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At least 37 records · Page 2

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DOE OSTI2026

Patch-Based Convolutional Neural Networks for Multiple Microstructural Features Detection in FIB-SEM Micrographs of Irradiated Nuclear Fuel

Focused ion beam scanning electron microscopy (FIB-SEM) tomography has increasingly been utilized for acquiring three-dimensional (3D) microstructure features at the sub-micron scale in irradiated nuclear materials. This technique involves sequential ion beam slicing followed by electron beam imaging and compositional mapping using energy dispersive spectroscopy (EDS). Despite its growing use, several challenges persist. These include the time-intensive nature of data collection of EDS data, difficulties in distinguishing between various microstructures, and issues with image alignment. These challenges currently limit the broader application of FIB-SEM tomography in the field. To overcome these limitations, we propose using convolutional neural networks (CNNs) to automate microstructure identification in SEM images. Our study introduces a new framework for identifying microstructures in irradiated U-10Zr (wt. %) metallic fuel with limited annotated data. The framework includes the creation of a reliable annotated dataset with paired SEM and ground truth data from EDS maps, the applications of CNNs for microstructure identification, and the validation of model performance. Specifically, we employed the Segment Anything Model (SAM) to align SEM images with corresponding EDS maps and focused ion beam (FIB) tomography SEM data. We evaluate several models, including Patch-based U-Net, Attention U-Net, and Residual U-Net, finding that patch-based U-Net exhibits superior segmentation performance and consistency. This approach reduces reliance on EDS detectors and aids in accelerating nuclear material analysis process, highlighting the potential of advanced deep learning techniques to improve microstructural understanding in nuclear material. This is the first framework to integrate SAM and Patch-based CNN models for semantic segmentation of irradiated nuclear materials, with potential applicability to other tomography datasets.

36 - MATERIALS SCIENCE↗

DOE OSTI2024

Measurements of Penning-Malmberg trap patch potentials and associated performance degradation

Antiprotons created by laser ionization of antihydrogen are observed to rapidly escape the ALPHA trap. Further, positron plasmas heat more quickly after the trap is illuminated by laser light for several hours. These phenomena can be caused by patch potentials—variations in the electrical potential along metal surfaces. A simple model of the effects of patch potentials explains the particle loss, and an experimental technique using trapped electrons is developed for measuring the electric field produced by the patch potentials. The model is validated by controlled experiments and simulations. Published by the American Physical Society 2024

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Carbon fiber/epoxy vitrimer composite patch cured with bio‐based curing agents for one‐step repair metallic sheet and its recyclability

Abstract Vitrimers have gained a great deal of attention from researchers, yet research on its application is still lacking. This study, a novel bio‐based vitrimer was developed from epoxy (EP) and bio‐based curing agents, that is, cashew nut shell liquid (CNSL) and citric acid (CA), and then reinforced by carbon fiber. The vitrimers with different ratios of acid to epoxy (R ratio) at 0.30–0.40 contained ester and ether linkages. All EP/CA/CNSL vitrimers showed the stress relaxation over 70–100°C due to transesterification. The vitrimers were applied as polymer matrices for the carbon fiber composites and then used as repair patches. By using the carbon fiber‐reinforced vitrimer with the R ratio of 0.30, patch repair on a damaged alloy sheet revealed that approximately 98% of the tensile strength of the damaged alloy sheet was recovered. The vitrimer can be dissolved from carbon fiber composite to recover carbon fiber. The recovered carbon fiber retained good tensile strength compared to the pristine composite. Based on this study, the EP/CA/CNSL vitrimers showed the comparable thermomechanical properties with the epoxy vitrimer cured by the petroleum‐based curing agent. The vitrimer composite patch could therefore be an alternative new repair method to extend the service life of damaged structures.

Lorwanishpaisarn, Narubeth↗

DOE OSTI2020

Current–Induced Ion Concentration Polarization at a Perfect Ion–Exchange Patch in an Infinite Insulating Wall

This research examines theoretically the ion concentration polarization, ion fluxes, and electrostatic fields near an ion exchange patch in the wall of an electrified fluidic channel. These phenomena are important in related microfluidic ion-preconcentration systems. Under an electric field, counterions enter the ion-exchange patch at one side and leave at the other, with salt depletion occurring near the entrance and accumulation near the exit. Furthermore, the high patch conductivity and the concentration profiles lead to local electric field perturbations that may facilitate preconcentration. This study includes analytical expressions of ion concentrations and electrochemical potentials at small to moderate electric fields, as well as numerical simulations. Additionally, a simple matrix of polynomial coefficients (obtained via fitting of numerical data) enables analytical calculation of the 2-dimensional concentration profiles at all electric fields within the range investigated in the numerical simulations. This is possible because a single dimensionless parameter controls this problem.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Hydrologic Connectivity and Patch‐To‐Hillslope Scale Relations in Dryland Ecosystems

Abstract In drylands, runoff during storms redistributes water and nutrients from bare soil areas to vegetated patches, subsidizing vegetation with additional resources. The extent of this redistribution depends on the interplay between surface roughness and permeability; greater permeability in vegetated patches promotes run‐on to vegetation, but greater surface roughness diverts runoff, producing tortuous flow paths that bypass vegetation. Here, this interplay is examined in virtual experiments using the 2D Saint Venant Equations to measure runoff connectivity. Flowpaths are delineated using tracers advected by the flow. Distances between tracer sources and sinks along flowpaths measure hydrologic connectivity at two lengthscales: connectivity to the hillslope outlet and within‐slope source‐sink connectivity. Differences between these connectivity lengthscales indicate how flow may “by‐pass” vegetated patches within hillslopes. At the hillslope scale, a derived power‐law relation between the runoff coefficient and outlet connectivity describes hillslope water losses, providing a foundation for identifying landscapes likely to shed water.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Fault Slip and Fluid Flow: Seismic Source Analysis to Assess Role of Multiple Slip Patches in Fault Permeability

The relationship between fault reactivation, microearthquakes (MEQs), and permeability evolution during fluid injection plays a critical role in energy harvesting and waste disposal. Recent studies have demonstrated the possibility of predicting fault permeability using cumulative seismic moments of MEQs quantitatively. To understand the underlying physical processes, we conduct fault reactivation experiments using Utah FORGE granitoid and analyze acoustic emission (AE) signals generated during stepwise increases in fluid injection pressure. Frequency analysis of thousands of calibrated AE signals reveals that fault reactivation produces multiple AE source patches with millimeter-scale radii—smaller than the sample fault radius. The cumulative area of the reactivated patches covers the fault multiple times over (∼10x–50x area) for each pressure step. These findings provide mechanistic insight that measured permeability enhancement is not driven by a single large slip event, but by the sequential and interacting activation of multiple slip patches that create a continuous flow pathway.

Nurshal, M. E. M. [Pennsylvania State University, ↗

DOE OSTI2021

A wearable patch for continuous analysis of thermoregulatory sweat at rest

The body naturally and continuously secretes sweat for thermoregulation during sedentary and routine activities at rates that can reflect underlying health conditions, including nerve damage, autonomic and metabolic disorders, and chronic stress. However, low secretion rates and evaporation pose challenges for collecting resting thermoregulatory sweat for non-invasive analysis of body physiology. Here we present wearable patches for continuous sweat monitoring at rest, using microfluidics to combat evaporation and enable selective monitoring of secretion rate. We integrate hydrophilic fillers for rapid sweat uptake into the sensing channel, reducing required sweat accumulation time towards real-time measurement. Along with sweat rate sensors, we integrate electrochemical sensors for pH, Cl - , and levodopa monitoring. We demonstrate patch functionality for dynamic sweat analysis related to routine activities, stress events, hypoglycemia-induced sweating, and Parkinson’s disease. By enabling sweat analysis compatible with sedentary, routine, and daily activities, these patches enable continuous, autonomous monitoring of body physiology at rest.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Bioorthogonal catalytic patch

The toxicity and complicated administration procedures of transition metal catalysts have hampered the applications of bioorthogonal catalysis in vivo. Here the authors fill the needles of a microneedle array patch with palladium nanoparticles deposited on titanium nanosheets and show that the device, applied locally on the skin of mouse models bearing melanoma, promotes intratumoural conversion of systemically injected caged doxorubicin into the active drug, reducing its toxicity and side effects. Bioorthogonal catalysis mediated by transition metals has inspired a new subfield of artificial chemistry complementary to enzymatic reactions, enabling the selective labelling of biomolecules or in situ synthesis of bioactive agents via non-natural processes. However, the effective deployment of bioorthogonal catalysis in vivo remains challenging, mired by the safety concerns of metal toxicity or complicated procedures to administer catalysts. Here, we describe a bioorthogonal catalytic device comprising a microneedle array patch integrated with Pd nanoparticles deposited on TiO 2 nanosheets. This device is robust and removable, and can mediate the local conversion of caged substrates into their active states in high-level living systems. In particular, we show that such a patch can promote the activation of a prodrug at subcutaneous tumour sites, restoring its parent drug's therapeutic anticancer properties. Finally, this in situ applied device potentiates local treatment efficacy and eliminates off-target prodrug activation and dose-dependent side effects in healthy organs or distant tissues.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2018

Charge-patching method for the calculation of electronic structure of polypeptides

Theoretical study of the electronic structures of protein is a fundamental challenge in computational biochemistry due to the large size of the systems. The electronic structure of a protein is important for some of the important protein functionalities, such as photosynthesis. Here, we explored the charge-patching method to calculate the electronic structure of polypeptides. This method generates the charge densities of the systems by patching the charge motifs calculated from small prototype systems. The method was tested on a range of polypeptides, including the glycine polypeptide in 2 7 -ribbon, α-helix, 3 10 -helix, and β-strand structures. After the charge density profiles of these systems were obtained, the electronic structures of these glycine polypeptides were further calculated based on density functional theory (DFT) using a folded-spectrum method. The highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO) were analyzed and compared with conventional direct DFT calculations. The charge-patching method results were found to be in good agreement with the directed DFT results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Scaling patch analysis of turbulent planar plume

Proper scaling in turbulent planar plumes is investigated in this study using a scaling patch approach. Based on the scaled boundary conditions, a proper velocity scale for the mean axial flow is the plume centerline velocity U ref = U ctr , and a proper temperature scale for the temperature excess is Θ ref = T ctr – T ∞ , where T ctr is the plume centerline temperature and T ∞ is the ambient fluid temperature. By seeking an admissible scaling, a key concept in the scaling patch approach, for the mean continuity, mean momentum, and mean energy equations, respectively, the following is found: (1) a proper scale for the mean transverse flow is V ref = ( d δ / d x ) U ctr , where d δ / d x is the growth rate of the plume width. (2) A proper scale for the Reynolds shear stress is R vu , ref = U ctr V ref = ( d δ / d x ) U ctr 2 , a mix of the scales for the mean axial and transverse flows. (3) A proper scale for the turbulent heat flux is R v θ , ref = V ref Θ ctr , a mix of the scales for the mean transverse flow and mean temperature excess. The mean transverse flow thus plays a critical role in the scaling of turbulent planar plumes. Approximate functions are developed for the scaled mean transverse flow, Reynolds shear stress, and turbulent temperature flux, and are found to agree favorably with experimental and numerical simulation data. The integral analysis of the mean momentum equation yields a Richardson number Ri, which remains invariant in the axial direction. The Richardson number is defined as Ri = def g β Θ ctr δ t / ( U ctr V ref ) ≈ 1 / 2 , where g is the gravitational acceleration, β is the thermal expansion coefficient, and δ t is the plume half-width based on the mean temperature profile. This Richardson number arises directly from the scaling patch analysis of the mean momentum equation, including both the streamwise and transverse velocity scales.

42 ENGINEERING↗

DOE OSTI2024

Current potential patches

A novel form of the current potential, a mathematical tool for the design of stellarators and stellarator coils, is developed. Specifically, these are current potentials with a finite-element basis, called current potential patches. Current potential patches leverage the relationship between distributions of magnetic dipoles and current potentials to explore limits of the access properties of stellarator coil sets. An example calculation is shown using the Helically Symmetric Experiment (HSX) equilibrium, demonstrating the method's use in coil design and understanding the limits of the access properties of coil sets. Current potential patches have additional desirable properties such as of promoting sparse current sheet solutions and identifying crucial locations of shaping current placement. A result is found for the HSX equilibrium that shaping currents covering only 22% of the winding surface are sufficient to produce the equilibrium to a good accuracy, provided a toroidal field is generated by an exterior coil set.

Elder, Todd↗

DOE OSTI2021

A Novel Miniaturized MIMO Microstrip Patch Antenna Array with EBG- and Slot-Loading

A compact four-element multiple-input multiple-output (MIMO) antenna array based on the miniaturized mi-crostrip patch is presented. The reduction in array form factor is realized by partially populating the ground plane with elec-tromagnetic band gap (EBG) cells constructed from cross slots, in combination with reactively loading each patch with a slot. The resultant 2 × 2 array system demonstrates excellent inter-element isolation and can be easily fabricated using traditional milling and printing techniques, as it exploits a 2D layout that can be conveniently implemented on two sides of a single-layer substrate, without the need for any via structures. The operation of the array near the 2.5 GHz band is verified with full-wave simulations. The size of the new design is approximately 42% of that employing conventional patch elements.

Liao, DaHan↗

DOE OSTI2021

Generative Patch Priors for Practical Compressive Image Recovery

In this work, we propose the generative patch prior (GPP) that defines a generative prior for compressive image recovery, based on patch-manifold models. Unlike learned, image-level priors that are restricted to the range space of a pre-trained generator, GPP can recover a wide variety of natural images using a pre-trained patch generator. Additionally, GPP retains the benefits of generative priors like high reconstruction quality at extremely low sensing rates, while also being much more generally applicable. We show that GPP outperforms several unsupervised and supervised techniques on three different sensing models – linear compressive sensing with known, and unknown calibration settings, and the non-linear phase retrieval problem. Finally, we propose an alternating optimization strategy using GPP for joint calibration-and-reconstruction which performs favorably against several baselines on a real world, uncalibrated compressive sensing dataset. The code and models for GPP are available on github.

compressed sensing↗

DOE OSTI2019

Regional and correlative sweat analysis using high-throughput microfluidic sensing patches toward decoding sweat

Recent technological advancements in wearable sensors have made it easier to detect sweat components, but our limited understanding of sweat restricts its application. A critical bottleneck for temporal and regional sweat analysis is achieving uniform, high-throughput fabrication of sweat sensor components, including microfluidic chip and sensing electrodes. To overcome this challenge, we introduce microfluidic sensing patches mass fabricated via roll-to-roll (R2R) processes. The patch allows sweat capture within a spiral microfluidic for real-time measurement of sweat parameters including [Na + ], [K + ], [glucose], and sweat rate in exercise and chemically induced sweat. The patch is demonstrated for investigating regional sweat composition, predicting whole-body fluid/electrolyte loss during exercise, uncovering relationships between sweat metrics, and tracking glucose dynamics to explore sweat-to-blood correlations in healthy and diabetic individuals. By enabling a comprehensive sweat analysis, the presented device is a crucial tool for advancing sweat testing beyond the research stage for point-of-care medical and athletic applications.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Semantic Stealth: Crafting Covert Adversarial Patches for Sentiment Classifiers Using Large Language Models

Deep learning models have been shown to be vulnerable to adversarial attacks, in which perturbations to their inputs cause the model to produce incorrect predictions. As opposed to adversarial attacks in computer vision, where small changes introduced to pixel values can drastically alter a model's output while remaining imperceptible to humans, text-based attacks are difficult to conceal due to the discrete nature of tokens. Consequently, unconstrained gradient-based attacks often produce adversarial examples that lack semantic meaning, rendering them detectable through visual inspection or perplexity filters. In contrast to methods that rely on gradient-based optimization in the embedding space, we propose an approach that leverages a Large Language Model's ability to generate grammatically correct and semantically meaningful text to craft adversarial patches that seamlessly blend in with the original input text. These patches can be used to alter the behavior of a target model, such as a text classifier. Since our approach does not rely on gradient backpropagation, it only requires access to the target model's confidence scores, making it a grey-box attack. We demonstrate the feasibility of our approach using open-source LLMs, including Intel's Neural Chat, Llama2, and Mistral-Instruct, to generate adversarial patches capable of altering the predictions of a distilBERT model fine-tuned on the IMDB reviews dataset for sentiment classification.

Roa Carvajal, Maria↗

DOE OSTI2025

CO2 and CH4 leaf-level fluxes and soil porewater concentrations from common vegetation patches in Louisiana’s coastal wetlands

This dataset contains leaf-level flux and soil porewater concentration measurements of carbon dioxide (CO2) and methane (CH4 ) in plots in the footprint of Ameriflux sites US-LA2 and US-LA3. Leaf fluxes in US-LA2 were measured on patches dominated by Sagittaria lancifolia and co-dominated by Sagittaria lancifolia and Typha latifolia. In US-LA3, fluxes were measured from distinct Juncus roemerianus and Spartina alterniflora patches. The porewater concentrations were collected across a vertical profile (~50 cm depth) at centric locations within 25 m2 plots where we measured the leaf fluxes. US-LA3 included an additional set of measurements in open water spots. We aimed to evaluate differences in leaf fluxes and porewater pools of CO2 and CH4 of representative ecohydrological patches across a salinity gradient. We also used this dataset to help develop ELM-Wet, a more realistic representation of wetland carbon biogeochemical processes within the U.S. Department of Energy’s Energy Exascale Earth System Model (E3SM) Land Model version 1 (ELM v.1). The files can be opened with regular text editors or spreadsheet programs. Version 2.0 (8/26/2025): This is the latest version of this dataset. The update includes additional samples of soil porewater CH4/CO2 concentrations from June-2021 to November-2022, as well as minor adjustments made to V1 samples via changing Henry's solubility to account for porewater salinity. Additionally leaf-level measurments of spectral indices, PSRI, NDVI, and PRI have been added to complement Leaf-level flux measurements. All V1 data sets have been integrated into V2 sheets, ensuring data from the previous version is contained with the additional samples and consistent with V2 metadata.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

MELCOR Code Change History: Revision 11932 to 14959 Patch Release Addendum

This document summarily provides brief descriptions of the MELCOR code enhancement made between code revision number 11932 and 14959. Revision 11932 represents the last official code release; therefore, the modeling features described within this document are provided to assist users that update to the newest official MELCOR code release, 14959. Along with the newly updated MELCOR Users' Guide and Reference Manual, users will be aware and able to assess the new capabilities for their modeling and analysis applications. Following the official release an addendum section has been added to this report detailing modifications made to the official release which support the accompanying patch release. The addendums address user reported issues and previously known issues within the official code release which extends the original Quick look document to also support the patch release. Furthermore, the addendums section documents the recent changes to input records in the Users' Guide applicable to the patch release and corrects a few issues in the revision 14959 release as well.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Limited-view Cone Beam CT reconstruction using 3D Patch-based Supervised and Adversarial Learning [Slides]

We present a novel machine learning CNN architecture that can learn from limited data combined appropriately with physics and statistical priors (e.g., forward models and noise models). To address the limited availability of training data we adopt a 3D patch-based approach for our models. Patch-based learning is central to several image reconstruction methods and demands fewer training data than DL approaches, as a single data volume can be broken into several millions of overlapping 3D sub-volumes or patches. This creates a very large number of training sub-volumes from a limited number of overall image volumes. A 3D Generative Adversarial Networks (GAN) is then trained to remove artifacts at the sub-volume level. The combination of a sub-volume-based approach with DL allows us to exploit the richness of the latter in extracting and representing image features, while avoiding risks associated with overfitting due to limited training data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗