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Results for “non-invasive imaging”

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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Time-lapse electrical resistivity and induced polarization monitoring of a simulated ecosystem-scale coastal flooding experiment

Accurate estimation of the spatio-temporal variation in soil saturation and salt concentration is valuable for calibrating and evaluating Earth system models as well as detecting important eco-hydrological interactions. Such representative models play a vital role in investigating the stability of ecosystems facing changing hydrologic disturbance regimes. Ecosystem-scale field experiments are a useful way to capture hydrological disturbance and gain a deeper understanding of the complex mechanisms driving environmental changes. However, previous studies have not explored the use of quantitative imaging at a large spatial scale to reproduce breakthrough curves and inform system response and recovery following hydrologic disturbance events. Therefore, in this study, non-invasive geophysical methods were used to capture the spatio-temporal variation in subsurface saturation and salt concentrations during an ecosystem-scale coastal forest flooding experiment.

coastal↗
DOE OSTI2022

DEVELOPMENT OF A QUANTUM ELECTRON BEAM DIAGNOSTIC APPARATUS

Spatial properties of electron beams are the essential parameters needed in particle physics and accelerator research. Beam characterization using optical detection methods through the interaction between photons and electrons such as Compton scattering, or electro-optic sampling of the electric field of electrons have been extensively explored and successfully implemented as non-invasive diagnostics at various accelerator facilities. However, such methods often suffer from inherently low sensitivity. Here we present the study of a new type of electron beam diagnostic device for direct optical imaging of electron beams at various energy levels. The concept is based on the extremely high sensitivity of atoms, prepared in a specific "dark superposition" quantum state, to the external electric or magnetic perturbations induced by the passing charged particle, which allows atoms to change polarization of the probe light or absorb probe light and to fluoresce, enabling direct 3D imaging of the charged particles with high resolution. We report our recent experiment results and the design effort on a compact apparatus intended to be tested with the relativistic electron beams at Jefferson Laboratory.

Zhang, S.↗
DOE OSTI2024

Patch2Self2: Self-supervised Denoising on Coresets via Matrix Sketching

Diffusion MRI (dMRI) non-invasively maps brain white matter yet necessitates denoising due to low signal-to-noise ratios. Patch2Self (P2S) employing self-supervised techniques and regression on a Casorati matrix effectively denoises dMRI images and has become the new de-facto standard in this field. P2S however is resource intensive both in terms of running time and memory usage as it uses all voxels (n) from all-but-one held-in volumes (d-1) to learn a linear mapping Phi : \mathbb R ^ n x(d-1) \mapsto \mathbb R ^ n for denoising the held-out volume. The increasing size and dimensionality of higher resolution dMRI acquisitions can make P2S infeasible for large-scale analyses. This work exploits the redundancy imposed by P2S to alleviate its performance issues and inspect regions that influence the noise disproportionately. Specifically this study makes a three-fold contribution: (1) We present Patch2Self2 (P2S2) a method that uses matrix sketching to perform self-supervised denoising. By solving a sub-problem on a smaller sub-space so called coreset we show how P2S2 can yield a significant speedup in training time while using less memory. (2) We present a theoretical analysis of P2S2 focusing on determining the optimal sketch size through rank estimation a key step in achieving a balance between denoising accuracy and computational efficiency. (3) We show how the so-called statistical leverage scores can be used to interpret the denoising of dMRI data a process that was traditionally treated as a black-box. Experimental results on both simulated and real data affirm that P2S2 maintains denoising quality while significantly enhancing speed and memory efficiency achieved by training on a reduced data subset.

Fadnavis, Shreyas↗
DOE OSTI2023

Laser-Induced Fluorescence for Monitoring Environmental Contamination and Stress in the Moss Thuidium plicatile

The ability to detect, measure, and locate the source of contaminants, especially heavy metals and radionuclides, is of ongoing interest. A common tool for contaminant identification and bioremediation is vegetation that can accumulate and indicate recent and historic pollution. However, large-scale sampling can be costly and labor-intensive. Hence, non-invasive in-situ techniques such as laser-induced fluorescence (LIF) are becoming useful and effective ways to observe the health of plants through the excitation of organic molecules, e.g., chlorophyll. The technique presented utilizes images collected of LIF in moss to identify different metals and environmental stressors. Analysis through image processing of LIF response was key to identifying Cu, Zn, Pb, and a mixture of the metals at nmol/cm 2 levels. Specifically, the RGB values from each image were used to create density histograms of each color channel’s relative pixel abundance at each decimal code value. These histograms were then used to compare color shifts linked to the successful identification of contaminated moss samples. Photoperiod and extraneous environmental stressors had minimal impact on the histogram color shift compared to metals and presented with a response that differentiated them from metal contamination.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Optical contrast analysis of α -RuCl 3 nanoflakes on oxidized silicon wafers

α-RuCl 3 , a narrow-band Mott insulator with a large work function, offers intriguing potential as a quantum material or as a charge acceptor for electrical contacts in van der Waals devices. In this work, we perform a systematic study of the optical reflection contrast of α-RuCl 3 nanoflakes on oxidized silicon wafers and estimate the accuracy of this imaging technique to assess the crystal thickness. Via spectroscopic micro-ellipsometry measurements, we characterize the wavelength-dependent complex refractive index of α-RuCl 3 nanoflakes of varying thickness in the visible and near-infrared. Building on these results, we simulate the optical contrast of α-RuCl 3 nanoflakes with thicknesses below 100 nm on SiO 2 /Si substrates under different illumination conditions. We compare the simulated optical contrast with experimental values extracted from optical microscopy images and obtain good agreement. Finally, we show that optical contrast imaging allows us to retrieve the thickness of the RuCl 3 nanoflakes exfoliated on an oxidized silicon substrate with a mean deviation of –0.2 nm for thicknesses below 100 nm with a standard deviation of only 1 nm. Our results demonstrate that optical contrast can be used as a non-invasive, fast, and reliable technique to estimate the α-RuCl 3 thickness.

2D materials↗
DOE OSTI2023

Using Low-Field Nuclear Magnetic Resonance and X-Ray Computed Microtomography Imaging to Explore Potential of Microbially-Induced Calcium Carbonate Precipitation Treatment to Seal Shale Fractures

Microbially-induced calcium carbonate precipitation (MICP) is a biological process in which microbially produced urease enzymes convert urea and calcium into solid calcium carbonate (CaCO 3 ) deposits. Studies have shown that MICP can be used to seal fractures in shale, raising the possibility of applying this technology to restimulate fracking wells by plugging underperforming fractures. For this and other applications to become a reality, non-invasive tools are needed to determine how effectively MICP seals shale fractures under subsurface conditions. In this study, a 2.54 cm wide and 5.08 cm long Marcellus shale core with a single, ~1 mm wide fracture held open by sand "proppant" underwent MICP-treatment at 60°C until reaching three orders of magnitude permeability reduction. Low-field nuclear magnetic resonance (LF-NMR) and X-Ray computed microtomography (μ-CT) techniques were used to assess the extent of biomineralization within the fracture. These tools revealed that while CaCO 3 precipitation occurred throughout the fracture, there was preferential precipitation around proppant, and the core sealed at the effluent end before filling most of the fracture. Both tools were able to independently calculate of the amount of solid biomineral formed inside the fracture. Furthermore, this study found that the distribution of proppant within the shale fracture was an important parameter controlling the degree of biomineralization.

clastic rock↗
DOE OSTI2024

Low latency optical-based mode tracking with machine learning deployed on FPGAs on a tokamak

Active feedback control in magnetic confinement fusion devices is desirable to mitigate plasma instabilities and enable robust operation. Optical high-speed cameras provide a powerful, non-invasive diagnostic and can be suitable for these applications. Here, in this study, we process high-speed camera data, at rates exceeding 100 kfps, on in situ field-programmable gate array (FPGA) hardware to track magnetohydrodynamic (MHD) mode evolution and generate control signals in real time. Our system utilizes a convolutional neural network (CNN) model, which predicts the n = 1 MHD mode amplitude and phase using camera images with better accuracy than other tested non-deep-learning-based methods. By implementing this model directly within the standard FPGA readout hardware of the high-speed camera diagnostic, our mode tracking system achieves a total trigger-to-output latency of 17.6 μs and a throughput of up to 120 kfps. This study at the High Beta Tokamak-Extended Pulse (HBT-EP) experiment demonstrates an FPGA-based high-speed camera data acquisition and processing system, enabling application in real-time machine-learning-based tokamak diagnostic and control as well as potential applications in other scientific domains.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Retinal microvascular and neuronal pathologies probed in vivo by adaptive optical two-photon fluorescence microscopy

The retina, behind the transparent optics of the eye, is the only neural tissue whose physiology and pathology can be non-invasively probed by optical microscopy. The aberrations intrinsic to the mouse eye, however, prevent high-resolution investigation of retinal structure and function in vivo. Optimizing the design of a two-photon fluorescence microscope (2PFM) and sample preparation procedure, we found that adaptive optics (AO), by measuring and correcting ocular aberrations, is essential for resolving putative synaptic structures and achieving three-dimensional cellular resolution in the mouse retina in vivo. Applying AO-2PFM to longitudinal retinal imaging in transgenic models of retinal pathology, we characterized microvascular lesions with sub-capillary details in a proliferative vascular retinopathy model, and found Lidocaine to effectively suppress retinal ganglion cell hyperactivity in a retinal degeneration model. Tracking structural and functional changes at high-resolution longitudinally, AO-2PFM enables microscopic investigations of retinal pathology and pharmacology for disease diagnosis and treatment in vivo.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Quantitative local state of charge mapping by operando electrochemical fluorescence microscopy in porous electrodes

We introduce operando quantitative electrochemical fluorescence state of charge mapping (QEFSM), a non-invasive technique to study operating electrochemical systems along with a new design of optically transparent microfluidic redox flow cells compatible with the most demanding optical requirements. QEFSM allows quantitative mappings of the concentration of a particular oxidation state of a redox-active species within a porous electrode during its operation. In this study, we used confocal microscopy to map the fluorescence signal of the reduced form of 2,7-anthraquinone disulfonate (AQDS) in a set of multistep-chronoamperometry experiments. Calibrating these images and incorporating an analytical model of quinhydrone heterodimer formation with no free parameters, and accounting for the emission of each species involved, we determined the local molecular concentration and the state of charge (SOC) fields within a commercial porous electrode during operation. With this method, electrochemical conversion and species advection, reaction and diffusion can be monitored at heretofore unprecedented transverse and axial resolution (1 μm and 25 μm, respectively) at frame rates of 0.5 Hz, opening new routes to understanding local electrochemical processes in porous electrodes. Here, we observed pore-scale SOC inhomogeneities appearing when the fraction of electroactive species converted in a single pass through the electrode becomes large.

42 ENGINEERING↗
DOE OSTI2025

Evaluating User Errors and Temporal Trends in Marine Fish Communities Using 360-Degree Underwater Photography

The use of environmental DNA (eDNA) sampling has been proposed as a complementary method to monitor fish species in marine environments, offering a non-invasive and potentially more efficient approach to marine species observations. eDNA monitoring could be especially useful in and around sites targeted for marine energy generation as these regions need regular monitoring that would be impractical with traditional techniques. Before we can fully rely upon eDNA, we must first verify its accuracy against other proven methods, such as the use of underwater photography. In this study, I deployed a 360-degree camera in the tidal channel of Sequim Bay once a month during several hours overlapping slack tide. I investigated how having multiple people identify and count fish on underwater images could affect the overall results. Using chi square tests in R, I compared my fish identifications and counts to those made by another intern on the same images recorded in August. I found significant differences in the number of species identified and the total individual counts between the two different datasets. I also tested the statistical differences in both Shannon diversity and Pielou evenness indices between the August, September, and November camera deployments using a Hutcheson t-test. Only one significant difference was found in the Shannon index comparisons, and none were found between the Pielou evenness comparisons. These findings show that if multiple identifiers are used to process underwater images, quality control checks must be made to reduce the potential for error. This also points toward the possibility to leverage more advanced image analysis processes, such as automated image analysis software. The findings from this study also show that the dynamics of marine fish communities can vary over a few months; however, further analysis is needed to determine the extent of the seasonal changes in Sequim Bay.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Revolutionizing Waste Management: AI-Powered Real-Time Characterization for Efficient Handling of Non-Recyclable Municipal Solid Waste

According to EPA, -300 MM tons of municipal solid waste (MSW) was available in the US as of 2018. Of that total material, nearly 50% was landfilled resulting in a significant loss for the potential to convert its energy value into cost effective and sustainable biofuels. Redirecting this material away from the landfill and into conversion ready feedstock for energy generation can directly address DOE's selling price < $2.50/GGE while securing the US national energy independence [1]. However, the paramount challenges in any rational fuel conversion strategy are understanding the chemical makeup, quality and associated calorific value of the MSW. Understanding these parameters is critical in achieving any acceptable fuel conversion and requires rapid characterization followed by accurate separation technologies. Therefore, we are proposing to address the rapid characterization by building a non-invasive, rapid, and highly accurate Artificial Intelligence (AI)-enabled spectrometric/optical approach augmented with multi-sensory information for advanced characterization of domestic heterogeneous MSW. North Carolina State University (NCSU) and the National Renewable Energy Laboratory (NREL), in partnership with strong support from the Town of Cary and IBM, Inc., will closely work together to implement this ground-breaking technology for the effective characterization of MSW for sustainable and affordable production of conversion-ready feedstocks, while solving the environment issue of planetary proportions.

artificial intelligence↗
DOE OSTI2024

Conditional guided generative diffusion for particle accelerator beam diagnostics

Abstract Advanced accelerator-based light sources such as free electron lasers (FEL) accelerate highly relativistic electron beams to generate incredibly short (10s of femtoseconds) coherent flashes of light for dynamic imaging, whose brightness exceeds that of traditional synchrotron-based light sources by orders of magnitude. FEL operation requires precise control of the shape and energy of the extremely short electron bunches whose characteristics directly translate into the properties of the produced light. Control of short intense beams is difficult due to beam characteristics drifting with time and complex collective effects such as space charge and coherent synchrotron radiation. Detailed diagnostics of beam properties are therefore essential for precise beam control. Such measurements typically rely on a destructive approach based on a combination of a transverse deflecting resonant cavity followed by a dipole magnet in order to measure a beam’s 2D time vs energy longitudinal phase-space distribution. In this paper, we develop a non-invasive virtual diagnostic of an electron beam’s longitudinal phase space at megapixel resolution (1024 × 1024) based on a generative conditional diffusion model. We demonstrate the model’s generative ability on experimental data from the European X-ray FEL.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Where do the fish go in winter? A year of observing seasonal changes in Sequim Bay’s nearshore fish community

The use of environmental DNA (eDNA) sampling has been proposed as a complementary method to monitor fish species in marine environments. eDNA offers a non-invasive, cost-effective, and scalable way to detect aquatic species. It is appealing in environments where traditional methods are limited by access or visibility, especially in complex or sensitive habitats such as tidal channels and other marine energy sites. Before eDNA can be fully relied upon, we must verify its accuracy against established methods, like underwater photography. In this study, we collected eDNA samples and concurrently deployed a 360-degree camera near the floating dock of PNNL-Sequim in the tidal channel of Sequim Bay once a month for twelve consecutive months. During deployments, the camera remained on the seafloor for several hours overlapping slack tide and captured time-lapse photographs at ten second intervals. Counts and identifications of fish species observed in the images were used to calculate monthly Shannon diversity and Pielou evenness indices. These values were compared across the months using a Kruskal-Wallis test paired with a Conover-Iman post-hoc test. Cliff’s Delta was also calculated to quantify the effect size of the monthly differences. No fish were observed from December through April, likely due to seasonal behavior changes within the local fish community. Fish returned to the shoreline in May, with the greatest diversity and evenness recorded in September. These findings reveal substantial seasonal variation in nearshore fish communities. Many monthly comparisons were found to contain statistically significant differences within the diversity and evenness, and even more were found to have large effect sizes, signifying large ecological changes throughout the seasons. The absence of fish observed during the winter months is a key outcome of this survey that will hopefully be reflected in the eDNA results still to come, which would help validate the eDNA approach.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Quantum Enhanced Tracker (Final Report)

A new concept of charged particle detector, called Quantum Enhanced Tracker (QET) is proposed and intended for optical imaging of charged particle tracks. We present a quantum-based detection method for reconstructing the spatial profile of an electron beam by passing it through a dilute vapor of rubidium atoms. The perturbation of the atomic spin’s quantum state by the electron beam’s magnetic field is detected via nonlinear magneto-optical polarization rotation. Consequently, the electron beam’s position, size and current density can be measured, and its transverse profile reconstructed by analyzing the polarization rotation of a transverse probe laser. This method was experimentally studied using e-beams with currents ranging from 1 to 200 μA and energies between 10 to 20 keV. The results show that this approach is sensitive to the e-beam current and independent of e-beam energy. This technique provides a potentially 3-D capable approach for non-invasive characterization and monitoring of charged particles used in accelerators and nuclear physics research.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Soil architecture and subsurface stratigraphic heterogeneities across land-lake interfaces along Lake Erie.

Uploaded raw datasets from electrical resistivity tomography (ERT), ground penetrating radar (GPR), electromagnetic induction (EMI) and insitu sensors were acquired across land-lake interfaces along Lake Erie. These datasets were useful to delineate the soil architecture and subsurface stratigraphic heterogeneities. We combined multiple geophysical methods with lithostratigraphic logs from borehole cores and data from soil and borehole sensors to investigate spatial heterogeneities across land-lake interfaces. The apparent electrical conductivity (Eca) maps matched closely with the soil maps from public database and also detected additional soil units that were missing in the traditional soil maps. This implies that electromagnetic induction (EMI) could be relied upon for non invasive characterization of soils in sampling restricted sites where only non-invasive measurements are feasible. Results from electrical resistivity tomography (ERT) and Ground penetrating radar (GPR) are consistent with the surficial geology of the study area, and revealed that the vertical variabilities at the sites are mainly driven by stratigraphy.The ERT data (.stg) were acquired from three different sites portage river (PTR), crane creek (CRC) and old woman creek (OWC). The ".stg" files can be opened with ERT inversion software such as EarthImager, ResIpy or Res2DInv. The GPR data (.GPZ) were also acquired from the three sites, and the ".GPZ" data files can be opened with EKKO_project 5 software from Sensors & Software Inc., or with any other standard GPR software. The EM data (.csv) were acquired from the three sites while the soil sensor data (.csv) here were acquired only from crane creek site. The ".csv) files can be opened with MS Excel or any other spread sheet software.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Review of Ultrasonic Methods for Monitoring, Damage Detection, and Processing of Lithium-Ion Batteries Throughout Their Life Cycle

Lithium-ion batteries (LIBs) are the leading technology used in consumer electronics, electric vehicles, and grid-level electrochemical energy storage applications. The ever-increasing use of LIBs has highlighted a gap in understanding of their behavior throughout their life cycle. Current monitoring systems rely on electrical and sometimes temperature measurements to assess the internal state which limits information about complex electrochemical processes. In response, ultrasonic testing (UT) has shown promise for non-invasive assessment due to its ease of use and sensitivity to mechanical changes which are correlated with electrochemical changes within the battery. We summarize the research in UT methods applied to LIBs throughout their life cycle. We also discuss physics-based and data-driven modeling approaches used to interpret ultrasonic signals in the context of LIBs, with an emphasis on the existing challenge of establishing rigorous links between electrochemical behavior and elastic and poroelastic wave physics to gain insight regarding physical changes in the LIB that can be directly measured using UT. Finally, we discuss the challenges of implementing UT across the LIB life cycle and identify opportunities for further research. This review aims to provide helpful guidance to researchers and practitioners of UT in the growing field of UT for electrochemical battery systems.

25 ENERGY STORAGE↗
DOE OSTI2022

N-dependent dynamics of root growth and nitrate and ammonium uptake are altered by the bacterium Herbaspirillum seropedicae in the cereal model Brachypodium distachyon

Nitrogen (N) fixation in cereals by root-associated bacteria is a promising solution for reducing use of chemical N fertilizers in agriculture. However, plant and bacterial responses are unpredictable across environments. We hypothesized that cereal responses to N-fixing bacteria are dynamic, depending on N supply and time. To quantify the dynamics, a gnotobiotic, fabricated ecosystem (EcoFAB) was adapted to analyse N mass balance, to image shoot and root growth, and to measure gene expression of Brachypodium distachyon inoculated with the N-fixing bacterium Herbaspirillum seropedicae. Phenotyping throughput of EcoFAB-N was 25–30 plants h -1 with open software and imaging systems. Herbaspirillum seropedicae inoculation of B. distachyon shifted root and shoot growth, nitrate versus ammonium uptake, and gene expression with time; directions and magnitude depended on N availability. Primary roots were longer and root hairs shorter regardless of N, with stronger changes at low N. At higher N, H. seropedicae provided 11% of the total plant N that came from sources other than the seed or the nutrient solution. The time-resolved phenotypic and molecular data point to distinct modes of action: at 5 mM NH 4 NO 3 the benefit appears through N fixation, while at 0.5 mM NH 4 NO 3 the mechanism appears to be plant physiological, with H. seropedicae promoting uptake of N from the root medium.Future work could fine-tune plant and root-associated microorganisms to growth and nutrient dynamics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Membrane potential sensing: Material design and method development for single particle optical electrophysiology

We review the development of “single” nanoparticle-based inorganic and organic voltage sensors, which can eventually become a viable tool for “non-genetic optogenetics.” The voltage sensing is accomplished with optical imaging at the fast temporal response and high spatial resolutions in a large field of view. Inorganic voltage nanosensors utilize the Quantum Confined Stark Effect (QCSE) to sense local electric fields. Engineered nanoparticles achieve substantial single-particle voltage sensitivity (~2% Δλ spectral Stark shift up to ~30% ΔF/F per 160 mV) at room temperature due to enhanced charge separation. A dedicated home-built fluorescence microscope records spectrally resolved images to measure the QCSE induced spectral shift at the single-particle level. Biomaterial based surface ligands are designed and developed based on theoretical simulations. The hybrid nanobiomaterials satisfy anisotropic facet-selective coating, enabling effective compartmentalization beyond non-specific staining. Self-spiking- and patched-HEK293 cells and cortical neurons, when stained with hybrid nanobiomaterials, show clear photoluminescence intensity changes in response to membrane potential (MP) changes. Organic voltage nanosensors based on polystyrene beads and nanodisk technology utilize Fluorescence (Förster) Resonance Energy Transfer (FRET) to sense local electric fields. Voltage sensing FRET pairs achieve voltage sensitivity up to ~35% ΔF/F per 120 mV in cultures. Non-invasive MP recording from individual targeted sites (synapses and spines) with nanodisks has been realized. However, both of these QCSE- and FRET-based voltage nanosensors yet need to reach the milestone of recording individual action potentials from individual targeted sites.

59 BASIC BIOLOGICAL SCIENCES↗