIALS SCIENCE