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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 307 records · Page 17

Entrapment Behavior of Solid Surrogate Fission Products at Engineered UN Nano‐Hetero‐Interfaces Within Metallic Nuclear Fuels

Nanometric hetero-interfaces provide a wealth of scientific and engineering opportunities due to their complex and often misunderstood properties that can differ from their respective bulk constituents. In this work, the ability for engineered nanostructures within a bulk U─Mo alloy to arrest simulant fission products is investigated experimentally and computationally. Nanostructured 90 wt% U/ 10 wt% Mo (U-10Mo) with 7.1 at% Nd is consolidated using spark-plasma- sintering (SPS) techniques and is heat-treated at 500 °C under vacuum for 24, 100, 500, and 1000 h. Analysis on the sintered and heat-treated U-10Mo reveals rapid kinetics in Nd diffusion to nanocluster sites, with evidence of Nd diffusion occurring during sintering and during the following heat-treatment. The segregation behavior of Nd at two different U─Mo/UN interfaces is computationally verified using density functional theory (DFT) to reinforce experimental data.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Opportunities for retrieval and tool augmented large language models in scientific facilities

Upgrades to advanced scientific user facilities such as next-generation x-ray light sources, nanoscience centers, and neutron facilities are revolutionizing our understanding of materials across the spectrum of the physical sciences, from life sciences to microelectronics. However, these facility and instrument upgrades come with a significant increase in complexity. Driven by more exacting scientific needs, instruments and experiments become more intricate each year. This increased operational complexity makes it ever more challenging for domain scientists to design experiments that effectively leverage the capabilities of and operate on these advanced instruments. Large language models (LLMs) can perform complex information retrieval, assist in knowledge-intensive tasks across applications, and provide guidance on tool usage. Using x-ray light sources, leadership computing, and nanoscience centers as representative examples, we describe preliminary experiments with a Context-Aware Language Model for Science (CALMS) to assist scientists with instrument operations and complex experimentation. With the ability to retrieve relevant information from facility documentation, CALMS can answer simple questions on scientific capabilities and other operational procedures. With the ability to interface with software tools and experimental hardware, CALMS can conversationally operate scientific instruments. By making information more accessible and acting on user needs, LLMs could expand and diversify scientific facilities’ users and accelerate scientific output.

97 MATHEMATICS AND COMPUTING↗

ChemGraph as an agentic framework for computational chemistry workflows

Atomistic simulations are essential in chemistry and materials science but remain challenging to run due to the expert knowledge required for the setup, execution, and validation stages of these calculations. We present ChemGraph, an agentic framework powered by artificial intelligence and state-of-the-art simulation tools to streamline and automate computational chemistry and materials science workflows. ChemGraph leverages graph neural network-based foundation models for accurate yet computationally efficient calculations and large language models (LLMs) for natural language understanding, task planning, and scientific reasoning to provide an intuitive and interactive interface. We evaluate ChemGraph across 13 benchmark tasks and demonstrate that smaller LLMs (GPT-4o-mini, Claude-3.5-haiku, Qwen-2.5-14B) perform well on simple workflows, while more complex tasks benefit from using larger models. Importantly, we show that decomposing complex tasks into smaller subtasks through a multi-agent framework enables GPT-4o to reach perfect accuracy and smaller LLMs to match or exceed single-agent GPT-4o's performance in these benchmarks.

Computational chemistry↗

Massive all-atom analysis of 2D materials with quantum properties (Final report)

Improvements in microscopy have enabled the acquisition of data at a scale that is difficult to process manually, making automated machine learning approaches to analyzing experimental images essential. In this project, we developed and applied machine learning (ML) workflows for atomic resolution scanning transmission electron microscopy (STEM) images. This development included improving both methodology as well as generating user-friendly codes. We developed machine learning architectures which, after training, automatically identify the location and types of defects throughout a material. We used these data to produce class-averaged images of 2D atomic coordinates with up to 0.3 pm precision, uncovering the structure and oscillations of long-range strain fields around point defects in WSe 2-2x Te 2x . We also resolved a long-standing problem in this field in the training of ML models, a lack of labeled experimental data, by developing a cycle-GAN that transformed simulated-generated labeled data into labeled data indistinguishable from experiment and therefore suitable for training. This removed the remaining parts of the ML data processing workflow where human intervention was still critical and therefore a bottleneck to working at scale. Codes have been developed and released for this full machine learning workflow. ML approaches to partially automate STEM acquisition were also developed. Finally we applied ML and other advanced data processing methods to several materials science problems in two-dimensional materials, including studying the evolution of hyperuniformity with defect concentration in WSe2, understanding phase transformations in transition metal dichalcogenides during in-situ heating in the STEM, and exploring how 2D interfaces transform from twisted into aligned structures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Chemical Imaging for In Situ Detection and Discrimination of Aquatic Toxins Targeting Voltage Gated Sodium Channels

Biologically derived neurotoxins from cyanobacteria and algae impact environmental resources in addition to being considered a potential biological threat to human and animal health. Activity based assays are essential to detecting and responding to toxic neurotoxin events either naturally occurring or deliberate. Two toxins of interest include saxitoxin and brevetoxin. These toxins bind to and alter the function of voltage-gated sodium channels (NaV channels) which are essential for generating cell membrane action potential. We report the development and refinement of a System for Analysis at Liquid Vacuum Interface (SALVI) to assess the functional activity of saxitoxin and brevetoxin. This approach utilizes a vacuum-compatible microfluidic reactor that permits analysis at the liquid vacuum interface of human derived cells with a neurotoxin of interest in a biologically relevant environment.

54 ENVIRONMENTAL SCIENCES↗

Nano-Plasticity of an Electrified Ionic Liquid/Electrode Interface: Uncovering Hard–Soft Structuring via Controlled Metal Fill Factor

Here, ionic liquids (ILs) nanostructuring at electrified interfaces is of both fundamental and practical interest as these materials are increasingly gaining prominence in energy storage and conversion processes. However, much remains unresolved about IL potential-controlled (re)organization under highly polarized interfaces, mostly due to the difficulty of selectively probing both the distal and proximal surface layers of adsorbed ions. In this work, the structural dynamics of the innermost layer (<10 nm from the surface) were independently interrogated from that of the ionic layers in the sub-surface region (>100 nm from the surface), using an infrared (IR) spectroscopy approach. By tuning the metal fill factor of gold films deposited on conductive metal oxide-modified IR internal reflection elements, the charge-driven (re)structuring of the inner and distal layers of 1-butyl-1-methylpyrrolidinium trifluoromethanesulfonate is unveiled. Within a relatively wide potential region (~±1 V) bounding the potential of zero charges, the ionic liquid is shown to undergo a reversible (i.e., soft) reorganization whereby the innermost layer of anions (cations) is exchanged by a layer of cations (anions). Kinetically unhindered changes in the number density of constituent cations and anions largely follow electrostatic expectations in the subsurface region, whereas the innermost layer exhibits a pronounced hysteresis and very slow relaxation. Under larger negative potential bias, IL restructuring is characterized by a highly irreversible (i.e., hard) and intense interfacial densification of the BMPy + cations, consistent with the formation of nanoscale segregated liquids. The outcomes of this work reveal a plastic IL nanostructuring under a strong electric field.

36 MATERIALS SCIENCE↗

Enhancing corrosion resistance of lightweight metal alloys through laser shock peening

In this study, we investigated the effects of laser shock peening (LSP) on the corrosion resistance of lightweight metal alloys, specifically AA6061 and AZ31. LSP was performed underwater, using a nanosecond pulse laser and without using a protective coating or layer on the workpiece. The corrosion behaviors of these alloys were analyzed through electrochemical tests, including open circuit potential, electrochemical impedance spectroscopy, and potentiodynamic polarization measurements. The results demonstrated that LSP significantly improved the polarization resistance, and higher laser power intensities led to increased corrosion resistance and reduced corrosion rates. This enhancement in anti-corrosion performance is attributed to the formation of a protective oxide layer on the surface, acting as a barrier against corrosion. In conclusion, the findings underscore the potential of laser surface treatment as a viable technique for enhancing the corrosion resistance of lightweight metal alloys.

36 MATERIALS SCIENCE↗

Perovskite Grown in Gallium Nitride Nanowire Matrix for Stable and High‐Efficiency X‐Ray Detection

High-quality quasi-2D perovskites in a GaN nano-wire matrix are grown to build a 3D hetero-structure for high-performance X-ray sensing. In the 3D hetero-structure, GaN nano-wire matrix serves as an n-type charge collector that can rapidly extract carriers through the bulk film of the perovskite layer. Together with a p-type top electrode, a p–i–n diode with the 3D hetero-structure is built, that exhibits a rectified current–voltage characteristic. After analyzing the interface energy alignment, it is found that the fermi levels of the perovskite and GaN are aligned in the dark, and a quasi-fermi level splits upon illumination, introducing a built-in electrical field at the interface. As a result, strong photo-induced current is observed from the diode without an external field. Finally, the 3D diode for X-ray detection demonstration is used, revealing a sensitivity of 308.9 µC Gy air -1 cm -2 at an exceptionally low applied field of 0.125 V µm -1 . The X-ray-induced signal from the 3D diode is stable after 155 cycles of X-ray irradiation under a constant electric field. This demonstration informs a new 3D architecture for high-performance X-ray sensing, and it shows that GaN is a robust n-type interface for perovskite optoelectronic devices.

36 MATERIALS SCIENCE↗

ToF-SIMS spectral data analysis of Paenibacillus sp. 300A biofilms and planktonic cells

Analysis of bacterial biofilms is particularly challenging and important with diverse applications from systems biology to biotechnology. Among the variety of techniques that have been applied, time-of-flight secondary ion mass spectrometry (ToF-SIMS) has many promising features in studying the surface characteristics of biofilms. ToF-SIMS offers high spatial resolution and high mass accuracy, which permit surface sensitive analysis of biofilm components. Thus, ToF-SIMS provides a powerful solution to addressing the challenge of bacterial biofilm analysis. This dataset covers ToF-SIMS analysis of Paenibacillus sp. 300A (300A) isolated from the Hanford site in Richland, WA. The strain is known to have metal and sulfur reducing properties and can be used for bioremediation, wastewater treatment, bioengineering and technology development. There is a current need to identify small molecules and fragments produced from bacterial biofilms. Static ToF-SIMS spectra of 300A were obtained using an IONTOF TOF-SIMS V instrument equipped with a 25 keV Bi 3 + metal ion gun. Identified molecules and molecular fragments are compared against known biological databases and the reported peaks have at least 65 ppm mass accuracy. These molecules range from lipids and fatty acids to flavonoids, quinolones, and other naturally occurring organic compounds. It is anticipated that the spectral identification of key peaks will assist detection of metabolites, extracellular polymeric substance molecules like polysaccharides, and biologically relevant small molecules using ToF-SIMS in future surface and interface research of bacterial biofilms.

Biofilms↗

Adsorption-Induced Surface Magnetism

We report the emergence of adsorption-induced magnetism from heterohelicene molecules on a nonmagnetic Cu(100) surface. Spin-polarized low-energy electron microscopy measurements reveal spin-dependent electron reflectivity for enantiopure 7,12,17-trioxa[11]helicene (TO[11]H) monolayers, indicating the formation of a spin-polarized state localized in the topmost copper layer. Control experiments on clean Cu(100) and TO[11]H on highly oriented pyrolytic graphite show no such effect, excluding artifacts and chirality-induced spin selectivity as origins. Spin-polarized density functional theory calculations with hybrid functionals attribute the magnetism to strong chemisorption, which induces hybridization between the molecular HOMO and copper s- and d-states, driving asymmetric spin-polarized charge redistribution at the interface. An extended Newns-Anderson-Grimley model incorporating on-site Coulomb repulsion in Cu d-orbitals reproduces the emergence of interfacial spin polarization above a threshold interaction strength, highlighting the key roles of hybridization parameters and Coulomb correlation. These findings reveal a mechanism for inducing magnetism at molecule-metal interfaces without inherently magnetic components, offering avenues for engineering spin-polarized states in organic-inorganic hybrid systems.

Hubbard model↗

Label-based Virtual Directories In dCache

Traditional filesystems organize data in directories. These directories are typically a collection of files whose grouping is based on a single criterion, e.g., the starting date of an experiment, experiment name, beamline ID, measurement device, or instrument. However, each file in a directory can belong to several logical groups, such as a special event type, experiment condition, or a part of a selected dataset. dCache is a storage system developed to store large amounts of scientific data, used by many HEP and Photon Science experiments. With recent developments in dCache, we have introduced a concept of file tagging, which dynamically groups files with the same label into virtual directories. The file labels can be added, removed, renamed, and deleted through the admin interface or via REST API. The files in virtual directories are exposed through all protocols supported by dCache. This contribution will describe the details of the implementation for file tagging in dCache and present our future development plans on automatic metadata extractions, a feature that will significantly simplify data management. Additionally, we are exploring the future use of virtual directories as a way to translate scientific data catalogs into filesystem views for direct data analysis.

Sahakyan, Marina [DESY]↗

Final Technical Report for DE-SC0021049: Manipulating interfacial reactivity with atomically layered heterostructures

This final technical report summarizes the work accomplished in this DOE Early Career Research Program project that has established moiré superlattice materials and two-dimensional (2D) heterostructures as a highly tunable platform for controlling heterogeneous charge transfer (ET) kinetics at solid-liquid interfaces. By precisely engineering van der Waals heterostructures of atomically thin 2D materials, particularly bilayer and trilayer graphene with controlled twist angles, this project demonstrated systematic control of interfacial charge transfer rates spanning three orders of magnitude. This research addresses fundamental questions about how electronic structure, charge localization, and atomic layer-dependent properties govern charge transfer at electrochemical interfaces, with broad implications for energy conversion, electrocatalysis, and next-generation electrochemical devices.

36 MATERIALS SCIENCE↗

Hands-On, Heads-Up: Blending Cyber T&E with Data Science-Driven Training in Jupyter Notebooks

In an era of increasingly sophisticated threats to critical infrastructure, cybersecurity professionals must be more than just aware; they must be immersed, agile, and equipped to operate in environments where failure is not an option. Nowhere is this truer than in the nuclear sector, where cyber-physical systems, regulatory scrutiny, and insider threat potential demand a new generation of hands-on, technically fluent defenders. This paper presents a unified training approach that integrates Cybersecurity Test and Evaluation (T&E) with data science techniques using Jupyter Notebooks as the interactive lab environment. The program centers on a modular, scenario-driven curriculum designed to build not just knowledge but practical capability in the assessment and defense of radiation detection systems, firmware interfaces, and operational security postures.

98 - NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL↗

Influence of surface chemistry on Li nucleation energetics on graphene-based surfaces

Lithium metal is a promising high-capacity anode material for solid-state batteries, but it typically suffers from poor cyclability. Carbon scaffold hosts have the potential to improve this performance due to their high electronic conductivity and large surface area, which facilitates lithium-ion adsorption and desorption. Scaffold surface chemistry is known to significantly influence performance outcomes, but the details of these interactions are not fully understood. Here, this study employs first-principles simulations to explore lithium transport and nucleation on graphene anodes with various surface chemistries. Using enhanced sampling techniques, ab initio molecular dynamics, and density functional theory calculations, we find that although surface chemistry has a minimal impact on lithium interfacial transport, it influences surface nucleation significantly. Both heteroatom dopants and intrinsic defects lower the nucleation barrier, creating a more favorable environment for lithium nucleation compared to pristine graphene. In addition, our results reveal a complex interplay between surface lithium concentration, lithium transport, and nucleation kinetics. These findings highlight the potential of surface modifications to precisely control nucleation processes on carbon-based anodes and provide design guidance for reducing dendrite formation and improving the cycle life of solid-state batteries.

36 MATERIALS SCIENCE↗

Rising Water Levels and Vegetation Shifts Drive Substantial Reductions in Methane Emissions and Carbon Dioxide Uptake in a Great Lakes Coastal Freshwater Wetland

ABSTRACT Coastal freshwater wetlands are critical ecosystems for both local and global carbon cycles, sequestering substantial carbon while also emitting methane (CH 4 ) due to anoxic conditions. Estuarine freshwater wetlands face unique challenges from fluctuating water levels, which influence water quality, vegetation, and carbon cycling. However, the response of CH 4 fluxes and their drivers to altered hydrology and vegetation remains unclear, hindering mechanistic modeling. To address these knowledge gaps, we studied an estuarine freshwater wetland in the Great Lakes region, where rising water levels led to a vegetation shift from emergent Typha dominance in 2015–2016 to floating‐leaved species in 2020–2022. Using eddy covariance flux measurements during the peak growing season (June–September) of both periods, we observed a 60% decrease in CH 4 emissions, from 81 ± 4 g C m −2 in 2015–2016 to 31 ± 3 g C m −2 in 2020–2022. This decline was driven by two main factors: (1) higher water levels, which suppressed ebullitive fluxes via increased hydrostatic pressure and extended CH 4 residence time, enhancing oxidation potential in the water column; and (2) reduced CH 4 conductance through plants. Net carbon dioxide (CO 2 ) uptake decreased by 90%, from −267 ± 26 g C m −2 in 2015–2016 to −27 ± 49 g C m −2 in 2020–2022. Additionally, diel CH 4 flux patterns shifted, with a distinct morning peak observed in 2015–2016 but absent in 2020–2022, suggesting changes in plant‐mediated transport and a potential decoupling from photosynthesis. The dominant factors influencing CH 4 fluxes shifted from water temperature and gross primary productivity in 2015–2016 to atmospheric pressure in 2020–2022, suggesting an increased role of ebullition as a primary transport pathway. Our results demonstrate that changes in water levels and vegetation can substantially alter CH 4 and CO 2 fluxes in coastal freshwater wetlands, underscoring the critical role of hydrological shifts in driving carbon dynamics in these ecosystems.

54 ENVIRONMENTAL SCIENCES↗

Application of printed strain gauges in prototypical nuclear reactor conditions

This report discusses the current development and testing of additively manufactured temperature sensors and resistive/ capacitive strain gauges. This has potential to improve the sensor design and manufacturing techniques to meet the requirements of in-pile monitoring of mechanical properties and structural health of materials and specimens in current and advanced nuclear test reactors (i.e., in terms of environment conditions, sample geometry, and materials compatibility). The developmental additively manufactured strain gauges are exposed to separate effects testing (i.e., mechanical strain (up to 1000 µe), high temperature (up to 700 °C)) to determine environmental factors that affect the performance of the strain gauge. The robustness and integrity of a printed strain gauge layer exposed to a molten salt environment for up to 500 hours was evaluated, with the goal of assessing material compatibility of printed strain sensors for instrumented surveillance test articles in molten salt reactors. In addition, sensor qualification methodologies are further developed for determining the reliability and robustness at the interface of the additively manufactured strain gauge materials.

36 - MATERIALS SCIENCE↗

SQMS Nanofabrication Taskforce: Towards Fabrication of High Coherence Superconducting Qubits

SQMS Nanofabrication Taskforce, which brings together experts in nanofabrication and materials science at the SQMS Center, has been launched to implement novel materials, substrates, and fabrication techniques for high coherence superconducting quantum devices. In a first coordinated effort, the Nanofabrication Taskforce developed fabrication processes to eliminate the lossy materials at surfaces and interfaces of superconducting qubits to enhance qubit coherence. The initial results of this study demonstrated T1 enhancement by almost an order of magnitude with best T1 s reaching ~ 600 $\mu$s. [1] We attribute this improvement to the replacement of lossy native Nb oxide layer with native Ta oxide, which is thinner and less disordered. we are now currently working on strategies with an aim towards moving qubit coherence times to millisecond timescales and beyond. The results of a systematic study will be presented to address substrate preparation, alternative materials as low loss platforms (Nb, Ta, and Re), novel non-oxide forming low loss capping layers such as proximitized Au, optimized qubit designs, and optimized Josephson junction materials, processing, and design.

Bal, Mustafa↗