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Aging Optimization of Aluminum-Lithium Alloy C458 for Application to Cryotank Structures

Compared with aluminum alloys such as 2219, which is widely used in space vehicle for cryogenic tanks and unpressurized structures, aluminum-lithium alloys possess attractive combinations of lower density and higher modulus along with comparable mechanical properties. These characteristics have resulted in the successful use of the aluminum-lithium alloy 2195 (Al-1.0 Li-4.0 Cu-0.4 Mg-0.4 Ag-0.12 Zr) for the Space Shuttle External Tank, and the consideration of newer U.S. aluminum-lithium alloys such as L277 and C458 for future space vehicles. These newer alloys generally have lithium content less than 2 wt. % and their composition and processing have been carefully tailored to increase the toughness and reduce the mechanical property anisotropy of the earlier generation alloys such 2090 and 8090. Alloy processing, particularly the aging treatment, has a significant influence on the strength-toughness combinations and their dependence on service environments for aluminum-lithium alloys. Work at NASA Marshall Space Flight Center on alloy 2195 has shown that the cryogenic toughness can be improved by employing a two-step aging process. This is accomplished by aging at a lower temperature in the first step to suppress nucleation of the strengthening precipitate at sub-grain boundaries while promoting nucleation in the interior of the grains. Second step aging at the normal aging temperature results in precipitate growth to the optimum size. A design of experiments aging study was conducted for plate. To achieve the T8 temper, Alloy C458 (Al-1.8 Li-2.7 Cu-0.3 Mg-0.08 Zr-0.3 Mn-0.6 Zn) is typically aged at 300F for 24hours. In this study, a two-step aging treatment was developed through a comprehensive 2(exp 4) full factorial design of experiments study and the typical one-step aging used as a reference. Based on the higher lithium content of C458 compared with 2195, the first step aging temperature was varied between 175F and 250F. The second step aging temperatures was varied between 275F and 325F, which is in the range of the single-step aging temperature. The results of the design of experiments used for the T8 temper as well as a smaller set of experiments for the T6 temper will be presented. The process of selecting the optimum aging treatment, based on the measured mechanical properties at room and cryogenic temperature as well as the observed deformation mechanisms, will be presented in detail. The implications for the use of alloy C458 in cryotanks will be discussed.

Sova, B. J.↗

Aging Optimization of Aluminum-Lithium Alloy C458 for Application to Cryotank Structures

Compared with aluminum alloys such as 2219, which is widely used in space vehicle for cryogenic tanks and unpressurized structures, aluminum-lithium alloys possess attractive combinations of lower density and higher modulus along with comparable mechanical properties. These characteristics have resulted in the successful use of the aluminum-lithium alloy 2195 (Al-1.0 Li-4.0 Cu-0.4 Mg-0.4 Ag-0.12 Zr) for the Space Shuttle External Tank, and the consideration of newer U.S. aluminum-lithium alloys such as L277 and C458 for future space vehicles. These newer alloys generally have lithium content less than 2 wt. % and their composition and processing have been carefully tailored to increase the toughness and reduce the mechanical property anisotropy of the earlier generation alloys such 2090 and 8090. Alloy processing, particularly the aging treatment, has a significant influence on the strength-toughness combinations and their dependence on service environments for aluminum-lithium alloys. Work at NASA Marshall Space Flight Center on alloy 2195 has shown that the cryogenic toughness can be improved by employing a two-step aging process. This is accomplished by aging at a lower temperature in the first step to suppress nucleation of the strengthening precipitate at sub-grain boundaries while promoting nucleation in the interior of the grains. Second step aging at the normal aging temperature results in precipitate growth to the optimum size. A design of experiments aging study was conducted for plate. To achieve the T8 temper, Alloy C458 (Al-1.8 Li-2.7 Cu-0.3 Mg- 0.08 Zr-0.3 Mn-0.6 Zn) is typically aged at 300 F for 24 hours. In this study, a two-step aging treatment was developed through a comprehensive 24 full factorial design of experiments study and the typical one-step aging used as a reference. Based on the higher lithium content of C458 compared with 2195, the first step aging temperature was varied between 175 F and 250 F. The second step aging temperatures was varied between 275 F and 325 F, which is in the range of the single-step aging temperature. The results of the design of experiments used for the T8 temper as well as a smaller set of experiments for the T6 temper will be presented. The process of selecting the optimum aging treatment, based on the measured mechanical properties at room and cryogenic temperature as well as the observed deformation mechanisms, will be presented in detail. The implications for the use of alloy C458 in cryotanks will be discussed.

Sova, B. J.↗

Materials Development for Auxiliary Components for Large Compact Mo/Au TES Arrays

We describe our current fabrication process for arrays of superconducting transition edge sensor microcalorimeters, which incorporates superconducting Mo/Au bilayers and micromachined silicon structures. We focus on materials and integration methods for array heatsinking with our bilayer and micromachining processes. The thin superconducting molybdenum bottom layer strongly influences the superconducting behavior and overall film characteristics of our molybdenum/gold transition-edge sensors (TES). Concurrent with our successful TES microcalorimeter array development, we have started to investigate the thin film properties of molybdenum monolayers within a given phase space of several important process parameters. The monolayers are sputtered or electron-beam deposited exclusively on LPCVD silicon nitride coated silicon wafers. In our current bilayer process, molybdenum is electron-beam deposited at high wafer temperatures in excess of 500 degrees C. Identifying process parameters that yield high quality bilayers at a significantly lower temperature will increase options for incorporating process-sensitive auxiliary array components (AAC) such as array heat sinking and electrical interconnects into our overall device process. We are currently developing two competing technical approaches for heat sinking large compact TES microcalorimeter arrays. Our efforts to improve array heat sinking and mitigate thermal cross-talk between pixels include copper backside deposition on completed device chips and copper-filled micro-trenches surface-machined into wafers. In addition, we fabricated prototypes of copper through-wafer microvias as a potential way to read out the arrays. We present an overview on the results of our molybdenum monolayer study and its implications concerning our device fabrication. We discuss the design, fabrication process, and recent test results of our AAC development.

Finkbeiner, F. m.↗

Develop a new integrated macro→micro←nano (MMN) multiscale modeling framework to optimize high strength aluminum alloys and processes for vehicle light-weighting​

Bending tests provide a means to study plane strain fracture performance of 6000 series aluminum alloys. Metrics from bending tests have been correlated with self-pierce riveting (SPR) performance of a high strength AA6111 automotive aluminum alloy in previous works. Using the ORNL HPC resources, this project developed an innovative macro→micro←nano (MMN) multiscale microstructure-based finite element (FE) code to further understanding of the relationship between microstructure and fracture properties of high-strength 6000-series alloys. This work started with microstructural characterization in both mesoscale and nanoscale and bending performance characterization of AA6111 HS2-T6 alloy at Ford, the MMN framework was applied to this alloy to simulate 3-point VDA bending. From the results of the macro-modeling of 3-point VDA bending, the critical region of fracture was identified, and the region geometry was used to construct the micro-model. The fracture criterion of micron-scale precipitates and aluminum matrix which contains submicron and nano particles (AL-SMP-NP) in the micro-model was calibrated and validated by comparing simulated and measured bending results. With the AL-SMP-NP fracture strain obtained, the fracture strain of Al-matrix containing nano particles (ALNP) will similarly be determined by a submicron scale-model using an edge-constrained FE modeling approach developed by Hu et al. With the ALNP fracture strain obtained, the fracture strain of Al-matrix containing no particles will similarly be determined by a nano scale-model using an edge-constrained FE modeling approach. After the MMN framework is built and fracture criterion calibrated, nano-model FE simulations with virtual microstructures was performed to obtain a reduced order model (ROM) of the fracture criterion of the ALNP as a function of volume fraction, size, and distribution of the nanoparticle. This nano→submicron→micro modeling part allows exploration of the influence of different material nanostructures from different process conditions on the bending properties within the multiscale bending simulation framework and the ROM of material bendability as a function of nanoparticle size and shape was established. This obtained reduced order model (ROM) could help guide the design and selection of materials to improve existing SPR process models that could replace trial-and-error rivet/die selection and help to design new rivet/die combinations capable of robustly joining new higher strength 6000 5 series alloys in automotive body structures. This would enable lightweighting of Ford vehicles leading to greater fuel efficiency and reduce manufacturing time and energy.

36 MATERIALS SCIENCE↗

Meshfree simulation and prediction of recrystallized grain size in friction stir processed 316L stainless steel

Friction stir processing (FSP) is a promising solid-phase microstructural modification technique that can repair and enhance damaged stainless steel surfaces exposed to harsh environments. The quality of the repaired material is closely correlated to the recrystallized grain size in the stir zone (SZ), which is influenced by the thermomechanical conditions dictated by FSP process parameters. Thus, establishing a reliable relationship between these parameters and recrystallized grain size in the SZ is crucial for optimizing repair quality. However, existing experimental approaches often rely on indirect temperatures measured far from the SZ, along with rough strain rate estimations, which are imprecise and time-consuming. Meanwhile, existing mesh-based modeling methods usually face numerical challenges when dealing with the large material deformations inherent in FSP. Here, to address these issues, this study introduces a meshfree process model for FSP based on the smoothed particle hydrodynamics (SPH) method, aimed at predicting process conditions under different parameters. The model is validated using experimental data from 11 combinations of tool traverse and rotation speeds on 316 L stainless steel. Correlations between process parameters, material flow, temperature, strain, strain rate, and recrystallized grain size are revealed through SPH simulations and electron backscatter diffraction (EBSD) imaging. The results show that in situ SZ temperatures range from 1071 to 1322°C, which exceed the tool temperature by over 300°C. Furthermore, SZ temperature, strain rate, and grain size increase monotonically with higher tool temperature and faster traverse speed. A relationship is then established between the model-predicted Zener-Hollomon parameter and the recrystallized grain size based on EBSD data, expressed as ln(d) = -0.364 ln(Z) + 14.673. Finally, this relationship exhibits satisfactory accuracy with errors of less than 26.9% in predicting grain sizes at various SZ locations, which offers valuable insights for optimizing FSP repair processes for 316 L stainless steel.

316L stainless steel↗

Influence of Oxygenated Compounds on Reaction Products in a Microwave Plasma Methane Pyrolysis Assembly for Post-Processing of Sabatier Methane

The state-of-the-art Carbon Dioxide Reduction Assembly (CRA) was delivered to the International Space Station (ISS) in April 2010. The system is designed to accept carbon dioxide from the Carbon Dioxide Removal Assembly and hydrogen from the Oxygen Generation Assembly. The two gases are reacted in the CRA in a Sabatier reactor to produce water and methane. Venting of methane results in an oxygen resupply requirement of about 378 lbs per crew member per year. If the oxygen is supplied as water, the total weight for resupply is about 476 lb per crew member per year. For long-term missions beyond low Earth orbit, during which resupply capabilities will be further limited, recovery of hydrogen from methane is highly desirable. For this purpose, NASA is pursuing development of a Plasma Pyrolysis Assembly (PPA) capable of recovering hydrogen from methane. Under certain conditions, water vapor and carbon dioxide (nominally intended to be separated from the CRA outlet stream) may be present in the PPA feed stream. Thus, testing was conducted in 2010 to determine the effect of these "oxygenated" compounds on PPA performance, particularly the effect of inlet carbon dioxide and water variations on the PPA product stream. This paper discusses the test set-up, analysis, and results of this testing

Mansell, J. Matthew↗

Influence of Oxygenated Compounds on Reaction Products in a Microwave Plasma Methane Pyrolysis Assembly for Post-Processing of Sabatier Methane

The state-of-the-art Carbon Dioxide Reduction Assembly (CRA) was delivered to the International Space Station (ISS) in April 2010. The system is designed to accept carbon dioxide from the Carbon Dioxide Removal Assembly and hydrogen from the Oxygen Generation Assembly. The two gases are reacted in the CRA in a Sabatier reactor to produce water and methane. Venting of methane results in an oxygen resupply requirement of about 378 lbs per crew member per year. If the oxygen is supplied as water, the total weight for resupply is about 476 lb per crew member per year. For long-term missions beyond low Earth orbit, during which resupply capabilities will be further limited, recovery of hydrogen from methane is highly desirable. For this purpose, NASA is pursuing development of a Plasma Pyrolysis Assembly (PPA) capable of recovering hydrogen from methane. Under certain conditions, water vapor and carbon dioxide (nominally intended to be separated from the CRA outlet stream) may be present in the PPA feed stream. Thus, testing was conducted in 2010 to determine the effect of these oxygenated compounds on PPA performance, particularly the effect of inlet carbon dioxide and water variations on the PPA product stream. This paper discusses the test set-up, analysis, and results of this testing.

Mansell, J. Matthew↗

Technical descriptions of the experimental dynamical downscaling simulations over North America by the CAM–MPAS variable-resolution model

Abstract. Comprehensive assessment of climate datasets is important for communicating model projections and associated uncertainties to stakeholders. Uncertainties can arise not only from assumptions and biases within the model but also from external factors such as computational constraint and data processing. To understand sources of uncertainties in global variable-resolution (VR) dynamical downscaling, we produced a regional climate dataset using the Model for Prediction Across Scales (MPAS; dynamical core version 4.0) coupled to the Community Atmosphere Model (CAM; version 5.4), which we refer to as CAM–MPAS hereafter. This document provides technical details of the model configuration, simulations, computational requirements, post-processing, and data archive of the experimental CAM–MPAS downscaling data. The CAM–MPAS model is configured with VR meshes featuring higher resolutions over North America as well as quasi-uniform-resolution meshes across the globe. The dataset includes multiple uniform- (240 and 120 km) and variable-resolution (50–200, 25–100, and 12–46 km) simulations for both the present-day (1990–2010) and future (2080–2100) periods, closely following the protocol of the North American Coordinated Regional Climate Downscaling Experiment. A deviation from the protocol is the pseudo-warming experiment for the future period, using the ocean boundary conditions produced by adding the sea surface temperature and sea-ice changes from the low-resolution version of the Max Planck Institute Earth System Model (MPI-ESM-LR) in the Coupled Model Intercomparison Project Phase 5 to the present-day ocean state from a reanalysis product. Some unique aspects of global VR models are evaluated to provide background knowledge to data users and to explore good practices for modelers who use VR models for regional downscaling. In the coarse-resolution domain, strong resolution sensitivity of the hydrological cycles exists over the tropics but does not appear to affect the midlatitude circulations in the Northern Hemisphere, including the downscaling target of North America. The pseudo-warming experiment leads to similar responses of large-scale circulations to the imposed radiative and boundary forcings in the CAM–MPAS and MPI-ESM-LR models, but their climatological states in the historical period differ over various regions, including North America. Such differences are carried to the future period, suggesting the importance of the base state climatology. Within the refined domain, precipitation statistics improve with higher resolutions, and such statistical inference is verified to be negligibly influenced by horizontal remapping during post-processing. Limited (≈50 % slower) throughput of the current code is found on a recent many-core/wide-vector high-performance computing system, which limits the lengths of the 12–46 km simulations and indirectly affects sampling uncertainty. Our experience shows that global and technical aspects of the VR downscaling framework require further investigations to reduce uncertainties for regional climate projection.

58 GEOSCIENCES↗

A Data Processing Pipeline To Extract A Knowledge Graph From Sec Documents For Socio-technical Analysis Of Critical Infrastructure Influence

The code is written in Python and consists of the following pipeline that is implemented in Apache Airflow. This pipeline intends to understand the companies that are directly or indirectly involved with a type of critical infrastructure system at some point in that system's lifecycle. The pipeline takes a configuration file that specifies a list of initial companies to consider, a geographic region of interest (disk) expressed as a latitude/longitude point and distance, and a set of SEC form types from which to extract entities and relations. There are three main components to this pipeline as currently implemented: Social Network Extraction, Critical Infrastructure Network Extraction, and Inference and Fusion. First, Social Network Extraction, implemented as the `organizations_sec` component of the workflow graph queries the SEC EDGAR webservice using the list of initial companies from the configuration file. Given this, it extracts metadata that documents the number of each type of form for the given set of companies and their location. This forms metadata represents a catalog of data sources for the extracted social network knowledge graph. The pipeline then downloads these forms from the website and saves them in a build directory for further processing. These documents are then parsed for entities and relations. Second, the Critical Network Extraction component extracts entities and relations for a critical infrastructure sector. Currently, we focus on Electric Vehicle charging stations and this information is available via the Department of Energy (DOE) database on fueling stations maintained by NREL. Third, the Inference and Fusion component relates the social network graph to the critical infrastructure graph in order to understand the impact of a company within a geographic region. Relations include ownership of the EV Charging Station asset as well as maintenance/ownership of the EV payment networks. The fused network can be represented in many ways and currently we emit a knowledge graph.

Weaver, GabrielA.↗

Mn(II)-induced phase transformation of Mn(IV) oxide in seawater

Manganese (Mn) oxides are key components of oceanic and lacustrine Mn nodules and influence metal cycling through oxidation and adsorption processes. Layered Mn oxides (LMOs) are the most common minerals in these nodules and the immediate products of microbially mediated Mn(II) oxidation by O 2 . LMOs can transform into tunneled Mn oxides (TMOs), Mn oxyhydroxides (MnOOH), or Mn(II,III) phase (Mn 3 O 4 ). LMOs often concur with Mn(II) in the environment and the adsorption and oxidation of Mn(II) by LMOs can greatly promote the transformation of LMOs to those phases. However, the Mn(II)-promoted transformation of LMOs in seawater—rich in various cations (300 mM Na + , 10 mM K + , 50 mM Ca 2+ , and 10 mM Mg 2+ ) remains poorly understood. We examined the transformation of δ-MnO 2 in artificial seawater (pH 8.2) under anoxic conditions with the Mn(II)/MnO 2 ratio (r) ranging from 0.08 to 3.83. To assess the effect of ionic strength (IS), parallel experiments were conducted in a mixed 530 mM NaCl and 10 mM KCl solution (having seawater ionic strength but without Ca 2+ and Mg 2+ ) and in 100 mM NaCl solution as a control. At low r (0.08), δ-MnO 2 transformed into triclinic birnessite and a 4 × 4 TMO in 100 mM NaCl solution, which, however, was suppressed in seawater due to strong interactions of Ca 2+ /Mg 2+ with δ-MnO 2 . In the mixed 530 mM NaCl and 10 mM KCl solution (the same ionic strength as of seawater), the transformation occurred extensively but the products had lower crystallinity compared to in 100 mM NaCl solution. At the high Mn(II)/MnO 2 ratios (0.5 ≤ r ≤ 3.83), δ-MnO 2 transformed extensively into MnOOH phases and hausmannite (Mn 3 O 4 ) in 100 mM NaCl solution. The seawater suppressed the transformation, but the suppression became weaker with increasing Mn(II)/MnO 2 ratio. For example, the transformation was completely suppressed at r = 0.5 but essentially negligible at r = 3.83. The suppression at these high Mn(II)/MnO 2 ratios was mainly ascribed to the influence of Ca 2+ and Mg 2+ rather than of the high IS, and the weaker suppression at the higher Mn(II)/MnO 2 ratio suggests stronger competition of Mn(II) with Ca 2+ /Mg 2+ for interacting with δ-MnO 2 . Moreover, the composition and crystallinity of the transformation products (i.e., the relative abundance of MnOOH (α, β, and γ) and Mn 3 O 4 ) were influenced by both the high ionic strength and the presence of Ca 2+ and Mg 2+ . Therefore, even though Ca 2+ and Mg 2+ concentrations are much lower than Na + in seawater, their impacts on the transformation are dominant. Our study explains why MnOOH phases, hausmannite, and TMOs are less common than LMOs in oceanic environments, partially because seawater chemistry suppresses their formation. LMOs are the most reactive for metal adsorption and oxidation among all Mn oxides. Thus, the high stability of LMOs in an oceanic environment confers the high impacts of Mn oxides on metal cycling in the ocean.

Divalent manganese↗

Accelerating Discovery of Solid‐State Thin‐Film Metal Dealloying for 3D Nanoarchitecture Materials Design through Laser Thermal Gradient Treatment

Thin‐film solid‐state metal dealloying (thin‐film SSMD) is a promising method for fabricating nanostructures with controlled morphology and efficiency, offering advantages over conventional bulk materials processing methods for integration into practical applications. Although machine learning (ML) has facilitated the design of dealloying systems, the selection of key thermal treatment parameters for nanostructure formation remains largely unknown and dependent on experimental trial and error. To overcome this challenge, a workflow enabling high‐throughput characterization of thermal treatment parameters is demonstrated using a laser‐based thermal treatment to create temperature gradients on single thin‐film samples of Nb‐Al/Sc and Nb‐Al/Cu. This continuous thermal space enables observation of dealloying transitions and the resulting nanostructures of interest. Through synchrotron X‐ray multimodal and high‐throughput characterization, critical transitions and nanostructures can be rapidly captured and subsequently verified using electron microscopy. The key temperatures driving chemical reactions and morphological evolutions are clearly identified. While the oxidation may influence nanostructure formation during thin‐film treatment, the dealloying process at the dealloying front involves interactions solely between the dealloying elements, highlighting the availability and viability of the selected systems. Further, this approach enables efficient exploration of the dealloying process and validation of ML predictions, thereby accelerating the discovery of thin‐film SSMD systems with targeted nanostructures.

36 MATERIALS SCIENCE↗

Far-Reaching Impacts of African Dust- A Calipso Perspective

African dust can transport across the tropical Atlantic and reach the Amazon basin, exerting far-reaching impacts on climate in downwind regions. The transported dust influences the surface-atmosphere interactions and cloud and precipitation processes through perturbing the surface radiative budget and atmospheric radiative heating and acting as cloud condensation nuclei and ice nuclei. Dust also influences biogeochemical cycle and climate through providing nutrients vital to the productivity of ocean biomass and Amazon forests. Assessing these climate impacts relies on an accurate quantification of dust transport and deposition. Currently model simulations show extremely large diversity, which calls for a need of observational constraints. Kaufman et al. (2005) estimated from MODIS aerosol measurements that about 144 Tg of dust is deposited into the tropical Atlantic and 50 Tg of dust into the Amazon in 2001. This estimated dust import to Amazon is a factor of 3-4 higher than other observations and models. However, several studies have argued that the oversimplified characterization of dust vertical profile in the study would have introduced large uncertainty and very likely a high bias. In this study we quantify the trans-Atlantic dust transport and deposition by using 7 years (2007-2013) observations from CALIPSO lidar. CALIPSO acquires high-resolution aerosol extinction and depolarization profiles in both cloud-free and above-cloud conditions. The unique CALIPSO capability of profiling aerosols above clouds offers an unprecedented opportunity of examining uncertainties associated with the use of MODIS clear-sky data. Dust is separated from other types of aerosols using the depolarization measurements. We estimated that on the basis of 7-year average, 118142 Tg of dust is deposited into the tropical Atlantic and 3860 Tg of dust into the Amazon basin. Substantial interannual variations are observed during the period, with the maximum to minimum ratio of about 1.6 and 2.5 for the deposition to the tropical Atlantic and Amazon, respectively. The MODIS-based estimates appear to fall within the range of CALIPSO-based estimates; and the difference between MODIS and CALIPSO estimates can be largely attributed to the interannual variability, which is corroborated by long-term surface dust concentration observations in the tropical Atlantic. Considering that CALIPSO generally tends to underestimate the aerosol loading, our estimate is likely to represent a low bound for the dust transport and deposition estimate. The finding suggests that models have substantial biases and considerable effort is needed to improve model simulations of dust cycle.

dust↗

Initial Assessment of the Effects of Nonmetallic Inclusions on Fatigue Life of Powder-Metallurgy-Processed Udimet(TM) 720

The fatigue lives of modern powder metallurgy (PM) disk alloys are influenced by variabilities in alloy microstructure and mechanical properties. These properties can vary due to the different steps of materials/component processing and machining. One of these variables, the presence of nonmetallic inclusions, has been shown to significantly degrade low-cycle fatigue (LCF) life. Nonmetallic inclusions are inherent defects in powder alloys that are a by-product of powder-processing techniques. Contamination of the powder can occur in the melt, during powder atomization, or during any of the various handling processes through consolidation. In modern nickel disk powder processing facilities, the levels of inclusion contamination have been reduced to less than 1 part per million by weight. Despite the efforts of manufacturers to ensure the cleanliness of their powder production processes, the presence of inclusions remains a source of great concern for the designer. the objective of this study was to investigate the effects on fatigue life of these inclusions. Since natural inclusions occur so infrequently, elevated levels of inclusions were carefully introduced in a nickel-based disk superalloy, Udimet 720 (registered trademark of Special Metals Corporation), produced using PM processing. Multiple strain-controlled fatigue tests were then performed on this material at 650 C. Analyses were performed to compare the LCF lives and failure initiation sites as functions of inclusion content and fatigue conditions. A large majority of the failures in specimens with introduced inclusions occurred at cracks initiating from inclusions at the specimen surface. The inclusions could reduce fatigue life by up to 100 times. These effects were found to be dependent on strain range and strain ratio. Tests at lower strain ranges and higher strain ratios produced larger effects of inclusions on life.

Gabb, T. P.↗

Probing the surface oxidation process in hexagonal boron nitride epilayers

Thermal neutron detectors based on hexagonal boron nitride ( h -BN) epilayers have demonstrated a record high efficiency among solid-state detectors at 58%. It was found that the performance of h -BN detectors is profoundly influenced by charge recombination at the surfaces. The dynamic process of surface oxidation in h -BN epilayers has been probed by x-ray photoelectron spectroscopy. The spectra of high-resolution (0.1 eV) scans indicated that the linewidth of the B 1s peak at 190.6 eV increased and the peak intensity decreased with an increase in exposure time in-air (t air ). The main B 1s peak at 190.6 eV evolved into multiple peaks at a higher binding energy position due to oxygen impurities tending to occupy nitrogen sites and form the B–O bond. Time constants of the oxidation process have been determined, revealing that the formation process of the B–O bond is very fast and within minutes in h -BN. The results suggest that reducing nitrogen vacancy generation during growth and employing surface treatment techniques would further improve the performance of h -BN devices.

2D materials↗

Impact of Nutrition on the Gut Microbiota: Implications for Parkinson’s Disease

Abstract Parkinson’s disease (PD) is a multifactorial neurodegenerative disease that is characterized by the degeneration of dopaminergic neurons in the substantia nigra pars compacta and by the anomalous accumulation of α-synuclein aggregates into Lewy bodies and Lewy neurites. Research suggests 2 distinct subtypes of PD: the brain-first subtype if the pathology arises from the brain and then spreads to the peripheral nervous system (PNS) and the body-first subtype, where the pathological process begins in the PNS and then spreads to the central nervous system. This review primarily focuses on the body-first subtype. The influence of the gut microbiota on the development of PD has been the subject of growing interest among researchers. It has been suggested that gut inflammation may be closely associated with pathogenesis in PD, therefore leading to the hypothesis that gut microbiota modulation could play a significant role in this process. Nutrition can influence gut health and alter the risk and progression of PD by altering inflammatory markers. This review provides an overview of recent research that correlates variations in gut microbiota composition between patients with PD and healthy individuals with the impact of certain nutrients and dietary patterns, including the Mediterranean diet, the Western diet, and the ketogenic diet. It explores how these diets influence gut microbiota composition and, consequently, the risk of PD. Last, it examines fecal transplantation and the use of prebiotics, probiotics, or synbiotics as potential therapeutic strategies to balance the gut microbiome, aiming to reduce the risk or delay the progression of PD.

Sobral, Joana (ORCID:0009000334922337)↗

A Data Processing Pipeline To Extract A Knowledge Graph From Heterogeneous Data For Socio-technical Analysis Of Critical Infrastructure Influence

The code is written in Python and consists of the following pipeline that is implemented in Apache Airflow. This pipeline intends to understand the companies that are directly or indirectly involved with a type of critical infrastructure system at some point in that system's lifecycle. The pipeline takes a configuration file that specifies a list of initial companies to consider, a geographic region of interest, and a set of SEC form types as well as other data sources (e.g. CrunchBase) from which to extract entities and relations. There are four main components to this pipeline as currently implemented: Entity Extraction, Network Construction, Analysis, and Visualization. First, Entity Extraction, is implemented as the `topear-extract_organizations` Apache Airflow workflow. Given an initial query that specifies a geographic region of interest and a time interval, the software will extract CI facilities of interest and organizations that have a direct influence relationship to those facilities (e.g. ownership). During the course of the LDRD, we focused on Electric Vehicle charging stations and this information is available via the Department of Energy (DOE) database on fueling stations maintained by NREL. Within the context of the DOE CESER project, we have focused on Battery Energy Storage Systems (BESS). Second, the Network Extraction component will iteratively construct a social network graph given the set of organizations and people extracted in the previous step. Organizations (and eventually People if desired) are then fed as a query to the `topgear-construct_social_network` Apache Airflow workflow which given a set of initial companies and data sets (e.g. SEC EDGAR form types, OpenCorporates, Crunchbase). This Airflow workflow will iteratively query such data sources to discover relationships with new organizations and people. For example, this module can iteratively query SEC EDGAR for metadata that documents the number of each type of form for the given set of companies and their location. This forms metadata represents a catalog of data sources from SEC EDGAR for the extracted social network knowledge graph. The pipeline then downloads these forms from the website and saves them in a build directory for further processing. These documents are then parsed for entities and relations. Again, we note that in additional to SEC data sources, this step can also pull in information on organizations via API services such as CrunchBase and OpenCorporates or bulk data sources. At the end of this step, the resultant social network, the Critical Infrastructure network, and the edges that encode relationships between organizations and CI facilities, form the Adversarial Socio-Technical Network (ASTN) that informs the analysis. Third, the Analysis component processes these generated ASTN. Previously, that has included the ability to compare prevalence of different vendors for a given infrastructure component type across different regions as well as identify common public and private investors across those vendors. This was demonstrated for EV Charging Stations across several different metropolitan areas within an IEEE PES GridEdge publication. More recently, we have looked at ways to identify infrastructure owners and operators of BESS with the most nameplate capacity across different states as well as other indictors of risk resulting from changes in ownership over time. Finally, the Visualization component consists of an HTML/CSS/JS framework by which users can interact geospatial, operational, and organizational relationships across a given portfolio of Critical Infrastructure facilities. The objective is to provide a library of UI/UX modules that can be repurposed for stakeholder-specific dashboards. All of the modules are related via a common event model that enables UI actions in one view to percolate across the other views.

Weaver, Gabriel [Idaho National Laboratory (INL), ↗

Over three decades, and counting, of near-surface turbulent flux measurements from the Atmospheric Radiation Measurement (ARM) user facility

Processes mediating the coupling of terrestrial, aquatic, biospheric, and atmospheric systems influence weather, climate, and ecosystem dynamics via transfer of energy, momentum, water, and carbon (or other species). These exchange processes are quantified by measurements of near-surface turbulent fluxes. Understanding processes at these interfaces provides insight toward understanding and predicting current and future states within the Earth system. The Atmospheric Radiation Measurement (ARM) user facility has been conducting measurements of near-surface turbulent fluxes since the early 1990s at long-term fixed locations and shorter-term mobile deployments across the Earth. ARM has utilized two established methods for conducting these measurements: energy balance Bowen ratio (EBBR) and eddy covariance (EC). Primary measurements from the former include sensible and latent heat flux, while the latter also measures fluxes of momentum and carbon (primarily carbon dioxide, with methane fluxes measured at two locations to date). The EBBR systems have been deployed at 22 locations, and, to date, the EC systems have been deployed at over 50 sites, with plans for additional novel site locations in the future. Herein, the history, evolution, and key aspects of these instrument systems are documented, along with information on data quality assurance and post-processing, as well as best use practices. Additionally, three data validation experiments were recently conducted, and their key findings are summarized. Finally, ancillary datasets acquired by ARM, which can contextualize and aid interpretation of the near-surface turbulent flux measurements, are discussed. The datasets described herein include the eddy correlation flux measurement system: 30ECOR (https://doi.org/10.5439/1879993, Sullivan et al., 1997), 30QCECOR (https://doi.org/10.5439/1097546, Gaustad, 2003), ECORSF (https://doi.org/10.5439/1494128, Sullivan et al., 2019a), and associated AmeriFlux and Methane Value-Added Product, AMCMETHANE (https://doi.org/10.5439/1508268, Billesbach, 2011); the energy balance Bowen ratio system: 30EBBR (https://doi.org/10.5439/1023895, Sullivan et al., 1993) and 30BAEBBR (https://doi.org/10.5439/1027268, Gaustad and Xie, 1993); and the carbon dioxide flux measurement system: CO2FLX (https://doi.org/10.5439/1287574, https://doi.org/10.5439/1287575, https://doi.org/10.5439/1287576, Koontz et al., 2015a, b, c; https://doi.org/10.5439/1989774, https://doi.org/10.5439/1989776, https://doi.org/10.5439/1992202, Biraud and Chan, 2002a, b, c). These data can be found by searching the above data stream names at https://adc.arm.gov/discovery/#/results/ (last access: 8 September 2025).

Sullivan, Ryan C. [Argonne National Laboratory (AN↗

Selection of rolling-element bearing steels for long-life applications

Nearly four decades of research in bearing steel metallurgy and processing have resulted in improvements in bearing life by a factor of 100 over that obtained in the early 1940s. For critical applications such as aircraft, these improvements have resulted in longer lived, more reliable commercial aircraft engines. Material factors such as hardness, retained austenite, grain size and carbide size, number, and area can influence rolling-element fatigue life. Bearing steel processing such as double vacuum melting can have a greater effect on bearing life than material chemistry. The selection and specification of a bearing steel is dependent on the integration of all these considerations into the bearing design and application. The paper reviews rolling-element fatigue data and analysis which can enable the engineer or metallurgist to select a rolling-element bearing steel for critical applications where long life is required.

Zaretsky, Erwin V.↗