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774 records · Page 23

Enhancement of Superconductivity in WP via Oxide-Assisted Chemical Vapor Transport

Tungsten monophosphide (WP) has been reported to superconduct below 0.8 K, and theoretical work has predicted an unconventional Cooper pairing mechanism. Here we present data for WP single crystals grown by means of chemical vapor transport (CVT) of WO3, P, and I2. In comparison to synthesis using WP powder as a starting material, this technique results in samples with substantially decreased low-temperature scattering and favors a more three-dimensional morphology. We also find that the resistive superconducting transitions in these samples begin above 1 K. Variation in Tc is often found in strongly correlated superconductors, and its presence in WP could be the result of influence from a competing order and/or a non-s-wave gap.

Chemistry

The Electron‐Density Distribution of UCl 4 and Its Topology from X‐ray Diffraction

Abstract The chemistry of electrons in actinide complexes and materials is still poorly understood and represents a serious challenge and opportunity for experiment and theory. The study of the electron density distribution of the ground state of such systems through X‐ray diffraction represents a unique opportunity to quantitatively investigate different chemical bonding interactions at once, but was considered “almost impossible” on heavy‐atom systems, until very recently. Here, we present a combined experimental and theoretical investigation of the electron density distribution in UCl_ 4 crystals and comparison with the previously reported spin density distribution from polarized neutron diffraction. All approaches provide a consistent picture in terms of electron and spin density distribution, and chemical bond characterization. More importantly, the synergy between experiments and quantum‐mechanical calculations allows to highlight the remarkable sensitivity of X‐ray diffraction to electrons in materials.

Chemistry

Impact of Advances in Anion Exchange Membranes and Ionomers on Alkaline Fuel Cells

Abstract The operation of low‐temperature electrochemical energy conversion systems (fuel cells, electrolyzers) at high pH values is of perennial interest due to the possibility of moving away from expensive platinum group metal catalysts and reducing cost. Historically, the anion exchange membranes (AEMs) and ionomers have been hampered by performance (ionic conductivity, mechanical strength) and chemical stability issues. In this context, select developments over the past decade in alternate AEM chemistries, water management methods, and production of membrane electrode assemblies (MEAs) that have enabled a significant leap in performance of alkaline fuel cells are examined. These developments are linked to performance improvements in alkaline H 2 /O 2 fuel cells and also consider developments in alkaline fuel cells using nitrogen‐containing fuels (ammonia, hydrazine), carbon‐containing fuels (alcohols, glycols), and boron‐containing fuels (sodium borohydride, ammonia borane). Finally, current challenges and bottlenecks are identified, and potential solutions are proposed.

Chemistry

Machine learning pipeline for denoising low signal-to-noise ratio and out-of-distribution transmission electron microscopy datasets

High-resolution transmission electron microscopy (HRTEM) is crucial for observing material’s structural and morphological evolution at Angstrom scales, but the electron beam can alter these processes. Devices such as CMOS-based direct-electron detectors operating in electron-counting mode can be utilized to substantially reduce the electron dosage. However, the resulting images often lead to a low signal-to-noise ratio, which requires frame integration that sacrifices temporal resolution. Several machine learning (ML) models have been recently developed to successfully denoise HRTEM images. Yet, these models are often computationally expensive, and their inference speeds on GPUs are outpaced by the imaging speed of advanced detectors, precluding in situ analysis. Furthermore, the performance of these denoising models on datasets with imaging conditions that deviate from the training datasets has not been evaluated. To mitigate these gaps, we propose a new self-supervised ML denoising pipeline specifically designed for time-series HRTEM images. This pipeline integrates a blind-spot convolution neural network with pre-processing and post-processing steps, including drift correction and low-pass filtering. Results demonstrate that our model outperforms various other ML and non-ML denoising methods in noise reduction and contrast enhancement, leading to improved visual clarity of atomic features. Additionally, the model is drastically faster than U-Net-based ML models and demonstrates excellent out-of-distribution generalization. The model’s computational inference speed is in the order of milliseconds per image, rendering it suitable for application in in-situ HRTEM experiments.

36 MATERIALS SCIENCE

Simulating hindered grain boundary diffusion using the smoothed boundary method

Abstract Grain boundaries can greatly affect the transport properties of polycrystalline materials, particularly when the grain size approaches the nanoscale. While grain boundaries often enhance diffusion by providing a fast pathway for chemical transport, some material systems, such as those of solid oxide fuel cells and battery cathode particles, exhibit the opposite behavior, where grain boundaries act to hinder diffusion. To facilitate the study of systems with hindered grain boundary diffusion, we propose a model that utilizes the smoothed boundary method to simulate the dynamic concentration evolution in polycrystalline systems. The model employs domain parameters with diffuse interfaces to describe the grains, thereby enabling solutions with explicit consideration of their complex geometries. The intrinsic error arising from the diffuse interface approach employed in our proposed model is explored by comparing the results against a sharp interface model for a variety of parameter sets. Finally, two case studies are considered to demonstrate potential applications of the model. First, a nanocrystalline yttria-stabilized zirconia solid oxide fuel cell system is investigated, and the effective diffusivities are extracted from the simulation results and are compared to the values obtained through mean-field approximations. Second, the concentration evolution during lithiation of a polycrystalline battery cathode particle is simulated to demonstrate the method’s capability.

Materials Science

TRACE Input Modernization

This work presents a Tom’s Obvious Minimal Language (TOML)-based representation of input for the US Nuclear Regulatory Commission’s TRAC/RELAP Advanced Computational Engine (TRACE) thermal hydraulics code. Implemented using the Workbench Analysis Sequence Processor (WASP), the approach maps traditional TRACE input structures to a hierarchical format composed of named parameters, typed values, and native data collections. The resulting representation preserves TRACE’s existing modeling capabilities while providing a modern, structured interface for model development and management. WASP further extends TOML through a file import directive that supports modular model composition and reusable input organization. In addition, WASP provides extended array data entry convenience with various data repeat and interpolation capabilities. Examples of the new TOML syntax are provided for major TRACE input categories, including hydraulic components, heat structures, control systems, and trip logic. The TOML representation establishes a foundation for improved validation, tooling, automation, and model maintainability while remaining compatible with existing TRACE workflows. To facilitate migration to the TOML-based input format, the TRACE executable now supports conversion of native TRACE input into an intermediate JSON representation. A Python utility subsequently transforms the JSON data into an equivalent TOML model. Lastly, the TRACE executable now supports execution using TOML-formatted input.

Lefebvre, Robert A. [Oak Ridge National Laboratory

The Dark Energy Survey supernova program: a reanalysis of cosmology results and evidence for evolving dark energy with an updated Type Ia supernova calibration

We present improved cosmological constraints from a re-analysis of the Dark Energy Survey (DES) 5-year sample of Type Ia supernovae (DES-SN5YR). This re-analysis includes an improved photometric cross-calibration, recent white dwarf observations to cross-calibrate between DES and low-redshift surveys, retraining the salt3 light-curve model and fixing a numerical approximation in the host-galaxy colour law. Our fully recalibrated sample, which we call DES-Dovekie, comprises ~1600 likely Type Ia SNe from DES and ~200 low-redshift SNe from other surveys. With DES-Dovekie, we obtain Ω m = 0.330 ± 0.015 in flat Lambda-cold dark matter (⁠ΛCDM) which changes Ω m by –0.022 compared to DES-SN5YR. Combining DES-Dovekie with cosmic microwave background data from Planck, Atacama Cosmology Telescope, and South Pole Telescope and the DESI DR2 measurements in a flat CDM cosmology, we find ω 0 = –0.803 ± 0.054 and ω a = –0.72 ± 0.21⁠. Our results hold a significance of 3.2σ, reduced from 4.2σ for DES-SN5YR, to reject the null hypothesis that the data are compatible with the cosmological constant. This significance is equivalent to a Bayesian model preference odds of approximately 5:1 in favour of the flat ω 0 ω a CDM model. Using generally accepted thresholds for model preference, our updated data exhibits only a weak preference for evolving dark energy.

dark energy

Deriving the Landauer Principle From the Quantum Shannon Entropy

We derive an expression to determine the equilibrium probability distribution of a quantum state in contact with a noisy thermal environment that formally separates contributions from quantum and classical forms of probabilistic uncertainty. A statistical mechanical interpretation of this probability distribution enables us to derive an expression for the minimum free energy costs for arbitrary (reversible or irreversible) quantum state changes. In conclusion, based on this derivation, we demonstrate that–in contrast to classical systems–the free energy required to erase or reset a qubit depends sensitively on both the fidelity of the target state and on the physical properties of the environment, such as the number of quantum bath states, due primarily to the entropic effects of system-bath entanglement.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Restoration of weak localization in bilayer graphene by a molecular thin film

Quantum coherent effects can be probed in multilayer graphene through electronic transport measurements at low temperatures. In particular, bilayer graphene (BLG) is known to be susceptible to quantum interference corrections of the conductivity, presenting weak localization at all electronic densities, and dependent on different scattering mechanisms such as those related to the trigonal warping of the electron dispersion near the K and K′ valleys. Proximity effects with a molecular thin film influence these scattering mechanisms, which can be quantified through the known theory of magnetoconductance for BLG. Here, we present electronic transport measurements in a copper-phthalocyanine (CuPc) / BLG / hexagonal boron nitride (h-BN) heterostructure that suggest the restoration of weak localization in BLG, associated to a reduction of trigonal warping effects, that are known to suppress weak localization in BLG. Additionally, we observe a charge transfer of 3.6×10 12 cm −2 from the BLG to the molecules, as well as a very small degradation of the mobility of the BLG/h-BN heterostructure upon the deposition of CuPc. The molecular arrangement of the CuPc thin film is characterized in a control sample through transmission electron microscopy, that we relate to the electronic transport results.

bilayer graphene

Charmonium Transport in Heavy-Ion Collisions at the LHC

We provide an update on our semi-classical transport approach for quarkonium production in high-energy heavy-ion collisions, focusing on 𝐽/𝜓 and 𝜓(2𝑆) mesons in 5.02 TeV Pb-Pb collisions at the Large Hadron Collider (LHC) at both forward and mid-rapidity. In particular, we employ the most recent charm-production cross sections reported in pp collisions, which are pivotal for the magnitude of the regeneration contribution, and their modifications due to cold-nuclear-matter (CNM) effects. Multi-differential observables are calculated in terms of nuclear modification factors as a function of centrality, transverse momentum, and rapidity, including the contributions from feeddown from bottom hadron decays. For our predictions for 𝜓(2𝑆) production, the mechanism of sequential regeneration relative to the more strongly bound 𝐽/𝜓 meson plays an important role in interpreting recent ALICE data.

Astronomy & Astrophysics

Recyclable Materials for Resource Constrained Environments

In-space manufacturing exhibits severe limitations in resources as astronauts are only afforded with the materials that are brought on-board the space craft. Consequently, the use of recyclable and re-usable materials is paramount. Researchers at NLR leverage their expertise in polymer and recycling chemistry to develop material systems capable of high performance applications with intentional consideration on multi-life use through chemical recycling, mechanical recycling, bio-degradation, and thermoforming. Disclosed within this poster presentation are highlighted projects that illustrate several recyclable by design material systems that have been developed.

09 BIOMASS FUELS

EvoDiffMol: evolutionary diffusion framework for 3D molecular design with optimized properties

Designing molecules with specific target properties remains a fundamental challenge in computational chemistry. While existing approaches show promise, most rely on simplified representations like SMILES strings or 2D graphs that lack essential three-dimensional geometric information. We present EvoDiffMol, a computational framework that integrates evolutionary algorithms with three-dimensional diffusion models for property-driven molecular generation. The method operates through adaptive evolutionary optimization, where population-based selection guides the generation process toward desired property landscapes. EvoDiffMol supports both unconstrained molecular design and scaffold-constrained generation that preserves fixed substructures while optimizing complementary regions. Comprehensive evaluation demonstrates exceptional performance, achieving the highest drug-likeness score (0.94) among all compared state-of-the-art methods while maintaining excellent validity, uniqueness, and novelty. Beyond single property optimization, the framework demonstrates flexible multi-property optimization capabilities, simultaneously controlling multiple molecular descriptors including synthetic accessibility, lipophilicity, topological polar surface area, and clinically relevant ADMET properties such as cardiotoxicity (hERG) and intestinal permeability (Caco-2). This adaptability spans from simple descriptors to practical pharmaceutical endpoints without requiring complete model retraining. The framework achieves precise control over target property values, generating molecules with properties closely matching specified targets for both single and multiple descriptors. Scaffold-constrained experiments preserve fixed molecular cores while maintaining effective property optimization. The three-dimensional representation offers advantages in maintaining structural validity during iterative optimization, with potential for geometry-aware applications in materials science and drug discovery.

3D molecular generation

Density Functional Theory Analysis of Candidate Tritium Permeation Barriers for Vanadium Alloys as a Fusion Structural Material

Vanadium alloys are being considered as a candidate structural material for the breeder blanket component of future fusion reactors due to their good thermal conductivity, low activation, and chemical compatibility with FLiBe. However, vanadium has a high hydrogen solubility, resulting in hydrogen diffusion and trapping in the vanadium structural alloy and lower than expected tritium breeding ratios. To mitigate the permeation of hydrogen into the structural alloy, a tritium permeation barrier will be coated onto the vanadium alloy. Multiple materials have been proposed as candidate tritium permeation barriers, but the extent to which each of these materials impacts hydrogen diffusion and trapping is still unknown. In this project, we perform atomic-scale calculations to narrow down the list of potential tritium permeation barrier candidates and to understand the mechanisms through which hydrogen diffusion is affected in these materials.

36 MATERIALS SCIENCE

Commercialization of the NLR Hydrogen Wide Area Monitor (HyWAM): Cooperative Research and Development (Final Report)

Hydrogen wide area monitoring refers to the temporal and quantitative 3-dimenasional spatial profiling of hydrogen plumes following either intentional or unintentional hydrogen releases. A hydrogen wide area monitor (HyWAM) would have applications as a research tool, for example to provide empirical data on the behavior of hydrogen dispersions following a release, which in turn can be used to validate modelling studies. Support of modeling studies and commercial applications are interrelated, since modeling can serve to guide HyWAM deployment for enhanced safety within medium to large scale hydrogen operations, such as those envisioned by H2@Scale.

08 HYDROGEN

Software Validation Work With The ZPPR-15 Data

The analysis activities for fast reactors involve using many different pieces of software that are relied upon for their predictive capabilities. For this software to be considered reliable, documented proof that the predictions of the software are accurate is required. In this manuscript, the validation work that covers some of the Argonne software used in fast reactor design activities is discussed and displayed. This validation work includes neutron and gamma flux distributions, reaction rate distributions, and reactivity worth. In an ideal world, a reactor development program would have access to a comprehensive set of experimental facilities to help inform the design aspects of the reactor itself. While thermal-hydraulics experiments, and to a limited degree mechanical experiments, can be carried out today for validation needs, neutronics related experimental facilities are rather impractical because of the lack of experimental facilities. Given the desired time table for construction of new reactors, the reconstitution or creation of new neutronic experimental facilities is untenable and thus those reactor development programs must rely upon any available experimental measurements that are qualitatively similar to the design. While a methodology has been proposed to assess the similarity between the past experimental measurements and the reactor itself, that aspect is beyond the scope of this manuscript. In this manuscript, the focus is entirely placed on the analysis results for a series of experiments carried out at the ZPPR facility in Idaho in the mid-1980s. In this regard, this manuscript only shows the validation of the stated neutronics software for specific loadings of the ZPPR reactor. Because of the fuel form, its proposed enrichment, and the material content of the reactor core, the ZPPR-15 experiments were identified as potential validation data for the reactor. The ZPPR-15 experiments were intended as mockups of a 330 MWe Integral Fast Reactor program which was a follow on program to the Clinch River Breeder Reactor. In the ZPPR-15 series of experiments, measurements of the neutron spectrum, control rod worth, sodium void worth, foil reaction rate distributions, Doppler worth of heated samples, gamma dose, and axial expansion worth were all carried out and published. In many cases, these reactivity coefficients are good candidates to validate the reactivity coefficient calculation scheme used by the analysis software and included in the safety analysis activities of fast reactor development projects today. This manuscript discusses the modeling methodology and accuracy of the calculated experimental results using the LANL software MCNP and the ANL software package ARC (Argonne Reactor Codes). As will be shown, for many of the experimental measurements, the two software packages are found to be good predictive analysis tools for those experiments. In other cases, problems with the analysis methodology or underlying cross section data are exposed which indicates where predictive analysis is not as reliable. Finally, in some of the measurements the conclusion is reached that the experimental measurement cannot be reproduced with the analysis software as it is simply too difficult.

Aliberti, Gerardo

Ultrafast Nanoimaging of Carrier Funneling in Composition-Graded Semiconductor Nanowires

Recent advances in bandgap engineering of low-dimensional semiconductors have enabled high-efficiency carrier transport in miniaturized electronic and optoelectronic devices. The physical properties and functionalities of these materials are governed by complex carrier dynamics coupled with multiple transport mechanisms in tailored band structures. Here, we report ultrafast nanoimaging of carrier funneling and recombination in composition-grade CdSxSe1-x nanowires using pump-probe near-field nanoscopy. Leveraging the high resolution of this technique in both space and time, we resolve nanoscale local carrier dynamics along composition-graded nanowires, revealing the local variation of composition-dependent carrier mobilities and lifetimes that significantly differ from their uniform composition counterparts. Furthermore, we demonstrate a length-dependent behavior wherein shorter nanowires exhibit enhanced funneling effects, accelerating carrier transport by up to 33%. Our findings provide direct visualization of nanoscale carrier transport while supporting an effective approach for investigating complex carrier interactions in inhomogeneous semiconductor nanostructures, with implications for optimizing next-generation optoelectronic devices.

Yang, Rundi

Nuclear Physics Made Very, Very Easy

The fundamental approach to nuclear physics was prepared to introduce basic reactor principles to various groups of non-nuclear technical personnel associated with NERVA Test Operations. NERVA Test Operations functions as the field test group for the Nuclear Rocket Engine Program. Nuclear Engine for Rocket Vehicle Application (NERVA) program is the combined efforts of Aerojet-General Corporation as prime contractor, and Westinghouse Astronuclear Laboratory as the major subcontractor, for the assembly and testing of nuclear rocket engines. Development of the NERVA Program is under the direction of the Space Nuclear Propulsion Office, a joint agency of the U. S. Atomic Energy Commission and the National Aeronautics and Space Administration. This report is being reprinted for use in the U. S. Atomic Energy Commission and National Aeronautics and Space Administration educational and technology utilization programs.

22 GENERAL STUDIES OF NUCLEAR REACTORS

Theoretical perspective on phase stability and polarization switching in ferroelectric hafnia

Fluorite-based ferroelectric materials are revolutionizing the application space of polar semiconductors. These materials leverage robust polarization of extremely thin films, compatibility with the silicon chip processing, and decades of manufacturing experience to enable a new generation of ferroelectric memory devices. As a new paradigm for ferroelectrics, understanding of phase transitions and the switching mechanism in fluorites is essential both for advancing applications and for fundamental science. In this article, we outline the recent progress that has been made to understand the relative phase stability, phase transition and order parameter coupling, ferroelectric switching through unique nucleation and growth processes, and how defects affect these phases and processes. The main challenges, opportunities, and next steps for leveraging these materials for next-generation devices are reviewed.

Condensed Matter Physics