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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 OSTI2021

Recent Advances in Synthesis and Application of Lignin Nanoparticles

The ability to engineer material at its nanoscale has shown great potentials in overcoming significant obstacles in numerous fields. Because of its abundance, biodegradability, renewability, and eco-friendliness nature, lignin has become an ideal precursor for producing nanoscale materials from both research and industrial communities. Nanolignin, also known as colloidal lignin particle (CLP) or lignin nanoparticle (LNP), has received significant interest in recent years and its production and application in numerous fields represent an important aspect of lignin valorization. LNPs could be produced via several techniques including sonication, solvent exchange, and precipitation, which could be divided into wet and dry methods. Applications of LNPs in UV protection, cosmetics, food package, coatings, and drug delivery have been reported in the literature. Despite being extensively studied, LNPs as well as their derived materials with controlled shape and architecture are still largely underexploited. This book chapter mainly covers recent advances in the preparation of LNPs and their use in the novel and advanced applications in different areas.

Meng, Xianzhi↗
DOE OSTI2020

ATOMIC Simulations and Experimental Data for Basalt-like Compounds

This data consists of simulations and experimental measurements of laser-induced breakdown spectroscopy (LIBS). The simulations are produced by ATOMIC, a general purpose plasma modeling and kinetics code that has been designed to compute emission (or absorption) spectra from plasmas [2]. The makeup of the plasma was considered to be divided into some proportion water, some proportion Martian atmosphere (CO2), and some proportion target (from the rock or object impacted by the laser), where these proportions add to 1. Based on expert knowledge, the proportion of water was kept in the range [0.0,0.5] and the proportion of atmosphere was kept in the range [0.02, 0.9]. Our overall suite of simulations contains six sets of simulations that differ in which elements were considered to make up the target. Within each set, we used uniformly drawn temperatures and log mass densities within pre-specified ranges. The temperature range was [0.5,1.5] eV and the log (base 10) mass density range was [-7,-4]. The proportion of water, atmosphere, and target were drawn from a symmetric Dirichlet distribution, but draws in which the propor- tion of water or atmosphere exceeded the pre-specified limits were rejected from the design. Up to eleven constituent elements (Si, Al, Fe, Mg, Ca, O, Ti, Mn, Na, K, P) were considered for the target, as they are the most common elements found in basalt compounds and were used in [1]. For each run, the proportions of the constituent elements making up the target were drawn from a symmetric Dirichlet distribution. We ran 1,350 simulations that included nonzero proportions of all eleven elements. We also ran simulations which excluded some of these elements. In particular, we ran 1,000 simulations that only included nonzero proportions for the six most common elements (Si, Al, Fe, Mg, Ca, O). We also ran five sets, each with 500 simulations, that only included nonzero proportions for five of the six most common elements (but where all sets included O). Thus, we generated a total of 4,850 spectra representing basalt-like compounds in which the target was comprised of oxygen and between four and ten other elements. The ATOMIC code produced spectra over a range of 240nm - 880nm that roughly mimics the range collected by the ChemCam instrument on the Mars rover Curiosity. Each spectra had 32,000 wavelengths split across three spectrometer ranges (to mimic ChemCam). The experimental data, described in [1], measures a prepared basalt sample. All files are kept in directories whose names indicate the set of elements considered for the target with file names numbered to indicate the line in the design files used to produce the simulation. The designs are provided as text files with names indicating their purpose. The experimental data is provided as a CSV file which contains a header with measurement information, followed by a collection of 50 shots across a collection of wavelengths, along with the computed median and mean across shots.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Feed status and skin injury modulate immunopathology, global gene expression, and survival in channel catfish during virulent Aeromonas hydrophila infection

Introduction VirulentAeromonas hydrophilais a major pathogen in channel catfish (Ictalurus punctatus), that causes motileAeromonassepticemia and significant economic losses. We investigated the effect of feeding status and skin integrity on the host immune response, disease survival, and gastrointestinal pathology following a vAh challenge. Methods Using a bath immersion model, channel catfish were divided into four treatment groups: fin clipped and fed (FCF), fin clipped but not fed (FCN), not fin clipped but fed (NCF), and not fin clipped nor fed (NCN) alongside non-challenged control groups The FCF and NCF groups were fed 2 h prior to the challenge, but the FCN and NCN groups were not. Survival analysis, histopathological assessment, and RNA sequencing were conducted across groups at different time intervals throughout the vAh challenge. Results Survival rates were lowest in the FCF and FCN groups (30% and 23% survival, respectively), suggesting that both feeding and skin damage contributed to disease severity. Histopathological analyses revealed more severe intestinal and gastric lesions in fed groups, characterized by epithelial necrosis, hemorrhage, and edema. Transcriptomic analysis among the groups identified significant differentially expressed genes associated with inflammation, apoptosis, and metabolic stress, with notable upregulation of interleukin 1-beta (il-1β), and complement C3 (c3). Gene ontology enrichment highlighted distinct immune activation patterns between fed and unfed groups, with enhanced pathogen recognition and pro-inflammatory responses in unfed fish. Discussion These findings suggest feeding prior to infection may exacerbate disease pathology, potentially by creating a physiological state conducive to facilitate pathogen proliferation and dampened early immune responses, whereas short-term fasting appears to promote early immune activation. This study provides novel insights into the complex interplay between feed status, physical injury, and immune response to vAh infection.

Immunology↗
DOE OSTI2022

Mechanism of tethered agonist-mediated signaling by polycystin-1

Mutations of polycystin-1 (PC1) are the major cause (85% of cases) of autosomal dominant polycystic kidney disease (ADPKD), which is the fourth leading cause of kidney failure. PC1 is thought to function as an atypical G protein-coupled receptor, yet the mechanism by which PC1 regulates G-protein signaling remains poorly understood. A significant portion of ADPKD mutations of PC1 encode a protein with defects in maturation or reduced function that may be amenable to functional rescue. In this work, we have combined complementary biochemical and cellular assay experiments and accelerated molecular simulations, which revealed an allosteric transduction pathway in activation of the PC1 C-terminal fragment. Our findings will facilitate future rational drug design efforts targeting the PC1 signaling function. Polycystin-1 (PC1) is an important unusual G protein-coupled receptor (GPCR) with 11 transmembrane domains, and its mutations account for 85% of cases of autosomal dominant polycystic kidney disease (ADPKD). PC1 shares multiple characteristics with Adhesion GPCRs. These include a GPCR proteolysis site that autocatalytically divides these proteins into extracellular, N-terminal, and membrane-embedded, C-terminal fragments (CTF), and a tethered agonist (TA) within the N-terminal stalk of the CTF that is suggested to activate signaling. However, the mechanism by which a TA can activate PC1 is not known. Here, we have combined functional cellular signaling experiments of PC1 CTF expression constructs encoding wild type, stalkless, and three different ADPKD stalk variants with all-atom Gaussian accelerated molecular dynamics (GaMD) simulations to investigate TA-mediated signaling activation. Correlations of residue motions and free-energy profiles calculated from the GaMD simulations correlated with the differential signaling abilities of wild type and stalk variants of PC1 CTF. They suggested an allosteric mechanism involving residue interactions connecting the stalk, Tetragonal Opening for Polycystins (TOP) domain, and putative pore loop in TA-mediated activation of PC1 CTF. Key interacting residues such as N3074–S3585 and R3848–E4078 predicted from the GaMD simulations were validated by mutagenesis experiments. Together, these complementary analyses have provided insights into a TA-mediated activation mechanism of PC1 CTF signaling, which will be important for future rational drug design targeting PC1.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Survey of Deep Learning and Physics-Based Approaches in Computational Wave Imaging

Computational wave imaging (CWI) extracts hidden structure and physical properties of a volume of material by analyzing wave signals that traverse that volume. Applications include seismic exploration of the Earth’s subsurface, acoustic imaging and nondestructive testing (NDT) in material science, and ultrasound computed tomography (USCT) in medicine. Current approaches for solving CWI problems can be divided into two categories: those rooted in traditional physics and those based on deep learning. Physics-based methods stand out for their ability to provide high-resolution and quantitatively accurate estimates of acoustic properties within the medium. However, they can be computationally intensive and are susceptible to ill-posedness and nonconvexity typical of CWI problems. Machine learning (ML)-based computational methods have recently emerged, offering a different perspective to address these challenges. Diverse scientific communities have independently pursued the integration of deep learning in CWI. This review discusses how contemporary scientific ML techniques, and deep neural networks in particular, have been developed to enhance and integrate with traditional physics-based methods for solving CWI problems. We present a structured framework that consolidates existing research spanning multiple domains, including computational imaging, wave physics, and data science. This study concludes with important lessons learned from existing ML-based methods and identifies technical hurdles and emerging trends through a systematic analysis of the extensive literature on this topic.

42 ENGINEERING↗
DOE OSTI2023

Laboratory-Scale Coal-Derived Graphene Process (Final Report)

The Energy & Environmental Research Center (EERC) conducted a laboratory-scale coal-derived graphene (CDG) project focused on developing a technological process for making graphene from four U.S. domestic coal or coal wastes, including lignite from North Dakota, subbituminous coal from Wyoming, bituminous coal from Utah, and anthracite from Pennsylvania. The project was divided into two performance or budget periods (BPs), with BP1 comprising the up-front laboratory experiments to make graphene materials from coal beginning on May 1, 2020, to April 30, 2022. BP2 was conducted from May 1, 2022, to April 30, 2023, and was focused on analyzing the CDG process economic feasibility and the technical gaps for technological scale-up and commercialization. During this project, a few different coal-derived high-value products have been demonstrated, including graphite, graphene oxide (GO), reduced graphene oxide (rGO), and graphene quantum dots (GQDs). A new graphite microstructure was discovered and named “croissant graphite” because of the exterior morphological and textural resemblance to croissant food items sold in commercial groceries stores. The new graphite structure and the associated preparation from coal or coal waste feedstocks has been the subject of a U.S. patent application. The systematic experimental processes involving coal cleaning, upgrading, and conversion to high-value carbon products culminated into a developed upgraded coal-to-products (UCP) technology that is being pursued for potential fast-track commercialization, if funding is available. It is envisioned that commercialization of the UCP technology would increase consumption of U.S. domestic coals or coal wastes to make environmentally sustainable high-value products for the electronics industry, high-energy-storage applications, and clean energy technologies such as electric vehicle (EV) lithium-ion batteries (LIBs), for which graphite has become a critical mineral commodity. Croissant graphite microstructures, when observed by field emission scanning electron microscopy (FESEM), display wavy surface morphology and often grow from a base that is made of graphitized particles with honeycomb-like layers, which are believed to be graphene layers. While more studies are needed to fully ascertain the mechanisms of the croissant graphite microstructure formation, it is postulated that their growth may begin from curling of the graphene sheets into ribbon-like structures, and continuous growth and densification of the ribbon-like structures forms croissant microstructures. Additional studies are ongoing to evaluate the electrochemical performance of croissant graphite for LIB applications and to determine the experimental conditions necessary to tune on/off croissant formation so that it can be either optimized or suppressed depending on performance evaluation results. In addition to the discovery of croissant graphite, the graphitization process from the four coal ranks in general was successful. X-ray diffraction (XRD) analysis showed that the degree of graphitization (DoG) ranged from 12% to 80% in an early sample set, and further optimization on lignite coal produces a DoG of about 92%, which was spectacular to see as lignite is the lowest-rank coal. Thus, it is expected that the graphitization performance for higher-rank coals will be similar or better when optimized as well. The coal-derived graphite was used to make GO and rGO. Analytical characterization, e.g., by methods such as Raman spectroscopy, XRD, Fourier transform infrared (FTIR) spectroscopy and FESEM, showed that the sequence of converting the coal to graphite, exfoliating it to GO, and then chemically reducing the GO to rGO was successful. Although coal naturally contains aromatic compounds and some relatively small-sized condensed aromatic units, it does not contain graphene sheets. In the UCP process, the aromatic domains in the coals, particularly low-rank coals, are concentrated and condensed further into graphene sheets, which are ordered into a 3D stack during graphitization. The synthesized graphite is then unpacked by methods such as exfoliation to various graphene products. GQDs were synthesized from all four coal types, and their optical properties were demonstrated to be tunable by the coal precursor preprocessing treatments. In all four coal types, enhanced optical properties were observed for the produced GDQs with incremental improvements made to the coal precursors. GQDs produced from raw coal samples displayed lower ultraviolet–visible (UV–Vis) spectroscopy absorbance intensity compared to those obtained from cleaned and upgraded coal residues. The photoluminescence (PL) intensities also varied with pretreatment conditions and with the concentration of GQDs in aqueous solutions. GQDs obtained from anthracite show longer emission wavelengths and can be excited by visible light as opposed to GQDs derived from the other coal ranks. UV fluorescence 3D maps and spectra revealed that the emission wavelength at which the GQDs solutions display the highest intensity was slightly redshifted based on the coal precursor pretreatments. In low-rank coal (lignite and subbituminous) samples, two clusters were observed in the maps for GQDs, which may suggest that there are potentially two types of fluorophores in solution or two main size populations. The ability to tune the properties of GQDs based on processing methods can be exploited to make GQDs for various optical display or optoelectronics applications. The results also highlight the importance of removing coal-borne impurities to improve the quality of the coal precursor for preparation of graphene products. Coal and/or coal wastes preprocessing methods were developed and applied to clean and upgrade the coal precursors prior to graphitization and subsequent conversion to graphene products. The preprocessing methods involve high specific-gravity separations, mineral acid cleaning (no hydrofluoric acid), and subsequent upgrading by reducing the coal-borne heteroatom (nitrogen, sulfur, and oxygen) content using proprietary chemical agents. Analytical characterization revealed that the preprocessing steps were successful, with ash reductions that range from 38% to 80% and residual ash content that was below the 5 wt% initial target. Based on proximate and ultimate analysis, the heteroatom reduction reactions produced upgraded coal residues with the oxygen content reduced by 8% to 24%, with additional reductions in the nitrogen and sulfur contents. An initial assessment of the waste streams from the UCP process shows very small to negligible environmental impact due to CO 2 , NO x , and SO x because most process steps are performed under inert atmosphere with argon. Consequently, reactive oxygen environments that tend to create these species are avoided. The inorganic and potentially hazardous species are released into aqueous waste streams that are easy to handle for proper disposal. The liquid waste streams were found to contain low-level concentrations of rare-earth elements (REEs), which could be concentrated and recovered as value-added by-products. Additionally, the volatile and gaseous fractions from carbonization and heat treatment contain useful organic compounds that can also be recovered as potential valuable by-products. Thus, the UCP technology is considered an environmentally sustainable and promising emerging technology for making high-value products from coal and coal wastes, with potential additional value-added by-products. Analysis of potential markets for the coal-derived carbon products shows a strong demand in both niche market sectors and across a wide variety of other industrial sectors. Graphite is currently considered a critical mineral commodity that has a large and growing demand in the LIB industry for EV applications. Based on data from Fortune Business Insights (2022) and Marketwatch (2023) reports, the average global graphite market is projected to reach about 33 billion by 2028, growing at a compound annual growth rate (CAGR) of about 7%, with much of this growth expected to be in the LIB industry. GO and rGO have strong market potentials in various application areas, such as coatings for anticorrosion, anti-icing, and antimicrobial protection, thermal barriers, wear resistance, sensors, additive manufacturing such as 3D inks, and others. GQDs are the emerging key player in the bioimaging, photovoltaics, and light-emitting diodes (LEDs) applications, with the potential to replace traditional semiconductor quantum dots (SQDs), which are based on metallic systems that are more toxic and more expensive. Biomedical applications of GQDs are becoming more attractive because of low to no toxicity and extremely low cost compared to SQDs. The major challenges for scale-up and commercialization of coal-derived carbon products such as graphene vary from the inherent attributes of graphene itself to reluctance to accept graphene in new manufacturing processes because of the uncertainty of the unknown. The 2D nature of graphene materials with a thickness of one atom presents significant challenges to proper handling/processing, and process scale-up becomes difficult because it requires high-end, expensive equipment, even for routine handling and analysis for quality assurance and control. Pristine graphene can also be extremely difficult to work into other matrices, thus hindering downstream processibility, especially at large scale. Currently, the cost of graphene and graphene products is still high and presents an economic risk that tends to slow down investment in scaling up emerging technologies. The lack of a standard for graphene materials for quality assurance and quality control poses a great challenge not only for the markets but also for commercialization efforts. A first-look economic feasibility analysis of the UCP technology provided valuable information that suggests the UCP process would be feasible, especially when it is scaled to a pilot scale and could be more competitive at the full scale. Graphitization was found to be the most energy-consuming and most capital-intensive step in the overall process. In small laboratory- and bench-scale experiments, labor is a significant contributor to the total process costs. Although these energy, capital, and labor constraints contribute to a higher selling price for the product, a preliminary economic model suggests that the process would be feasible at large scale when the process is fully integrated, optimized, and automated.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

N-Doped Graphene (N-G)/MOF(ZIF-8)-Based/Derived Materials for Electrochemical Energy Applications: Synthesis, Characteristics, and Functionality

In recent years, graphene-type materials originating from metal–organic frameworks (MOFs) or integrated with MOFs have exhibited notable performances across various applications. However, a comprehensive understanding of these complex materials and their functionalities remains obscure. While some studies have reviewed graphene/MOF composites from different perspectives, due to their structural–functional intricacies, it is crucial to conduct more in-depth reviews focusing on specific sets of graphene/MOF composites designed for particular applications. In this review, we thoroughly investigate the syntheses, characteristics, and performances of N-G/MOF(ZIF-8)-based/derived materials employed in electrochemical energy conversion and storage systems. Special attention is given to realizing their fundamental functionalities. The discussions are divided into three segments based on the application of N-G/ZIF-8-based/derived materials as electrode materials for batteries, electrodes for electrochemical capacitors, and electrocatalysts. As electrodes for batteries, N-G/MOF(ZIF-8) materials can mitigate issues like an electrode volume expansion for Li-ion batteries and the ‘shuttle effect’ for Li-S batteries. As electrodes for electrochemical capacitors, these materials can considerably improve the ion transfer rate and electronic conductivity, thereby enhancing the specific capacitance while maintaining the structural stability. Also, it was observed that these materials could occasionally outperform standard platinum-based catalysts for the electrochemical oxygen reduction reaction (ORR). The reported electrochemical performances and structural parameters of these materials were carefully tabulated in uniform units and scales. Through a critical analysis of the present synthesis trends, characteristics, and functionalities of these materials, specific aspects were identified that required further exploration to fully utilize their inherent capabilities.

Electrochemistry↗
DOE OSTI2024

Neuroinflammation is dependent on sex and ovarian hormone presence following acute woodsmoke exposure

Woodsmoke (WS) exposure is associated with significant health-related sequelae. Different populations can potentially exhibit varying susceptibility, based on endocrine phenotypes, to WS and investigating neurological impacts following inhaled WS is a growing area of research. In this study, a whole-body inhalation chamber was used to expose both male and female C57BL/6 mice (n = 8 per group) to either control filtered air (FA) or acute WS (0.861 ± 0.210 mg/m 3 ) for 4 h/d for 2 days. Neuroinflammatory and lipid-based biological markers were then assessed. In a second set of studies, female mice were divided into two groups: one group was ovariectomized (OVX) to simulate an ovarian hormone-deficient state (surgical menopause), and the other underwent Sham surgery as controls, to mechanistically assess the impact of ovarian hormone presence on neuroinflammation following FA and acute WS exposure to simulate an acute wildfire episode. There was a statistically significant impact of sex (P ≤ 0.05) and statistically significant interactions between sex and treatment in IL-1β, CXCL-1, TGF-β, and IL-6 brain relative gene expression. Hippocampal and cortex genes also exhibited significant changes in acute WS-exposed Sham and OVX mice, particularly in TGF-β (hippocampus) and CCL-2 and CXCL-1 (cortex). Cortex GFAP optical density (OD) showed a notable elevation in male mice exposed to acute WS, compared to the control FA. Sham and OVX females demonstrated differential GFAP expression, depending on brain region. Overall, targeted lipidomics in phosphatidylcholine (PC) and phosphatidylethanolamine (PE) serum and brain lipids demonstrated more significant changes between control FA and acute WS exposure in female mice, compared to males. In summary, male and female mice show distinct neuroinflammatory markers in response to acute WS exposure. Furthermore, ovarian hormone deficiency may impact the neuroinflammatory response following an acute WS event.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Galaxy Zoo: kinematics of strongly and weakly barred galaxies

ABSTRACT We study the bar pattern speeds and corotation radii of 225 barred galaxies, using integral field unit data from MaNGA and the Tremaine–Weinberg method. Our sample, which is divided between strongly and weakly barred galaxies identified via Galaxy Zoo, is the largest that this method has been applied to. We find lower pattern speeds for strongly barred galaxies than for weakly barred galaxies. As simulations show that the pattern speed decreases as the bar exchanges angular momentum with its host, these results suggest that strong bars are more evolved than weak bars. Interestingly, the corotation radius is not different between weakly and strongly barred galaxies, despite being proportional to bar length. We also find that the corotation radius is significantly different between quenching and star-forming galaxies. Additionally, we find that strongly barred galaxies have significantly lower values for $\mathcal {R}$, the ratio between the corotation radius and the bar radius, than weakly barred galaxies, despite a big overlap in both distributions. This ratio classifies bars into ultrafast bars ($\mathcal {R} \lt $ 1.0; 11 per cent of our sample), fast bars (1.0 $\lt \mathcal {R} \lt $ 1.4; 27 per cent), and slow bars ($\mathcal {R} \gt $ 1.4; 62 per cent). Simulations show that $\mathcal {R}$ is correlated with the bar formation mechanism, so our results suggest that strong bars are more likely to be formed by different mechanisms than weak bars. Finally, we find a lower fraction of ultrafast bars than most other studies, which decreases the recently claimed tension with Lambda cold dark matter. However, the median value of $\mathcal {R}$ is still lower than what is predicted by simulations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Validation of Stage N3 of the Eighth Edition AJCC Staging System for Nasopharyngeal Carcinoma

Objectives To validate stage nodal (N)3 of the 8th edition American Joint Committee on Cancer (AJCC) staging system for nasopharyngeal carcinoma (NPC). Methods This retrospective cohort study extracted NPC patients from the Surveillance, Epidemiology, and End Results database between 2004 and 2016. Pathologically confirmed patients with complete data of level IV, N3a, and N3b lymph node metastasis were investigated. The included patients were divided into level IV, N3a, and N3b groups. Five‐year overall survival (OS) and cancer‐specific survival (CSS) were compared among the three groups. Results A total of 693 patients were included: 285 (41.13%) patients in the level IV group, 124 (17.89%) patients in the N3a group, and 284 (40.98%) patients in the N3b group. The 5‐year OS (57.1%, 55.0%, and 55.2%) and CSS (64.4%, 63.5%, and 64.4%) were not different among the level IV, N3a, and N3b groups. Multivariate regression analysis revealed that N stage was not an independent prognostic factor for OS (hazard ratio [HR] = 1.03, 95% confidence interval [CI]: 0.91–1.17; P = .65) or CSS (HR = 1.03, 95% CI: 0.89–1.19; P = .70). Conclusion Stage N3 of the 8th edition AJCC staging system for NPC is reasonable. Level of Evidence III Laryngoscope , 131:535–540, 2021

Pan, Xin‐Bin↗
DOE OSTI2025

An Overview of the Molten Salt Thermal Properties Database–Thermophysical, Version 4.0 (MSTDB-TP V.4.0)

A central repository of thermophysical and thermochemical properties of molten salt compositions of relevance to molten salt reactors (MSRs) is vital in supporting the broad community of MSR developers, who are at various stages of developing and deploying their reactor designs. In general, these MSR designs differ significantly from developer to developer (e.g., with respect to the hardness of the neutron spectra, level of fissile loading, target multicomponent temperatures and power levels, and moderating capabilities). Therefore, the fuel and coolant salts being considered vary greatly: they may be chlorides or fluorides, they utilize different actinides at different ratios, and the cations in the melt are selected based on perceived advantages and disadvantages. Considering the general need for thermal properties, and the vastness of the array of potential candidate salt mixtures, the Molten Salt Thermal Properties Database (MSTDB) was initiated in 2018 with the goal of providing thermophysical and thermochemical characterization of key molten salt compounds and mixtures across their temperature and compositional domains. The MSTDB is thus divided into the thermophysical arm (MSTDB-TP) and the thermochemical arm (MSTDB-TC). The MSTDB is an effort funded by the Department of Energy, Office of Nuclear Energy (DOE-NE) Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, and the MSR Campaign. This report provides an overview of the MSTDB-TP v4.0 in terms of the data contained within, the state of the tools used to access the data, the availability of predictive models that leverage the raw data in the database, the preliminary status of developmental efforts that are currently underway, and an account of future goals for MSTDB-TP. The primary goal for the update from MSTDB-TP v.3.1 to v4.0 was the incorporation of surface tension data into the database; this property is important for thermal hydraulics modeling and species transport in other tools that have been developed under the NEAMS program. A breakdown of the surface tension data that have been added into MSTDB-TP v4.0 is provided herein, and the manner in which the quality of the data has been assessed is also documented. For MSTDB-TP v4.0, newly published thermophysical property data—primarily from collaborative experimental efforts under the MSR Campaign—have been incorporated into the database, and the resulting expansion is documented here. Because of the size to which MSTDB-TP has grown, the raw data format has now been recast into JavaScript Object Notation (JSON) format for easier connection with the MSTDB-TP application programming interface (API). Saline; the pre-existing comma-separated value (CSV) format has been deprecated but is still maintained, accessible, and up to date. As a final effort in packaging the MSTDB-TP v4.0 update, the graphical user interface (GUI) for MSTDB has been updated to allow full accessibility to the density and viscosity predictive models, which are based on Redlich-Kister expansions of MSTDB-TP raw data. Some other major aspects of this report, in terms of preliminary and future work, include: (1) documentation of the formalism and preliminary testing of a kinetic theory model that may act as a predictive model for thermal conductivity; (2) documentation of the candidate predictive models that may be considered in the future for surface tension, making use of the surface tension data now in MSTDB-TP v4.0; (3) a preliminary account of a data collection process that will enable the filling of additional gaps within MSTDB-TP, namely with data which have been collected computationally (e.g., through ab initio molecular dynamics).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Study of impacts of two types of cellular aging on the yeast bud morphogenesis

Understanding the mechanisms of the cellular aging processes is crucial for attempting to extend organismal lifespan and for studying age-related degenerative diseases. Yeast cells divide through budding, providing a classical biological model for studying cellular aging. With their powerful genetics, relatively short cell cycle, and well-established signaling pathways also found in animals, yeast cells offer valuable insights into the aging process. Recent experiments suggested the existence of two aging modes in yeast characterized by nucleolar and mitochondrial declines, respectively. By analyzing experimental data, this study shows that cells evolving into those two aging modes behave differently when they are young. While buds grow linearly in both modes, cells that consistently generate spherical buds throughout their lifespan demonstrate greater efficacy in controlling bud size and growth rate at young ages. A three-dimensional multiscale chemical-mechanical model was developed and used to suggest and test hypothesized impacts of aging on bud morphogenesis. Experimentally calibrated model simulations showed that during the early stage of budding, tubular bud shape in one aging mode could be generated by locally inserting new materials at the bud tip, a process guided by the polarized Cdc42 signal. Furthermore, the aspect ratio of the tubular bud could be stabilized during the late stage as observed in experiments in this work. The model simulation results suggest that the localization of new cell surface material insertion, regulated by chemical signal polarization, could be weakened due to cellular aging in yeast and other cell types, leading to the change and stabilization of the bud aspect ratio.

Tsai, Kevin↗
DOE OSTI2026

ZTF SN Ia DR2 follow-up: Exploring the origin of the Type Ia supernova host galaxy step through Si II velocities

The relation between Type Ia supernovae (SNe Ia) and the stellar masses of their host galaxy is well documented. In particular, Hubble residuals display a distinct luminosity shift based on host mass. This is known as the mass step. This effect is widely used as an additional correction factor in the standardisation of SN Ia luminosities. We investigate the Hubble residuals and the mass step of normal SNe Ia in the context of Si IIλ6355 velocities based on 277 normal SNe Ia that are near their peak in the second data release (DR2) of the Zwicky Transient Facility (ZTF). We divided the sample into high-velocity (HV) and normal-velocity (NV) SNe Ia, separated at 12,000 km s −1 . This produced a sample of 70 HV and 207 NV objects. We then explored potential environment- and/or progenitor-related effects by investigating the Si IIλ6355 velocities with parameters such as the light-curve stretch x 1 , the colour c, and the host galaxy properties. Although we only find a marginal difference between the Hubble residuals of HV and NV SNe Ia, the NV mass step is 0.149 ± 0.024 mag (6.3σ). The HV mass step is smaller, 0.046 ± 0.041 mag (1.1σ), and is consistent with zero. The difference between the NV and HV mass steps is modest, at ∼2.2σ. Moreover, the clearest subtype difference appears for SNe in central regions (d DLR < 1), where NV SNe Ia show a large mass step, whereas HV SNe Ia are consistent with no step, yielding a difference of 3.1–3.6σ between NV and HV SNe Ia. We observe a host-colour step for both subtypes. NV SNe Ia show a step of 0.142 ± 0.024 mag (5.9σ), while HV SNe Ia show a step of 0.158 ± 0.042 mag (3.8σ), where the HV SNe Ia step appears to be larger, but the significance is lower because the sample size is smaller. Overall, the NV and HV colour steps are statistically consistent. HV SNe Ia also show modest (∼2.5–3σ) steps in certain subsets, such as those in outer regions (d DLR > 1), whereas NV SNe display stronger environmental trends. Our results indicate that NV SNe Ia appear to be more environmentally sensitive, particularly in central likely metal-rich and older regions, while HV SNe Ia show weaker and subset-dependent trends. This suggests that applying a universal mass-step correction might introduce biases, and that incorporating refined classifications and/or environment-dependent factors, such as the location within the host, might improve future cosmological analyses beyond the standard x 1 and c cuts.

supernovae: general↗
DOE OSTI2022

[Retracted] Research on Application Experience Design of Ice and Snow Sports Equipment Based on Bee Colony Model

Sports equipment is the key to the smooth development of ice and snow sports. With the rapid development of social economy and the improvement of people’s living standards, the demand for ice and snow sports equipment is increasing day by day. This article presents an improved method based on the chaos theory and the bee colony algorithm to quantify the application experience design of ice and snow sports equipment and reduce the influence of uncertain factors on the design results. First, the chaos theory can establish the dataset of application experience design and analyze the discreteness of the set. According to the bee colony algorithm, the dataset is divided into several groups, and each group obtains the best application experience design by using the design optimization strategy. Finally, the results are mixed to obtain the final experience design results. Through MATLAB simulation analysis and verification, the improved bee colony model can improve the accuracy of application experience design of ice and snow sports equipment in an uncertain environment, shorten the overall design time, and meet the requirements of application experience design of different ice and snow sports equipment. Therefore, the model proposed in this paper is suitable for the application experience design of ice and snow sports equipment.

Li, Yuanjing (ORCID:000000018276647X)↗
DOE OSTI2020

A simple model to scope out parameter space for indirect drive designs on NIF

In this work, we present a simple model to scope out parameter space for indirect-drive, inertial confinement fusion designs for the National Ignition Facility laser. Because the parameter space is large, simple models can be used to identify regions of parameter space for further study with more sophisticated models and experiments. We include a model for Hohlraum radiation drive and symmetry—both based on empirical scalings from the data. The model for radiation drive is based on assuming that the high atomic number (Z) Hohlraum wall dominates the energy balance during the high power, peak of the pulse (≳ 300 TW). We find that the time-dependent radiation drive flux can be described by the running integral of the laser energy divided by the Hohlraum area multiplied by constant slopes in two distinct time periods. The first period is when the laser power rises rapidly, so the radiation temperature increases due to changes in laser power and wall albedo. The second period is during peak power—here, the laser power is typically held constant—so, the radiation temperature increases only due to changes in the wall albedo. This model is applied to several NIF designs with different Hohlraum sizes, laser pulse length durations, and peak powers and energies. Drive and symmetry models can be combined to find regions of parameter space that have high capsule absorbed energy while maintaining a symmetric implosion. We propose a new metric for evaluating designs based on minimizing the radius at which the maximum implosion kinetic energy is achieved.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

The pectin puzzle: Decoding the fine structure of rhamnogalacturonan-I (RG-I) in Arabidopsis thaliana uncovers new pectin features

Pectin is generally divided into four distinct structural categories, namely homogalacturonan, xylogalacturonan, rhamnogalacturonan I (RG-I) and rhamnogalacturonan II. While much of the structural diversity of homogalacturonan, xylogalacturonan and rhamnogalacturonan II has been elucidated, the structural features of RG-I are less well understood. In this work, we employed multiple complementary analytical techniques to present a detailed structural analysis of RG-I in the model species Arabidopsis thaliana . Starting with highly purified RG-I from different Arabidopsis tissues, we employed comparative linkage and nuclear magnetic resonance analysis along with mass spectrometry analysis of enzymatically digested RG-I oligosaccharides. Besides the presence of the canonical α-1,5-arabinan, β-1,4-galactan, β-1,6-galactan and arabinogalactan RG-I side chains of varying lengths, we show that a large portion of the β-1,6-galactan is terminated by either 4-O-methyl β-glucuronic acid (GlcA) residues or, to a smaller degree, β-GlcA that lacks the Me-ether group. Importantly, O-acetylation of RG-I GalA residues is a minor modification while 10 % of the backbone Rha residues are 3-O-acetylated, and most of the acetylated Rha is additionally branched with β-galactose substituents. Taken together, the combined results of these different analytical techniques present the most comprehensive structural overview of Arabidopsis thaliana RG-I to date.

25 ENERGY STORAGE↗
DOE OSTI2022

A Scalable Pipeline for Gigapixel Whole Slide Imaging Analysis on Leadership Class HPC Systems

Whole Slide Imaging (WSI) captures microscopic details of a patient's histopathological features at multiple res-olutions organized across different levels. Images produced by WSI are gigapixel-sized, and saving a single image in memory requires a few gigabytes which is scarce since a complicated model occupies tens of gigabytes. Performing a simple met-ric operation on these large images is also expensive. High-performance computing (HPC) can help us quickly analyze such large images using distributed training of complex deep learning models. One popular approach in analyzing these images is to divide a WSI image into smaller tiles (patches) and then train a simpler model with these reduced-sized but large numbers of patches. However, we need to solve three pre-processing challenges efficiently for pursuing this patch-based approach. 1) Creating small patches from a high-resolution image can result in a high number (hundreds of thousands per image) of patches. Storing and processing these images can be challenging due to a large number of I/O and arithmetic operations. To reduce I/Oand memory accesses, an optimal balance between the size and number of patches must exist to reduce I/O and memory accesses. 2) WSI images may have tiny annotated regions for cancer tissue and a significant portion with normal and fatty tissues; correct patch sampling should avoid dataset imbalance. 3) storing and retrieving many patches to and from disk storage might incur I/O latency while training a deep learning model. An efficient distributed data loader should reduce I/O latency during the training and inference steps. This paper explores these three challenges and provides empirical and algorithmic solutions deployed on the Summit supercomputer hosted at the Oak Ridge Leadership Computing Facility.

Dash, Sajal↗