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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

PROCESS-STRUCTURE-PROPERTY RELATIONSHIPS IN LASER POWDER BED FUSION PRODUCED 17-4 PH STEEL

Laser powder bed fusion (LPBF) is a metal additive manufacturing method that produces non-traditional microstructures as a result of the rapid solidification and thermal cycling inherent to the process. When using LPBF-produced material in application, these unique microstructures challenge the applicability of well developed mechanical property databases achieved by conventional heat treatments. For wider adoption of this technology, a more holistic understanding is necessary on how process attributes develop material structure, which dictate mechanical properties. This dissertation explores the process– structure–property relationships in LPBF 17-4 PH steel through systematic evaluation of atmospheric processing and heat treatment effects on microstructure and mechanical performance. Specimens were fabricated under controlled build environments, subjected to a range of solutionizing, homogenizing, and aging treatments, and characterized using optical microscopy, electron back scatter diffraction (EBSD), and X-ray diffraction (XRD) to quantify phase evolution. Tensile testing was performed to directly link heat treatment pathway and nitrogen absorption to mechanical performance. This work demonstrates where conventional heat treatment standards are applicable to LPBF 17-4 PH steel and where modifications are required. By directly correlating phase stability, nitrogen effects, and tensile response, this work provides practical guidelines for tailoring post-processing strategies. These findings underscore that successful application of LPBF 17-4 PH steel requires explicit consideration of both build environment and post-processing. By linking processing conditions to microstructure and performance, this work advances understanding of critical variables that govern reliability of additively manufactured precipitation-hardened stainless steels in demanding applications.

Brown, Benjamin [Kansas City National Security Cam↗
DOE OSTI2026

Open quantum system approach to inclusive jet production in heavy-ion collisions

We derive a factorization formula for inclusive jet production in heavy-ion collisions using the tools of Effective Field Theory (EFT). We show how physics at widely separated scales in this process can be systematically separated by matching to EFTs at successively lower virtualities. Owing to a strong scale separation, we recover a vacuum-like DGLAP evolution above the jet scale, while the additional low-energy scales induced by the medium effectively probe the internal structure of the jet. As a result, the cross section can be written as a series with an increasing number of subjets characterized by perturbative matching coefficients each of which is convolved with a distinct function. These functions encode broadening, medium-induced radiations as well as quantum interference such as the Landau-Pomeranchuk-Migdal effect and color coherence dynamics to all orders in perturbation theory. As a first application of this EFT framework, we investigate the case of an unresolved jet and show how the cross section can be factorized and fully separate the jet dynamics from the universal physics of the medium. To compare to the existing literature, we explicitly compute the medium jet function at next-to-leading order in the coupling and leading order in medium opacity.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Foundations of machine learning for low-temperature plasmas: methods and case studies

Abstract Machine learning (ML) and artificial intelligence have proven to be an invaluable tool in tackling a vast array of scientific, engineering, and societal problems. The main drivers behind the recent proliferation of ML in practically all aspects of science and technology can be attributed to: (a) improved data acquisition and inexpensive data storage; (b) exponential growth in computing power; and (c) availability of open-source software and resources that have made the use of state-of-the-art ML algorithms widely accessible. The impact of ML on the field of low-temperature plasmas (LTPs) could be particularly significant in the emerging applications that involve plasma treatment of complex interfaces in areas ranging from the manufacture of microelectronics and processing of quantum materials, to the LTP-driven electrification of the chemical industry, and to medicine and biotechnology. This is primarily due to the complex and poorly-understood nature of the plasma-surface interactions in these applications that pose unique challenges to the modeling, diagnostics, and predictive control of LTPs. As the use of ML is becoming more prevalent, it is increasingly paramount for the LTP community to be able to critically analyze and assess the concepts and techniques behind data-driven approaches. To this end, the goal of this paper is to provide a tutorial overview of some of the widely-used ML methods that can be useful, amongst others, for discovering and correlating patterns in the data that may be otherwise impractical to decipher by human intuition alone, for learning multivariable nonlinear data-driven prediction models that are capable of describing the complex behavior of plasma interacting with interfaces, and for guiding the design of experiments to explore the parameter space of plasma-assisted processes in a systematic and resource-efficient manner. We illustrate the utility of various supervised, unsupervised and active learning methods using LTP datasets consisting of commonly-available, information-rich measurements (e.g. optical emission spectra, current–voltage characteristics, scanning electron microscope images, infrared surface temperature measurements, Fourier transform infrared spectra). All the ML demonstrations presented in this paper are carried out using open-source software; the datasets and codes are made publicly available. The FAIR guiding principles for scientific data management and stewardship can accelerate the adoption and development of ML in the LTP community.

Physics↗
DOE OSTI2022

Design and analysis of a ten-turbine floating wind farm with shared mooring lines

This paper discusses the development and analysis of a novel design for a 10-turbine floating wind farm with shared mooring lines. Shared mooring lines tether adjacent floating platforms together, reducing the number of anchors required but increasing system complexity. We present a systematic, multistage design process for shared mooring systems, involving linearized analysis of array layout options, quasi-static mooring line optimization, and design refinement based on coupled dynamic loads analysis. The design developed from this process is thought to represent one of the most advantageous shared-mooring configurations for this scale of floating wind array. It features perpendicular anchor line pairs and allows shared, multiline anchors, making it an example of a shared-mooring-and-anchor array. Comparing the performance and cost characteristics of the shared-mooring design with more conventional three-line individual mooring systems shows equivalent dynamic response characteristics and stationkeeping system cost savings of 25% when using shared mooring lines and shared anchors. The design is also advantageous in the case of a mooring line failure, with offsets and redundancy characteristics similar to four-line individual mooring systems.

17 WIND ENERGY↗
DOE OSTI2025

Improved heavy-ion PID using scintillation light detector with neural network analysis: a Monte Carlo simulation study

The photon collection efficiency of gaseous scintillator detectors varies according to the position of the impinging charged particles in the medium that generates scintillation light. Thus, when impinging particles are distributed over a large area, the intrinsic photon-number resolution of the system is affected by a large variation. This work presents and discusses a method for adjusting the total number of detected photons to account for variation in the photon collection efficiency as a function of the position of the light source within the scintillating medium. The method was developed and validated by processing data from systematic simulation studies based on GEANT4 that model the response of the Energy Loss Optical Scintillation System (ELOSS) detector. The position of the charged particle is calculated using a deep neural network algorithm. This is accomplished by analyzing the distribution of scintillation light recorded by the array of photosensors. The estimated particle position is then used to calculate the correction factor and adjust the amount of captured light to account for variations in the photon collection efficiency. The neural network algorithm provides excellent tracking capabilities, achieving sub-millimeter position resolution and an angular resolution of 12 mrad, approaching the performance of traditional tracking detectors (e.g., drift chambers). The present method can be generalized to any optical scintillation system where the photon collection efficiency depends on the position of the impinging particle.

Heavy-ion detectors↗
DOE OSTI2021

Unbalanced Parallel I/O: An Often-Neglected Side Effect of Lossy Scientific Data Compression

Lossy compression techniques have demonstrated promising results in significantly reducing the scientific data size while guaranteeing the compression error bounds. However, one important yet often neglected side effect of lossy scientific data compression is its impact on the performance of parallel I/O. Our key observation is that the compressed data size is often highly skewed across processes in lossy scientific compression. To understand this behavior, we conduct extensive experiments where we apply three lossy compressors MGARD, ZFP, and SZ, which are specifically designed and optimized for scientific data, to three real-world scientific applications Gray-Scott simulation, WarpX, and XGC. Our analysis result demonstrates that the size of the compressed data is always skewed even if the original data is evenly decomposed among processes. Such skewness widely exists in different scientific applications using different compressors as long as the information density of the data varies across processes. We then systematically study how this side effect of lossy scientific data compression impacts the performance of parallel I/O. We observe that the skewness in the sizes of the compressed data often leads to I/O imbalance, which can significantly reduce the efficiency of I/O bandwidth utilization if not properly handled. In addition, writing data concurrently to a single shared file through MPI-IO library is more sensitive to the unbalanced I/O loads. Therefore, we believe our research community should pay more attention to the unbalanced parallel I/O caused by lossy scientific data compression.

Wang, Xinying↗
DOE OSTI2025

Laser damage of crazed electron-beam high-reflectors following infrared and ultraviolet irradiation in the nanosecond pulse regime

Laser damage of optical components can be a limiting factor in scaling the energetics of high-peak and average power laser systems. Specifically for optical coatings, damage under nanosecond pulsed irradiation is initiated by pre-existing defects in the coating layers, including those that cause discontinuities in the structure, like craze lines. Crazing or cracking in a multilayer dielectric optical coating is induced when the overall coating stress is sufficiently tensile, and is an occasionally observed issue when employing more porous deposition techniques like electron-beam evaporation. Here, in this study, electron-beam high-reflectors were fabricated utilizing process parameters that are known to induce crazing based on prior processing history to systematically evaluate the impact of crazing on reflector damage performance for 1064 and 355 nm lasers. The crazing that was observed was apparently nucleated at nodular defects. When the cross-section of these nodules was investigated, it was observed that there were cracks into the fused silica substrate of approximately 5 µm in depth. The craze lines were irradiated with 1064 and 355 nm light at fluences slightly above the onset of damage initiation fluence of the coating. The 1064 nm irradiated sub-apertures exhibit laser damage but with no spatial correlation with the craze line, whereas the 355 nm irradiated area exhibited many damage sites along the craze line. Finite-difference time-domain electric-field simulations were conducted, and ∼2× field amplification in hafnia was observed for the 355 nm wavelength case. The laser damage can be attributed to a slight electric-field intensification coincidental with an area where UV damage-prone precursors are known to occur. The 355 nm laser damage in uncoated fused silica substrates has been previously correlated to initiate through localized UV absorption at the broken silica bonds in the tips of fractures.

Harthcock, Colin [Lawrence Livermore National Labo↗
DOE OSTI2022

Novel and effective surface passivation for high efficiency n- and p-type Silicon solar cell

The project objective was to develop a novel Si surface passivation method using chalcogens, sulfur (S) and/or selenium (Se), as passivating elements, to withstand industry-standard high temperature contacting and metallization schemes for p-type Si based passivated emitter and rear contact (p-PERC) solar cells. The back surface passivation of PERC cells has been improved drastically with the invention and successful application of an Al 2 O 3 passivation layer. However, the front n + diffused junction surface is still poorly passivated by the standard amorphous silicon nitride (SiNx) anti-reflection coating (ARC) layer. This project sought to address the passivation challenges of both front n+ emitter and undiffused p-Si back surface. Improved p-PERC solar cell performance with open circuit voltage (V OC ) > 680 mV and efficiency of 22% were targeted to validate superior defect passivation properties as compared to standard SiO 2 / Al 2 O 3 passivation. During this project, we systematically investigated process-structure-properties-performance relationships of this novel advanced defect passivation approach. The S/Se passivation was carried out by reacting industrial Czochralski (Cz) Si wafers in H 2 S and H 2 Se gases in a chemical vapor deposition (CVD) reactor at temperatures up to 700°C. After an exhaustive optimization of the process parameters (temperature, time, and gas concentration), we established an optimized process and demonstrated extremely low surface recombination velocities (SRVs) of 1.5 cm/s and 8 cm/s on n-type and p-type Si, respectively, by S-passivation. In-depth surface and interface characterization were performed using soft x-ray and photoelectron spectroscopies (XPS, UPS, XES), combined with capacitance-voltage-frequency (C-V-f) measurements, to decipher the surface chemical/electronic structure and interface defect state densities. These measurements provided critical understanding of the defect passivation mechanism and elucidated the presence of surface S-Si bonds, a reduction of surface dipoles, and low interface state densities (D it ) < 10 11 cm -2 ev -1 . We also found that the Se-passivation is inferior to the S-passivation (by at least one order of magnitude in SRV). Application of the optimized S-passivation to the n+ diffused emitter surface led to a low surface recombination current density, J0 ≈ 40 fA/cm 2 (~ 1/4 of the industry-standard SiNx-passivation), and high implied V OC (686 mV) in p-PERC solar cell structures. The S-passivation process also was found to improve the bulk quality of the p-type Si, better than the SiO 2 or Al 2 O 3 passivation processes. After successful demonstration of efficient passivation of Si surface defects by S, we extensively studied the air, thermal, and illumination stability of the passivation structure. S-passivation itself degrades in air due to competing reactions with moisture and oxygen to form oxides, which can be eliminated by a SiNx capping layer (also acting as a anti-reflective coating). After SiNx process optimization, we demonstrated illumination and thermally stable S-passivation with SRV < 5 cm/s and J 0 < 80 fA/cm 2 . These enhancements in Si passivation, incorporated into p-PERC cells, achieved an efficiency of 19.93% with V OC = 649 mV, using manufacturing metallization and contacting schemes. The low cell performance (cell V OC is much less than the implied V OC = 686 mV, anticipated from surface passivation) was identified due to degradation of S-passivation during the metal firing step (out-diffusion of S from the Si interface to the SiNx surface). The S-passivation of Si surfaces shows significant promise with excellent passivation quality, essential for high performance (high V OC , high efficiency) solar cells. Integration of this innovative defect passivation into devices, however, demands further development of the capping layer, low temperature (<700°C) metallization process, and/or engineering of advanced device structures. Surface passivation-dominated advanced Si solar cells, such as tunnel oxide passivated contacts and Si heterojunctions, are increasingly of interest due to their high-performance potential and will have a growing photovoltaic market share in the near future.

14 SOLAR ENERGY↗
DOE OSTI2023

Searching for Spectroscopic Signatures of Ongoing Quenching in SDSS Galaxies

In this paper, we estimate the “star formation change parameter,” SFR 79 , which characterizes the current SFR relative to the average during the last 800 Myr, for ~300,000 galaxies selected from the Sloan Digital Sky Survey (SDSS). The goals are to examine, in a much larger and independent sample, the trends previously reported in a sample of star-forming (SF) MaNGA galaxies and also to search for spectroscopic signatures of ongoing quenching in the so-called “Green Valley,” which is generally believed to contain galaxies that are migrating from the SF population to the quenched population of galaxies. Measuring SFR 79 for our large sample of SDSS galaxies, we first confirm the basic results of SF galaxies published by Wang & Lilly. We then discuss in detail the calibration and meaning of SFR 79 for galaxies that are well below the SFMS and establish the expected statistical signature of systematic ongoing quenching from modeling the z ~ 0 quenching rate of the SF population. We conclude that it is not possible at present to establish unambiguous observational evidence for systematic ongoing quenching processes, due to limitations both in the noise of the observational data, in particular in the measurements of H δ absorption, and in the calibration of SFR 79 , as well as biases introduced by the necessity of selecting objects with significant H α emission. We do however see plausible indications of ongoing quenching, which are quantitatively consistent with expectations from “growth+quenching” models of galaxy evolution and a typical e-folding timescale for quenching of ~500 Myr.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Observation of Cosmic-Ray Anisotropy in the Southern Hemisphere with 12 yr of Data Collected by the IceCube Neutrino Observatory

We analyzed the 7.92 × 10 11 cosmic-ray-induced muon events collected by the IceCube Neutrino Observatory from 2011 May 13, when the fully constructed experiment started to take data, to 2023 May 12. This data set provides an up-to-date cosmic-ray arrival direction distribution in the Southern Hemisphere with unprecedented statistical accuracy covering more than a full period length of a solar cycle. Improvements in Monte Carlo event simulation and better handling of year-to-year differences in data processing significantly reduce systematic uncertainties below the level of statistical fluctuations compared to the previously published results. We confirm the observation of a change in the angular structure of the cosmic-ray anisotropy between 10 TeV and 1 PeV, more specifically in the 100–300 TeV energy range. For the first time, we analyzed the angular power spectrum at different energies. The observed variations of the power spectra with energy suggest relatively reduced large-scale features at high energy compared to those of medium and small scales. The large volume of data enhances the statistical significance at higher energies, up to the PeV scale, and smaller angular scales, down to approximately 6° compared to previous findings.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Quantifying Temperature Dependence of Pu(IV) Absorbance Spectra for Advanced Online Monitoring of Nuclear Processes

This article presents a systematic study of Pu(IV) absorbance spectral features as a function of temperature to develop an understanding of this parameter’s effect on chemometric models that can be used as online monitoring tools to support nuclear processing. The descriptive and predictive models that provide real-time feedback of these processes are usually constructed with data collected in conditions typical of a laboratory environment, which can differ drastically from a processing environment. To assess the impact of temperature on Pu(IV) absorbance spectra, 11 samples of Pu(IV) were synthesized with varying HNO 3 concentrations ranging from 0.6 to 9.5 M and heated between 15 and 45 °C. Ultraviolet (UV)–visible (vis)–near-infrared (NIR) absorption spectra collected at different HNO 3 concentrations and temperatures revealed that features associated with Pu(IV) are sensitive to temperature at all HNO 3 concentrations and that changes in features depend on HNO 3 concentration. The contributions of temperature and HNO 3 concentration to variation in Pu(IV) spectral features were evaluated using the principal component analysis of spectra that were baseline-corrected with an asymmetric least-squares method. Furthermore, predictive modeling for HNO 3 concentration with partial least-squares regression of UV–vis–NIR spectra highlighted the importance of accounting for temperature in the calibration set to optimize model performance. This methodology constitutes a new, systematic approach to account for the effect of temperature on the absorption spectra of metal ions and is useful for process monitoring applications in many industries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

On single-crystal total scattering data reduction and correction protocols for analysis in direct space

Data reduction and correction steps and processed data reproducibility in the emerging single-crystal total-scattering-based technique of three-dimensional differential atomic pair distribution function (3D-ΔPDF) analysis are explored. All steps from sample measurement to data processing are outlined using a crystal of CuIr 2 S 4 as an example, studied in a setup equipped with a high-energy X-ray beam and a flat-panel area detector. Computational overhead as pertains to data sampling and the associated data-processing steps is also discussed. Various aspects of the final 3D-ΔPDF reproducibility are explicitly tested by varying the data-processing order and included steps, and by carrying out a crystal-to-crystal data comparison. Situations in which the 3D-ΔPDF is robust are identified, and caution against a few particular cases which can lead to inconsistent 3D-ΔPDFs is noted. Although not all the approaches applied herein will be valid across all systems, and a more in-depth analysis of some of the effects of the data-processing steps may still needed, the methods collected herein represent the start of a more systematic discussion about data processing and corrections in this field.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Melt Pool characteristics on surface roughness and printability of 316L stainless steel in laser powder bed fusion

Purpose Surface quality and porosity significantly influence the structural and functional properties of the final product. This study aims to establish and explain the underlying relationships among processing parameters, top surface roughness and porosity level in additively manufactured 316L stainless steel. Design/methodology/approach A systematic variation of printing process parameters was conducted to print cubic samples based on laser power, speed and their combinations of energy density. Melt pool morphologies and dimensions, surface roughness quantified by arithmetic mean height (Sa) and porosity levels were characterized via optical confocal microscopy. Findings The study reveals that the laser power required to achieve optimal top surface quality increases with the volumetric energy density (VED) levels. A smooth top surface (Sa < 15 µm) or a rough surface with humps at high VEDs (VED > 133.3 J/mm 3 ) can serve as indicators for fully dense bulk samples, while rough top surfaces resulting from melt pool discontinuity correlate with high porosity levels. Under insufficient VED, melt pool discontinuity dominates the top surface. At high VEDs, surface quality improves with increased power as mitigation of melt pool discontinuity, followed by the deterioration with hump formation. Originality/value This study reveals and summarizes the formation mechanism of dominant features on top surface features and offers a potential method to predict the porosity by observing the top surface features with consideration of processing conditions.

Engineering↗
DOE OSTI2025

Resolving Mesoscale Convective Systems: Grid Spacing Sensitivity in the Tropics and Midlatitudes

Abstract Mesoscale convective systems (MCSs) are a critical global water cycle component and drive extreme precipitation events in tropical and midlatitude regions. However, simulating deep convection remains challenging for modern numerical weather and climate models due to the complex interactions of processes from microscales to synoptic scales. Recent models with kilometer‐scale horizontal grid spacings offer notable improvements in simulating deep convection compared to coarser‐resolution models. Still, deficiencies in representing key physical processes, such as entrainment, lead to systematic biases. Additionally, evaluating model outputs using process‐oriented observational data remain difficult. This study presents an ensemble of MCS simulations with spanning the deep convective gray zone ( from 12 km to 125 m) in the Southern Great Plains of the U.S. and the Amazon Basin. Comparing these simulations with Atmospheric Radiation Measurement (ARM) wind profiler observations, we find greater sensitivity in the Amazon Basin compared to the Great Plains. Convective drafts converge structurally at sub‐kilometer scales, but some deficiencies remain. In both regions, simulated up and downdrafts are too deep and extreme downdrafts are not strong enough. Furthermore, Amazonian updrafts are too strong. Overall, we observe higher sensitivity in the tropics, including an artificial buildup in vertical kinetic energy at scales of , suggesting a need for 250 m in this region. Nevertheless, bulk convergence—agreement of storm‐average statistics—is achievable with kilometer‐scale simulations within a 10% error margin with 1 km providing a good balance between accuracy and computational cost.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Confronting the Challenge of Modeling Cloud and Precipitation Microphysics

In the atmosphere, microphysics refers to the microscale processes that affect cloud and precipitation particles and is a key linkage among the various components of Earth’s atmospheric water and energy cycles. The representation of microphysical processes in models continues to pose a major challenge leading to uncertainty in numerical weather forecasts and climate simulations. In this paper, the problem of treating microphysics in models is divided into two parts: i) how to represent the population of cloud and precipitation particles, given the impossibility of simulating all particles individually within a cloud, and ii) uncertainties in the microphysical process rates owing to fundamental gaps in knowledge of cloud physics. The recently-developed Lagrangian particle-based method is advocated as a way to address several conceptual and practical challenges of representing particle populations using traditional bulk and bin microphysics parameterization schemes. For addressing critical gaps in cloud physics knowledge, sustained investment for observational advances from laboratory experiments, new probe development, and next-generation instruments in space is needed. Greater emphasis on laboratory work, which has apparently declined over the past several decades relative to other areas of cloud physics research, is argued to be an essential ingredient for improving process-level understanding. More systematic use of natural cloud and precipitation observations to constrain microphysics schemes is also advocated. Because it is generally difficult to quantify individual microphysical process rates from these observations directly, this presents an inverse problem that can be viewed from the standpoint of Bayesian statistics. Following this idea, a probabilistic framework is proposed that combines elements from statistical and physical modeling. Besides providing rigorous constraint of schemes, there is an added benefit of quantifying uncertainty systematically. Finally, a broader hierarchical approach is proposed to accelerate improvements in microphysics schemes, leveraging the advances described in this paper related to process modeling (using Lagrangian particle-based schemes), laboratory experimentation, cloud and precipitation observations, and statistical methods.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Synthesis and Advanced Characterization of Polymer–Protein Core–Shell Nanoparticles

Enzyme immobilization techniques are widely researched due to their wide range of applications. Polymer–protein core–shell nanoparticles (CSNPs) have emerged as a promising technique for enzyme/protein immobilization via a self-assembly process. Based on the desired application, different sizes and distribution of the polymer–protein CSNPs may be required. This work systematically studies the assembly process of poly(4-vinyl pyridine) and bovine serum albumin CSNPs. Average particle size was controlled by varying the concentrations of each reagent. Particle size and size distributions were monitored by dynamic light scattering, ultra-small-angle X-ray scattering, small-angle X-ray scattering and transmission electron microscopy. Results showed a wide range of CSNPs could be assembled ranging from an average radius as small as 52.3 nm, to particles above 1 µm by adjusting reagent concentrations. In situ X-ray scattering techniques monitored particle assembly as a function of time showing the initial particle growth followed by a decrease in particle size as they reach equilibrium. The results outline a general strategy that can be applied to other CSNP systems to better control particle size and distribution for various applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Barium stars as tracers of s -process nucleosynthesis in AGB stars: II. Using machine learning techniques on 169 stars

Barium (Ba) stars are characterised by an abundance of heavy elements made by the slow neutron capture process (s-process). This peculiar observed signature is due to the mass transfer from a stellar companion, bound in a binary stellar system, to the Ba star observed today. The signature is created when the stellar companion is an asymptotic giant branch (AGB) star. We aim to analyse the abundance pattern of 169 Ba stars using machine learning techniques and the AGB final surface abundances predicted by the FRUITY and Monash stellar models. We developed machine learning algorithms that use the abundance pattern of Ba stars as input to classify the initial mass and metallicity of each Ba star’s companion star using stellar model predictions. We used two algorithms. The first exploits neural networks to recognise patterns, and the second is a nearest-neighbour algorithm that focuses on finding the AGB model that predicts the final surface abundances closest to the observed Ba star values. In the second algorithm, we included the error bars and observational uncertainties in order to find the best-fit model. The classification process was based on the abundances of Fe, Rb, Sr, Zr, Ru, Nd, Ce, Sm, and Eu. We selected these elements by systematically removing s-process elements from our AGB model abundance distributions and identifying the elements whose removal had the biggest positive effect on the classification. We excluded Nb, Y, Mo, and La. Our final classification combined the output of both algorithms to identify an initial mass and metallicity range for each Ba star companion. With our analysis tools, we identified the main properties for 166 of the 169 Ba stars in the stellar sample. The classifications based on both stellar sets of AGB final abundances show similar distributions, with an average initial mass of M = 2.23 M ⊙ and 2.34 M ⊙ and an average [Fe/H] = –0.21 and –0.11, respectively. We investigated why the removal of Nb, Y, Mo, and La improves our classification and identified 43 stars for which the exclusion had the biggest effect. We found that these stars have statistically significant and different abundances for these elements compared to the other Ba stars in our sample. We discuss the possible reasons for these differences in the abundance patterns.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

ZnO/CuO nanostructures anchored over Ni/Cu tubular films via pulse electrodeposition for photocatalytic and antibacterial applications

In this work, we report the fabrication of Ni and Cu tubular substrates and the synthesis of ZnO/CuO nanocomposite on them through the process of pulse electrodeposition. The systematic variation in CuO incorporation in the ZnO matrix and the processing technique were noticed to affect the structural, optical, photocatalytic, and anti-bacterial properties, which are well in accordance with the Field Emission-Scanning Electron Microscope, X-ray Diffraction, Fourier transform Infrared Spectroscopy and UV-Differential reflectance spectroscopy results. The remediation capabilities of the photocatalytic substrates were assessed through the degradation of methylene blue (MB) dye under solar irradiation. Optimized CuO incorporation within the ZnO nanorods resulted in the degradation of a 20 ppm of MB dye solution within 40 min and a higher concentration of 50 ppm within 95 min. The Ni and Cu electroformed tubes as substrates provided not only a reusable supporting frame but also a large surface-area for the growth of ZnO/CuO nanocomposite. The current study also dealt with the anti-bacterial efficacy of the above-mentioned substrates against E.coli. Hence, the Ni and Cu tubular thin film substrates with nanorods of ZnO/CuO composite were explored for the removal of organic as well as biological contaminants from waste water.

36 MATERIALS SCIENCE↗