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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Halide Perovskites and Their Derivatives for Efficient, High‐Resolution Direct Radiation Detection: Design Strategies and Applications

Abstract The past decade has witnessed a rapid rise in the performance of optoelectronic devices based on lead‐halide perovskites (LHPs). The large mobility‐lifetime products and defect tolerance of these materials, essential for optoelectronics, also make them well‐suited for radiation detectors, especially given the heavy elements present, which is essential for strong X‐ray and γ‐ray attenuation. Over the past decade, LHP thick films, wafers, and single crystals have given rise to direct radiation detectors that have outperformed incumbent technologies in terms of sensitivity (reported values up to 3.5 × 10 6 µC Gy air −1 cm −2 ), limit of detection (directly measured values down to 1.5 nGy air s −1 ), along with competitive energy and imaging resolution at room temperature. At the same time, lead‐free perovskite‐inspired materials (e.g., methylammonium bismuth iodide), which have underperformed in solar cells, have recently matched and, in some areas (e.g., in polarization stability), surpassed the performance of LHP detectors. These advances open up opportunities to achieve devices for safer medical imaging, as well as more effective non‐invasive analysis for security, nuclear safety, or product inspection applications. Herein, the principles behind the rapid rises in performance of LHP and perovskite‐inspired material detectors, and how their properties and performance link with critical applications in non‐invasive diagnostics are discussed. The key strategies to engineer the performance of these materials, and the important challenges to overcome to commercialize these new technologies are also discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The role of pre-existing heterogeneities in materials under shock and spall

There has been a challenge for many decades to understand how heterogeneities influence the behavior of materials under shock loading, eventually leading to spall formation and failure. Experimental, analytical, and computational techniques have matured to the point where systematic studies of materials with complex microstructures under shock loading and the associated failure mechanisms are feasible. This is enabled by more accurate diagnostics as well as characterization methods. As interest in complex materials grows, understanding and predicting the role of heterogeneities in determining the dynamic behavior becomes crucial. Early computational studies, hydrocodes, in particular, historically preclude any irregularities in the form of defects and impurities in the material microstructure for the sake of simplification and to retain the hydrodynamic conservation equations. Contemporary computational methods, notably molecular dynamics simulations, can overcome this limitation by incorporating inhomogeneities albeit at a much lower length and time scale. This review discusses literature that has focused on investigating the role of various imperfections in the shock and spall behavior, emphasizing mainly heterogeneities such as second-phase particles, inclusions, and voids under both shock compression and release. Pre-existing defects are found in most engineering materials, ranging from thermodynamically necessary vacancies, to interstitial and dislocation, to microstructural features such as inclusions, second phase particles, voids, grain boundaries, and triple junctions. This literature review explores the interaction of these heterogeneities under shock loading during compression and release. Systematic characterization of material heterogeneities before and after shock loading, along with direct measurements of Hugoniot elastic limit and spall strength, allows for more generalized theories to be formulated. Further, continuous improvement toward time-resolved, in situ experimental data strengthens the ability to elucidate upon results gathered from simulations and analytical models, thus improving the overall ability to understand and predict how materials behave under dynamic loading.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Through-Thickness Microstructure Characterization in a Centrifugally Cast Austenitic Stainless Steel Nuclear Reactor Primary Loop Pipe Using Time-of-Flight Neutron Diffraction

The US code of Federal Regulations mandates regular inspection of centrifugally cast austenitic stainless steel pipe, commonly used in primary cooling loops in light-water nuclear power plants. These pipes typically have a wall thickness of ~8 cm. Unfortunately, inspection using conventional ultrasonic techniques is not reliable as the microstructure strongly attenuates ultrasonic waves. Work is ongoing to simulate the behavior of acoustic waves in this microstructure and ultimately develop an acoustic inspection method for reactor inspections. In order to account for elastic anisotropy in the material, the texture in the steel was measured as a function of radial distance though the pipe wall. Experiments were conducted on two 10 × 12.7 × 80 mm radial sections of a cast pipe using neutron diffraction scans of 2 mm slices using the HIPPO time-of-flight neutron diffractometer at the Los Alamos Neutron Science Center (LANSCE, Los Alamos, NM, USA). Strong textures dominated by a small number of austenite grains with their (100) direction aligned in the radial direction of the pipe were observed. ODF analysis indicated that up to 70% of the probed volume was occupied by just three single-grain orientations, consistent with grain sizes of almost 1 cm. Texture and phase fraction of both ferrite and austenite phases were measured along the length of the samples. These results will inform the development of a more robust diagnostic tool for regular inspection of this material.

42 ENGINEERING↗
DOE OSTI2025

An Investigation of Thermal Properties of 2D Materials [Dissertation]

Studying the thermal conductivity of 2D materials is important due to the applications of 2D materials in fields such as thermal management, thermoelectricity, renewable energy, and sensors. As such, measurements of the thermal conductivity of these 2D materials become important to measure. Thermal conductivity is often difficult to measure for 2D materials due to their atomically thin nature and many experimental methods for doing so requiring contact with the sample, which can alter the thermal properties. A non-contact method for calculating the thermal conductivity of 2D materials supported on substrates in order to model the thermal conductivity of 2D materials for devices, is proposed and experimentally performed in this dissertation. The optothermal Raman technique is a useful non-contact diagnostic technique useful in determining the thermal conductivity of 2D materials. The optothermal Raman typically does not account for heat losses due to convection or radiation or substrate resistance, which are shown to be important factors to consider when developing an optothermal Raman model. Additionally, the calculation of the interfacial thermal conductance between the bottom surface of the sample and the top surface of the substrate, plays an important role in determining the final value of the thermal conductivity of a supported sample, and will yield differing results based on whether or not the conductance is calculated using an approach such as the Diffuse Mismatch Model (DMM) or calculated directly by varying the laser heating profile (usually done by changing the laser objective). This is shown to be the case for both graphene on Ni, graphene on Cu, and SnSe 2 on Cu. In addition to experimentally calculating the thermal conductivity of a 2D material with the optothermal Raman technique, the thermal conductivity of 2D materials can also be calculated using computational methods. The three-phonon method is a method which can be used to simulate phonon scattering processes and determine the thermal conductivity of semiconductors, wherein phonon scattering is the dominant mechanism which determines the thermal conductivity. The three-phonon method uses relaxation times for phonon scattering with other phonons, electrons, and other material system elements, such as isotopes or material defects, in order to create a single-mode relaxation time approximation (SMRTA), which is used to calculate the final value of the thermal conductivity. An important consideration when determining the thermal conductivity of a 2D material using this method is the device geometry, which is reflected in this work as the phonon-boundary scattering relaxation time. This inclusion is important along with the inclusion of phonon-electron scattering in accurately determining the thermal conductivity of a 2D material. In both the optothermal Raman experiments and the three-phonon method computations, strain is shown to have a demonstrable effect on the thermal conductivity of 2D materials. When a 1.1% strain was applied to the mechanical properties of SnSe, the three-phonon processes yielded a lower thermal conductivity than the no-strain case. For the optothermal Raman experiments, the strain induced in the Cu substrate and transferred to a single-layer graphene (SLG) sample yields a trend where the thermal conductivity of the SLG decreases with respect to strain applied. In the case where the interfacial thermal conductance was calculated directly, the conductance increased with respect to strain applied. This presents strain as a reliable and viable method for tuning the thermal properties of 2D materials for device applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

In-situ spectroscopic ellipsometry for real-time characterization of the effects of high-flux helium plasmas on tungsten surfaces

Tungsten samples were exposed to He plasmas generated by an RF source (Γ i = 3.5 x 10 16 He cm -2 s -1 , ion energy = 92 eV.) The range of exposure conditions selected here is conducive to the growth of nearsurface He bubbles, and at higher fluence, the formation of W nanotendrils ranging between 50 — 100 nm in diameter. The evolution of these surface features was probed using a fixed-angle ellipsometer (280 — 1000 nm wavelength range) with direct line-of-sight to the sample. Over the parameter space explored here, changes in the two angles (p, S) that define the polarization of the reflected light followed a distinct trajectory with increasing plasma fluence. Ex-situ ellipsometry of 22 additional tungsten specimens tested at a wide range of plasma fluences and temperatures mapped onto these in-situ results well. We used helium ion microscopy and focused ion beam profiling to provide a direct calibration of the ellipsometry measurements. Our results indicate that for a reproducible process such as the growth helium-induced surface morphologies, ellipsometry is a practical in-situ diagnostic to study how fusion plasmas modify materials. To study more general effects of plasmas on surfaces, including co-deposition and sputtering, different approaches to modelling the optical properties of the exposed surfaces are also considered.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Current advances on Talbot–Lau x-ray imaging diagnostics for high energy density experiments (invited)

Talbot–Lau x-ray interferometry is a refraction-based diagnostic that can map electron density gradients through phase-contrast methods. The Talbot–Lau x-ray deflectometry (TXD) diagnostics have been deployed in several high energy density experiments. To improve diagnostic performance, a monochromatic TXD was implemented on the Multi-Tera Watt (MTW) laser using 8 keV multilayer mirrors (Δθ/θ = 4.5%-5.6%). Copper foil and wire targets were irradiated at 10 14 –10 15 W/cm 2 . Laser pulse length (~10 to 80 ps) and backlighter target configurations were explored in the context of Moiré fringe contrast and spatial resolution. Foil and wire targets delivered increased contrast <30%. The best spatial resolution (<6 μm) was measured for foils irradiated 80° from the surface. Further TXD diagnostic capability enhancement was achieved through the development of advanced data postprocessing tools. The Talbot Interferometry Analysis (TIA) code enabled x-ray refraction measurements from the MTW monochromatic TXD. Additionally, phase, attenuation, and dark-field maps of an ablating x-pinch load were retrieved through TXD. The images show a dense wire core of ~60 μm diameter surrounded by low-density material of ~40 μm thickness with an outer diameter ratio of ~2.3. Attenuation at 8 keV was measured at ~20% for the dense core and ~10% for the low-density material. Instrumental and experimental limitations for monochromatic TXD diagnostics are presented. Enhanced postprocessing capabilities enabled by TIA are demonstrated in the context of high-intensity laser and pulsed power experimental data analysis. Significant advances in TXD diagnostic capabilities are presented. Furthermore, these results inform future diagnostic technique upgrades that will improve the accuracy of plasma characterization through TXD.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Simulation and Emulation of X-Ray Diffraction from Dynamic Compression Experiments

Many important aspects of the dynamic thermo-mechanical response of materials occur at the mesoscale, i.e. a physical scale of interactions smaller than what can be adequately described by homogenous behaviors, yet larger than the scale of the atomic lattice. Concurrent advancements in computational power, continuum theory, and experimental diagnostics are enabling unprecedented understanding of such interactions. However, we cannot develop a sufficient level of confidence in such mesoscale capability until the constitutive description of the underlying constituents is reliably representative of their actual physical behavior. Therefore, there is a strong need to combine experimental, modeling, and data-science techniques to validate models of the thermomechanical response of individual single crystals. One experimental diagnostic with high potential impact to shock physics and materials science is in-situ x-ray diffraction. This paper is primarily focused on simulation of x-ray diffraction in shock physics, but with an aim toward quantifying parametric uncertainty of simulation models. Here, we develop and demonstrate a data-science and model-driven approach to constrain the parameterization of continuum models of crystal lattice deformation associated with the shock response of crystalline materials. The framework is built around the connection between continuum hydrodynamic simulations of lattice deformation and a new Bragg diffraction simulation code, BarberShop. The dynamic deformation of a crystal lattice is modeled using the DiscoFlux model within an arbitrary Lagrangian-Eulerian hydrodynamic code, FLAG. These detailed continuum simulations of lattice deformation can be computationally slow, thus a statistical model is used to emulate the evolution of lattice deformation fields in time and across the considered model parameter space. Emulated lattice deformation fields can then be generated rapidly for any combination of physics model parameters. In turn, these fields can be fed into BarberShop to realize a rapid prediction of Bragg diffraction patterns associated with particular values of physics model parameters. The framework enables parameterization of the single crystal model to obtain Bragg diffraction patterns that most closely resemble a corresponding measurement. Furthermore, the framework naturally provides sensitivities of the lattice deformation to the physics parameters. We highlight the utility of this framework through the application to a synthetic closed-loop inverse problem leading to the parameterization of a single crystal material model. As a model problem, we consider the dynamic response of the energetic molecular crystal, cyclotrimethylenetrinitramine (or RDX), under dynamic compression induced by simulated flyer plate impact experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Completion document for MRT 8824 - Upgrade NIF’s gaseous radiochemistry diagnostics (RAGS) to support weapons science

This milestone highlights the successful upgrade and deployment of the Radiochemical Analysis of Gaseous Samples (RAGS) system, which delivers high-quality measurements (<20% uncertainty) of activated gaseous species from NIF implosions. These measurements are critical for supporting Stockpile Stewardship Program (SSP) relevant platforms, including LANL’s Double Shell and LLNL’s Pushered Single Shell campaigns. The RAGS diagnostic technique enables analysis of short-range mixing in implosions using high-Z shells, which are otherwise inaccessible to conventional x-ray diagnostic methods. By facilitating the investigation of high-Z material mixing into fusion burn, this system provides essential data for quantifying and interpreting results in high-energy density (HED) experiments. This report details the physics motivation, diagnostic fundamentals, planned and enacted upgrade work, and the quantification of uncertainty for the upgraded system.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2021

Broad background in electron diffraction of 2D materials as a signature of their superior quality

Abstract An unusually broad bell-shaped component (BSC) has been previously observed in surface electron diffraction on different types of 2D systems. It was suggested to be an indicator of uniformity of epitaxial graphene (Gr) and hexagonal boron nitride (hBN). In the current study we use low-energy electron microscopy and micro-diffraction to directly relate the BSC to the crystal quality of the diffracting 2D material. Specially designed lateral heterostructures were used to map the spatial evolution of the diffraction profile across different 2D materials, namely pure hBN, BCN alloy and pure Gr, where the alloy region exhibits deteriorated structural coherency. The presented results show that the BSC intensity has a minimum in the alloyed region, consequently showing that BSC is sensitive to the lateral domain size and homogeneity of the material under examination. This is further confirmed by the presence of a larger number of sharp moiré spots when the BSC is most pronounced in the pure hBN and Gr regions. Consequently, it is proposed that the BSC can be used as a diagnostic tool for determining the quality of the 2D materials.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Semi-supervised Machine Learning Enables the Robust Detection of Multireference Character at Low Cost

Multireference (MR) diagnostics are common tools for identifying strongly correlated electronic structure that makes single-reference (SR) methods (e.g., density functional theory or DFT) insufficient for accurate property prediction. However, MR diagnostics typically require computationally demanding correlated wave function theory (WFT) calculations, and diagnostics often disagree or fail to predict MR effects on properties. To overcome these challenges, we introduce a semi-supervised machine learning (ML) approach with virtual adversarial training (VAT) of an MR classifier using 15 WFT and DFT MR diagnostics as inputs. In semi-supervised learning, only the most extreme SR or MR points are labeled, and the remaining point labels are learned. The resulting VAT model outperforms the alternatives, as quantified by the distinct property distributions of SR- and MR-classified molecules. Additionally, to reduce the cost of generating inputs to the VAT model, we leverage the VAT model’s robustness to noisy inputs by replacing WFT MR diagnostics with regression predictions in an MR decision engine workflow that preserves excellent performance. We demonstrate the transferability of our approach to larger molecules and those with distinct chemical composition from the training set. This MR decision engine demonstrates promise as a low-cost, high-accuracy approach to the automatic detection of strong correlation for predictive high-throughput screening.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Non-circular electron beam spot welds in stainless steel alloys

Circularly symmetric-shaped spot welds are desirable for welding applications as they relate to heat and fluid flow conditions in the melt pool with predictable weld penetrations and repeatable results. Non-circular spot welds on the other hand result in undesirable and unpredictable weld penetrations or non-bridging of the liquid melt pool across the joint. Two known causes for non-circular melt pools occur when welding dissimilar metals, or when welding with skewed electron or laser beams that are not perpendicular to the surface. A largely unexplored additional factor, shown here, is an asymmetric power density distribution within the beam that can create non-circular melt pools even though the beam dimensions are much smaller than the melt pool itself.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Distinct Surface and Bulk Thermal Behaviors of LiNi 0.6 Mn 0.2 Co 0.2 O 2 Cathode Materials as a Function of State of Charge

Understanding how structural and chemical transformations take place in particles under thermal conditions can inform designing thermally robust electrode materials. Such a study necessitates the use of diagnostic techniques that are capable of probing the transformations at multiple length scales and at different states of charge (SOC). In this study, the thermal behavior ofLiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC-622) was examined as a function of SOC, using an array of bulk and surface-sensitive techniques. In general, thermal stability decreases as lithium content is lowered and conversion in the bulk to progressively reduced metal oxides (spinels, rock salt) occurs as the temperature is raised. Hard X-ray absorption spectroscopy (XAS) and X-ray Raman spectroscopy (XRS) experiments, which probe the bulk, reveal that Ni and Co are eventually reduced when partially delithiated samples (regardless of the SOC) are heated, although Mn is not. Surface-sensitive synchrotron techniques, such as soft XAS and transmission X-ray microscopy (TXM), however, reveal that for 50% delithiated samples, apparent oxidation of nickel occurs at particle surfaces under some circumstances. This is partially compensated by reduction of cobalt but may also be a consequence of redistribution of lithium ions upon heating. TXM results indicate the movement of reduced nickel ions into particle interiors or oxidized nickel ions to the surface or both. These experiments illustrate the complexity of the thermal behavior of NMC cathode materials. The study also informs the importance of investigating the surface and bulk difference as a function of SOC when studying the thermal behaviors of battery materials.

25 ENERGY STORAGE↗
DOE OSTI2025

In situ Detection of Plasma Induced Surface Interaction based on Deep Learning based Visual Diagnostics (Technical Report)

It is characteristic for many plasma devices to undergo plasma-material interaction leading to surface erosion. These processes, often not easily detectable, lead to changes in device performance and lifespan. State-of-the-art lifetime tests and wear experiments require over 1000s hours. A self-consistent model for accurately predicting the erosion's effects is not available. In situ detection of these processes is not a trivial task since the surface variations at the early stages have a micron scale. Such limitations not only restrict testing and prediction capabilities but also slow the development of new thrusters and limit mission duration. To address these challenges, an in-situ diagnostic for real-time erosion assessment has been developed, aiming to expedite lifetime testing and broaden experimental campaigns. Several works were dedicated to real-time and in situ monitoring of material erosion during plasma exposure using laser holography, microscopy, and with telemicroscopes. However, the applicability of these approaches is limited due to complexity, cost and less flexibility as they often require placing diagnostic equipment inside the vacuum chamber. In collaboration with Princeton Collaborative Research Facility (PCRF), Princeton Plasma Physics Laboratory (PPPL), a new diagnostic approach is developed, where geometry modifications to the ceramic channel walls were introduced that would result in accelerated channel erosion. We employed Long-distance microscope (LDM) imagery, combined with Deep-Learning based Shape from focus or depth from focus (DFF or SFF) approach, that provides an accessible and cost-effective solution. LDM employs focus variation techniques to continuously capture multiple images of the target object at distinct focal planes. DFF, an optical focus variation method, generates a 3D topographical surface depth map from a sequence of variably focused images. Combined with the developed diagnostic, this approach offers a controllable means to study erosion under accelerated conditions. In this work, we develop Neural Network-based DFF algorithm applicable for LDM data to quantitatively evaluate plasma induced surface modification from LDM data. Next, we develop Deep Learning-based super-resolution depth map image reconstruction technique to increase the resolution of depth maps obtained from DFF algorithm to improve the accuracy of erosion measurements. Thirdly, we develop several image processing techniques to remove noise and improve the quality of depth map image. Here we report the results of initial tests for this approach. An experimental setup designed and built in PPPL was employed that consists of a 3-cm gridded ion source that produces a neutralized argon beam with energies up to 600 eV. A hexagonal boron nitride (h-BN) ceramic target, designed based on computational predictions, was used. Tests were conducted to reconstruct the complex geometry of the target under the lighting conditions of the operated ion source.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

In situ laser profilometry for material segmentation and digital reconstruction of a multicomponent additively manufactured part

In addition to its ability to produce geometrically complex parts, additive manufacturing offers a unique opportunity to collect data about a component while it is being fabricated. However, there has only been limited effort to characterize parts morphologically and compositionally in situ. In this article, we present a layer-by-layer, laser profilometry-based in situ characterization technique as a method to digitally reconstruct a multi-material part. Data collected by the laser profilometer yields height maps and grayscale images which are voxelized using purpose-built software to volumetrically reconstruct the part. Additionally, the same part was also analyzed using X-ray computed tomography (CT) which was not able to resolve the different compositional regions within the part, but captured the filament morphology. The part was then bisected to compare the digital reconstruction to the actual part morphology and composition. Overall, the digital reconstruction was in good agreement with both the CT and bisected images. Deviations between the digital reconstruction and the CT/bisected images are likely the result of image segmentation settings or material shifts after data was collected. The in situ characterization method demonstrated here sets the stage for real time process monitoring and paves the way for additively manufactured parts that are “born qualified.”

36 MATERIALS SCIENCE↗
DOE OSTI2021

Multiscale operando X-ray investigations provide insights into electro-chemo-mechanical behavior of lithium intercalation cathodes

The electrochemical performance and cycle life of lithium-ion batteries (LIBs) depend on the electrochemical, chemical, and mechanical behavior of electrodes and electrolytes. Despite extensive studies conducted previously, challenges exist to decouple these behaviors, capture the evolution of electro-chemo-mechanical behavior in realistic conditions, and correlate atomic-scale stress evolution to micro-scale bulk mechanical degradation. Here, we report multiscale operando techniques to investigate polydisperse battery electrodes by integrating volume-averaged quantitative synchrotron X-ray scattering with high-resolution transmission X-ray microscopy (TXM). The former provides us information spanning a wide spatial range, from Angstrom-level atomic structures to micrometer-level particle scales, while the latter provides time-resolved 2D images of the particles during cycling. The complementarity of the two operando techniques is demonstrated by an over-lithiation test of LiCoO 2 electrodes, where particles crack and eventually pulverize. Additionally, the techniques are applied to study LiCoO 2 cycling stability from 3.0 V to 4.5 V. Operando X-ray scattering result shows nanometer-scale features keep forming in LiCoO 2 electrodes during cycling, resulting in an increased projected area observed by the TXM experiment. The formation of such features is inhibited by a polymer coating on the electrode, leading to vastly improved cycling stability. The polymer coating alleviates LiCoO 2 surface deterioration, reduces side product generation, and inhibits LiCoO 2 particles volume expansion during the cycling test. These operando multimodal X-ray techniques presented herein thus offer a novel, multiscale diagnostic modality for studying existing and emerging battery materials, aiding the development of next-generation LIBs.

25 ENERGY STORAGE↗
DOE OSTI2023

Data-Driven Approaches for Bead Geometry Prediction Via Melt Pool Monitoring

In the realm of additive manufacturing, the selection of process parameters to avoid over and under deposition entails a time-consuming and resource-intensive trial-and-error approach. Given the distinct characteristics of each part geometry, there is a pressing need for advancing real-time process monitoring and control to ensure consistent and reliable part dimensional accuracy. Here, this research shows that support vector regression (SVR) and convolutional neural network (CNN) models offer a promising solution for real-time process control due to the models’ abilities to recognize complex, non-linear patterns with high accuracy. A novel experiment was designed to compare the performance of SVR and CNN models to indirectly detect bead height from a coaxial image of a melt pool from a single-layer, single bead build. The study showed that both SVR and CNN models trained on melt pool data collected from a coaxial optical camera can accurately predict the bead height with a mean absolute percentage error of 3.67% and 3.68%, respectively.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Geant4 Simulations on Faraday Cup Design for PIP-II Laser Wire Scanner System

The Proton Improvement Plan-II (PIP-II) accelerator upgrade at Fermilab represents a groundbreaking leap forward in high-energy physics research. This ambitious initiative involves enhancing Fermilab's accelerator complexby replacing the current linear accelerator (linac) with awarm front end (WFE) capable of accelerating H- beamsup to 2.1 MeV. Subsequently, a superconducting linac further accelerates these beams up to 800 MeV. To preciselymeasure the transverse beam profile, a combination of traditional wire scanners at the WFE section and Laser wirescanners along the superconducting linac are planned forimplementation. This investigation is centered on refiningthe Faraday cup design for the PIP-II Laser wire scannersby utilizing GEANT4, a Monte Carlo simulation toolkit.Leveraging this method enables a comprehensive analysisof particle trajectories, energy deposition, secondary particle emission, backscattering, etc., facilitating optimizationthrough adjustments to cup geometries, materials, andplacement to maximize its efficacy in beam diagnostics.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Inactivation of highly transmissible livestock and avian viruses including influenza A and Newcastle disease virus for molecular diagnostics

There is a critical need for an inactivation method that completely inactivates pathogens at the time of sample collection while maintaining the nucleic acid quality required for diagnostic PCR testing. This inactivation method is required to alleviate concerns about transmission potential, minimize shipping complications and cost, and enable testing in lower containment laboratories, thereby enhancing disease diagnostics through improved turn-around time. This study evaluated a panel of 10 surrogate viruses that represent highly pathogenic animal diseases. These results showed that a commercial PrimeStore® molecular transport media (PSMTM) completely inactivated all viruses tested by >99.99%, as determined by infectivity and serial passage assays. However, the detection of viral nucleic acid by qRT-PCR was comparable in PSMTM and control-treated conditions. These results were consistent when viruses were evaluated in the presence of biological material such as sera and cloacal swabs to mimic diagnostic sample conditions for non-avian and avian viruses, respectively. The results of this study may be utilized by diagnostic testing laboratories for highly pathogenic agents affecting animal and human populations. These results may be used to revise guidance for select agent diagnostic testing and the shipment of infectious substances.

60 APPLIED LIFE SCIENCES↗