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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

HunStat2 – a simple and low-cost potentiostat with electrochemical impedance spectroscopy capability

We have developed a low-cost (30 USD), simple do-it-yourself (DIY) potentiostat with cyclic voltammetry (CV), open circuit potential (OCP) and electrochemical impedance spectroscopy (EIS) capability. The HunStat2 potentiostat is based on Analog Devices' AD5941 Analog Front End chip, which significantly simplifies the construction of potentiostats for both direct and alternating current (DC and AC, respectively) techniques. Interested readers are provided with circuit diagrams and a bill of materials to build the potentiostat on their own. In addition, control software is also provided free of charge. The software enables acquisition and visualization of data. In summary, HunStat2 introduces a simple and low-cost DIY potentiostat recommended for both analytical and educational purposes.

Vamos, Istvan [Lajos Petrik Vocational Chemistry S↗
DOE OSTI2024

Faraday: A High-temperature Electrolysis Data Explorer

Faraday is a high-temperature electrolysis data visualization tool, which reveals the performance of various button cells under test conditions. These tests and the resulting analytics on their data constitute a state of the industry as the US Department of Energy pushes for the production of hydrogen. Faraday leverages the Idaho National Laboratory's DeepLynx data warehouse to standardize and query button cell data. Faraday programmatically accesses this data in DeepLynx by traversing the schema, represented by a custom ontology. The user interface queries DeepLynx for timeseries data associated with specific button cells in the warehouse, and renders them using JavaScript charts. Additional charting and data analysis techniques are made possible by an auxiliary Python server.

Woodruff, Nathan↗
DOE OSTI2026

AIF for Vis (Active Inference for simulating human interpretation of data visualization) [SWR-26-084]

AIF for Vis contains the Active Inference models and analysis scripts used to study a simple visualization-interpretation task: estimating the average value of two bars in a bar chart. The work is a proof of concept for translating hypothesized cognitive strategies into executable, inspectable process models. We implement two idealized strategies inspired by dual-process accounts of visualization-aided decision making: *Fast model: a compressed, heuristic strategy that estimates the visual midpoint of the two bars and maintains a single belief over their average. *Slow model: a sequential, analytic strategy that estimates the two bar heights separately and maintains them in working memory before computing an average. Both models use a common Active-Inference-inspired framework for sequential perception, belief updating, action selection, and reporting. Their different internal representations produce distinct predicted vulnerabilities: *the Fast model is more susceptible to tick-salience bias; *the Slow model is more susceptible to working-memory decay. The repository includes the model implementations, scripts used for the experiments reported in the paper, precomputed trial-level results, and plotting scripts.

Goldwyn, Harrison [National Laboratory of the Rock↗
DOE OSTI2021

A Focused Ion Beam-Scanning Transmission Electron Microscopy with Energy-Dispersive X-ray Spectroscopy Study on Technetium Incorporation within Iron Oxides through Fe(OH) 2 (s) Mineral Transformation

Incorporation of Tc(IV) into iron oxide/hydroxide minerals has been explored and proposed as a promising pathway to preventing Tc(IV) reoxidation to environmentally mobile pertechnetate (TcO 4 - ) and improving long-term immobilization of radioactive technetium-99 (Tc). However, visual evidence evaluating the distribution of Tc(IV) incorporated within iron oxide/hydroxide phases has not been available, until now, despite potential implications on Tc(IV) stability within the host phase. For the purpose of this study Tc(IV) incorporation into iron oxide/hydroxide phases was facilitated via Fe(OH) 2 (s) oxidation and mineral transformation to magnetite (Fe 3 O 4 ). Focused ion beam - scanning transmission electron microscopy equipped with energy-dispersive X-ray spectroscopy (FIB/STEM-EDS) methods were then combined with X-ray diffraction and absorption spectroscopy techniques to characterize and visually demonstrate that, for the first time, Tc(IV) is heterogeneously incorporated into different iron oxide/hydroxide phases as Tc(IV)-incorporated magnetite and/or TcO 2 ·2H 2 O(s) via different incorporation mechanisms. Heterogeneous distribution of Tc(IV) in magnetite suggests either (i) TcO4- is reduced quickly at the magnetite surface and then encapsulated into magnetite during continued octahedral crystal growth, or (ii) Tc(IV) alternatively partitioned into multiple layers of a blocky, plate-like morphological magnetite structure showing stratified Tc. With limited Tc-hematite (Fe 2 O 3 ) incorporation, the results suggest that TcO 2 ·2H 2 O(s) is formed and mainly associated/embedded in fibrous nanometer-sized polycrystalline hematite. This work highlights the power of modern state-of-the-art FIB/STEM-EDS approach to provide essential visual insights of the Tc-iron oxide/hydroxide incorporation and generate reliable mechanism-informed designs for waste forms relying on Tc mineral incorporation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

K-region tetrasubstituted deep-blue pyrene-based luminogens: Visual detection of trace nitroaniline

In recent years, fluorescence sensors have been widely used in explosive detection due to their portability and high efficiency. Here, in the present work, two K-region tetrasubstituted deep-blue pyrene-based luminogens were designed and synthesized by introducing electron-donating groups. The optical properties were investigated by experimental and density functional theory (DFT) methods. Reasonable luminescence efficiency and electron rich characteristic allowed for the possible detection of nitro-explosives. Both luminogens, especially TFPy, exhibit a sensitive response towards nitroanilines (NA), with a limit of detection (LOD) for p-NA as low as 2.75 × 10 –8 M, which is mainly attributed to the electron-donating substituents on the periphery of the pyrene core and the extended π-conjugated structure. These research results establish a low-cost and simple strategy for the detection of trace nitroaniline.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Building a FAIR data ecosystem for incorporating single-cell transcriptomics data into agricultural genome to phenome research

Introduction The agriculture genomics community has numerous data submission standards available, but the standards for describing and storing single-cell (SC, e.g., scRNA- seq) data are comparatively underdeveloped. Methods To bridge this gap, we leveraged recent advancements in human genomics infrastructure, such as the integration of the Human Cell Atlas Data Portal with Terra, a secure, scalable, open-source platform for biomedical researchers to access data, run analysis tools, and collaborate. In parallel, the Single Cell Expression Atlas at EMBL-EBI offers a comprehensive data ingestion portal for high-throughput sequencing datasets, including plants, protists, and animals (including humans). Developing data tools connecting these resources would offer significant advantages to the agricultural genomics community. The FAANG data portal at EMBL-EBI emphasizes delivering rich metadata and highly accurate and reliable annotation of farmed animals but is not computationally linked to either of these resources. Results Herein, we describe a pilot-scale project that determines whether the current FAANG metadata standards for livestock can be used to ingest scRNA-seq datasets into Terra in a manner consistent with HCA Data Portal standards. Importantly, rich scRNA-seq metadata can now be brokered through the FAANG data portal using a semi-automated process, thereby avoiding the need for substantial expert curation. We have further extended the functionality of this tool so that validated and ingested SC files within the HCA Data Portal are transferred to Terra for further analysis. In addition, we verified data ingestion into Terra, hosted on Azure, and demonstrated the use of a workflow to analyze the first ingested porcine scRNA-seq dataset. Additionally, we have also developed prototype tools to visualize the output of scRNA-seq analyses on genome browsers to compare gene expression patterns across tissues and cell populations. This JBrowse tool now features distinct tracks, showcasing PBMC scRNA-seq alongside two bulk RNA-seq experiments. Discussion We intend to further build upon these existing tools to construct a scientist-friendly data resource and analytical ecosystem based on Findable, Accessible, Interoperable, and Reusable (FAIR) SC principles to facilitate SC-level genomic analysis through data ingestion, storage, retrieval, re-use, visualization, and comparative annotation across agricultural species.

Genetics & Heredity↗
DOE OSTI2025

Immersive Analytics in Critical Spatial Domains: From Materials to Energy Systems

Immersive analytics (IA) leverages virtual reality, augmented reality, and mixed reality to transform how users interact with complex datasets across domains such as science, industry, and education. These immersive technologies offer spatial and multimodal environments that foster intuitive exploration, but they also introduce challenges related to cognitive load, interface design, and system performance. Here, this article presents a comprehensive review of visualization techniques, interaction models, and multimodal inputs utilized in IA. Drawing on case studies in scientific visualization, industrial training, and educational communication, we examine both the potential and limitations of current systems. Finally, we propose future research directions, focusing on real‐time collaboration, adaptive user interfaces, and scalable data exploration strategies to advance the field.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Continuous Emulation and Multiscale Visualization of Traffic Flow Using Stationary Roadside Sensor Data

With the advent of the next-generation traffic monitoring systems, there has been a significant increase in the spatial-temporal resolution of vehicle mobility data in many cities. Effective analysis and visualization of such data can provide transportation planners with data-driven insights, which can facilitate the understanding of multiscale traffic dynamics. In this paper, we present a web-based traffic emulator for emulating and visualizing near-real-time and historical traffic flows on highways using data from road-side sensors. To construct a continuous traffic flow, the emulator adopts an analytical pipeline that can (a) integrate traffic data collected from discrete road-side radar detection sensors, (b) interpolate traffic conditions (vehicle speed and volume) on unmeasured road segments based on traffic flow theory, and (c) generate lane-specific vehicle trajectories and movements using a mathematically optimized representation of the road network. Our app also provides an integrated visual workflow that allows users to explore the interconnected traffic dynamics using an appropriate traffic flow visualization selected based on the level of detail. We devise two innovative geo-visualization techniques that utilize an animated strips-network representation and a lane usage matrix to visualize lane performances. To ensure a smooth emulation of large-scale traffic flow in an easy-to-access web environment, we implement the emulator using client-side GPU-accelerated techniques. Lastly, we close with a case study that visualizes traffic dynamics of two scenarios - an afternoon peak hour and a traffic accident - in Chattanooga, Tennessee. Our app visualizes the responses of traffic dynamics during different traffic conditions, and to the presence of the traffic accident at different spatial scales.

42 ENGINEERING↗
DOE OSTI2018

Automation of Data Collection Methods for Online Monitoring of Nuclear Power Plants

Maintenance activities in the United States nuclear power industry are mainly centered on preventive and corrective maintenance. Predictive maintenance, which is a variable time basis maintenance strategy that is dependent on the condition of the equipment, is less utilized but potentially more effective. In the current maintenance practices, the nuclear power plants rely on manual processes to supply information to a human decision making process. The plants have several processes that generate information that is not typically used beyond the intended target for collecting that information. This information is a source of data that is manually collected by labor intensive tasks. The data is therefore expensive to collect, yet limited in use. The industry has realized the opportunity present in reducing the labor intensive tasks by automating them and increasing the uses of the data collected by either developing advanced predictive maintenance methods using data-driven decision making that could span from trending to machine learning and artificial intelligence. This shift in maintenance strategy may result in high cost saving impact. In addition to reducing labor requirements and frequency of maintenance activities, this shift in strategy will reduce the materials portion of the operations and maintenance cost as well. The aim of this specific effort is to focus on the automation of data collection process. It is part of a series of planned efforts to target multiple elements of migrating the current preventive maintenance approach in nuclear power plants to a data-driven approach. These elements include data collection, management, analysis, visualization, in addition to value analysis and change enabling. The other five elements of migration were not considered because they are planned to be explicitly studied in multiple parallel efforts. Challenges including regulations requirements or limitations are planned in a future effort that focuses on change enabling. The risk and benefit/cost of the approach shift is planned in another effort targeted towards value. The storage, communication, computational power, data architecture, and protection are part of the information infrastructure and are planned in dedicated data management effort. The best means to present the data for assisted human decision making is planned in a data visualization effort. The data interpretation and patterns recognition for machine decision making is planned through multiple efforts in data analytics over the following years. This work identified seventeen data sources collection methods in nuclear power plants that could be automated for an integrated data platform that enables comprehensive and informed decision making. For each of the identified seventeen data sources, the base, modern, and state of the art states were described. The current state of data collection used by most utilities was identified as the "base state". The current achievable state was identified as the "modern state", a state that has either been achieved by at least some US utilities or in other industries. The future state that requires research and development to reach was identified as the "state of the art" state. The described states used an out-of-the-box thinking approach. This effort found that there is a hug potential for task automation and data fidelity improvements by evolving the current industry data collection methods. The majority of the processes analyzed were found to be manual and labor intensive and fell in the base state. As a result, the modern state often targeted reducing the manual logging efforts by using electronic and semi-intelligent means or complementing the work with sensors and mobile or fixed technologies that can reduce the demand of labor activities. The state of the art state involved applications advanced methods of data correlation, data mining, and machine learning along with increasing the spatial distribution and fidelity of data, coupling multiple data sources, and enabling the use of sophisticated mobile devices and machine comprehension methods.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Liquid-to-gas transfer of sodium in a liquid cathode glow discharge

Abstract Plasma-liquid interactions have been extensively studied with a focus on the transport of reactive species from the plasma to the liquid phase and their induced liquid phase chemistry and resulting applications. While solute transfer from the liquid to the gas phase in plasmas has been widely used in analytical chemistry, the underlying processes remain relatively unexplored. We report spatially and temporally resolved absolute density measurements of sodium in a plasma with a NaCl solution cathode using two-photon absorption laser induced fluorescence (TaLIF). The observed non-linear increase in sodium density with solution conductivity is shown to correlate with droplet generation as visualized by Mie scattering. The findings are explained by droplet generation by electrospray induced by Taylor cone formation as underpinning mechanism for the introduction of sodium in the plasma. An analytical sheath model combined with a scaling law shows an increase in electric field force with solution conductivity that is consistent with the observed non-linear increase in sodium density in the plasma with solution conductivity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Role of electron pathway in dimensionally increasing water splitting reaction sites in liquid electrolytes

Hydrogen from water splitting is one of the most promising alternatives for fossil fuels in solving the global energy crisis, while its electrochemical reaction mechanism, especially in liquid electrolytes, remains unclear. Herein, how the electrode conductivity affects the reaction sites of oxygen evolution reactions (OERs) in acidic and alkaline solutions was investigated by employing visualization system and electrochemical testing. Inserting Au nanolayers greatly increased electrode conductivities, improved OER kinetics and reduced cell ohmic resistance, leading to excellent water splitting performances in both acidic and alkaline electrolytes. Furthermore, the in-situ visualization results showed more reaction sites and higher catalyst utilizations were achieved by augmenting the electrode conductivity, and reaction sites increased from 1-dimension to 2-dimension. Additionally, it was discovered that electrical conductivities of acidic and alkaline solutions are insufficient to overcome the sharp drop of potential in the electrical double layer for activating OER uniformly on low-conductivity catalysts, indicating the importance of electrical conductivity of the electrode in acidic and alkaline water electrolyzers. This study provided a guidance on how to develop efficient and compact electrodes for acidic and alkaline water electrolyzer stacks and other electrochemical devices, such as fuel cell, N2 reduction, CO 2 conversion, etc.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Direct atomic fabrication and dopant positioning in Si using electron beams with active real-time image-based feedback

We report that semiconductor fabrication is a mainstay of modern civilization, enabling the myriad applications and technologies that underpin everyday life. However, while sub-10 nanometer devices are already entering the mainstream, the end of the Moore's law roadmap still lacks tools capable of bulk semiconductor fabrication on sub-nanometer and atomic levels, with probe-based manipulation being explored as the only known pathway. Here we demonstrate that the atomic-sized focused beam of a scanning transmission electron microscope can be used to manipulate semiconductors such as Si on the atomic level, inducing growth of crystalline Si from the amorphous phase, reentrant amorphization, milling, and dopant front motion. These phenomena are visualized in real-time with atomic resolution. We further implement active feedback control based on real-time image analytics to automatically control the e-beam motion, enabling shape control and providing a pathway for atom-by-atom correction of fabricated structures in the near future. Lastly, these observations open a new epoch for atom-by-atom manufacturing in bulk, the long-held dream of nanotechnology.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Designing Unmanned Aerial Survey Monitoring Program to Assess Floating Litter Contamination

Monitoring marine contamination by floating litter can be particularly challenging since debris are continuously moving over a large spatial extent pushed by currents, waves, and winds. Floating litter contamination have mostly relied on opportunistic surveys from vessels, modeling and, more recently, remote sensing with spectral analysis. This study explores how a low-cost commercial unmanned aircraft system equipped with a high-resolution RGB camera can be used as an alternative to conduct floating litter surveys in coastal waters or from vessels. The study compares different processing and analytical strategies and discusses operational constraints. Collected UAS images were analyzed using three different approaches: (i) manual counting (MC), using visual inspection and image annotation with object counts as a baseline; (ii) pixel-based detection, an automated color analysis process to assess overall contamination; and (iii) machine learning (ML), automated object detection and identification using state-of-the-art convolutional neural network (CNNs). Our findings illustrate that MC still remains the most precise method for classifying different floating objects. ML still has a heterogeneous performance in correctly identifying different classes of floating litter; however, it demonstrates promising results in detecting floating items, which can be leveraged to scale up monitoring efforts and be used in automated analysis of large sets of imagery to assess relative floating litter contamination.

Almeida, Sílvia (ORCID:0000000320636826)↗
DOE OSTI2020

In-situ visualization of corrosion behavior of Al CoCrFeNi high-entropy alloys during electrochemical polarization

In this study, the corrosion behavior of the Al x CoCrFeNi (x = 0.3, 0.5, 0.7) high-entropy alloys (HEAs) is investigated by an in-situ visualization system. Surface morphology changes on both micro-spatial and temporal scales are monitored in the 3.5 wt% NaCl solution during the potentiodynamic polarization. The microstructures of the Al x CoCrFeNi HEAs are characterized by SEM, EBSD, and EDS. The results show that the microstructure evolves from singe face-centered cubic (FCC) phase to multi-phases by increasing the Al content. The in-situ observations directly reveal the different localized corrosion processes in the AlxCoCrFeNi HEAs. In the single FCC phase Al 0.3 CoCrFeNi HEA, localized corrosion shows in the form of pitting. In the Al 0.5 CoCrFeNi and Al 0.7 CoCrFeNi alloys, which possess FCC and body-centered cubic (BCC) phases, the localized corrosion initiates and propagates in the Cr-depleted BCC phase. In addition, the in-situ visualization uncovers the evolution of current serration, which represents the propagation and repassivation of metastable pit during the polarization. The frequent occurrence of metastable pits indicates distinct repassivation ability of the Al 0.3 CoCrFeNi HEA.

36 MATERIALS SCIENCE↗
DOE OSTI2018

The Lund jet plane

Lund diagrams, a theoretical representation of the phase space within jets, have long been used in discussing parton showers and resummations. We point out that they can be created for individual jets through repeated Cambridge/Aachen declustering, providing a powerful visual representation of the radiation within any given jet. Concentrating here on the primary Lund plane, we outline some of its analytical properties, highlight its scope for constraining Monte Carlo simulations and comment on its relation with existing observables such as the zg variable and the iterated soft-drop multiplicity. We then examine its use for boosted electroweak boson tagging at high momenta. It provides good performance when used as an input to machine learning. Much of this performance can be reproduced also within a transparent log-likelihood method, whose underlying assumption is that different regions of the primary Lund plane are largely decorrelated. This suggests a potential for unique insight and experimental validation of the features being used by machine-learning approaches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Determining Coal Ash Impacts on Radium and Thorium Background Levels in Soil Using Rare Earth Element Analyses - 18604

One challenge at large remediation sites contaminated with radiological materials is differentiating between low-level site-related contamination and NORM. This is because sites contaminated with radiological materials, such as thorium processing and mining and milling facilities, often generate wastes that contain contaminants that are similar to NORM deposits. For sites in urban areas, this issue is further compounded due to the presence of historic industrial fill (historic fill) containing materials such as fly ash, coal ash, and red brick, that exhibit elevated radioactivity levels. These materials often have activity levels near, or even well above, a site's cleanup goal. At a large Superfund Site in the eastern US (Site), many of the suspected Site-related fill areas are commingled with coal and fly ash. As the cleanup criteria for the radionuclides of concern (ROC), radium (Ra) and thorium (Th), is 5 pico-Curies per gram above background, a four-pronged approach was developed to determine if the coal and fly ash are impacting the background levels of the ROCs. This evaluation included a review of boring logs to visually confirm the presence of historic fill, as well as coal fragments and coal ash; a literature review to establish the typical concentrations of Ra and Th found in coal and fly ash from US sources; the use of rare earth analyses to establish chemical signatures for non-Site related historic fill containing coal ash versus Site-related fill; and a quantitative analysis of Site-related data to determine if the radioactivity levels in historic fill containing coal were elevated. Soil samples were collected from two locations at the Site; fill areas containing coal ash that were not suspected to be impacted by Site activities, as well as fill areas containing coal ash that were associated with the former processing facility. These samples were analyzed for rare earth elements (REE), as well as Ra-228 and Th-232 and the ratios of lanthanum, cerium, and neodymium to Ra-228 and Th-232 were established for each sample. Based on a comparison of these data, a strong correlation was established between the rare earth/thorium decay chain ratios and the classification of material as either Site or non-Site related. These data were used to develop a higher background activity for fill areas containing non-Site related NORM. While the cleanup level defined in the Record of Decision remained unchanged, the higher background derived from the fly ash/coal ash material, as identified by REE analyses, resulted in higher project screening levels, which ensured that excavation activities did not 'chase' material that was not Site-related. To date, use of the coal ash background level has saved millions of dollars in cleanup costs since non-Site related contamination is not being remediated. Use of this approach to determine the appropriate background level for a site is relatively straightforward since it relies on visual observation of the soil for coal and fly ash, along with REE analyses, which is an inexpensive, quick, and established analytical method for soil samples. As long as a good rare earth profile of both contaminated and natural (in this case fly ash and coal ash) material can be established, the results can be quite definitive, which could result in significant volume reduction by minimizing the amount of material excavated and disposed of. This will lead to cost and time savings for what could be an otherwise costly and potentially complex excavation. Anyone performing environmental remediation of NORM contaminated sites may benefit from this paper and presentation. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Visual Brick model authoring tool for building metadata standardization

In this study, the Brick ontology is a unified semantic metadata standard for building assets and their relationships, serving as a key enabler for effective interoperability and automation of building systems and analytics. However, creating a Brick model, in other words, standard semantic metadata based on the Brick ontology for a building dataset, can be a complex task. This paper presents two case studies of the creation of Brick models for real-world residential and commercial building datasets, highlighting the challenges during the Brick model creation process. Additionally, the paper introduces VizBrick, an interactive authoring tool for creating semantic building metadata. VizBrick facilitates the creation of Brick models by providing an intuitive visual interface and interactive capabilities, such as keyword search, automatic mapping suggestions, and recommendations. The use of VizBrick is shown to significantly reduce the time and effort required during the Brick model creation process.

42 ENGINEERING↗
DOE OSTI2022

Recent progress in in-situ visualization of electrochemical reactions in electrochemical energy devices

A growing body of evidence indicates that bubble dynamics are crucial performance-limiting factors on electrochemical reactions and energy conversion efficiencies in both half-cell and full cell device levels. This review aims to summarize the recent progress in in-situ visualization characterizations of electrochemical reactions and reactant/product transport in electrochemical energy systems. The latest achievements of various new electrodes, transparent cell designs, and development for simultaneous visualization of reactions at both electrodes and electrolyte/electrode interface are highlighted. The new insights into the influence of bubbles on reaction sites and associated electrochemical performances are discussed. Lastly, some perspectives on potential strategies for mitigating the bubble-induced energy losses are proposed for future research directions and opportunities in water electrolysis and other electrochemical energy systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗