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At least 163 records · Page 9

Efficient facemask decontamination via forced ozone convection

The COVID-19 crisis has taken a significant toll on human life and the global economy since its start in early 2020. Healthcare professionals have been particularly vulnerable because of the unprecedented shortage of Facepiece Respirators (FPRs), which act as fundamental tools to protect the medical staff treating the coronavirus patients. In addition, many FPRs are designed to be disposable single-use devices, creating an issue related to the generation of large quantities of non-biodegradable waste. In this contribution, we describe a plasma-based decontamination technique designed to circumvent the shortages of FPRs and alleviate the environmental problems posed by waste generation. The system utilizes a Dielectric Barrier Discharge (DBD) to generate ozone and feed it through the fibers of the FPRs. The flow-through configuration is different than canonical ozone-based sterilization methods, in which the equipment is placed in a sealed ozone-containing enclosure without any flow through the mask polymer fibers. We demonstrate the rapid decontamination of surgical masks using Escherichia coli ( E. coli ) and Vesicular Stomatitis Virus (VSV) as model pathogens, with the flow-through configuration providing a drastic reduction in sterilization time compared to the canonical approach. We also demonstrate that there is no deterioration in mask structure or filtration efficiency resulting from sterilization. Finally, we show that this decontamination approach can be implemented using readily available tools, such as a plastic box, a glass tube, few 3D printed components, and the high-voltage power supply from a plasma globe toy. The prototype assembled for this study is portable and affordable, with effectiveness comparable to that of larger and more expensive equipment.

36 MATERIALS SCIENCE↗

Self Assembled Monolayers for Passivated Contacts

Passivated contacts mitigate defects typically encountered due metallization of solar cells. We deposit amorphous silicon (a-Si:H) on an oxidized silicon wafer via PECVD and anneal at high temperature to crystallize into polysilicon passivated contact. One drawback is the absorption of the polysilicon between grid fingers, so removal of this material is desirable to maximize Jsc. Alternatively, interdigitated back contact cells rely on a gap between n- and p- fingers, which is commonly etched to ensure electronic isolation. We utilize a self assembled monolayer (SAM) using hexamethyldisilazane (HMDS) as a precursor to pattern and etch amorphous silicon (a-Si:H) and polysilicon without the need for photoresist. Ultraviolet light exposure oxidizes the HMDS by photocleaving the organic groups [1] of the SAM leaving a patterned SiO2. Directly soaking this in TMAH will eventually etch the SAM and the silicon, where the SiO2 serves as an etch mask. Inversely, a dilute HF dip selectively etches this SiO2 and the SAM remains. A subsequent soak in TMAH selectively etches the underlying silicon, where the SAM serves as an etch mask. Importantly, we find that the SAM can remain intact for metallization, where we measure 10 mO-cm2 specific contact resistivity on n-type polysilicon.

passivation↗

Engineering a tumor-selective prodrug T-cell engager bispecific antibody for safer immunotherapy

T-cell engaging (TCE) bispecific antibodies are potent drugs that trigger the immune system to eliminate cancer cells, but administration can be accompanied by toxic side effects that limit dosing. TCEs function by binding to cell surface receptors on T cells, frequently CD3, with one arm of the bispecific antibody while the other arm binds to cell surface antigens on cancer cells. On-target, off-tumor toxicity can arise when the target antigen is also present on healthy cells. The toxicity of TCEs may be ameliorated through the use of pro-drug forms of the TCE, which are not fully functional until recruited to the tumor microenvironment. This can be accomplished by masking the anti-CD3 arm of the TCE with an autoinhibitory motif that is released by tumor-enriched proteases. Here, we solve the crystal structure of the antigen-binding fragment of a novel anti-CD3 antibody, E10, in complex with its epitope from CD3 and use this information to engineer a masked form of the antibody that can activate by the tumor-enriched protease matrix metalloproteinase 2 (MMP-2). We demonstrate with binding experiments and in vitro T-cell activation and killing assays that our designed prodrug TCE is capable of tumor-selective T-cell activity that is dependent upon MMP-2. Furthermore, we demonstrate that a similar masking strategy can be used to create a pro-drug form of the frequently used anti-CD3 antibody SP34. This study showcases an approach to developing immune-modulating therapeutics that prioritizes safety and has the potential to advance cancer immunotherapy treatment strategies.

60 APPLIED LIFE SCIENCES↗

Weighted FFT estimators for 1D and 3D correlations of the Lyman- α forest

Correlations in the Lyman-α (Lyα) forest, both as a function of line of sight separation (1D) and 3D separation, provide a unique window to the distribution of matter at redshifts not accessible by current galaxy surveys. While optimal quadratic estimators have been used to measure 1D correlations, they are computationally expensive and difficult to extend to 3D analyses. On the other hand, estimators based on the Fast Fourier Transform (FFT) are significantly faster, but are affected by missing data in the spectra (masked pixels) and so far have not used pixel weights to reduce the uncertainties in the measurement. In this publication we describe how to compute the window matrix that enables forward-modelling the impact of masked pixels and weights on the FFT-based estimators. Here, we use Gaussian and hydrodynamical simulations with artificially masked pixels to validate the method on the measurement of 1D correlations. Finally, we show that the formalism can be extended to model the impact on 3D correlations, in particular on the cross-spectrum, the correlation of 1D Fourier modes as a function of transverse separation. This work will enable more precise clustering measurements with the Lyα forest dataset recently collected by the Dark Energy Spectroscopic Instrument (DESI).

Lokken, Martine [Univ. Autonoma de Barcelona (Spai↗

First Direct-Detection Results on Sub-GeV Dark Matter Using the SENSEI Detector at SNOLAB

Here, we present the first results from a dark matter search using six Skipper-CCDs in the SENSEI detector operating at SNOLAB. We employ a bias-mitigation technique of hiding approximately 46% of our total data and aggressively mask images to remove backgrounds. Given a total exposure after masking of 100.72 gram-days from well-performing sensors, we observe 55 two-electron events, 4 three-electron events, and no events containing 4–10 electrons. The two-electron events are consistent with pileup from one-electron events. Among the 4 three-electron events, 2 appear in pixels that are likely impacted by detector defects, although not strongly enough to trigger our “hot-pixel” mask. We use these data to set world-leading constraints on sub-GeV dark matter interacting with electrons and nuclei.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Determination of hard X-ray polarization from two-dimensional images

In this work, an estimate of synchrotron hard X-ray incident beam polarization is obtained by partial two-dimensional image masking followed by integration. With the correct polarization applied to each pixel in the image, the resulting one-dimensional pattern shows no discontinuities arising from the application of the mask. Minimization of the difference between the sums of the masked and unmasked powder patterns allows estimation of the polarization to ±0.001.

47 OTHER INSTRUMENTATION↗

A coded aperture microscope for X-ray fluorescence full-field imaging

The design and construction of an instrument for full-field imaging of the X-ray fluorescence emitted by a fully illuminated sample are presented. The aim is to produce an X-ray microscope with a few micrometers spatial resolution, which does not need to scan the sample. Since the fluorescence from a spatially inhomogeneous sample may contain many fluorescence lines, the optic which will provide the magnification of the emissions must be achromatic, i.e. its optical properties must be energy-independent. The only optics which fulfill this requirement in the X-ray regime are mirrors and pinholes. The throughput of a simple pinhole is very low, so the concept of coded apertures is an attractive extension which improves the throughput by having many pinholes, and retains the achromatic property. Modified uniformly redundant arrays (MURAs) with 10 µm openings and 50% open area have been fabricated using gold in a lithographic technique, fabricated on a 1 µm-thick silicon nitride membrane. The gold is 25 µm thick, offering good contrast up to 20 keV. The silicon nitride is transparent down into the soft X-ray region. MURAs with various orders, from 19 up to 73, as well as their respective negative (a mask where open and closed positions are inversed compared with the original mask), have been made. Having both signs of mask will reduce near-field artifacts and make it possible to correct for any lack of contrast.

36 MATERIALS SCIENCE↗

Trap-Assisted Dopant Compensation Prevents Shunting in poly-Si Passivating Interdigitated Back Contact Silicon Solar Cells

Interdigitated back contact (IBC) solar cells achieve the highest efficiencies of single-junction architectures, but complicated patterning of the rear fingers and spreading of dopants during processing inhibit their mainstream adoption due to concerns of shunting between the IBC fingers. One method of simplifying patterning at the rear is by using contact masks combined with plasma-enhanced chemical vapor deposition (PECVD) or ion implantation. However, the intrinsic isolation region becomes contaminated during high-temperature annealing by lateral diffusion of dopants and during masked PECVD by spreading of dopant radicals through region between the mask and the substrate. Despite this contamination, we show through scanning spreading resistance microscopy and Kelvin probe force microscopy that a ~20 µm wide compensating region exists with high enough resistivity to prevent shunting. We model this p-i-n poly-Si system using two simulation models: a simple resistor model considering only the capture of charge carriers by trap defects in poly-Si to reduce the conductivity, and a more refined 1-dimensional finite element model using Poisson’s equation, drift-diffusion equations, and recombination of carriers. Using this model, we show that high defect density significantly decreases the current across the region between the p- and n-type fingers, preventing shunting.

atom probe↗

Deep Learning Denoiser

SAND2022-14744 O The Deep Learning Denoiser uses a trained deep convolutional neural network (CNN) model to decompose an input waveform into a signal and noise waveform. In the approach, the CNN provides a signal mask and a noise mask for an input signal. The Short-Time Fourier Transform (STFT) of the estimated signal is obtained by multiplying the signal mask with the STFT of the input signal. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Koch, Clinton↗

pnnl/SAMIAm

We apply semantic boosting to the Segment Anything Model (SAM) to obtain microstructure segmentation for transmission electron microscopy. Our booster, SAM-I-Am, extracts geometric and textural features of various intermediate masks to perform mask removal and mask merging operations

Mesfin, Waqwoya↗

River bank erosion and accretion rates, and planform metrics of the East River, downstream of Gothic Colorado over intervals between 1955 and 2015

This dataset provides the tabular summary of analysis of an alluvial floodplain reach of the East River, downstream of Gothic, CO near Crested Butte. The measurements include bank erosion and accretion rates, channel width, bank curvature, and the aspect/orientation of the river banks. The measurements were derived from binary masks of the location of the river channel from aerial and satellite imagery collected on seven dates over a sixty-year timespan: 1955, 1973, 1983, 1990, 2001, 2011, and 2015. The masks were analyzed using the Spatially Continuous Riverbank Erosion and Accretion Measurements (SCREAM) software detailed in Rowland et al. 2016. The masks used in this analysis can be found an accompanying dataset (DOI: ). Rates of change along the East River were measured over a total of 8-time intervals: 1955-1973; 1955-2015; 1973-1983; 1983-1990; 1990-2001; 2001-2011; 2001-2015; and 2011-2015.In files with “summary” in the name, the data is provided at a pixel level, where each mapped bank pixel has an associated erosion or accretion value, a channel width, a curvature value, and an aspect each river and time period will have an individual file. Files with “Segments” in name provide data that is averaged along segments of the rivers. These segments are approximately 10 channel widths in length. In addition to erosion and accretion rates, the segment-based results include area measurements of erosion and accretion, islands, and channels. The number of islands is also included.

54 ENVIRONMENTAL SCIENCES↗

Deep Learning Denoising Applied to Regional Distance Seismic Data in Utah

Seismic waveform data are generally contaminated by noise from various sources. Suppressing this noise effectively so that the remaining signal of interest can be successfully exploited remains a fundamental problem for the seismological community. To date, the most common noise suppression methods have been based on frequency filtering. These methods, however, are less effective when the signal of interest and noise share similar frequency bands. Inspired by source separation studies in the field of music information retrieval (Jansson et al., 2017) and a recent study in seismology (Zhu et al., 2019), we implemented a seismic denoising method that uses a trained deep convolutional neural network (CNN) model to decompose an input waveform into a signal of interest and noise. In our approach, the CNN provides a signal mask and a noise mask for an input signal. The short-time Fourier transform (STFT) of the estimated signal is obtained by multiplying the signal mask with the STFT of the input signal. To build and test the denoiser, we used carefully compiled signal and noise datasets of seismograms recorded by the University of Utah Seismograph Stations network. Results of test runs involving more than 9000 constructed waveforms suggest that on average the denoiser improves the signal-to-noise ratios (SNRs) by ~5 db, and that most of the recovered signal waveforms have high similarity with respect to the target waveforms (average correlation coefficient of ~0.80) and suffer little distortion. Application to real data suggests that our denoiser achieves on average a factor of up to ~2-5 improvement in SNR over band-pass filtering and can suppress many types of noise that band-pass filtering cannot. For individual waveforms, the improvement can be as high as ~15 db.

58 GEOSCIENCES↗

RivGraph: Automatic extraction and analysis of river and delta channel network topology

River networks sustain life and landscapes by carrying and distributing water, sediment, and nutrients throughout ecosystems and communities. At the largest scale, river networks drain continents through tree-like tributary networks. At typically smaller scales, river deltas and braided rivers form loopy, complex distributary river networks via avulsions and bifurcations.In order to model flows through these networks or analyze network structure, the topology, or connectivity, of the network must be resolved. Additionally, morphologic properties of each river channel as well as the direction of flow through the channel inform how fluxes travel through the network’s channels. Riv Graphis a Python package that automates the extraction and characterization of river channel networks from a user-provided binary image, or mask, of a channel network (Fig. 1). Masks may be derived from (typically remotely-sensed) imagery, simulations, or even hand-drawn. RivGraph will create explicit representations of the channel network by resolving river centerlines as links, and junctions as nodes. Flow directions are solved for each link of the network without using auxiliary data, e.g., a digital elevation model (DEM). Morphologic properties are computed as well, including link lengths, widths, sinuosities, branching angles,and braiding indices. If provided,RivGraph will preserve georeferencing information of the mask and will export results as ESRI shapefiles, GeoJSONs, and GeoTIFFs for easy import into GIS software.RivGraph can also return extracted networks as networkx objects for convenient interfacing with the full-featured networkx package (Hagberg et al., 2008). Finally, RivGraph offers a suite of topologic metrics that were specifically designed for river channel network analysis (Tejedor et al., 2015b).

54 ENVIRONMENTAL SCIENCES↗

Array of Graphene Variable Capacitors on 100 mm Silicon Wafers for Vibration-Based Applications

Highly flexible, electrically conductive freestanding graphene membranes hold great promise for vibration-based applications. This study focuses on their integration into mainstream semiconductor manufacturing methods. We designed a two-mask lithography process that creates an array of freestanding graphene-based variable capacitors on 100 mm silicon wafers. The first mask forms long trenches terminated by square wells featuring cone-shaped tips at their centers. The second mask fabricates metal traces from each tip to its contact pad along the trench and a second contact pad opposite the square well. A graphene membrane is then suspended over the square well to form a variable capacitor. The same capacitor structures were also built on 5 mm by 5 mm bare dies containing an integrated circuit underneath. We used atomic force microscopy, optical microscopy, and capacitance measurements in time to characterize the samples.

36 MATERIALS SCIENCE↗

Improvements in the Sample Space for the Backscattering Silicon Spectrometer (BASIS)

The increase in neutron flux at the Oak Ridge National Laboratory (ORNL) Spallation Neutron Source (SNS), currently operating at 2.0 MW proton beam power, has created new opportunities for higher-throughput neutron scattering experiments while also increasing the importance of minimizing background scattering and optimizing sample-environment operations. To address these challenges on the Backscattering Silicon Spectrometer (BA-SIS), several upgrades were developed and evaluated, including boron carbide (B₄C) masking for flat-plate sample containers, multi-cell sample holders used with a vertically translating sample stick, and an automated helium pump and purge (HPP) system for closed-cycle refrigerators. Neutron diffraction measurements demonstrate that B₄C masks reduce background scattering by 49–67%, outperforming both borated aluminum and boron nitride masks while introducing no additional Bragg reflections within the instrument’s accessible Q-range. Commissioning tests of a double-cell flat-plate sample contain-er showed no measurable crosstalk between adjacent sample compartments and con-firmed stable thermal performance, enabling multiple samples to be measured without re-peated temperature cycling. In addition, the automated HPP system provided reproducible sample-space gas handling with approximately ±1 mbar precision while reducing the need for operator intervention and supporting remote operation. Together, these developments improve signal-to-noise performance, increase experimental throughput, and enhance operational efficiency at BASIS, supporting the instrument’s continued operation under higher neutron flux conditions.

Jalarvo, Niina [ORNL] (ORCID:0000000306446866)↗

Identifying insects, clouds, and precipitation using vertically pointing polarimetric radar Doppler velocity spectra

Abstract. This study presents a method to identify and distinguish insects, clouds, and precipitation in 35 GHz (Ka-band) vertically pointing polarimetric radar Doppler velocity power spectra and then produce masks indicating the occurrence of hydrometeors (i.e., clouds or precipitation) and insects at each range gate. The polarimetric radar used in this study transmits a linear polarized wave and receives signals in collinear (CoPol) and cross-linear (XPol) polarized channels. The measured CoPol and XPol Doppler velocity spectra are used to calculate linear depolarization ratio (LDR) spectra. The insect–hydrometeor discrimination method uses CoPol and XPol spectral information in two separate algorithms with their spectral results merged and then filtered into single value products at each range gate. The first algorithm discriminates between insects and clouds in the CoPol Doppler velocity power spectra based on the spectra texture, or spectra roughness, which varies due to the scattering characteristics of insects vs. cloud particles. The second algorithm distinguishes insects from raindrops and ice particles by exploiting the larger Doppler velocity spectra LDR produced by asymmetric insects. Since XPol power return is always less than CoPol power return for the same target (i.e., insect or hydrometeor), fewer insects and hydrometeors are detected in the LDR algorithm than the CoPol algorithm, which drives the need for a CoPol based algorithm. After performing both CoPol and LDR detection algorithms, regions of insect and hydrometeor scattering from both algorithms are combined in the Doppler velocity spectra domain and then filtered to produce a binary hydrometeor mask indicating the occurrence of cloud, raindrops, or ice particles at each range gate. Forty-seven summertime days were processed with the insect–hydrometeor discrimination method using US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program Ka-band zenith pointing radar observations in northern Oklahoma, USA. For these 47 d, over 70 % of the hydrometeor mask column bottoms were within ±100 m of simultaneous ceilometer cloud base heights. All datasets and images are available to the public on the DOE ARM repository.

54 ENVIRONMENTAL SCIENCES↗

Methods of making a component with variable magnetization and related components

A method of forming a component having a variation in saturation magnetization is presented. The method includes selectively diffusing nitrogen into a metallic component of a masked metallic component by exposing the masked metallic component to a nitrogen-rich atmosphere. The masked metallic component includes a patterned oxide layer formed on a surface of the metallic component, and the patterned oxide layer includes an oxide of a metal present in the metallic component. A related component is also presented.

36 MATERIALS SCIENCE↗

System and method for sub micron additive manufacturing

An apparatus is disclosed for performing an additive manufacturing operation to form a structure by processing a photopolymer resist material. The apparatus may incorporate a laser for generating a laser beam, and a tunable mask for receiving the laser beam which has an optically dispersive element. The mask splits the laser beam into a plurality of emergent beams each having a subplurality of beamlets of varying or identical intensity, with each beamlet emerging from a unique subsection of illuminated regions of the mask. A collimator collimates at least one of the emergent beams to form a collimated beam. One or more focusing elements focuses the collimated beam into a focused beam which is projected as a focused image plane on or within the resist material. The focused beam simultaneously illuminates a layer of the resist material to process an entire layer in a parallel fashion.

Saha, Sourabh Kumar↗