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NASA NTRS2002

Path-Integrated Attenuation from Airborne X-Band Radar and Passive Radiometer Measurements: Implication for Rainfall Measurements

This study compares path-integrated attenuation (PIA), in precipitation over the ocean, derived from a single-frequency X-band radar, using the surface reference technique (SRT), with that deduced from a radiometer also operating at X band. The data were collected during TRMM field campaigns. The PIA derived from radar using the SRT does not involve any assumptions regarding the precipitation but it assumes that the cross-section of the surface is stable, that is, it is not significantly altered by factors such as surface roughness. The PIA deduced from the radiometer, however, involves assumptions regarding the temperature and emissivity of the surface and absorption and scattering by the intervening precipitation, which in turn depend upon the size, concentration and composition of the precipitation particles. The comparison of the PIA from the two instruments serves not only as a check between the radar and the radiometer but also may yield insights into the structure of the intervening precipitation. Such study can provide valuable information for TRMM in which both radar and radiometers are used for rain measurements. The radiometer PIA was first deduced from the brightness temperature using a simple one-layer radiative transfer model assuming no scattering, an isothermal atmosphere. The initial results show a general agreement between the PIAs deduced from the two instruments. Largo disagreement was found at high values of PIAs that may have been caused saturation of the X-band brightness temperature or by uncertainties in wind roughening of the sea surface that affects the SRT. Further results including the effects of scattering and a non-isothermal atmosphere will be shown at the conference.

Tian, Lin↗

DOE OSTI2013

Synthesis of mesoporous Bi{sub 2}O{sub 3}/CeO{sub 2} microsphere for photocatalytic degradation of Orange II dye

Graphical abstract: - Highlights: • Bi{sub 2}O{sub 3}/CeO{sub 2} microspheres were successfully synthesized by a hydrothermal procedure. • Bi{sub 2}O{sub 3}/CeO{sub 2} microspheres were used to remove wastewater pollutant containing azo dye. • The activity of Bi{sub 2}O{sub 3}/CeO{sub 2} is synergically enhanced compared to its pristine forms. - Abstract: We report on the visible-light responsive porous assembly of Bi{sub 2}O{sub 3}/CeO{sub 2} microspheres, which were synthesized via a simple hydrothermal reaction between Bi(NO{sub 3}){sub 3}·5H{sub 2}O and Ce(NO{sub 3}){sub 3}·6H{sub 2}O in the presence of ethylene glycol and ethanol. Systematic structural (X-ray diffraction (XRD)), morphological (field emission scanning electron microscopy (FE-SEM) and transmission electron microscopic (TEM)), BET surface area and diffuse reflectance spectral (DRS) analyses were carried out to characterize the formed product. The effects of experimental parameters on the microstructural and morphological behavior of Bi{sub 2}O{sub 3}/CeO{sub 2} composites were discussed. The semiconductor material as obtained was evaluated as a heterogeneous photocatalyst for the photolytic degradation of an azo dye in water and the degradation was found to follow pseudo-first-order rate kinetics. The study compares the rate constants of the new hybrid catalyst to a pristine Bi{sub 2}O{sub 3} and CeO{sub 2}, which has excellent catalytic properties under visible light irradiation for the degradation of Orange II dye.

36 MATERIALS SCIENCE↗

DOE OSTI2014

Metal-sulfide mineral ores, Fenton chemistry and disease. Particle induced inflammatory stress response in lung cells

The inhalation of mineral particulates and other earth materials, such as coal, can initiate or enhance disease in humans. Workers in occupations with high particulate exposure, such as mining, are particularly at risk. The ability of a material to generate an inflammatory stress response (ISR), a measure of particle toxicity, is a useful tool in evaluating said exposure risk. ISR is defined as the upregulation of cellular reactive oxygen species (ROS) normalized to cell viability. This study compares the ISR of A549 human lung epithelial cells after exposure to well-characterized common metal-sulfide ore mineral separates. The evaluation of the deleterious nature of ore minerals is based on a range of particle loadings (serial dilutions of 0.002 m 2 /mL stock) and exposure periods (beginning at 30 min and measured systematically for up to 24 h). There is a wide range in ISR values generated by the ore minerals. The ISR values produced by the sphalerite samples are within the range of inert materials. Arsenopyrite generated a small ISR that was largely driven by cell death. Galena showed a similar, but more pronounced response. Copper-bearing ore minerals generated the greatest ISR, both by upregulating cellular ROS and generating substantial and sustained cell death. Chalcopyrite and bornite, both containing ferrous iron, generated the greatest ISR overall. Particles containing Fenton metals as major constituents produce the highest ISR, while other heavy metals mainly generate cell death. Furthermore, this study highlights the importance of evaluating the chemistry, oxidation states and structure of a material when assessing risk management.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRSDate not supplied

Identification and Study of Validation Level Test Cases for Computational Modeling of Non-Charring Ablators

Computational modeling of Thermal Protection System (TPS) materials, used for aerospace applications, provides numerous advantages in preliminary selection and design of a heatshield material and shape for atmospheric entry vehicles. However, to serve as a reliable tool for prediction of material thermal and ablative behavior, the modeling approach needs to be validated against real experimental and flight data, preferably at a range of applied conditions. The validation study is typically very complex as it requires reliable measured data not only for the material thermal response and surface recession, but also well characterized environmental conditions. The validation problem becomes even more complex when the material thermal response is dictated by multi-physics effects such as solid conduction, in-depth thermal decomposition, pyrolysis gas flow and chemical reactions. The multi-physics effects complicate not only the modeling effort, but also the experimental measurement for validation of various aspects of the highly coupled problem. In this study, an attempt is made to identify suitable experimental data that could serve as a source for validation of material thermal response modeling tools. To reduce the computational complexity, this study focuses only on non-charring ablators, where the material thermal response could be modeled with a single governing equation for solid conduction and the ablation is limited only to the surface of the material. With a well characterized and publicly available experimental data being sparse, the study is limited in presenting test cases for only three materials: camphor, graphite and FiberForm® in the sequence of increased modeling complexity. Graphite is a commonly used TPS material for aerospace applications, both for leading edges of high-speed vehicles and internal insulation of solid rocket motors. FiberForm® is a porous carbon pre-form used in preparation of the well known PICA material Tran et al. [1996]. Inclusion of camphor into the list is conditioned with the relative simplicity in modeling the material thermal and chemical response and the low-enthalpy flow environment. In addition, camphor has been used as a simple test material for study of flow transition behavior by Stock and Ginoux [1973] and assessment of a heatshield shape change at flight relevant conditions by Rotondi et al. [2022]. In this work, the identified experimental data was extracted from the public literature and test cases that yet have been published. As it was found from the review, not a single test case contains an exhaustive set of data that would validate every aspect of the material physics. However, in the data collected, various aspects of the material behavior can be still validated, such as surface and in-depth temperature, amount of recession and a shape change. The identified experimental data for each case is accompanied with a characterized flow environment and simulated boundary conditions predicted by a Data-Parallel Line Relaxation (DPLR) code Wright et al. [1998]. In addition, material thermal response numerical simulations in each test case are performed with Kentucky Aerothermodynamics and Thermal Response System (KATS-MR) Zibitsker et al. [2022] providing a comparative study and a sanity check for the proposed validation data. Sample results from the performed numerical study are shown below. Figure 1 shows distribution of surface heat flux and pressure values on a hemi-cylinder model made of FiberForm® and tested in HyMETS arc-jet facility. The results are shown for the high pressure condition among the two tests. Flow simulation was performed with DPLR code on a quarter of original geometry. In the figure, the quarter shape was mirrored across zx and xy planes to show the complete distribution. Figure 2 shows the material response results for the high pressure case (7500 Pa), simulated with KATS-MR and a comparison to the experimental data for the surface temperature and shape shape. The simulation was performed on a 2-D slice, extracted in the xy plane at the middle of the sample. Figure 3 shows the material response simulation for the low pressure case (3500 Pa) and a comparison to the experimental data for surface temperature and shape change.

ablation↗

DOE OSTI2013

Intrinsic thermodynamic and kinetic properties of Sb electrodes for Li-ion and Na-ion batteries: Experiment and Theory

A detailed comparative study between electrochemical lithiation and sodiation of pure antimony (Sb), relating changes in structural, thermodynamic, kinetic and electrochemical properties has been carried out. For this purpose, a wide range of measurements using electrochemical (galvanostatic cycling, GITT, PITT), x-ray diffraction (XRD) and x-ray photoelectron spectroscopy (XPS) methods as well as density functional theory (DFT) based investigations have been undertaken. Assessment of the thermodynamics reveals that the reaction proceeds identically during the first and second cycles for Li whereas it differs between the first and subsequent cycles for Na. For Li the difference between the first and subsequent cycles is rooted in an improvement of the kinetics likely due to the decrease of Sb particle size whereas the reaction with Na proceeds through a different pathway from the first to subsequent cycles and is associated with the formation of amorphous NaxSb phases. For the first time we rationalize the amorphization of NaxSb phases by the long ranged strain propagation due to Na-vacancy compared to Li-Sb. At full discharge, our XRD results show for the first time that a minor fraction of hexagonal Li3Sb forms concomitantly with cubic Li3Sb. The XRD results confirm that Sb crystallizes into hexagonal Na3Sb at full sodiation. The kinetics of the reaction is assessed by rate performance tests which highlight that both Li and Na can diffuse rapidly throughout micron thick films at room temperature. However, it is found that the (de)insertion of Li provides lower overpotentials and larger storage capacities compared to Na. The difference in rate performance is complemented by diffusion coefficient determinations near the 0 V region where both materials are crystallized into M3Sb (M=Li, Na), and the results show that the apparent diffusion coefficients for Li are equivalent or one order of magnitude higher than those for Na. Interestingly, calculations show that the energy barrier for near-neighbor vacancy motion, predominant in these close-packed phases is about twice for Na than for Li. Our analysis tries to relate the lower intrinsic diffusivity of Na compared to Li with the long-range strain propagation induced by the former, thereby leading to an intrinsic origin of differences in rates, mechanical properties and amorphization. Finally, the surface chemistry of Sb electrodes cycled in NaClO4 dissolved in pure PC with(out) the addition of 5wt% EC or FEC shows presence of ethers and NaF for the EC- and FEC-based electrolytes, respectively, and SEI films rich in Na-based carbonates.

Baggetto, Loic↗

DOE OSTI2024

The Key Role of Grain Boundary Dynamics in Revolutionizing the Potential of Solid Electrolytes

Solid electrolytes (SEs) have the potential to enhance the safety and performance of Li-metal batteries. However, the existence of grain boundaries in polycrystalline SEs presents a significant challenge for both ionic and electronic migration, promoting the propagation of detrimental lithium dendrites. This study compares the roles of grain boundaries in electrical properties of three distinct SEs including garnet-type Li 6.5 La 3 Zr 1.5 Ta 0.5 O 12 (LLZO), argyrodite-type Li 6 PS 5 Cl (LPSC), and NASICON-type Li 1+x+y Al x (Ti,Ge) 2-x Si y P 3-y O 12 (LATP). Results demonstrate that the electronic and ionic conductivities of solid-state electrolytes are affected differently by grain boundaries, depending on the specific type of electrolyte. For instance, LLZO and LATP experience dielectric breakdown at 3.7 and 5.3 V, respectively, while LPSC does not exhibit such behavior. Here, a new chemical modification is proposed that simultaneously alters the composition of both the surface and grain boundaries of SEs, ultimately reducing electronic conductivity for the LLZO SEs. Consequently, the proposed LLZO exhibits unprecedented dendrite-free cycling stability, achieving a remarkable 12 000-h lifetime at room temperature, surpassing conventional strategies such as surface coatings in dendrite mitigation. This study highlights the significance of modifying grain boundaries to design safe and durable Li-metal batteries. It provides new insights for developing SEs that are highly resistant to dendrite formation.

36 MATERIALS SCIENCE↗

NASA NTRS2010

A Comparison of Satellite Based, Modeled Derived Daily Solar Radiation Data with Observed Data for the Continental US

Many applications of simulation models and related decision support tools for agriculture and natural resource management require daily meteorological data as inputs. Availability and quality of such data, however, often constrain research and decision support activities that require use of these tools. Daily solar radiation (SRAD) data are especially problematic because the instruments require electronic integrators, accurate sensors are expensive, and calibration standards are seldom available. The Prediction Of Worldwide Energy Resources (NASA/POWER; power.larc.nasa.gov) project at the NASA Langley Research Center estimates daily solar radiation based on data that are derived from satellite observations of outgoing visible radiances and atmospheric parameters based upon satellite observations and assimilation models. The solar data are available for a global 1 degree x 1 degree coordinate grid. SRAD can also be estimated based on attenuation of extraterrestrial radiation (Q0) using daily temperature and rainfall data to estimate the optical thickness of the atmosphere. This study compares daily solar radiation data from NASA/POWER (SRADNP) with instrument readings from 295 stations (SRADOB), as well as with values that were estimated with the WGENR solar generator. WGENR was used both with daily temperature and precipitation records from the stations reporting solar data and records from the NOAA Cooperative Observer Program (COOP), thus providing two additional sources of solar data, SRADWG and SRADCO. Values of SRADNP for different grid cells consistently showed higher correlations (typically 0.85 to 0.95) with SRADOB data than did SRADWG or SRADCO for sites within the corresponding cells. Mean values of SRADOB, SRADWG and SRADNP for sites within a grid cell usually were within 1 MJm-2d-1 of each other, but NASA/POWER values averaged 1.1 MJm-2d-1 lower than SRADOB. The magnitude of this bias was greater at lower latitudes and during summer months and may be at least partially explained by assumptions in ambient aerosol properties. Overall, the NASA/POWER solar radiation data are a promising resource for regional modeling studies where realistic accounting of historic variation is required.

White, Jeffrey W.↗

DOE OSTI2022

Experimental measurements and mathematical modeling of cold plate for aviation thermal management

Herein, this study, which has been motivated by the recent applications of the cold plate device in aviation thermal management, reports on physics-based mathematical models derived from the conservation laws of mass, momentum, and energy, and empiricism-based models. One of the objectives of the present work is to report on an elaborate and successful experimental work carried out on an additively manufactured device for the purpose of rigorously validating the numerical predictions. The excellent agreement between the numerical predictions and measured performance provides much needed confidence in the implementation, in the software package, of the offset-strip fin passage correlations, as well as in the software implementation of user-defined wavy fin correlations for aerospace heat exchangers and cold plates operating with ram air at Reynolds numbers below 8000. The contributions of this work can also be found in the development of a new and accurate thermal-hydraulic analysis procedure, referred to in this paper as plate-fin analogy. Results from this procedure are compared with those from thermal resistance network. The comparative study in this paper of the bulk and discrete enthalpy flux method is also new, as is the relative assessment of four off-set strip fin thermal-hydraulic models.

42 ENGINEERING↗

NASA NTRS2010

Why Haven't Mars Rovers Landed Where They Were Expected to?

In a recent study (Desai, 2008) of the actual landing sites for the Mars Pathfinder, Mars Exploration Rovers and the Phoenix Mars Lander, data collected indicates that these missions landed at least 13 km downrange of their targeted landing sites. A direct reason is that density measurements taken during entry, descent and landing were consistently found to be lower than those predicted by Mars atmospheric models. The basis of this study is to further investigate this problem to see if certain aspects of current Mars atmospheric models need to be reevaluated. This study compared four different atmospheric profiles at nine pairs of comparable sites around Mars. The comparable sites are similar in location and Local True Solar Time; however they are from different Mars years. One year had normal conditions, while the other year experienced a global dust storm. Three of the atmospheric profiles were obtained by the Mars Global Surveyor (MGS); these data sets include a Radio Science profile and Thermal Emission Spectrometer data in limb and nadir projections. The three MGS data sets were selected from large observational databases to allow the sites to have data observed at nearcoincident times. The last atmospheric profile is from the Mars Global Reference Atmospheric Model (Mars-GRAM), an engineering level atmospheric model widely used for mission applications. Through careful data evaluation, several conclusions were drawn. Ratios among the data show that the three observed MGS profiles were consistent with each other, although they were recorded by three different methods. Mars-GRAM data had larger differences from the observed data. Mars-GRAM particularly had issues with consistently overestimating upper atmosphere atmospheric density, as noted in Desai s study. Differences between the observed atmospheric density profiles from the Mars-GRAM atmospheric density profile could be attributed to a temperature bias in the model, especially in the upper atmosphere.

Badger, Andrew M.↗

NASA NTRS2019

Empirical Absolute Calibration Model for Multiple Pseudo-Invariant Calibration Sites

This work extends an empirical absolute calibration model initially developed for the Libya 4 Pseudo-Invariant Calibration Site (PICS) to five additional Saharan Desert PICS (Egypt 1, Libya 1, Niger 1, Niger 2, and Sudan 1), and demonstrates the efficacy of the resulting models at predicting sensor top-of-atmosphere (TOA) reflectance. It attempts to generate absolute calibration models for these PICS that have an accuracy and precision comparable to or better than the current Libya 4 model, with the intent of providing additional opportunities for sensor calibration. In addition, this work attempts to validate the general applicability of the model to other sites. The method uses Terra Moderate Resolution Imaging Spectroradiometer (MODIS) as the reference radiometer and Earth Observing-1 (EO-1) Hyperion image data to provide a representative hyperspectral reflectance profile of the PICS. Data from a region of interest (ROI) in an “optimal region” of 3% temporal, spatial, and spectral stability within the PICS are used for developing the model. The developed models were used to simulate observations of the Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+), Landsat 8 (L8) Operational Land Imager (OLI), Sentinel 2A (S2A) MultiSpectral Instrument (MSI) and Sentinel 2B (S2B) MultiSpectral Instrument (MSI) from their respective launch date through 2018. The models developed for the Egypt 1, Libya 1 and Sudan 1 PICS have an estimated accuracy of approximately 3% and precision of approximately 2% for the sensors used in the study, comparable to the current Libya 4 model. The models developed for the Niger 1 and Niger 2 sites are significantly less accurate with similar precision.

Raut, Bipin↗

DOE OSTI2024

Evidential Deep Learning: Enhancing Predictive Uncertainty Estimation for Earth System Science Applications

Abstract Robust quantification of predictive uncertainty is a critical addition needed for machine learning applied to weather and climate problems to improve the understanding of what is driving prediction sensitivity. Ensembles of machine learning models provide predictive uncertainty estimates in a conceptually simple way but require multiple models for training and prediction, increasing computational cost and latency. Parametric deep learning can estimate uncertainty with one model by predicting the parameters of a probability distribution but does not account for epistemic uncertainty. Evidential deep learning, a technique that extends parametric deep learning to higher-order distributions, can account for both aleatoric and epistemic uncertainties with one model. This study compares the uncertainty derived from evidential neural networks to that obtained from ensembles. Through applications of the classification of winter precipitation type and regression of surface-layer fluxes, we show evidential deep learning models attaining predictive accuracy rivaling standard methods while robustly quantifying both sources of uncertainty. We evaluate the uncertainty in terms of how well the predictions are calibrated and how well the uncertainty correlates with prediction error. Analyses of uncertainty in the context of the inputs reveal sensitivities to underlying meteorological processes, facilitating interpretation of the models. The conceptual simplicity, interpretability, and computational efficiency of evidential neural networks make them highly extensible, offering a promising approach for reliable and practical uncertainty quantification in Earth system science modeling. To encourage broader adoption of evidential deep learning, we have developed a new Python package, Machine Integration and Learning for Earth Systems (MILES) group Generalized Uncertainty for Earth System Science (GUESS) (MILES-GUESS) ( https://github.com/ai2es/miles-guess ), that enables users to train and evaluate both evidential and ensemble deep learning. Significance Statement This study demonstrates a new technique, evidential deep learning, for robust and computationally efficient uncertainty quantification in modeling the Earth system. The method integrates probabilistic principles into deep neural networks, enabling the estimation of both aleatoric uncertainty from noisy data and epistemic uncertainty from model limitations using a single model. Our analyses reveal how decomposing these uncertainties provides valuable insights into reliability, accuracy, and model shortcomings. We show that the approach can rival standard methods in classification and regression tasks within atmospheric science while offering practical advantages such as computational efficiency. With further advances, evidential networks have the potential to enhance risk assessment and decision-making across meteorology by improving uncertainty quantification, a longstanding challenge. This work establishes a strong foundation and motivation for the broader adoption of evidential learning, where properly quantifying uncertainties is critical yet lacking.

Schreck, John S.↗

NASA NTRSDate not supplied

Observing Ice Phase Clouds and Precipitation with Millimeter- and Submillimeter-wave Radiometry during the IMPACTS field campaign: Algorithm Development for the Emerging Class of Microwave Radiometers

Millimeter- and submillimeter-wave (mmWave, submm) radiometers provide significant information content on atmospheric water in liquid, ice, and vapor phases. Recent sensors, such as the Global Precipitation Measurement (GPM) or the Temporal Experiment for Storms and Tropical Systems Technology – Demonstration (TEMPEST-D), use mmWave bands to improve estimation of ice-phase precipitation, and future missions, such as the Atmosphere Observing System (AOS), will extend to submm to provide additional information on thinner ice clouds, linking clouds and precipitation and therefore elucidating the links between weather, climate, and the water cycle. To support the expanded use of mmWave/submm radiometry and exploit the available information content on condensed water mass, we demonstrate ice and liquid water path retrievals for NASA Goddard Space Flight Center's airborne radiometers the Conical Scanning Millimeter-wave Imaging Radiometer (CoSMIR) and the Configurable Scanning Submillimeter-wave Instrument/Radiometer (CoSSIR, formerly the Compact Scanning Submillimeter Imaging Radiometer). The analysis is based on data collected during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Storms (IMPACTS) field campaign. A simulation study compares and contrasts retrievals for CoSMIR and CoSSIR, with CoSSIR demonstrating higher skill in ice retrievals, particularly for thin clouds, and the CoSMIR frequencies performing better for liquid. Additionally, we look at dual-polarized radiances observed by CoSMIR during the first two IMPACTS deployments to understand the polarization signatures induced by oriented hydrometeors. Results will be presented in the context of upcoming missions and sensors including AOS and the Ice Cloud Imager (ICI). We will describe the objectives for the expected first flight of the newly upgraded CoSSIR during the final IMPACTS deployment, and we will share novel science investigations we plan to undertake with CoSSIR's new capabilities. Popular Summary: Ice in clouds and falling snow is an important component of weather, climate, and water resources. To better use a new class of sensors that provide information on atmospheric ice, we developed an approach to measure ice clouds and falling snow using airborne data taken during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Storms (IMPACTS), a field campaign to study winter storms. We look at the results for two similar instruments to understand how those differences affect these measurements of clouds and snow, and we further investigate the information the sensors can provide on properties of the clouds and snow.

Ian S Adams↗

NASA NTRSDate not supplied

Observing Ice Phase Clouds and Precipitation with Millimeter- and Submillimeter-wave Radiometry during the IMPACTS field campaign: Algorithm Development for the Emerging Class of Microwave Radiometers

Ian S Adams↗

DOE OSTI2022

Unstructured clinical notes within the 24 hours since admission predict short, mid & long-term mortality in adult ICU patients

Mortality prediction for intensive care unit (ICU) patients is crucial for improving outcomes and efficient utilization of resources. Accessibility of electronic health records (EHR) has enabled data-driven predictive modeling using machine learning. However, very few studies rely solely on unstructured clinical notes from the EHR for mortality prediction. In this work, we propose a framework to predict short, mid, and long-term mortality in adult ICU patients using unstructured clinical notes from the MIMIC III database, natural language processing (NLP), and machine learning (ML) models. Depending on the statistical description of the patients’ length of stay, we define the short-term as 48-hour and 4-day period, the mid-term as 7-day and 10-day period, and the long-term as 15-day and 30-day period after admission. We found that by only using clinical notes within the 24 hours of admission, our framework can achieve a high area under the receiver operating characteristics (AU-ROC) score for short, mid and long-term mortality prediction tasks. The test AU-ROC scores are 0.87, 0.83, 0.83, 0.82, 0.82, and 0.82 for 48-hour, 4-day, 7-day, 10-day, 15-day, and 30-day period mortality prediction, respectively. We also provide a comparative study among three types of feature extraction techniques from NLP: frequency-based technique, fixed embedding-based technique, and dynamic embedding-based technique. Lastly, we provide an interpretation of the NLP-based predictive models using feature-importance scores.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Polarized metal–metal multiple bonding and reactivity of phosphinoamide-bridged heterobimetallic group IV/cobalt compounds

Heterobimetallic complexes are studied for their ability to mimic biological systems as well as active sites in heterogeneous catalysts. While specific interest in early/late heterobimetallic systems has fluctuated, they serve as important models to fundamentally understand metal–metal bonding. Specifically, the polarized metal–metal multiple bonds formed in highly reduced early/late heterobimetallic complexes exemplify how each metal modulates the electronic environment and reactivity of the complex as a whole. In this Perspective, we chronicle the development of phosphinoamide-supported group IV/cobalt heterobimetallic complexes. This combination of metals allows access to a low valent Co −I center, which performs a rich variety of bond activation reactions when coupled with the pendent Lewis acidic metal center. Conversely, the low valent late transition metal is also observed to act as an electron reservoir, allowing for redox processes to occur at the d 0 group IV metal site. Most of the bond activation reactions carried out by phosphinoamide-bridged M/Co −I (M = Ti, Zr, Hf) complexes are facilitated by cleavage of metal–metal multiple bonds, which serve as readily accessible electron reservoirs. Comparative studies in which both the number of buttressing ligands as well as the identity of the early metal were varied to give a library of heterobimetallic complexes are summarized, providing a thorough understanding of the reactivity of M/Co −I heterobimetallic systems

Hunter, Nathanael H.↗

DOE OSTI2019

Comparison of Local Recurrence Risk Estimates After Breast-Conserving Surgery for DCIS: DCIS Nomogram Versus Refined Oncotype DX Breast DCIS Score

Background: A ductal carcinoma in situ (DCIS) Nomogram integrating 10 clinicopathologic/treatment factors and a Refined DCIS Score (RDS) that incorporates a genomic assay and three clinicopathologic factors (Oncotype DX DCIS Score) are available to estimate DCIS 10-year local recurrence risk (LRR). This study compared these estimates. Methods: Patients 50 years of age or older with DCIS size 2.5 cm or smaller and a genomic assay available were identified. An RDS within 1–2% of the range of Nomogram LRR estimates obtained by assuming use and non-use of endocrine therapy (Nomogram ± ET) was defined as concordant. Assuming a 10-year risk threshold of 10% for recommending radiation, Nomogram ± ET and RDS estimates were compared, and threshold concordance was determined. Results: For 54 (92%) of 59 patients, the RDS and Nomogram ± ET LRR estimates were concordant. For the remaining 5 (8%) of the 59 patients, the RDS LRR estimates were lower than the Nomogram + ET estimates, with an absolute difference of 3–8%, and thus were discordant. For these five patients, the RDS estimates of 10-year LRR were lower than 10% (range 5–8%) and the Nomogram + ET estimates were 10% or higher (range 11–14%). These five patients with both discordant and threshold-discordant estimates all had close margins (≤ 2 mm). Conclusions: Among 92% of women 50 years of age or older with DCIS size 2.5 cm or smaller, free-of-charge online Nomogram 10-year LRR estimates were concordant with those obtained using the commercially available RDS (> $4600). Among the 8% with discordant risk estimates, the RDS appeared to underestimate the LRR and may lead to inappropriate omission of radiotherapy. Unless other data show a clinically significant advantage of the RDS (Oncotype DX DCIS Score), the study data suggest that for women 50 years of age or older with DCIS size 2.5 cm or smaller, its use is not warranted.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2023

Trap characterization of high-growth-rate laser-assisted MOCVD GaN

A detailed study comparing defect incorporation between laser-assisted metal-organic chemical vapor deposition (MOCVD)-grown GaN and conventional low- and high-growth-rate MOCVD GaN was conducted. Using deep-level transient and optical spectroscopy, traps throughout the bandgap were characterized where traps were found at EC-0.25 eV, EC-0.57 eV, EC-0.72 eV, EC-0.9 eV, EC-1.35 eV, EC-2.6 eV, and EC-3.28 eV in all three samples. This indicates no new traps were observed in the laser-assisted MOCVD GaN sample. Overall, the trap concentrations in the laser-assisted MOCVD sample were ∼2× higher than the optimal low-growth-rate sample, but this is primarily due to the increase in gallium vacancy EC-2.6 eV and carbon-related EC-3.28 eV trap concentrations. The EC-0.9 eV trap concentration was ∼2× higher in the laser-assisted sample, so proton irradiation experiments were conducted to identify the physical source of this level. The results indicated this was a native point defect likely related to gallium interstitials. Overall, this study shows that the laser-assisted MOCVD growth method is promising for future thick, high-quality GaN epilayers after further growth optimizations.

Physics↗

DOE OSTI2023

Machine-to-machine variability of roughness and corrosion in additively manufactured 316L stainless steel

Numerous studies on the corrosion response of metal AM have been conducted. Nonetheless, the specimens being tested are commonly ground or polished to remove the outer as-built surface. If metal AM is truly going to be employed as a transformative technology that can produce complex shapes that do not require traditional machining, then the material needs to be evaluated in the as-built state. The reality is that AM alloys have shown significant inconsistencies regarding as-built surface texture, topology, and residual stress. One metric that has shown significant unpredictability in the literature is the susceptibility to localized corrosion of typically passive alloys, such as stainless steel (SS). There are a large number of studies that have attempted to understand the corrosion response of metal AM materials, but these studies are typically performed on materials that have been printed on a single machine and often mechanically polished to a smooth finish. This study compares the corrosion response of as-built AM, laser-beam powder bed fusion (LB-PBF), 316L SS parts that have been fabricated on five different machines. The majority of this work focused on understanding the susceptibility to localized corrosion of AM metals with respect to machine-dependent variables, namely surface roughness, and build angle. Surface roughness data was collected using scanning white light triangulation, laser scanning confocal microscopy, and coherence scanning interferometry. The results show that there is significant variability (p two-tail < 0.05) in the susceptibility to local corrosion initiation of LB-PBF 316L SS samples built on different machines. Surface oxides were probed with electron dispersive spectroscopy and revealed that variations in local corrosion susceptibility likely arise from differences in the stability of the passive film caused by chemical segregation, unique microstructure, and tortuous roughness features at the as-built surfaces. The variability of roughness and corrosion properties from test samples printed on different machines was corroborated by property measurements performed at five different testing sites, proving reproducibility of the data. Most importantly, this study shows that if the as-built surface layer is removed through grinding or electropolishing the machine-to-machine variation observed in the corrosion susceptibility is reduced.

36 MATERIALS SCIENCE↗