Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Mask”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A Spectroscopic Study of Mars-analog Materials with Amorphous Sulfate and Chloride Phases: Implications for Detecting Amorphous Materials on the Martian Surface

The Chemistry and Mineralogy X-ray diffraction (XRD) instrument aboard the Curiosity rover consistently identifies amorphous material at Gale Crater, which is compositionally variable, but often includes elevated sulfur and iron, suggesting that amorphous ferric sulfate (AFS) may be present. Understanding how desiccating ferric sulfate brines affect the spectra of Martian material analogs is necessary for interpreting complex/realistic reaction assemblages. Visible and near-infrared reflectance (VNIR), mid-infrared attenuated total reflectance (MIR, FTIR-ATR), and Raman spectra, along with XRD data are presented for basaltic glass, hematite, gypsum, nontronite, and magnesite, each at three grain sizes (<25, 25–63, and 63–180 μm), mixed with ferric sulfate (+/–NaCl), deliquesced, then rapidly desiccated in 11% relative humidity or via vacuum. All desiccated products are partially or completely XRD amorphous; crystalline phases include starting materials and trace precipitates, leaving the bulk of the ferric sulfate in the amorphous fraction. Due to considerable spectral masking, AFS detectability is highly dependent on spectroscopic technique and minerals present. This has strong implications for remote and in situ observations of Martian samples that include an amorphous component. AFS is only identifiable in VNIR spectra for magnesite, nontronite, and gypsum samples; hematite and basaltic glass samples appear similar to pure materials. Sulfate features dominate Raman spectra for nontronite and basaltic glass samples; the analog material dominates Raman spectra of hematite and gypsum samples. MIR data are least affected by masking, but basaltic glass is almost undetectable in MIR spectra of those mixtures. NaCl produces similar FTIR-ATR and Raman features, regardless of analog material.

58 GEOSCIENCES↗
DOE OSTI2022

PRMI: A Dataset of Minirhizotron Images for Diverse Plant Root Study

Understanding a plant's root system architecture (RSA) is crucial for a variety of plant science problem domains including sustainability and climate adaptation. Minirhizotron (MR) technology is a widely-used approach for phenotyping RSA non-destructively by capturing root imagery over time. Precisely segmenting roots from the soil in MR imagery is a critical step in studying RSA features. In this paper, we introduce a large-scale dataset of plant root images captured by MR technology. In total, there are over 72K RGB root images across six different species including cotton, papaya, peanut, sesame, sunflower, and switchgrass in the dataset. The images span a variety of conditions including varied root age, root structures, soil types, and depths under the soil surface. All of the images have been annotated with weak image-level labels indicating whether each image contains roots or not. The image-level labels can be used to support weakly supervised learning in plant root segmentation tasks. In addition, 63K images have been manually annotated to generate pixel-level binary masks indicating whether each pixel corresponds to root or not. These pixel-level binary masks can be used as ground truth for supervised learning in semantic segmentation tasks. By introducing this dataset, we aim to facilitate the automatic segmentation of roots and the research of RSA with deep learning and other image analysis algorithms.

Xu, Weihuang↗
DOE OSTI2022

Evaluating cloud liquid detection against Cloudnet using cloud radar Doppler spectra in a pre-trained artificial neural network

Detection of liquid-containing cloud layers in thick mixed-phase clouds or multi-layer cloud situations from ground-based remote-sensing instruments still poses observational challenges, yet improvements are crucial since the existence of multi-layer liquid layers in mixed-phase cloud situations influences cloud radiative effects, cloud lifetime, and precipitation formation processes. Hydrometeor target classifications such as from Cloudnet that require a lidar signal for the classification of liquid are limited to the maximum height of lidar signal penetration and thus often lead to underestimations of liquid-containing cloud layers. Here we evaluate the Cloudnet liquid detection against the approach of Luke et al. (2010) which extracts morphological features in cloud-penetrating cloud radar Doppler spectra measurements in an artificial neural network (ANN) approach to classify liquid beyond full lidar signal attenuation based on the simulation of the two lidar parameters particle backscatter coefficient and particle depolarization ratio. We show that the ANN of Luke et al. (2010) which was trained under Arctic conditions can successfully be applied to observations at the mid-latitudes obtained during the 7-week-long ACCEPT field experiment in Cabauw, the Netherlands, in 2014. In a sensitivity study covering the whole duration of the ACCEPT campaign, different liquid-detection thresholds for ANN-predicted lidar variables are applied and evaluated against the Cloudnet target classification. Independent validation of the liquid mask from the standard Cloudnet target classification against the ANN-based technique is realized by comparisons to observations of microwave radiometer liquid-water path, ceilometer liquid-layer base altitude, and radiosonde relative humidity. In addition, a case-study comparison against the cloud feature mask detected by the space-borne lidar aboard the CALIPSO satellite is presented. Three conclusions were drawn from the investigation. First, it was found that the threshold selection criteria of liquid-related lidar backscatter and depolarization alone control the liquid detection considerably. Second, all threshold values used in the ANN framework were found to outperform the Cloudnet target classification for deep or multi-layer cloud situations where the lidar signal is fully attenuated within low liquid layers and the cloud radar is able to detect the microphysical fingerprint of liquid in higher cloud layers. Third, if lidar data are available, Cloudnet is at least as good as the ANN. The times when Cloudnet outperforms the ANN in liquid detections are often associated with situations where cloud dynamics smear the imprint of cloud microphysics on the radar Doppler spectra.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

CSAPR2 cell-tracking data collected during TRACER

One of the challenges of analyzing convective cell properties is quick evolution of the individual convective cells. While the operational radar data provide great a data set to analyze the evolution of radar observables of convective precipitation clouds statistically, previous studies also suggested that, because of the quick evolution of cell life cycle, conventional radar volume scan strategies taking ~5-7 minutes might not capture the detailed evolution. The TRACER campaign deployed CSAPR2, which performed frequent update of RHI and sector PPI scans to track convective cells every < 2 minutes guided by a new cell-tracking framework, Multisensor Agile Adaptive Sampling (MAAS; Kollias et al. 2020). This allows for capturing fast-evolving radar observables. The submitted data files are CSAPR2 data in CfRadial format collected during the TRACER field campaign from June to September 2020. The data files include processed radar variables including: noise-masked reflectivity and differential reflectivity corrected for rain attenuation and systematic biases, noise-masked dealiased radial velocity, specific differential phase, locations of target cells (latitude, longitude, radar range), and radar-echo classification.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

SITCOMTN-165: Surface brightness profiles around massive galaxies in LSSTComCam data

Low surface brightness photometry of massive galaxies can probe the extended stellar halos and intracluster light but is often limited by background subtraction and masking systematics. Here we present radial surface brightness profiles for the brightest cluster galaxy of Abell 360 and 2dFGRS TGS323Z113 using Rubin Observatory Commissioning Camera (LSSTComCam) Data Preview 1 in the g, r, and z bands. Our results show that the LSSTComCam data can go down to ~28 mag arcsec^-2 in the r band. Comparison to DECaLS measurements processed with Legacyhalos shows good agreement of surface brightness profiles at small radii while the LSSTComCam data extend deeper at larger radii.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Nanostructured layer for graded index freeform optics

The present disclosure relates to a method for creating an optical component having a spatially controlled refractive index. The method may involve applying a thin metal material layer to a substrate. The thin metal material layer may then be heated to create a mask having a spatially varying nano-particle distribution. The substrate may then be etched, using the mask, to imprint a spatially patterned nanostructure pattern on a surface the substrate.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Low temperature cofired ceramic substrates and fabrication techniques for the same

A low temperature cofired ceramic substrate comprises a plurality of dielectric layers, at least one inner conductor layer, a plurality of bond pads, and a solder mask. The dielectric layers are formed from ceramic material and placed one on top of another to form a stack. The inner conductor is formed from electrically conductive paste and positioned on an upper surface of at least one inner dielectric layer. The bond pads are positioned on an outer surface of the stack. Each bond pad is formed from a plurality of conductive sublayers of thin film metal stacked one on top of another, with each conductive sublayer being formed from a different metal. The solder mask is positioned on the same outer surface of the stack as the bond pads and includes a plurality of openings, with each opening exposing at least a portion of one of the bond pads.

42 ENGINEERING↗
DOE OSTI2022

Cosmic ray muon clustering for the MicroBooNE liquid argon time projection chamber using sMask-RCNN

In this article, we describe a modified implementation of Mask Region-based Convolutional Neural Networks (Mask-RCNN) for cosmic ray muon clustering in a liquid argon TPC and applied to MicroBooNE neutrino data. Our implementation of this network, called sMask-RCNN, uses sparse submanifold convolutions to increase processing speed on sparse datasets, and is compared to the original dense version in several metrics. The networks are trained to use wire readout images from the MicroBooNE liquid argon time projection chamber as input and produce individually labeled particle interactions within the image. These outputs are identified as either cosmic ray muon or electron neutrino interactions. We find that sMask-RCNN has an average pixel clustering efficiency of 85.9% compared to the dense network's average pixel clustering efficiency of 89.1%. We demonstrate the ability of sMask-RCNN used in conjunction with MicroBooNE's state-of-the-art Wire-Cell cosmic tagger to veto events containing only cosmic ray muons. The addition of sMask-RCNN to the Wire-Cell cosmic tagger removes 70% of the remaining cosmic ray muon background events at the same electron neutrino event signal efficiency. This event veto can provide 99.7% rejection of cosmic ray-only background events while maintaining an electron neutrino event-level signal efficiency of 80.1%. In addition to cosmic ray muon identification, sMask-RCNN could be used to extract features and identify different particle interaction types in other 3D-tracking detectors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

System and method for curved light sheet projection during two-photon polymerization

A laser-based manufacturing system is disclosed for fabricating non-planar three-dimensional layers. The system may have a laser for producing a laser beam with a plurality of optical wavelengths. An optically dispersive element may be used for receiving the laser beam and splitting the beam into a plurality of distinct beam components, wherein each beam component has spatially separated optical spectral components. A phase mask may be used which is configured to receive at least one of the beam components emerging from the dispersive element and to create a modified beam. One or more focusing elements may then be used to receive the modified beam emerging from the phase mask and to focus the modified beam into a non-planar light sheet for use in fabricating a part.

Saha, Sourabh Kumar↗
DOE OSTI2022

System and method for x-ray compatible 2D streak camera for a snapshot multiframe imager

The present disclosure is directed to a snapshot multiframe imager having an aperture element having at least one aperture, an adjacently positioned random mask, an imaging element and a computer. The random mask has a plurality of micron scale apertures and receives light passing through the aperture element, which represents the spatial information from the scene being imaged, and generates a plurality of image frames encoded in a spatial domain. The imaging element may operate in a drift-scan mode receives the encoded image frames and generates a streaked pattern of electrons representing a plurality of images of the scene at a plurality of different times. The computer analyzes the streaked pattern of electrons and mathematically reconstructs the plurality of images.

Dayton, Matthew S.↗
DOE OSTI2023

Fundamentals of Defect-Free III-V Growth on Oxide-Nanopatterned GaAs Substrates

This talk describes the fundamentals underlying defect-free growth of large-area III-V devices on oxide-nanopatterned GaAs substrates, and applies them to the growth of 24.8% efficient GaAs solar cells with a dislocation density less than 5 x 10^5 cm^-2. In this application the nanopatterned oxide layer serves as a mechanically-weak layer for substrate separation and reuse, but in other applications it could serve as an optical element to diffract or redirect light. This presentation focuses on how the topology and dimensions of the oxide mask must be controlled to avoid defect formation wherever the epilayer coalesces over a mask feature.

ENGINEERING,SOLAR ENERGY↗
DOE OSTI2023

Method of chemical doping that uses CMOS-compatible processes

A method of Atomic Precision Advanced Manufacturing (APAM) is provided, in which a substrate is doped from a dopant precursor gas. The method involves covering a surface of the substrate with a hard mask, selectively removing material from the hard mask such that selected areas of the substrate surface are laid bare, exposing the laid-bare areas to the dopant precursor gas, and heating the substrate so as to incorporate dopant from the dopant precursor gas into the substrate surface.

Misra, Shashank↗
DOE OSTI2023

System and method for organic electronic device patterning

A method for fabricating an organic electronic device comprises providing a plurality of photoresist structures on a substrate, the substrate having a first electrode layer, the photoresist structures having a bottom surface attached to the substrate and a top surface opposite the bottom surface, the top surface having a dimension greater than a dimension of the bottom surface, positioning a mask over the structures, the mask having a plurality of openings, and depositing an emissive material over the substrate through at least one of the plurality of openings to form at least one emissive element. An organic electronic device and a method of fabricating an organic electronic component are also described.

Forrest, Stephen R.↗
DOE OSTI2024

Fabrication method for a component having magnetic and non-magnetic dual phases

Methods for forming a dual-phase magnetic component from an initial component comprising a non-magnetic austenite composition are provided. The method may include: forming a coating on a portion of the surface of the initial component to form a masked area while leaving an unmasked area thereon. Thereafter the initial component may be heated to a treatment temperature such that nitrogen diffuses out of the unmasked area of the initial component to transform the non-magnetic austenite composition to a magnetic phase in the unmasked area. Thereafter, the initial component may be cooled from the treatment temperature to form a dual-phase magnetic component having a magnetic region corresponding to the unmasked area and a non-magnetic region corresponding to the masked area.

Huang, Shenyan↗
DOE OSTI2025

Active Learning Meets Foundation Models: Fast Remote Sensing Data Annotation for Object Detection

Object detection in remote sensing demands extensive, high-quality annotations—a process that is both labor-intensive and time-consuming. In this work, we introduce a real-time active learning and semi-automated labeling framework that leverages foundation models to streamline dataset annotation for object detection in remote sensing imagery. For example, by integrating a Segment Anything Model (SAM), our approach generates mask-based bounding boxes that serve as the basis for dual sampling: (a) uncertainty estimation to pinpoint challenging samples, and (b) diversity assessment to ensure broad data coverage. Furthermore, our Dynamic Box Switching Module (DBS) addresses the well-known cold start problem for object detection models by replacing its suboptimal initial predictions with SAM-derived masks, thereby enhancing early-stage localization accuracy. Extensive evaluations on multiple remote sensing datasets plus a real-world user study, demonstrate that our framework not only reduces annotation effort, but also significantly boosts detection performance compared to traditional active learning sampling methods. The code for training and the user interface will be made available.

Burges, Marvin [ORNL] (ORCID:0000000312690769)↗
DOE OSTI2025

Filter-Banks for Ultra-Wideband Communications, Sensing, and Localization

Recently, filterbank multi-carrier spread spectrum (FBMC-SS) has been proposed as a candidate waveform for ultrawideband (UWB) communications. It has been noted that FBMCSS is a perfect match to this application, leading to a trivial method of matching to the required spectral mask at different regions of the world. FBMC-SS also allows easy rejection of high-power interfering signals that may appear over different parts of the UWB spectral band. In this paper, we concentrate on the use of staggered multitone spread spectrum (SMT-SS) for UWB communications. SMT makes use of offset QAM modulation to transmit data symbols over narrowband, overlapping subcarrier bands. This form of FBMC-SS is well-suited to UWB communications because it has good spectral efficiency and a flat power spectral density (PSD), resulting in good utilization of the UWB spectral mask. Additionally, we explore new methods for multi-coding that result in higher bit rates than previous FBMCSS systems. Moreover, we study methods for equalizing the UWB multipath channel and cancelling narrowband interference. Excellent performance of the proposed methods are substantiated by presenting simulation results.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Designer Metasurfaces for Antireflective Applications Enabled by Advanced Nanoparticle Technology

Optic processing advances have shifted system limitations, with current constraints consisting of antireflective (AR) coatings applied to optics and the inability to reduce size, weight, and price. Metasurfaces, and more broadly metaoptics, provide an avenue to overcome these limitations. The ability to generate substrate-engraved metasurfaces that can be tailored is demonstrated within a broad design space to satisfy large-area AR applications for bandpass or broadband needs, demonstrating an optically equivalent surface roughness standard deviation of only 5 Å. Using an advanced nanoparticle masking approach, two metasurfaces are fabricated: 1) vertical sidewall nanofeature metasurface (MS) for AR applications at 351 nm, and 2) sloped sidewall MS designed for broadband AR applications. For the 351 nm MS, the reflectance is measured to be 0.127%. In the case of the sloped sidewall MS, the reflectance is measured to be <0.25% over 400–700 nm and <1% over 400–1100 nm. To the best of the authors’ knowledge, this is the first demonstration of a broadband AR capable of this performance. The tunability of these structures, with a parameter space spanning even more remarkable designs such as broader bands and acceptance angles, coupled with high laser-induced damage durability and mechanical robustness, displays the strength of metasurfaces for AR applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Three-Dimensional Analysis of Particle Distribution on Filter Layers inside N95 Respirators by Deep Learning

The global COVID-19 pandemic has changed many aspects of daily lives. Wearing personal protective equipment, especially respirators (face masks), has become common for both the public and medical professionals, proving to be effective in preventing spread of the virus. Nevertheless, a detailed understanding of respirator filtration-layer internal structures and their physical configurations is lacking. Here, we report three-dimensional (3D) internal analysis of N95 filtration layers via X-ray tomography. Using deep learning methods, we uncover how the distribution and diameters of fibers within these layers directly affect contaminant particle filtration. The average porosity of the filter layers is found to be 89.1%. Contaminants are more efficiently captured by denser fiber regions, with fibers <1.8 μm in diameter being particularly effective, presumably because of the stronger electric field gradient on smaller diameter fibers. This study provides critical information for further development of N95-type respirators that combine high efficiency with good breathability.

42 ENGINEERING↗