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

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Identification of microRNAs responsive to arbuscular mycorrhizal fungi in Panicum virgatum (switchgrass)

Background: MicroRNAs (miRNAs) are important post-transcriptional regulators involved in the control of a range of processes, including symbiotic interactions in plants. MiRNA involvement in arbuscular mycorrhizae (AM) symbiosis has been mainly studied in model species, and our study is the first to analyze global miRNA expression in the roots of AM colonized switchgrass ( Panicum virgatum ), an emerging biofuel feedstock. AM symbiosis helps plants gain mineral nutrition from the soil and may enhance switchgrass biomass production on marginal lands. Our goals were to identify miRNAs and their corresponding target genes that are controlling AM symbiosis in switchgrass. Results: Through genome-wide analysis of next-generation miRNA sequencing reads generated from switchgrass roots, we identified 122 mature miRNAs, including 28 novel miRNAs. By comparing miRNA expression profiles of AM-inoculated and control switchgrass roots, we identified 15 AM-responsive miRNAs across lowland accession “Alamo”, upland accession “Dacotah”, and two upland/lowland F 1 hybrids. We used degradome sequencing to identify target genes of the AM-responsive miRNAs revealing targets of miRNAs residing on both K and N subgenomes. Notably, genes involved in copper ion binding were targeted by downregulated miRNAs, while upregulated miRNAs mainly targeted GRAS family transcription factors. Conclusion: Through miRNA analysis and degradome sequencing, we revealed that both upland and lowland switchgrass genotypes as well as upland-lowland hybrids respond to AM by altering miRNA expression. We demonstrated complex GRAS transcription factor regulation by the miR171 family, with some miR171 family members being AM responsive while others remained static. Copper miRNA downregulation was common amongst the genotypes tested and we identified superoxide dismutases and laccases as targets, suggesting that these Cu-miRNAs are likely involved in ROS detoxification and lignin deposition, respectively. Other prominent targets of the Cu miRNAs were blue copper proteins. Overall, the potential effect of AM colonization on lignin deposition pathways in this biofuel crop highlights the importance of considering AM and miRNA in future biofuel crop development strategies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Ethanol tolerance in engineered strains of Clostridium thermocellum

Abstract Clostridium thermocellum is a natively cellulolytic bacterium that is promising candidate for cellulosic biofuel production, and can produce ethanol at high yields (75–80% of theoretical) but the ethanol titers produced thus far are too low for commercial application. In several strains of C. thermocellum engineered for increased ethanol yield, ethanol titer seems to be limited by ethanol tolerance. Previous work to improve ethanol tolerance has focused on the WT organism. In this work, we focused on understanding ethanol tolerance in several engineered strains of C. thermocellum . We observed a tradeoff between ethanol tolerance and production. Adaptation for increased ethanol tolerance decreases ethanol production. Second, we observed a consistent genetic response to ethanol stress involving mutations at the AdhE locus. These mutations typically reduced NADH-linked ADH activity. About half of the ethanol tolerance phenotype could be attributed to the elimination of NADH-linked activity based on a targeted deletion of adhE . Finally, we observed that rich growth medium increases ethanol tolerance, but this effect is eliminated in an adhE deletion strain. Together, these suggest that ethanol inhibits growth and metabolism via a redox-imbalance mechanism. The improved understanding of mechanisms of ethanol tolerance described here lays a foundation for developing strains of C. thermocellum with improved ethanol production.

09 BIOMASS FUELS↗
DOE OSTI2022

End-User Perspectives on Using Quantitative Real-Time PCR and Genomic Sequencing in the Field

Quantitative real-time PCR and genomic sequencing have become mainstays for performing molecular detection of biological threat agents in the field. There are notional assessments of the benefits, disadvantages, and challenges that each of these technologies offers according to findings in the literature. However, direct comparison between these two technologies in the context of field-forward operations is lacking. Most market surveys, whether published in print form or provided online, are directed to product manufacturers who can address their respective specifications and operations. One method for comparing these technologies is surveying end-users who are best suited for discussing operational capabilities, as they have hands-on experience with state-of-the-art molecular detection platforms and protocols. These end-users include operators in military defense and first response, as well as various research scientists in the public sector such as government and service laboratories, private sector, and civil society such as academia and nonprofit organizations performing method development and executing these protocols in the field. Our objective was to initiate a survey specific to end-users and their feedback. We developed a questionnaire that asked respondents to (1) determine what technologies they currently use, (2) identify the settings where the technologies are used, whether lab-based or field-forward, and (3) rate the technologies according to a set list of criteria. Of particular interest are assessments of sensitivity, specificity, reproducibility, scalability, portability, and discovery power. This article summarizes the findings from the end-user perspective, highlighting technical and operational challenges.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Next steps in high-repetition-rate laser development for Thomson scattering

Design of a next generation high-rep-rate laser system is underway, aiming for a maximum rep rate of 100 kHz for 1 ms. This will be a "pulse-burst" laser, which is a type of heat-capacity laser. Heat-capacity laser operation is characterized by a burst of pulses of limited duration, with burst length ≤100 ms and pulse rep rate ≥1 kHz. Waste heat accumulates in the laser rod during the burst. This heat is deposited evenly throughout the rod volume, with very little heat removed during the burst, such that temperature rises evenly across the rod radius. Thus beam distortion due to thermal gradients is small. Heat is removed from the rod after the burst, with typically tens of seconds between bursts. Pulse-burst operation of flashlamp pumped Nd:YAG lasers is a cost-effective route to high-rep-rate capability. Pulse-burst laser systems with "fast burst" rep rates in the range of 10–20 kHz have been built for the Thomson scattering diagnostics on MST, NSTX-U, and LHD. For Thomson scattering diagnostic application, the typical requirements are 1064 nm, 1–2 J/pulse, ≤30 ns FWHM pulse, with a top-hat beam profile. A major requirement for this next generation laser system is flexibility in burst sequence programs, ranging from 1 kHz for 100 ms to 100 kHz for 1 ms, and a variety of scenarios in between so that operation can be tailored to plasma experiment requirements. Flashlamp pumping will be used for this next generation laser because it is inexpensive and flexible. A new switch-regulated flashlamp driver will provide improved flashlamp control at lower cost. Additional design issues such as the optimum flashlamp pumping spectrum and optimum Nd doping will be addressed. The use of commercial off-the-shelf components will be maximized in this laser system so that pulse-burst systems can be developed and built by others for new applications.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Control over Conformational Landscapes of Polypeptoids by Monomer Sequence Patterning

The ability to program chain conformation and structure through control over the monomer sequence of synthetic polymers has broad implications for next-generation material design. While related problems of protein-folding and de novo design have generated accurate predictions of 3D folded chain structures, generalization to synthetic polymers remains intractable due to the requirement of large structural databases and the intrinsically disordered nature of polymer building blocks. In this work, polypeptoids, a class of peptidomimetic synthetic polymers, are utilized to build a general workflow for the study of relationships between monomer sequence and dynamic 3D chain structure in solution. Furthermore, this work demonstrates how control over the monomer sequence can alter the conformational landscape of synthetic polymers to deviate dramatically from classical chain statistics. Specifically, the distribution of end-to-end distances, as measured by double electron-electron resonance spectroscopy in dilute solvent, is systematically skewed towards shorter distances with an increasing number of hydrophobes and further refined by hydrophobe arrangement in amphiphilic polypeptoid chains.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Automated experimental design of safe rampdowns via probabilistic machine learning

Abstract Typically the rampdown phase of a shot consists of a decrease in current and injected power and optionally a change in shape, but there is considerable flexibility in the rate, sequencing, and duration of these changes. On the next generation of tokamaks it is essential that this is done safely as the device could be damaged by the stored thermal and electromagnetic energy present in the plasma. This works presents a procedure for automatically choosing experimental rampdown designs to rapidly converge to an effective rampdown trajectory. This procedure uses probabilistic machine learning methods paired with acquisition functions taken from Bayesian optimization. In a set of 2022 experiments at DIII-D, the rampdown designs produced by our method maintained plasma control down to substantially lower current and energy levels than are typically observed. The actions predicted by the model significantly improved as the model was able to explore over the course of the experimental campaign.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

SIVB's 2024 In Vitro Biology Meeting Proceedings

SIVB's 2024 World Congress on In Vitro Biology took place in Saint Louis, Missouri, from June 8th to 12th, 2024. The conference featured renowned speakers from academic and non-academic institutions who will present recent advancements in critical areas like plant transformation, genome editing, synthetic biology, advanced breeding technologies, cellular agriculture, future food sources, chromosome engineering, epigenetics, artificial intelligence, and machine learning. The Society for In Vitro Biology (SIVB) has always considered the education and professional development of young researchers as an integral component of its mission. The 2024 World Congress program, along with SIVB’s student initiatives, was customized to foster scientific growth and professional development among students and young scientists empowering them in their professional journeys. The recording of the DOE supported "Single Cell RNA Sequencing" workshop was made publicly available at https://youtu.be/A0UnuYwefwg for easy retrieval and reference of all information shared during the live event, thereby increasing accessibility and knowledge transfer. Their are 14 articles in the proceedings and the full list of files is located at https://link.springer.com/journal/11626/volumes-and-issues/60-1/supplement.

10 SYNTHETIC FUELS↗
DOE OSTI2024

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗
DOE OSTI2025

Quantum-enhanced detection of viral cDNA via luminescence resonance energy transfer using upconversion and gold nanoparticles

Abstract The COVID-19 pandemic has profoundly impacted global economies and healthcare systems, revealing critical vulnerabilities in both. In response, our study introduces a sensitive and highly specific detection method for cDNA, leveraging Luminescence Resonance Energy Transfer (LRET) between upconversion nanoparticles (UCNPs) and gold nanoparticles (AuNPs), and achieves a detection limit of 242 fM for SARS-CoV-2 cDNA. This innovative sensing platform utilizes UCNPs conjugated with one primer and AuNPs with another, targeting the 5′ and 3′ ends of the SARS-CoV-2 cDNA, respectively, enabling precise differentiation of mismatched cDNA sequences and significantly improving detection specificity. Through rigorous experimental analysis, we established a quenching efficiency range from 10.4 % to 73.6 %, with an optimal midpoint of 42 %, thereby demonstrating the superior sensitivity of our method. Our work uses SARS-CoV-2 cDNA as a model system to demonstrate the potential of our LRET-based detection method. This proof-of-concept study highlights the adaptability of our platform for future diagnostic applications. Instrumental validation confirms the synthesis and formation of AuNPs, addressing the need for experimental verification of the preparation of nanomaterial. Our comparative analysis with existing SARS-CoV-2 detection methods revealed that our approach provides a low detection limit and high specificity for target cDNA sequences, underscoring its potential for targeted COVID-19 diagnostics. This study demonstrates the superior sensitivity and adaptability of using UCNPs and AuNPs for cDNA detection, offering significant advances in rapid, accessible diagnostic technologies. Our method, characterized by its low detection limit and high precision, represents a critical step forward in developing next-generation biosensors for managing current and future viral outbreaks. By adjusting primer sequences, this platform can be tailored to detect other pathogens, contributing to the enhancement of global healthcare responsiveness and infectious disease control.

Esmaeili, Shahriar [Institute for Quantum Science ↗
DOE OSTI2024

Design and Characterization of a Transcriptional Repression Toolkit for Plants

Regulation of gene expression is essential for all life. Tools to manipulate the gene expression level have therefore proven to be very valuable in efforts to engineer biological systems. However, there are few well-characterized genetic parts that reduce gene expression in plants, commonly known as transcriptional repressors. We characterized the repression activity of a library consisting of repression motifs from approximately 25% of the members of the largest known family of repressors. Combining sequence information with our trans-regulatory function data, we next generated a library of synthetic transcriptional repression motifs with function predicted in advance. After characterizing our synthetic library, we demonstrated not only that many of our synthetic constructs were functional as repressors but also that our advance predictions of repression strength were better than random guesses. Finally, we assessed the functionality of known transcriptional repression motifs from a wide range of eukaryotes. Our study represents the largest plant repressor motif library experimentally characterized to date, providing unique opportunities for tuning transcription in plants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Single-nuclei transcriptome analysis of IgM+ cells isolated from channel catfish (Ictalurus punctatus) spleen

Catfish production is the primary aquaculture sector in the United States, and the key cultured species is channel catfish (Ictalurus punctatus). The major causes of production losses are pathogenic diseases, and the spleen, an important site of adaptive immunity, is implicated in these diseases. To examine the channel catfish immune system, single-nuclei transcriptomes of sorted and captured IgM + cells were produced from adult channel catfish. Three channel catfish (~1 kg) were euthanized, the spleen dissected, and the tissue dissociated. The lymphocytes were isolated using a Ficoll gradient and IgM + cells were then sorted with flow cytometry. The IgM + cells were lysed and single-nuclei libraries generated using a Chromium Next GEM Single Cell 3’ GEM Kit and the Chromium X Instrument (10x Genomics) and sequenced with the Illumina NovaSeq X Plus sequencer. The reads were aligned to theI. punctatusreference assembly (Coco_2.0) using Cell Ranger, and normalization, cluster analysis, and differential gene expression analysis were carried out with Seurat. Across the three samples, approximately 753.5 million reads were generated for 18,686 cells. After filtering, 10,637 cells remained for the cluster analysis. The cluster analysis identified 16 clusters which were classified as B cells (10,276), natural killer-like (NK-like) cells (178), T cells or natural killer cells (45), hematopoietic stem and progenitor cells (HSPC)/megakaryocytes (MK) (66), myeloid/epithelial cells (40), and plasma cells (32). The B cell clusters were further defined as different populations of mature B cells, cycling B cells, and plasma cells. The plasma cells highly expressedighmand we demonstrated that the secreted form of the transcript was largely being expressed by these cells. This atlas provides insight into the gene expression of IgM + immune cells in channel catfish. The atlas is publicly available and could be used garner more important information regarding the gene expression of splenic immune cells.

Immunology↗
DOE OSTI2021

Next-generation yeast-two-hybrid analysis with Y2H-SCORES identifies novel interactors of the MLA immune receptor

Protein-protein interaction networks are one of the most effective representations of cellular behavior. In order to build these models, high-throughput techniques are required. Next-generation interaction screening (NGIS) protocols that combine yeast two-hybrid (Y2H) with deep sequencing are promising approaches to generate interactome networks in any organism. However, challenges remain to mining reliable information from these screens and thus, limit its broader implementation. Here, we present a computational framework, designated Y2H-SCORES, for analyzing high-throughput Y2H screens. Y2H-SCORES considers key aspects of NGIS experimental design and important characteristics of the resulting data that distinguish it from RNA-seq expression datasets. Three quantitative ranking scores were implemented to identify interacting partners, comprising: 1) significant enrichment under selection for positive interactions, 2) degree of interaction specificity among multi-bait comparisons, and 3) selection of in-frame interactors. Using simulation and an empirical dataset, we provide a quantitative assessment to predict interacting partners under a wide range of experimental scenarios, facilitating independent confirmation by one-to-one bait-prey tests. Simulation of Y2H-NGIS enabled us to identify conditions that maximize detection of true interactors, which can be achieved with protocols such as prey library normalization, maintenance of larger culture volumes and replication of experimental treatments. Y2H-SCORES can be implemented in different yeast-based interaction screenings, with an equivalent or superior performance than existing methods. Proof-of-concept was demonstrated by discovery and validation of novel interactions between the barley nucleotide-binding leucine-rich repeat (NLR) immune receptor MLA6, and fourteen proteins, including those that function in signaling, transcriptional regulation, and intracellular trafficking.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Improving Electronic Conductivity of Layered Oxides through the Formation of Two-Dimensional Heterointerface for Intercalation Batteries

Synthetic strategies for the improvement in electronic conductivities and electrochemical stabilities of transition metal oxide cathodes, which are limiting factors in the performance of commercial intercalation batteries, are required for next-generation, high-performance battery systems. Furthermore, the chemical preintercalation approach, consisting of a combined sequence of a sol–gel process, extended aging, and a hydrothermal treatment, is a versatile, wet synthesis technique that allows for the incorporation of a polar species between the layers of transition metal oxides. Here, formation of a layered 2D δ-C x V 2 O 5 · n H 2 O heterostructure occurs via chemical preintercalation of dopamine molecules between bilayers of vanadium oxide followed by the hydrothermal treatment of the precipitate, leading to carbonization of the organic molecules. The presence of carbon layers within the structure has been confirmed via a combined analysis of scanning electron microscopy, X-ray diffraction, thermogravimetric analysis, Raman spectroscopy, X-ray photoelectron spectroscopy, electrochemical impedance spectroscopy, four-probe conductivity measurements, and scanning transmission electron microscopy characterization. 2D δ-C x V 2 O 5 · n H 2 O heterostructure electrodes demonstrated significantly improved electrochemical performance, particularly at higher current densities, in Li-ion cells. The heterostructure electrodes exhibited 75% of the capacity retention when the current was changed from 20 mA g –1 (206 mAh g –1 ) to 300 mA g –1 (155 mAh g –1 ), while the reference δ-V 2 O 5 · n H 2 O electrodes exhibited only 10% capacity retention in the same experiment. Remarkably, 2D δ-C x V 2 O 5 · n H 2 O heterostructure electrodes demonstrated significantly improved capacity retention (94% after 30 cycles) for bilayered vanadium oxide electrodes in Li-ion cells during galvanostatic cycling at 20 mA g –1 . The improved electrochemical performance, in both extended cycling and rate capability studies, of the 2D δ-C x V 2 O 5 · n H 2 O heterostructure electrodes in the Li-ion system is ascribed to the intermittent formation of carbon layers within the bilayered structure, which leads to increased electronic conductivity and improved structural stability of the heterostructure compared to the reference δ-V 2 O 5 · n H 2 O electrodes.

25 ENERGY STORAGE↗
DOE OSTI2024

Powdery mildew effectors AVR A1 and BEC1016 target the ER J‐domain protein Hv ERdj3B required for immunity in barley

Abstract The barley powdery mildew fungus, Blumeria hordei (Bh), secretes hundreds of candidate secreted effector proteins (CSEPs) to facilitate pathogen infection and colonization. One of these, CSEP0008, is directly recognized by the barley nucleotide‐binding leucine‐rich‐repeat (NLR) receptor MLA1 and therefore is designated AVR A1 . Here, we show that AVR A1 and the sequence‐unrelated Bh effector BEC1016 (CSEP0491) suppress immunity in barley. We used yeast two‐hybrid next‐generation interaction screens (Y2H‐NGIS), followed by binary Y2H and in planta protein–protein interactions studies, and identified a common barley target of AVR A1 and BEC1016, the endoplasmic reticulum (ER)‐localized J‐domain protein Hv ERdj3B. Silencing of this ER quality control (ERQC) protein increased Bh penetration. Hv ERdj3B is ER luminal, and we showed using split GFP that AVR A1 and BEC1016 translocate into the ER signal peptide‐independently. Overexpression of the two effectors impeded trafficking of a vacuolar marker through the ER; silencing of Hv ERdj3B also exhibited this same cellular phenotype, coinciding with the effectors targeting this ERQC component. Together, these results suggest that the barley innate immunity, preventing Bh entry into epidermal cells, requires ERQC. Here, the J‐domain protein Hv ERdj3B appears to be essential and can be regulated by AVR A1 and BEC1016. Plant disease resistance often occurs upon direct or indirect recognition of pathogen effectors by host NLR receptors. Previous work has shown that AVR A1 is directly recognized in the cytosol by the immune receptor MLA1. We speculate that the AVR A1 J‐domain target being inside the ER, where it is inapproachable by NLRs, has forced the plant to evolve this challenging direct recognition.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Multi-modal dynamic radiography using short-pulse laser-generated probe beams

Radiography is an important tool for the interrogation of dynamic experiments in the fields of dynamic properties of materials, and in condensed matter, high explosive, and high-energy-density physics. Multi-modal radiography advances the hypothesis that combining the information delivered by multiple radiographic modalities can lead to more constrained (improved) “reconstruction” of the scene than can be obtained from a single probe. We identify four modalities: multi-probe, time sequence, multi-view, and multi-messenger. Multi-probe radiography is a promising candidate for a next-generation dynamic radiographic facility. High-energy X-rays are the most frequently used probe for dynamic radiography, although recent developments show the utility of proton (pRad), electron (eRad), and neutron probe beams. Because each probing species interacts with material in the radiographic scene through quantitatively different mechanisms, each returns independent information about the scene, which can add extra constraints to the reconstruction process. How to conduct detailed, quantitative “co-analysis” of multiple data streams remains an area of active research. Multi-beam, short-pulse, laser-generated probes offer sufficient dose, an appropriate spectrum, and appropriate spatio-temporal resolution to produce high-quality dynamic radiographs. This paper reports on technology development to advance the state of the art of multi-modal/multi-probe radiography and the pursuit of both deterministic and inferential (AI/ML assisted) co-analysis methodologies to produce more constrained reconstructions from multi-modal data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Emerging protein sequencing technologies: proteomics without mass spectrometry?

Liquid chromatography-tandem mass spectrometry (LC-MS/MS) has been a leading method for proteomics for 30 years. Advantages provided by LC-MS/MS are offset by significant disadvantages, including cost. Recently, several non-mass spectrometric methods have emerged, but little information is available about their capacity to analyze the complex mixtures routine for mass spectrometry. Areas Covered: We review recent non-mass-spectrometric methods for sequencing proteins and peptides, including those using nanopores, sequencing by degradation, reverse translation, and short-epitope mapping, with comments on bioinformatics challenges, fundamental limitations, and areas where new technologies will be more or less competitive with LC-MS/MS. In addition to conventional literature searches, instrument vendor websites, patents, webinars, and preprints were also consulted to give a more up-to-date picture. Expert Opinion: Many new technologies are promising. However, demonstrations that they outperform mass spectrometry in terms of peptides and proteins identified have not yet been published, and astute observers note important disadvantages, especially relating to the dynamic range of single-molecule measurements of complex mixtures. Still, even if the performance of emerging methods proves inferior to LC-MS/MS, their low cost could create a different kind of revolution: a dramatic increase in the number of biology laboratories engaging in new forms of proteomics research.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Coupled Roles of Surface Chemistry and Hydrogen-Assisted Cycling in Ruthenium Atomic Layer Deposition on Silicon Oxides

Ruthenium (Ru) is a promising interconnect material for advanced semiconductor technologies due to its favorable scaling characteristics, including a short electron mean free path and strong electromigration resistance. In semiconductor integration, silicon oxide-based dielectrics serve as dominant insulating materials and constitute ubiquitous interfaces for metallization; however, their formation-dependent surface chemistry and its impact on Ru growth remain insufficiently explored. Here, we investigate Ru ALD on native oxide SiO x (N-SiO x ) and thermally grown SiO 2 (T-SiO 2 ) as model substrates using bis(ethylcyclopentadienyl)ruthenium(II) [Ru(EtCp) 2 ] under two distinct reactant-sequence environments: AB-type (Ru(EtCp) 2 /O 2 ) and hydrogenassisted ABC-type (Ru(EtCp) 2 /O 2 /H 2 ). Under the AB-type process, both N-SiO x and T-SiO 2 exhibit pronounced nucleation delay. N-SiO x shows earlier nucleation and higher nucleation density than T-SiO 2 , plausibly attributed to differences in surface hydroxyl populations. Similar temperature-dependent phase evolution is observed on both substrates, with mixed Ru and RuO 2 phases at 250 °C and predominantly metallic Ru at 300 °C accompanied by increased morphological roughening. In contrast, incorporating an H 2 subpulse (ABC-type) mitigates nucleation delay, particularly on hydroxyl-deficient T-SiO 2 , thereby reducing the substratedependent disparity observed under AB cycling. Moreover, RuO 2 formation is suppressed even at 250 °C on both substrates, shifting growth toward more metallic Ru with reduced resistivity (∼20 μΩ·cm at ∼ 20 nm on N-SiO x ). These trends suggest that H 2 influences the surface reaction pathway, contributing to enhanced metallic stabilization and altered early stage growth kinetics. Overall, this work clarifies the coupled roles of substrate chemistry and reactant-sequence design in governing Ru nucleation and early stage film evolution, providing insight relevant to next-generation interconnect integration and future area-selective deposition strategies.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The Nucleosynthetic Yields of Core-collapse Supernovae: Prospects for the Next Generation of Gamma-Ray Astronomy

Though the neutrino-driven convection model for the core-collapse explosion mechanism has received strong support in recent years, there are still many uncertainties in the explosion parameters—such as explosion energy, remnant mass, and end-of-life stellar abundances as initial conditions. Using a broad set of spherically symmetric core-collapse simulations we examine the effects of these key parameters on explosive nucleosynthesis and final explosion yields. The post-bounce temperature and density evolution of zero-age main-sequence 15, 20, and 25 solar mass progenitors are post-processed through the Nucleosynthesis Grid nuclear network to obtain detailed explosive yields. In particular, this study focuses on radio isotopes that are of particular interest to the next generation of gamma-ray astronomical observations: 43 K, 47 Ca, 44 Sc, 47 Sc, 48 V, 48 Cr, 51 Cr, 52 Mn, 59 Fe, 56 Co, 57 Co, and 57 Ni. Furthermore, these nuclides may be key in advancing our understanding of the inner workings of core-collapse supernovae by probing the parameters of the explosion engine. We find that the isotopes that are strong indicators of explosion energy are 43 K, 47 Ca, 44 Sc, 47 Sc, and 59 Fe, those that are dependent on the progenitor structure are 48 V, 51 Cr, and 57 Co, and those that probe neither are 48 Cr, 52 Mn, 57 Ni, and 56 Co. We discuss the prospects of observing these radionuclides in supernova remnants.

79 ASTRONOMY AND ASTROPHYSICS↗