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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 523 records · Page 29

Quantifying Stern layer water alignment before and during the oxygen evolution reaction

While water’s oxygen is the electron source in the industrially important oxygen evolution reaction, the strong absorber problem clouds our view of how the Stern layer water molecules orient themselves in response to applied potentials. Here, we report nonlinear optical measurements on nickel electrodes held at pH 13 indicating a disorder-to-order transition in the Stern layer water molecules before the onset of Faradaic current. A full water monolayer (1.1 × 10 15 centimeter −2 ) aligns with oxygen atoms pointing toward the electrode at +0.8 volt and the associated work is 80 kilojoule per mole. Our experiments identify water flipping energetics as a target for understanding overpotentials, advance molecular electrochemistry, provide benchmarks for electrical double layer models, and serve as a diagnostic tool for understanding electrocatalysis.

Science & Technology - Other Topics↗

Cyber Knowledge Alignment

An automated workflow and introduces new approaches to curate existing cybersecurity knowledge from multiple sources. It also proposes AI/ML-based methods to infer knowledge alignments across different repositories.

Purohit, Sumit [Pacific Northwest National Laborat↗

Robot-Alignment

Fermilab's SRF Robotics group's automated alignment program. FERMILAB-CODE-2026-03-TD

Giffen, Nickolas [Northern Illinois Univ., DeKalb,↗

Regional Source-Type Discrimination Using Nonlinear Alignment Algorithms

The discrimination problem in seismology aims to accurately classify different underground source types based on local, regional, and/or teleseismic observations of ground motion. Typical discriminant approaches are rooted in fundamental, physics-based differences in radiation pattern or wave excitation, which can be frequency-dependent and may not make use of the full waveform. In this article, we explore whether phase and amplitude distances derived from dynamic time warping (DTW) and elastic shape analysis (ESA) can inform event discrimination. We demonstrate the ability to distinguish underground point sources using synthetic waveforms calculated for a 1D Earth model and various source mechanisms. We then apply the method to recorded data from events in the Korean Peninsula, which includes declared nuclear explosions, a collapse event, and naturally occurring earthquakes. Phase and amplitude distances derived from DTW and ESA are then used to classify the event types via dendrogram and k-nearest-neighbor clustering analyses. Using information from the full waveform, we show how different underground sources can be distinguished at regional distances. We highlight the potential of these nonlinear alignment algorithms for discrimination and comment on ways we can extend the framework presented here.

58 GEOSCIENCES↗

Integration of computer vision system to track the alignment SRF cavities into the test cryostat for PIP-II at Fermilab

PIP-II cryomodules use a computer vision system (H-BCAMs system) to monitor the alignment of SRF cavities and focusing lenses during assembly, testing, and operation. This contribution details the integration of the H-BCAMs into the Spoke Test Cryostat (STC) at Fermilab, which is utilized for cold testing SRF cavities prior to their integration into the string assembly. Thermal and structural finite element analyses were employed to estimate the cavities’ deformations, to be validated during cold testing in the STC using H-BCAMs. Notably, this marks the first instance of H-BCAMs integration into a cryostat and operation within a cryogenic environment.

43 PARTICLE ACCELERATORS↗

Eligibility Assessment of Items in the TA-60 Rack Assembly and Alignment Complex Legacy Storage Yard

The U.S. Department of Energy, National Nuclear Security Administration, Los Alamos Field Office (NA-LA), documented and evaluated seven structures in the Technical Area 60 (TA-60) Rack Assembly and Alignment Complex (RAAC) legacy storage yard at Los Alamos National Laboratory (LANL or Laboratory) for listing in the National Register of Historic Places (National Register). This documentation and evaluation was conducted in compliance with Section 106 of the National Historic Preservation Act of 1966, as amended; the Code of Federal Regulations (36 CFR 800); the Programmatic Agreement among the U.S. Department of Energy, National Nuclear Security Administration, Los Alamos Field Office, the New Mexico State Historic Preservation Office and the Advisory Council on Historic Preservation Concerning Management of the Historic Properties at Los Alamos National Laboratory, Los Alamos New Mexico (PA)1; and A Plan for the Management of the Cultural Heritage at Los Alamos National Laboratory, New Mexico (LANL’s Cultural Resources Management Plan (2017). NA-LA makes the following National Register eligibility determinations: la cuna; the rack transporter (jeep, rack trailer, and steering dolly); the Mexia diagnostic rack; the Mexia device canister; the Mexia device mounting stand; and the Mexia target stand are eligible for listing in the National Register, and the second steering dolly is not eligible for listing in the National Register. This National Register evaluation was completed because LANL proposes to develop a consolidated waste facility in TA-60 next to the former RAAC. Across 3.56 acres, LANL proposes to construct an 8,000-square-foot, pre-engineered waste storage building; a 1,500-square-foot office/warehouse building; and 28,500 square feet of covered storage. The development will also include access control features and fencing, parking spaces, and utilities. Additionally, the Laboratory will continue to use the southern part of TA-60-0017 and reuse TA-60-0086 and TA-60-0324 in the development. The consolidated waste facility will operate as a central accumulation area—storing universal waste, mixed low-level (radioactive) waste, hazardous chemicals, and New Mexico special waste—until the waste can be shipped off site.

99 GENERAL AND MISCELLANEOUS↗

Selection of Global Climate Model Data for Downscaling With Generative Machine Learning and Use in the Power Planning for Alignment of Climate and Energy Systems Project

The range of results from climate models and scenarios is important to the understanding of uncertainty in power planning analysis. A U.S. Department of Energy-funded analytic project called Power Planning for Alignment of Climate and Energy Systems is developing data and analytic methods to reflect the effects of climate change on key variables for power system planning, as part of the Grid Modernization Lab Consortium. This project will select and prepare global climate model results for use in power system planning models. A related report (Evaluation of Global Climate Models for Use in Energy Analysis) assesses the performance of various global climate models from the Coupled Model Intercomparison Project Phase 6 data archive for their historical skill with respect to energy system performance and for their future projections under multiple climate change scenarios. Building from that report, we describe the selection of a climate scenario (Shared Socioeconomic Pathway [SSP] 2-4.5) and five climate models: TaiESM1, EC-Earth3-CC, GFDL-CM4, EC-Earth3-Veg, and MPI-ESM1-2-HR. We describe the model selection criteria, which were based on the quality of the match between model results under historical conditions and on the representation of the range of future values for several variables. These results will be downscaled via an open-source generative machine learning method called Super-Resolution for Renewable Energy Resource Data with Climate Change Impacts.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Data Cards for Standardized Metadata Across DOE-Aligned Data Initiatives: Toward Transparent, Interoperable, and Governed Dataset Documentation

As data-intensive research, advanced computing, and artificial intelligence become increasingly central to scientific and operational workflows, the need for consistent, transparent, and machine-actionable documentation has grown correspondingly. Multiple DOE-aligned communities—including Office of Science, Genesis Mission, American Science Cloud (AmSC), National Nuclear Security Administration (NNSA) stewardship and governance, and related cross-laboratory collaborations—have independently developed metadata practices to support discovery, access, reuse, repository deposit, and compliance.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

A Preferences Corpus and Annotation Scheme for Human-Guided Alignment of Time-Series GPTs

The process of time-series forecasting such as predicting trajectories of silicon content in blast furnaces is a difficult task. Most time-series approaches today focus on scalar-type MSE loss optimization. This optimization approach, while widely common, could benefit from the use of human expert or process-level preferences. In this paper, we introduce a novel alignment and fine-tuning approach that involves learning from a corpus of preferred and dis-preferred time-series prediction trajectories. Our contributions include (1) a preference annotation pipeline for time-series forecasts, (2) the application of Score-based Preference Optimization (SPO) to train decoder-only transformers from preferences, and (3) results showing improvements in forecast quality. The approach is validated on both proprietary blast furnace data and the UCI Appliances Energy dataset. The proposed preference corpus and training strategy offer a new option for fine-tuning sequence models in industrial settings.

DPO↗

Field Emission Properties of Cu-Filled Vertically Aligned Carbon Nanotubes Grown Directly on Thin Cu Foils

Copper-filled vertically aligned carbon nanotubes (Cu@VACNTs) were grown directly on Cu foil substrates of 0.1 mm thicknesses at different temperatures via plasma-enhanced chemical vapor deposition (PECVD). By circumventing the need for additional catalyst layers or intensive substrate treatments, our in-situ technique offers a simplified and potentially scalable route for fabricating Cu@VACNTs with enhanced electrical and thermal properties on thin Cu foils. Comprehensive analysis using field emission scanning microscopy (FESEM), transmission electron microscopy (TEM), energy-dispersive X-ray spectroscopy (EDS) mappings, and X-ray diffraction (XRD) revealed uniform Cu filling within the VACNTs across a range of synthesis temperatures (650 °C, 700 °C, and 760 °C). Field emission (FE) measurements of the sample synthesized at 700 °C (S700) showed low turn-on and threshold fields of 2.33 V/μm and 3.29 V/μm, respectively. The findings demonstrate the viability of thin Cu substrates in creating dense and highly conductive Cu-filled VACNT arrays for advanced electronic and nanoelectronics applications.

36 MATERIALS SCIENCE↗

Vertically Aligned Carbon Nanotubes Grown on Copper Foil as Electrodes for Electrochemical Double Layer Capacitors

This study reports a binder-free, catalyst-free method for fabricating vertically aligned carbon nanotubes (VACNTs) directly on copper (Cu) foil using plasma-enhanced chemical vapor deposition (PECVD) for electrochemical double-layer capacitor (EDLC) applications. This approach eliminates the need for catalyst layers, polymeric binders, or substrate pre-treatments, simplifying electrode design and enhancing electrical integration. The resulting VACNTs form a dense, uniform, and porous array with strong adhesion to the Cu substrate, minimizing contact resistance and improving conductivity. Electrochemical analysis shows gravimetric specific capacitance (C grav ) and areal specific capacitance (C areal ) of 8 F g −1 and 3.5 mF cm −2 at a scan rate of 5 mV/s, with low equivalent series resistance (3.70 Ω) and charge transfer resistance (0.48 Ω), enabling efficient electron transport and rapid ion diffusion. The electrode demonstrates excellent rate capability and retains 92% of its initial specific capacitance after 3000 charge–discharge cycles, indicating strong cycling stability. These results demonstrate the potential of directly grown VACNT-based electrodes for high-performance EDLCs, particularly in applications requiring rapid charge–discharge cycles and sustained energy delivery.

25 ENERGY STORAGE↗

On the Need to Align Intent and Implementation in Uncertainty Quantification for Machine Learning

Quantifying uncertainties for machine learning (ML) models is a foundational challenge in modern data analysis. This challenge is compounded by at least two key aspects of the field: (a) inconsistent terminology surrounding uncertainty and estimation across disciplines, and (b) the varying technical requirements for establishing trustworthy uncertainties in diverse problem contexts. In this position paper, we aim to clarify the depth of these challenges by identifying these inconsistencies and articulating how different contexts impose distinct epistemic demands. We examine the current landscape of estimation targets (e.g., prediction, inference, simulation-based inference), uncertainty constructs (e.g., frequentist, Bayesian, fiducial), and the approaches used to map between them. Drawing on the literature, we highlight and explain examples of problematic mappings. To help address these issues, we advocate for standards that promote alignment between the \textit{intent} and \textit{implementation} of uncertainty quantification (UQ) approaches. We discuss several axes of trustworthiness that are necessary (if not sufficient) for reliable UQ in ML models, and show how these axes can inform the design and evaluation of uncertainty-aware ML systems. Our practical recommendations focus on scientific ML, offering illustrative cases and use scenarios, particularly in the context of simulation-based inference (SBI).

Trivedi, Shubhendu [MIT] (ORCID:0000000312374301)↗

Simple optical system used to align spectrograph

Optically fast, portable spectrograph incorporates auxiliary optics in a boresight technique to use the zero order of the grating for visual alignment. This device obtains moderately resolved spectra of a multitude of light sources.

Exton, R. J.↗

Self-aligning fixture used in lathe chuck jaw refacing

Self-aligning tool positions and rigidly holds lathe chuck jaws for refacing and truing of the clamping surface. The jaws clamp the fixture in the manner of clamping a workpiece. The fixture can be modified to accommodate four-jawed checks.

Linn, C. C.↗