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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

TangibleData: Interactive Data Visualization with Mid-Air Haptics

In this paper, we investigate the effects of mid-air haptics in interactive 3D data visualization. We build an interactive 3D data visualization tool that adapts hand gestures and mid-air haptics to provide tangible interaction in VR using ultrasound haptic feedback on 3D data visualization. We consider two types of 3D visualization datasets and provide different data encoding methods for haptic representations. Two user experiments are conducted to evaluate the effectiveness of our approach. The first experimental results show that adding a mid-air haptic modality can be beneficial regardless of noise conditions and useful for handling occlusion or discerning density and volume information. The second experiment results further show the strengths and weaknesses of direct touch and indirect touch modes. Our findings can shed light on designing and implementing a tangible interaction on 3D data visualization with mid-air haptic feedback.

Bhardwaj, Ayush↗
DOE OSTI2021

RCSB Protein Data Bank: Celebrating 50 years of the PDB with new tools for understanding and visualizing biological macromolecules in 3D

We report the Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), funded by the US National Science Foundation, National Institutes of Health, and Department of Energy, has served structural biologists and Protein Data Bank (PDB) data consumers worldwide since 1999. RCSB PDB, a founding member of the Worldwide Protein Data Bank (wwPDB) partnership, is the US data center for the global PDB archive housing biomolecular structure data. RCSB PDB is also responsible for the security of PDB data, as the wwPDB-designated Archive Keeper. Annually, RCSB PDB serves tens of thousands of three-dimensional (3D) macromolecular structure data depositors (using macromolecular crystallography, nuclear magnetic resonance spectroscopy, electron microscopy, and micro-electron diffraction) from all inhabited continents. RCSB PDB makes PDB data available from its research-focused RCSB.org web portal at no charge and without usage restrictions to millions of PDB data consumers working in every nation and territory worldwide. In addition, RCSB PDB operates an outreach and education PDB101.RCSB.org web portal that was used by more than 800,000 educators, students, and members of the public during calendar year 2020. This invited Tools Issue contribution describes (i) how the archive is growing and evolving as new experimental methods generate ever larger and more complex biomolecular structures; (ii) the importance of data standards and data remediation in effective management of the archive and facile integration with more than 50 external data resources; and (iii) new tools and features for 3D structure analysis and visualization made available during the past year via the RCSB.org web portal.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Visualizing Intrinsic 3D-Strain Distribution in Gold Coated ZnO Microstructures by Bragg Coherent X-Ray Diffraction Imaging and Transmission Electron Microscopy with Respect to Piezotronic Applications

Novel devices ranging from bio magnetic field sensors to energy harvesting nano machines utilize the piezotronic effect. For optimal function, understanding the interaction of electrical and strain phenomena within the semiconductor crystal is necessary. Here, studies of a model piezotronic system are presented, consisting of a ZnO microrod coated by a thin layer of gold, which forms a Schottky contact with the piezoelectric ZnO material. Coherent X-ray diffraction imaging (CXDI) and transmission electron microscopy (TEM) are used to visualize the structure and strain distribution, showing that the ZnO microrod exhibits strains of multiple origins in the bulk and at the interface. Strain values of -6 × 10 -4 have been measured by CXDI at the ZnO/Au interface. The origin is shown to be a combination of an interface strain, possibly caused by the Schottky contact formation, and distinct, localized electrical fields inside the crystal which are assigned to electron depletion and screening in a bent ZnO/Au piezotronic rod. These findings will contribute to sensor development and to a better understanding of piezotronic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

DeepLynx Ecosystem 2025

Poor data integration and governance continue to plague complex engineering projects, resulting in missed cost, schedule, and performance targets. Departments operate in isolated systems with manual data exchange, creating fragmented information that compounds errors and leads to significant delays and cost overruns. The DeepLynx ecosystem addresses these challenges through an open-source, modular data management platform that transforms fragmented project data into an integrated digital thread. Built on a federated microservice architecture, the ecosystem comprises seven specialized tools centered around DeepLynx Nexus, a unified data catalog with hierarchical organization and graph-based navigation capabilities. The ecosystem includes: DeepLynx Stream for real-time timeseries data ingestion from industrial sources; DeepLynx Ingest for governed data uploads with formal review workflows; DeepLynx Lattice for ontology-based entity and relationship extraction; DeepLynx Run for workflow orchestration and secure AI/ML compute; DeepLynx Visualize for 3D digital twin visualization; and DeepLynx Insight for AI-assisted document analysis with traceable, grounded responses. Deployable in cloud, on-premise, or hybrid environments using containerized Docker applications and Helm charts, the DeepLynx ecosystem provides flexible infrastructure that adapts to organizational requirements. By consolidating project data into a unified data lake with role-based access controls and OAuth2 authentication, DeepLynx enables digital thread and digital twin capabilities that improve decision-making, reduce risk, and support complex engineering workflows throughout the project lifecycle.

42 - ENGINEERING↗
DOE OSTI2022

A deep learning approach for semantic segmentation of unbalanced data in electron tomography of catalytic materials

In computed TEM tomography, image segmentation represents one of the most basic tasks with implications not only for 3D volume visualization, but more importantly for quantitative 3D analysis. In case of large and complex 3D data sets, segmentation can be an extremely difficult and laborious task, and thus has been one of the biggest hurdles for comprehensive 3D analysis. Heterogeneous catalysts have complex surface and bulk structures, and often sparse distribution of catalytic particles with relatively poor intrinsic contrast, which possess a unique challenge for image segmentation, including the current state-of-the-art deep learning methods. To tackle this problem, we apply a deep learning-based approach for the multi-class semantic segmentation of a γ-Alumina/Pt catalytic material in a class imbalance situation. Specifically, we used the weighted focal loss as a loss function and attached it to the U-Net’s fully convolutional network architecture. We assessed the accuracy of our results using Dice similarity coefficient (DSC), recall, precision, and Hausdorff distance (HD) metrics on the overlap between the ground-truth and predicted segmentations. Our adopted U-Net model with the weighted focal loss function achieved an average DSC score of 0.96 ± 0.003 in the γ-Alumina support material and 0.84 ± 0.03 in the Pt NPs segmentation tasks. We report an average boundary-overlap error of less than 2 nm at the 90th percentile of HD for γ-Alumina and Pt NPs segmentations. The complex surface morphology of γ-Alumina and its relation to the Pt NPs were visualized in 3D by the deep learning-assisted automatic segmentation of a large data set of high-angle annular dark-field (HAADF) scanning transmission electron microscopy (STEM) tomography reconstructions.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Quantitative visualization of synchronized insulin secretion from 3D-cultured cells

Quantitative visualization of synchronized insulin secretion was performed in an isolated rat pancreatic islet and a spheroid of rat pancreatic beta cell line using a method of video-rate bioluminescence imaging. Video-rate images of insulin secretion from 3D-cultured cells were obtained by expressing the fusion protein of insulin and Gaussia luciferase (Insulin-GLase). A subclonal rat INS-1E cell line stably expressing Insulin-GLase, named iGL, was established and a cluster of iGL cells showed oscillatory insulin secretion that was completely synchronized in response to high glucose. Furthermore, we demonstrated the effect of an antidiabetic drug, glibenclamide, on synchronized insulin secretion from 2D- and 3D-cultured iGL cells. The amount of secreted Insulin-GLase from iGL cells was also determined by a luminometer. Thus, our bioluminescence imaging method could generally be used for investigating protein secretion from living 3D-cultured cells. In addition, iGL cell line would be valuable for evaluating antidiabetic drugs. - Highlights: • An imaging method for protein secretion from 3D-cultured cells was established. • The fused protein of insulin to GLase, Insulin-GLase, was used as a reporter. • Synchronous insulin secretion was visualized in rat islets and spheroidal beta cells. • A rat beta cell line stably expressing Insulin-GLase, named iGL, was established. • Effect of an antidiabetic drug on insulin secretion was visualized in iGL cells.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Strain and crystallographic identification of the helically concaved gap surfaces of chiral nanoparticles

Identifying the three-dimensional (3D) crystal plane and strain-field distributions of nanocrystals is essential for optical, catalytic, and electronic applications. However, it remains a challenge to image concave surfaces of nanoparticles. Here, we develop a methodology for visualizing the 3D information of chiral gold nanoparticles ≈ 200 nm in size with concave gap structures by Bragg coherent X-ray diffraction imaging. The distribution of the high-Miller-index planes constituting the concave chiral gap is precisely determined. The highly strained region adjacent to the chiral gaps is resolved, which was correlated to the 432-symmetric morphology of the nanoparticles and its corresponding plasmonic properties are numerically predicted from the atomically defined structures. This approach can serve as a comprehensive characterization platform for visualizing the 3D crystallographic and strain distributions of nanoparticles with a few hundred nanometers, especially for applications where structural complexity and local heterogeneity are major determinants, as exemplified in plasmonics.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Growth of graphene underlayers by chemical vapor deposition

We present a simple and very convincing approach to visualizing that subsequent layers of graphene grow between the existing monolayer graphene and the copper catalyst in chemical vapor deposition (CVD). Graphene samples were grown by CVD and then transferred onto glass substrates by the bubbling method in two ways, either direct-transfer (DT) to yield poly (methyl methacrylate) (PMMA)/graphene/glass or (2) inverted transfer (IT) to yield graphene/PMMA/glass. Field emission scanning electron microscopy (FE-SEM) and atomic force microscopy (AFM) were used to reveal surface features for both the DT and IT samples. The results from FE-SEM and AFM topographic analyses of the surfaces revealed the underlayer growth of subsequent layers. The subsequent layers in the IT samples are visualized as 3D structures, where the smaller graphene layers lie above the larger layers stacked in a concentric manner. The results support the formation of the so-called “inverted wedding cake” stacking in multilayer graphene growth.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Advanced User Interface Capabilities [Slides]

This tutorial will review the data plotting and geometry visualization capabilities in the Fulcrum user interface. This tutorial will help you become familiar with Fulcrum’s 2D plot, and 2D and 3D geometry visualization features. You will learn how to identify plottable data items, compose and export plot and plot data for SCALE plot formats (SDF, Ampx MG/CE, PLT, F71, PTP, SPF, ORIGEN Gamma data, etc.) and visualize, navigate, cut, hide, and export the geometry and spatial data (fission-, dose-map, etc.) overlays in 2D and 3D. No prior experience with SCALE is required. Attendees can follow along using 6.3.0-beta.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

A 2.5d Yolo-Based Fusion Algorithm for 3d Localization Of Cells

Advances in microscopy techniques such as lattice-light-sheet, confocal, two-photon, and electron microscopy have enabled the visualization of 3D image volumes of tightly packed cells, extracellular structures in tissues, organelles, and subcellular components inside cells. These images sampled by 2D projections are often not accurately interpreted even by human experts. As a use case we focus on 3D image volumes of tightly packed nuclei in brain tissue. Due to out-of-plane excitation and low resolution in the z-axis, non-overlapping cells appear as overlapping 3D volumes and make detecting individual cells challenging. On the other hand, running 3D detection algorithms is computationally expensive and infeasible for large datasets. In addition, most existing 3D algorithms are designed to extract 3D objects by identifying the depth in the 2D images. In this work, we propose a YOLO-based 2.5D fusion algorithm for 3D localization of individual cells in densely packed volumes of nuclei. The proposed method fuses 2D detection of nuclei in sagittal, coronal, and axial planes and predicts six coordinates of the 3D bounding cubes around the detected 3D cells. Promising results were obtained on multiple examples of synthetic dense volumes of nuclei imitating confocal microscopy experimental datasets.

Ziabari, Amir↗
DOE OSTI2017

Preface to the Special Issue on TOUGH Symposium 2015

The TOUGH Symposium 2015 was held in Berkeley, California, September 28-30, 2015. The TOUGH family of codes, developed at the Energy Geosciences Division of Lawrence Berkeley National Laboratory (LBNL), is a suite of computer programs for the simulation of multiphase and multicomponent fluid and heat flows in porous and fractured media with applications in many geosciences fields, such as geothermal reservoir engineering, nuclear waste disposal, geological carbon sequestration, oil and gas reservoirs, gas hydrate research, vadose zone hydrology and environmental remediation. Since the first release in the 1980s, many modifications and enhancements have been continuously made to TOUGH and its various descendants (iTOUGH2, TOUGH+, TOUGH-MP, TOUGHREACT, TOUGH+HYDRATE, TMVOC...), at LBNL and elsewhere. Today, these codes are used worldwide in academia, government organizations and private companies in problems involving coupled hydrological, thermal, biogeochemical and geomechanical processes. The Symposia, organized every 2-3 years, bring together developers and users for an open exchange on recent code enhancements and applications. In 2015, the Symposium was attended by one hundred participants, representing thirty-four nationalities. This Special Issue in Computers & Geosciences gathers extended versions of selected Symposium proceedings related to (i) recent enhancements to the TOUGH family of codes and (ii) coupled flow and geomechanics processes modeling. In this special issue, a paper by Jung et al. provides a new base version of TOUGH, TOUGH3. This latest version addresses the computational robustness and efficiency needed for the increasing complexity of the simulated processes and the growing size of model domains. Moreover, it consolidates the serial and parallel versions into a single code, hence, inconsistencies between different versions are less likely to occur, and code maintenance and development become more efficient. Finsterle et al. present a review of the capabilities of iTOUGH2 and illustrate the workflow of an integrated simulation-optimization framework. Liu et al. present an approach to reduce the computational cost of performing Bayesian inverse modeling and demonstrate their approach using a synthetic experiment simulated with TOUGH2. Regarding the mesh generation process, the paper by Doughty presents a generalization of the grid-generation algorithm embedded in TOUGH2 (MESHMAKER) to create one-column grids with fractal dimension, useful for representing flow through fractures or highly heterogeneous media with fractal geometry, and also for inverse methods. Sentís and Gable present a module to interface the open source code Lagrit with TOUGH2, that assists in the processes of mesh generation and model setup, and that can be particularly useful for complex geometries and large models. Bonduà et al. present a pre-processing tool (VORO2MESH) that features a full 3D Voronoi approach for structured and unstructured grids, and an enhanced post-processor (TOUGH2Viewer) for the visualization of 3D Voronoi grids. The literature review shows that coupled fluid flow and geomechanics has gained increasing attention in the last years in many geosciences fields. In this context, several codes of the TOUGH family have been successfully coupled with geomechanics software. The paper by Rutqvist presents a review of some of these TOUGH-based geomechanics models, of which the TOUGH-FLAC simulator – presented for the first time in the TOUGH Symposium 2003 – is well-known worldwide and has been used in a large variety of applications, encompassing the application domains of the TOUGH codes. Blanco-Martín et al. present an extension of TOUGH-FLAC to the finite strain framework, motivated by the existence of large strains associated with rock salt deformation in the context of heat-generating nuclear waste disposal. Following a paper published in the Special Issue of the TOUGH Symposium 2012 in this journal, Kim et al. present the current status of the TOUGH-RSBN simulator for coupled hydro-mechanical modeling of hydraulic fracturing using a discrete fracture network approach, and present some validation and demonstration cases. Rinaldi and Nespoli present TOUGH-SEED, an injection-induced seismicity modeling approach using TOUGH2 and a geomechanics stochastic model, and apply it to the Basel EGS project. Finally, Rinaldi et al. use the PEST protocol implemented in iTOUGH2, combined with TOUGH-FLAC as the forward model, to perform inverse modeling for the In Salah CO2 demonstration site in Algeria. Using pore pressures and InSAR displacements as observations, this approach allows for a multi-physics joint inversion and takes advantage of the inverse capabilities of iTOUGH2 (parameter estimation, sensitivity analysis, uncertainty estimation …), applied to coupled fluid flow and geomechanics. On behalf of the members of the TOUGH Symposium 2015 Organizing Committee, I hope that this collection of papers will provide the readers of Computers & Geosciences with a recent view of the capabilities of the TOUGH family of codes, as well as with current modeling research domains in the geosciences. Last but not least, I would like to express my gratitude to all the reviewers who kindly contributed to this Special Issue, as well as the Journal staff who have made this publication possible.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Developing Digital Twin Visualizations: A Methodology and Case Study on Chemical Separation Processing

As advances in digital engineering continue to push the technological boundaries, digital twin (DT) visualizations for diagnostics and safeguards advancement become much more feasible and practical. DTs generate large and complex data streams that require effective user interfaces to provide monitoring and diagnostic capabilities. Unfortunately, while these frameworks exist, there is not much research on the systematic documentation of human–computer interaction (HCI) for DT visualization. This work presents a dual-mode visualization methodology (two dimensional [2D] graphical user interface dashboard and 3D mixed reality) designed to support diagnostic tasks in DT systems and building on a validated framework and applying established HCI principles. The methodology is demonstrated through a case study of aqueous processing at Idaho National Laboratory, using experimental data from the chemical solvent extraction runs. Our interfaces display real-time alerts and monitoring to inform users of safeguards anomalies. The interfaces use immersive 3D mixed-reality visualization for further system and experiment investigation. This work demonstrates how the systematic application of HCI principles can inform DT visualization design for diagnostic and safeguards applications. While formal user evaluation studies remain as future work, this paper documents the systematic design methodology and demonstrates a proof-of-concept implementation.

3D visualization↗
DOE OSTI2020

Open Chemistry, JupyterLab, REST, and quantum chemistry

Quantum chemistry must evolve if it wants to fully leverage the benefits of the internet age, where the worldwide web offers a vast tapestry of tools that enable users to communicate and interact with complex data at the speed and convenience of a button press. The Open Chemistry project has developed an open-source framework that offers an end-to-end solution for producing, sharing, and visualizing quantum chemical data interactively on the web using an array of modern tools and approaches. These tools build on some of the best open-source community projects such as Jupyter for interactive online notebooks, coupled with 3D accelerated visualization, state-of-the-art computational chemistry codes including NWChem and Psi4, and emerging machine learning and data mining tools such as ChemML and ANI. They offer flexible formats to import and export data, along with approaches to compare computational and experimental data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

SU-G-IeP4-08: Initial Investigations of Up-Converting Nanoparticles (UCNP) for 3D Tissue Imaging in Optical-ECT

Purpose: Near-IR absorptive up-converting nanoparticles (UCNPs) is a novel contrast for optical-ECT that allows auto-fluorescence-free 3D imaging of labeled cells in a matrix of large (∼1cm{sup 3}) unsectioned normal tissue. This has the potential to image small metastases or dormant cells that is difficult with down-converting fluorescing dyes due to auto-fluorescence. The feasibility of imaging UCNP in agarose phantoms and a mouse lung is demonstrated, aided by a 3D-printed optical-ECT stage designed to excite UCNP in a mouse lung. Methods: The UCNP, NaYF{sub 4}:Yb/Er (20/2%), studied in this work up-converts 980nm light to visible light peaking sharply at ∼540nm. To characterize the UCNP emission as a function of UCNP concentration, cylindrical 2.5%wt agarose phantoms infused with UCNP at concentrations of 25µg/mL and 50µg/mL were exposed to 1.5W 980nm laser coupled to an optical fiber. The fiber was held stably at 1cm above the stage via a custom 3D-printed stage. An optically cleared lung harvested from a BALBc mice was then injected with 100µL of 1mg/mL UCNP solution ex vivo. Tomographic imaging of the UCNP emission in lung was performed. Results: The laser beam tract is visualized within the agarose phantom. A line profile of UCNP emission at 25µg/mL versus 50µg/mL shows that increasing the UCNP concentration increases emission count. UCNPs injected into a cleared mouse lung disperse throughout the respiratory tract, allowing for visualization and 3D reconstruction. Excitation before and after UCNP injection shows the tissue exhibits no auto-fluorescence at 980nm, allowing clear view of the UCNP without any obscuring features such as conventional down-converting fluorescent tags. Conclusion: We confirm that up-conversion in tissue circumvents completely tissue auto-fluorescence, which allowed background-free 3D reconstruction of the UCNP distribution. We also confirm that raising the UCNP concentration increases emission and that UCNPs are retained in agarose samples during the optical clearing process.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

3D mapping of water in oolithic limestone at atmospheric and vacuum saturation using X-ray micro-CT differential imaging

Determining the distribution of fluids in porous sedimentary rocks is of great importance in many geological fields. However, this is not straightforward, especially in the case of complex sedimentary rocks like limestone, where a multidisciplinary approach is often needed to capture its broad, multimodal pore size distribution and complex pore geometries. This paper focuses on the porosity and fluid distribution in two varieties of Massangis limestone, a widely used natural building stone from the southeast part of the Paris basin (France). The Massangis limestone shows locally varying post-depositional alterations, resulting in different types of pore networks and very different water distributions within the limestone. Traditional techniques for characterizing the porosity and pore size distribution are compared with state-of-the-art neutron radiography and X-ray computed microtomography to visualize the distribution of water inside the limestone at different imbibition conditions. X-ray computed microtomography images have the great advantage to non-destructively visualize and analyze the pore space inside of a rock, but are often limited to the larger macropores in the rock due to resolution limitations. In this paper, differential imaging is successfully applied to the X-ray computed microtomography images to obtain sub-resolution information about fluid occupancy and to map the fluid distribution in three dimensions inside the scanned limestone samples. The detailed study of the pore space with differential imaging allows understanding the difference in the water uptake behavior of the limestone, a primary factor that affects the weathering of the rock. - Highlights: • The water distribution in a limestone was visualized in 3D with micro-CT. • Differential imaging allowed to map both macro and microporous zones in the rock. • The 3D study of the pore space clarified the difference in water uptake behavior. • Trapped air is visualized in the moldic macropores at atmospheric saturation.

36 MATERIALS SCIENCE↗