Search NASA⌕ Search

SEARCH · Search NASA

Results for “improve standardization”

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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

DOE BSSD Performance Management Metrics Report Q3

Microbiome data is complex, spanning information from microbial genomes within diverse communities, protein and metabolite readouts, and contextual information (metadata) captured from the environments from which these samples were collected. While the variety and scale of microbiome data generation has dramatically expanded over the past twenty years, infrastructure to support data management, sharing, and access has lagged. New ways to improve interoperability across existing resources and advancing community standards are necessary to support how researchers create, use, and reuse data. The National Microbiome Data Collaborative (NMDC) aims to advance a microbiome data sharing network through infrastructure, data standards, and community building.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

UHT-CAMANCHE: Ultra-High Temperature Ceramic Additively Manufactured Compact Heat Exchangers

The conceptual basis for this project is the convergence of advanced ultra-high temperature ceramic materials and additive manufacturing technologies to produce compact ceramic heat exchangers with complex internal flow path geometries. Task areas were broadly divided into materials and manufacturing development, heat exchanger design, component testing, and techno-economic analysis. Technical challenges included the design and commissioning of new test facilities, improving feature resolution and deposition rate of ceramic additive manufacturing techniques, establishing process-structure-property relationships in additively manufactured ultra-high temperature ceramics, and assessing high temperature materials compatibility in CO 2 environments. The primary candidate material evaluated in this work is a composite comprising zirconium diboride (ZrB2) with 30 vol. % silicon carbide (SiC) which was selected based on its desirable combination of high temperature mechanical properties, high thermal and electrical conductivities, and oxidation resistance. High solids loaded ZrB2-SiC pastes suitable for extrusion-based additive manufacturing were developed for the first time as part of this work. Materials compatibility studies indicate this material oxidizes in CO 2 to form a protective borosilicate scale which transforms to pure silica above 1000°C. Parts made by additive manufacturing displayed enlarged grain sizes produced by pressureless sintering as compared to hot-press sintering. Increases in microstructural coarseness have outsized effect on oxidation performance up to 1400°C due to incomplete oxidation of coarse large diameter SiC particles resulting in lower amounts of silica that apparently inhibit protective scale formation. Additive manufacturing as a forming technique did not appear to significantly affect thermal conductivity, hardness, or elastic modulus, though flexural strength was reduced by half or more as compared to traditionally hot-pressed materials. This effect was attributed to the presence of strength-limiting flaws (ca. 40 microns in size) originating from extrudate inhomogeneities that could potentially be eliminated with further process improvements. Attempts to attain economies of scale for production of multi-kilowatt scale heat exchangers by ceramic additive manufacturing proved difficult. Lack of automation and a modest extrusion rate while retaining fine feature resolution made the overall process labor intensive and limited experimental throughput. A number of full-scale components were taken through post-process heat treatments including drying, binder burnout, and sintering; however, none survived without significant flaws or cracks. Therefore, no operational data from a newly installed heat exchanger test loop were able to be obtained during the performance period. Continued research and development is recommended to improve economic feasibility of ceramic additive manufacturing by standardizing the use of advanced sensors, artificial intelligence, and automation tools to reduce associated labor costs and accelerate production rates. The materials and manufacturing techniques demonstrated in this work are likely to find applications in defense and energy applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Radiometric Testing of Germicidal UV Products, Round 2: Upper-Room Luminaires (CALiPER Report)

This report analyzes the independently tested performance of eight germicidal ultraviolet (GUV) upper-room luminaires marketed for use in occupied spaces and purchased between March and June 2023. Three of the luminaires used UV-emitting LEDs, and the remaining five luminaires used low-pressure mercury (LPM) lamps. Product testing covered radiometric and electrical performance for each luminaire. Initial performance was measured for all eight products, and four were additionally measured after 100 h and 500 h of operation. Measured performance was compared against manufacturer or vendor claims. Specifiers and buyers of GUV products need accurate performance claims and data to deploy GUV technology safely and effectively. As with the CALiPER GUV Round 1 report, this CALiPER GUV Round 2 report demonstrates that manufacturers and vendors need significant education and training to accurately test and report the performance of their GUV products. Further development of industry consensus standards and guidelines may address testing limitations and improve test methods, product performance, and the accuracy of performance claims.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Union through UNITY: Cosmology with 2000 SNe Using a Unified Bayesian Framework

Type Ia supernovae (SNe Ia) were instrumental in establishing the acceleration of the Universe’s expansion. By virtue of their combination of distance reach, precision, and prevalence, they continue to provide key cosmological constraints, complementing other cosmological probes. Individual SN surveys cover only over about a factor of 2 in redshift, so compilations of multiple SN data sets are strongly beneficial. We assemble an up-to-date “Union” compilation of 2087 cosmologically useful SNe Ia from 24 data sets (“Union3”). We take care to put all SNe on the same distance scale and update the light-curve fitting with SALT3 to use the full rest-frame optical. Over the next few years, the number of cosmologically useful SNe Ia will increase by more than a factor of 10, and keeping systematic uncertainties subdominant will be more challenging than ever. We discuss the importance of treating outliers, selection effects, light-curve shape/color populations/standardization relations, unexplained dispersion, and heterogeneous observations simultaneously. We present an updated Bayesian framework, called UNITY1.5 (Unified Nonlinear Inference for Type-Ia cosmologY), that incorporates significant improvements in our ability to model selection effects, standardization, and systematic uncertainties compared to earlier analyses. As an analysis byproduct, we also recover the posterior of the SN-only peculiar-velocity field, although we do not interpret it in this work. We compute updated cosmological constraints with Union3 and UNITY1.5, finding weak 1.7σ–2.6σ tension with flat cold dark matter and possible evidence for thawing dark energy (w0 > − 1, wa < 0). We release our SN distances, light-curve fits, and UNITY1.5 framework to the community.

Rubin, David↗
DOE OSTI2024

R&D to Ensure a Scientific Basis for Qualification Tests and Standards (Final Report)

Project return on investment in a photovoltaic (PV) system depends increasingly on maintaining high energy yields, and the system lifetime is a major factor in levelized cost of electricity (LCOE). Thus, the rate of PV deployment and the success of these assets depends upon reliable long-term power generation. The overarching objective of this program is to improve photovoltaic (PV) module reliability via development of tests and standards. Where reliability problems or risk are discovered, we can design tests to ensure that these liabilities don't affect future generations of products. Customers can use these tests to understand which products are susceptible to certain degradation mechanisms, and manufacturers can use the tests to design unwanted characteristics out of their products. The work under this program identifies PV reliability needs, performs characterization that provides scientific understanding of targeted degradation mechanisms, and translates those data into practical and predictive test protocols and standards. Major accomplishments include: A model for polarization-type potential induced degradation (PID-p) was developed and validated against experimental data. NREL is currently leading a new edition of IEC 62804-1 for PID detection. PID-p can cause large losses in current and voltage for some module designs on cloudy days. Finite element modeling (FEM) and experiment was used to determine when cells crack in a module. It was shown that cells in landscape orientation are much more likely to crack than those on portrait orientation. Shortly thereafter, the first products with portrait-oriented cells were introduced. Studies of how to test for light and elevated temperature degradation (LeTID) culminated with the publication of IEC TS 63342. Software to predict the progression of LeTID was developed, validated, and made publicly available. Field validated tests and international standards for durability of PV module coatings abrasion, backsheets, and encapsulants were developed. Examples are IEC 62788-1-1, IEC 62788-2 ED2, IEC TS 62788-7-2, IEC 62788-7-3 ED1, IEC 63209-2. NREL led the development a high-temperature testing technical specification, and published guidelines that enable installers to determine whether higher-temperature testing is needed, simply based on location and mounting configuration. In a number of our case studies, variations in the bills of materials or workmanship have been associated with variations in reliability. These observations emphasize the importance of quality assurance to reliability. A framework for criticality (i.e. Pareto) analysis was developed and published. The framework helps us and other researchers determine what problems should be addressed for reliability research to have the biggest industry impact. NREL continues to participate actively in international standards development and stakeholder engagement activities, including organizing an annual PV Reliability Workshop. These activities are important for ensuring we address issues that are relevant and timely, and that we convey our results to those who may benefit.

14 SOLAR ENERGY↗
DOE OSTI2026

Solar Radiation Research Laboratory (SRRL) Core Project Final Report: Fiscal Years 2022-2024

The Solar Radiation Research Laboratory (SRRL) at the National Laboratory of the Rockies (NLR) is a world-leading solar calibration and measurement facility and maintains and disseminates the World Radiation Reference (essentially the W/m2) for the United States that is essential for traceable and accurate measurements of solar radiation at all solar generation facilities. SRRL operates two calibration facilities that meet International Standards Organization-17025 (ISO-17025) standards and provide unique high-quality calibrations to NREL and other U.S. Department of Energy laboratories. The Baseline Measurement System (BMS) at SRRL provides a high-quality record of solar irradiance and surface meteorological conditions. SRRL capabilities are used to develop (1) improved methods for the calibration of solar radiometers; (2) new standards through the ISO, the International Electrotechnical Commission (IEC), and the American Standards for Testing of Materials (ASTM) International; (c) solar radiation and meteorological models; and (d) advanced instrumentation and methods for operating solar measurement stations. The SRRL datasets are also critical for the validation of new models and datasets, such as the National Solar Radiation Database (NSRDB). The research and development of solar radiation measurement systems and resource modeling techniques are essential for advancing the scientific basis for producing reliable resource data. Specifically, the spatial, temporal, and spectral (wavelength dependency) characteristics of the solar resource are required in several different time frames for various project phases.

14 SOLAR ENERGY↗
DOE OSTI2024

Refactoring the elastic–viscous–plastic solver from the sea ice model CICE v6.5.1 for improved performance

This study focuses on the performance of the elastic–viscous–plastic (EVP) dynamical solver within the sea ice model, CICE v6.5.1. The study has been conducted in two steps. First, the standard EVP solver was extracted from CICE for experiments with refactored versions, which are used for performance testing. Second, one refactored version was integrated and tested in the full CICE model to demonstrate that the new algorithms do not significantly impact the physical results. The study reveals two dominant bottlenecks, namely (1) the number of Message Parsing Interface (MPI) and Open Multi-Processing (OpenMP) synchronization points required for halo exchanges during each time step combined with the irregular domain of active sea ice points and (2) the lack of single-instruction, multiple-data (SIMD) code generation. The standard EVP solver has been refactored based on two generic patterns. The first pattern exposes how general finite differences on masked multi-dimensional arrays can be expressed in order to produce significantly better code generation by changing the memory access pattern from random access to direct access. The second pattern takes an alternative approach to handle static grid properties. The measured single-core performance improvement is more than a factor of 5 compared to the standard implementation. The refactored implementation of strong scales on the Intel® Xeon® Scalable Processors series node until the available bandwidth of the node is used. For the Intel® Xeon® CPU Max series, there is sufficient bandwidth to allow the strong scaling to continue for all the cores on the node, resulting in a single-node improvement factor of 35 over the standard implementation. This study also demonstrates improved performance on GPU processors.

58 GEOSCIENCES↗
DOE OSTI2026

Artificial Intelligence for Event Reconstruction and Higgs Physics at CMS and Future Colliders

This dissertation charts a trajectory in which advances in artificial intelligence (AI) play a central role in pushing the high-energy physics frontier, complementing progress driven by higher collision energies and larger colliders. The discovery potential of the LHC and future colliders relies on accurate reconstruction of increasingly complex particle collision events. In the CMS experiment, this task is performed by the particle-flow (PF) algorithm. This dissertation presents the first implementation of a machine-learning-based particle-flow (MLPF) reconstruction in the CMS detector based on transformer architectures. In simulated top quark--antiquark pair (ttbar) events under LHC Run~3 (2023--2024) conditions, MLPF improves jet energy resolution by 10--20\% compared to standard PF for jets with transverse momentum between 30--100\GeV. Runtime performance is evaluated using simulated multijet events, with a median inference time of 20\unit{ms} per event on an NVIDIA L4 GPU, compa red to approximately 110\unit{ms} for standard PF. The MLPF algorithm is also validated on Run~3 collision data, representing the first data-validated ML-based reconstruction pipeline at any LHC experiment. We then extend MLPF toward future electron--positron colliders and introduce the first full-simulation cross-detector transfer learning workflow for PF reconstruction. The model is pre-trained on simulated events from the Compact Linear Collider detector (CLICdet) and fine-tuned on the CLIC-like detector (CLD) proposed for the Future Circular Collider (FCC). This approach achieves up to a 40\% improvement in jet energy resolution over rule-based reconstruction while reducing the required training dataset size by an order of magnitude, demonstrating the potential of AI to accelerate detector development and optimization. This dissertation also demonstrates how modern AI techniques enhance the sensitivity of LHC physics analyses. A CMS search for highly Lorentz-boosted Higgs bosons decaying to \textrm{W} boson pairs is presented, focusing on the single-lepton final state. A dedicated fine-tuning strategy for \ParT yields an approximately 70\% increase in expected sensitivity relative to the baseline model. The analysis uses proton--proton collision data at a center-of-mass energy of \ensuremath{\sqrt{s}=13\TeV} collected by CMS between 2016 and 2018, corresponding to an integrated luminosity of 138\ensuremath{\ \mathrm{fb}^{-1}}. The expected significance of the search is $1.86\sigma$, with an observed signal strength of $-0.19^{+0.48}_{-0.46}$. Finally, explainable AI techniques are applied to the MLPF and \ParticleNet algorithms using layerwise relevance propagation, showing that both models base their predictions on physically meaningful features consistent with our physics intuition. Together, these results demonstrate how advanced AI methods can enhance reconstruction, analysis sensitivity, and interpretability, shaping the next era of experimental parti cle physics.

Mokhtar, Farouk [UC, San Diego]↗
DOE OSTI2025

Status of the Proton EDM Experiment (pEDM)

The Proton EDM Experiment (pEDM) is the first direct search for the proton electric dipole moment (EDM) with the aim of being the first experiment to probe the Standard Model (SM) prediction of any particle EDM. Phase-I of pEDM will achieve $10^{-29} e\cdot$cm, improving current indirect limits by four orders of magnitude. This will establish a new standard of precision in nucleon EDM searches and offer a unique sensitivity to better understand the Strong CP problem. The experiment is ideally positioned to explore physics beyond the Standard Model (BSM), with sensitivity to axionic dark matter via the signal of an oscillating proton EDM and across a wide mass range of BSM models from $\mathcal{O}(1\text{GeV})$ to $\mathcal{O}(10^3\text{TeV})$. Utilizing the frozen-spin technique in a highly symmetric storage ring that leverages existing infrastructure at Brookhaven National Laboratory (BNL), pEDM builds upon the technological foundation and experimental expertise of the highly successful Muon $g$$-$$2$ Experiments. With significant R&D and prototyping already underway, pEDM is preparing a conceptual design report (CDR) to offer a cost-effective, high-impact path to discovering new sources of CP violation and advancing our understanding of fundamental physics. It will play a vital role in complementing the physics goals of the next-generation collider while simultaneously contributing to sustaining particle physics research and training early-career researchers during gaps between major collider operations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

AMIA KDDM Working Group Collaborative Workshop: Enriching Electronic Health Records with Social Determinants of Health to Improve Outcomes and Health Equity

Prior research has demonstrated that social determinants of health (SDoH) are major drivers of health outcomes and contributors to widespread health inequities. It was estimated that, in the United States, SDoH could be responsible for up to 40% of all preventable deaths, significantly higher than the 10-15% for which better medical care is responsible. Public health interventions that target SDoH are instrumental for improving health outcomes and reducing long-standing health inequities. Currently, most mainstream EHR vendors have implemented SDoH screeners in their EHR systems. However, the utility of the screeners is low, rendering patient-level SDoH still widely unavailable in the structured fields. SDoH are sometimes mentioned in free-text clinical notes (e.g., social context section) where natural language processing (NLP) can be applied to extract relevant information. Contextual-level SDoH can be identified from multiple data sources, many of which are publicly available and spatiotemporally linked to EHR data. As such, there is an opportunity for the KDDM research community to create innovative solutions to draw meaningful insights by creating and using rich data with SDoH to improve health outcomes while reducing disparities. In this workshop organized by AMIA Knowledge Discovery and Data Mining Working Group (AMIA KDDM WG), we will invite world-leading experts from academia, national laboratories, and life science industry with varied backgrounds in biomedical informatics, epidemiology, data science, machine learning, natural language processing, and pediatric cardiology to discuss the best practice of capturing, standardizing, and using SDoH information in various applications aiming at improving outcomes and health equity.

He, Zhe↗
DOE OSTI2026

Evaluation of Compton suppression for enhancing trace element identification in neutron activation analysis of reference materials

Neutron activation analysis (NAA) is a powerful technique for identifying and quantifying trace elements in materials. However, challenges such as high dead times, spectral interferences, and high Compton continuum often arise. This study employs a Compton suppression system (CSS) to enhance NAA sensitivity by reducing the Compton continuum, thereby improving the peak-to-Compton ratio. National Institute of Standards and Technology certified reference materials 1632d, 1633c, and Canadian National Research Council TORT-1 were irradiated in a thermal and epithermal neutron flux under various irradiation, decay and counting times and analyzed using high-resolution gamma-ray spectroscopy with and without Compton suppression. The reduction factor was calculated to evaluate the effectiveness of the CSS, demonstrating significant background reduction and improved detection limits for trace elements. Additional experiments with a 137Cs point source demonstrated the impact of detector-source geometry on system performance, showing a decrease in the reduction factor as the source was moved further from the NaI detector. An optimum distance between the source and HPGe detector was observed, yielding the highest peak-to-Compton ratio. The results highlight the CSS's ability to minimize spectral interference and enhance elemental identification.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

tite

The TITE library provides type erasure implementation utilizing the tag_invoke paradigm proposed for standardization here: https://open-std.org/JTC1/SC22/WG21/docs/papers/2019/p1895r0.pdf. The implementation contained herein is largely modeled after that provided in the standardization proposal and available at https://godbolt.org/z/3TvO4f. Significant modification have been made to the original implementation to improve its suitability to be utilized for GPU architectures. In particular the implementation: - only requires a C++14 standard. - has been extended to obtain vtables for GPU device architectures in addition to CPU host architectures. - provides a gpu_allocator class appropriate for allocation of the type-erased object to GPU memory - provides copy semantics omitted from the original implementation-- - generally the copy semantics are to completely copy the type-erased object - when the usage of the type-erased object guarantees immutability the copy semantics are altered to reference-counted shallow copies (copies of pointers) for improved performance

Solomon, CJ↗
DOE OSTI2026

Full event interpretation with machine-learning-based particle-flow reconstruction in the CMS detector

The particle-flow (PF) algorithm constructs a global description of each particle collision by producing a comprehensive list of final-state particles, and is central to event reconstruction in the CMS experiment at the CERN LHC. The existing PF implementation relies on physics-motivated heuristics and assumptions that can be replaced by machine-learning (ML) models trained directly on simulated data and naturally suited to modern graphics processing units (GPUs). A state-of-the-art ML-based PF (MLPF) reconstruction algorithm, implemented within the CMS software framework, is presented. The MLPF algorithm performs a learnable full-event reconstruction on GPUs, generalizes across detector conditions and collision energies, and replaces multiple modular reconstruction steps with a single unified model. Physics performance comparable to standard PF reconstruction is achieved in both simulation and data, with improved jet energy resolution and inference time. In simulated top quark-antiquark events under LHC Run-3 (2023-2024) conditions, the jet energy resolution improves by 10-20% for jets with transverse momentum between 30-100 GeV. Inference time is evaluated using simulated multijet events, with a median of $20\,\hbox {ms}$ per event on an Nvidia L4 GPU, compared to approximately $110\,\hbox {ms}$ for the standard CMS PF reconstruction.

Hayrapetyan, Aram [Yerevan Phys. Inst.]↗
DOE OSTI2025

Laser ablation of high-loading Li-ion battery electrodes improves accessible capacity and cycle life for Behind-the-Meter Storage

Adoption of Behind-the-Meter Storage (BTMS) requires design of batteries that enable high safety, long cycle life, and low cost at the system level. Pairing Li 4 Ti 5 O 12 (LTO) with LiMn 2 O 4 (LMO) achieves targets related to safety and cycle life, but these materials' low energy densities contribute to higher cost at the system scale. Increasing electrode loading is a simple approach to improve energy density, but comes with a trade-off in electrode utilization due to long, tortuous Li + diffusion pathways. Here, laser ablation is used to microstructure (pattern) high-loading electrodes to enhance electrode performance through improved Li + diffusion pathways. Four cell types, comprising combinations of standard or patterned anode and cathode, were prepared to evaluate the effects of laser ablation at each electrode. A rate test shows that patterning electrodes enhances active material utilization at ≳1C rates. Patterning the cathode yields the most benefit, as cells with a patterned cathode demonstrate a ~20% higher accessible capacity than those without at 1.4C. Additionally, 1C capacity retention of cells with patterned cathode (91% through 3000 cycles) is significantly improved over cells with only the anode patterned (64%) and non-patterned electrodes (50%). Characterization of post-mortem cells before and after refreshing their electrolyte suggests that 1C capacity retention is improved by mitigation of electrode "dry-out". We hypothesize that the microstructure acts as a reservoir of additional electrolyte, or a path for gas to escape, so that active material remains wetted throughout long-term cycling, and/or the microstructure may reduce localized, gas-forming overpotentials in the high-loading electrode.

25 ENERGY STORAGE↗
DOE OSTI2026

Extensive analysis of reconstruction algorithms for DESI 2024 baryon acoustic oscillations

Reconstruction of the baryon acoustic oscillation (BAO) signal has been a standard procedure in BAO analyses over the past decade and has helped to improve the BAO parameter precision by a factor of ∼2 on average. The Dark Energy Spectroscopic Instrument (DESI) BAO analysis for the first year (DR1) data uses the “standard” reconstruction framework, in which the displacement field is estimated from the observed density field by solving the linearized continuity equation in redshift space, and galaxy and random positions are shifted in order to partially remove non-linearities. There are several approaches to solving for the displacement field in real survey data, including the multigrid (MG), iterative Fast Fourier Transform (iFFT), and iterative Fast Fourier Transform particle (iFFTP) algorithms. In this work, we analyze these algorithms and compare them with various metrics including two-point statistics and the displacement itself using realistic DESI mocks. We focus on three representative DESI samples, the emission line galaxies (ELG), quasars (QSO), and the bright galaxy sample (BGS), which cover the extreme redshifts and number densities, and potential wide-angle effects. We conclude that the MG and iFFT algorithms agree within 0.4% in post-reconstruction power spectrum on BAO scales with the RecSym convention, which does not remove large-scale redshift space distortions (RSDs), in all three tracers. The RecSym convention appears to be less sensitive to displacement errors than the RecIso convention, which attempts to remove large-scale RSDs. However, iFFTP deviates from the first two; thus, we recommend against using iFFTP without further development. In addition, we provide the optimal settings for reconstruction for five years of DESI observation. The analyses presented in this work pave the way for DESI DR1 analysis as well as future BAO analyses.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Active learning enables generation of molecules that advance the known Pareto front

Although generative models hold promise for discovering molecules with optimized desired properties, they often fail to suggest synthesizable molecules that improve upon the properties of the structures represented in the training distribution. We find that this limitation arises not only from the molecule generation process itself, but also from the poor generalization capabilities of molecular property predictors. We address this challenge by creating a closed-loop molecule generation pipeline with iterative retraining on new quantum chemical simulation data. Compared against static, single-pass generative modeling approaches, only our closed-loop iterative workflow generates molecules with properties extending beyond the training distribution (up to 0.44 standard deviations beyond the original range) and achieves a 79% improvement in out-of-distribution molecule classification accuracy. Furthermore, by conditioning molecular generation on thermodynamic stability data obtained during the iterative loop, the proportion of stable and hence potentially synthesizable molecules generated is 3.5x higher than the next-best model.

Chemistry↗
DOE OSTI2024

Improved Zika virus plaque assay using Vero/TMPRSS2 cell line

Plaque assay is the gold standard for the quantification of viable cytopathic viruses like Zika virus (ZIKV). Some strains of ZIKV produce plaques that are very difficult to accurately visualize and count on the commonly used Vero cell line. From data generated in our lab, we became curious if Vero/TMPRSS2 cells may be a better alternative; therefore, we compared the plaque forming units of two strains of ZIKV on Vero/TMPRSS2 cells to those produced by Vero cells. We also compared the virus stock titer generated on Vero/TMPRSS2 cells to that generated by the Vero cell line. Although the Vero cells generated higher quantity of ZIKV stocks, the Vero/TMPRSS2 cells produced plaques with significantly improved morphology and visibility and may, therefore, be a better alternative to use for performing plaque assays for strains of ZIKV that are more difficult to titer on regular Vero cells.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Development of thin-gap GEM- μ RWELL hybrid detectors

Micro Pattern Gaseous Detectors (MPGDs) are used for tracking in High Energy Physics and Nuclear Physics because of their large area, excellent spatial resolution capabilities and low cost. However, for high energy charged particles impacting at a large angle with respect to the axis perpendicular to detector plane, the spatial resolution degrades significantly because of the long trail of ionization charges produced in clusters all along the track in the drift region of the detector. The long ionization charge trail results in registering hits from large number of strips in the readout plane which makes it challenging to precisely reconstruct the particle’s position using simple center of gravity algorithm. As a result, the larger the drift gap, the more severe the deterioration of spatial resolution for inclined tracks. For the same reason, the position resolution is also severely degraded in a large magnetic field, where the Lorentz E x B effect causes the ionization charges to follow a curved and longer path in the detector gas volume. In this paper, we report on the development of thin-gap MPGDs as a way to maintain excellent spatial resolution capabilities of MPGD detectors over a wide angular range of incoming particles. In a thin-gap MPGD, the thickness of the gas volume in the drift region is reduced from typically 3 mm to 1 mm or less. We present preliminary test beam results demonstrating the improvement in spatial resolution from 400 m with a standard 3 mm gap μ RWELL prototype to ~140 μ m with a double amplification GEM- μ RWELL thin-gap hybrid detector. Here, we also discuss the impact of a thin-gap drift volume on other aspects of the performance of MPGD technologies such as the efficiency and detector stability.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗