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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 91 records · Page 5

Exogenous Hemin alleviated cadmium stress in maize (Zea mays L.) by enhancing leaf photosynthesis, AsA-GSH cycle and polyamine metabolism

Cadmium (Cd) stress is one of the principal abiotic stresses that inhibit maize growth. The research was to explore (hemin chloride) Hemin (100 μmol L −1 ) on photosynthesis, ascorbic acid (AsA)-glutathione (GSH) cycle system, and polyamine metabolism of maize under Cd stress (85 mg L −1 ) using nutrient solution hydroponics, with Tiannong 9 (Cd tolerant) and Fenghe 6 (Cd sensitive) as experimental materials. The results showed that Hemin can increase leaf photosynthetic pigment content and ameliorate the ratio of Chlorophyll a/chlorophyll b ( Chla / Chlb ) under Cd stress. The values of ribose 1, 5-diphosphate carboxylase/oxygenase (RuBPcase) and phosphoenolpyruvate carboxylase (PEPCase), and total xanthophyll cycle pool [(violoxanthin (V), antiflavin (A) and zeaxanthin (Z)] increased, which enhancing xanthophyll cycle (DEPS) de-epoxidation, and alleviating stomatal and non-stomatal limitation of leaf photosynthesis. Hemin significantly increased net photosynthetic rate ( P n ), stomatal conductance ( g s ), transpiration rate ( T r ), photochemical quenching coefficient ( qP ), PSII maximum photochemical efficiency ( F v /F m ), and electron transfer rate ( ETR ), which contributed to the improvement of the PSII photosynthetic system. Compared with Cd stress, Hemin can reduce thiobartolic acid reactant (TBARS) content, superoxide anion radical (O 2 − ) production rate, hydrogen peroxide (H 2 O 2 ) accumulation, and the extent of electrolyte leakage (EL); decreased the level of malondialdehyde (MDA) content and increased the activities of superoxide dismutase (SOD), peroxidase (POD) and catalase (CAT); slowed the decrease in dehydroascorbic acid reductase (DHAR) and monodehydroascorbate reductase (MDHAR) activity and the increase in glutathione reductase (GR) and ascorbate peroxidase (APX) activity in leaves; promoted the increase in AsA and GSH content, decreased dehydroascorbic acid (DHA) and oxidized glutathione (GSSG), and increased AsA/DHA and GSH/GSSG ratios under Cd stress. Hemin promoted the increase of conjugated and bound polyamine content, and the conversion process speed of free putrescine (Put) to free spermine (Spm) and spermidine (Spd) in maize; decreased polyamine oxidase (PAO) activity and increased diamine oxidase (DAO), arginine decarboxylase (ADC), ornithine decarboxylase (ODC) and S-adenosylmethionine decarboxylase (SAMDC) enzyme activities in leaves under Cd stress.

Piao, Lin↗

Screening Cu-Zeolites for Methane Activation Using Curriculum-Based Training

Machine learning (ML), when used synergistically with atomistic simulations, has recently emerged as a powerful tool for accelerated catalyst discovery. However, the application of these techniques has been limited by the lack of interpretable and transferable ML models. In this work, we propose a curriculum-based training (CBT) philosophy to systematically develop reactive machine learning potentials (rMLPs) for high-throughput screening of zeolite catalysts. Our CBT approach combines several different types of calculations to gradually teach the ML model about the relevant regions of the reactive potential energy surface. The resulting rMLPs are accurate, transferable, and interpretable. We further demonstrate the effectiveness of this approach by exhaustively screening thousands of [CuOCu] 2+ sites across hundreds of Cu-zeolites for the industrially relevant methane activation reaction. Specifically, this large-scale analysis of the entire International Zeolite Association (IZA) database identifies a set of previously unexplored zeolites (i.e., MEI, ATN, EWO, and CAS) that show the highest ensemble-averaged rates for [CuOCu] 2+ -catalyzed methane activation. We believe that this CBT philosophy can be generally applied to other zeolite-catalyzed reactions and, subsequently, to other types of heterogeneous catalysts. Thus, this represents an important step toward overcoming the long-standing barriers within the computational heterogeneous catalysis community.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Enhanced Menshutkin S N 2 Reactivity in Mesoporous Silica: The Influence of Surface Catalysis and Confinement

A significant enhancement in the Menshutkin S N 2 reaction between 1-methylimidazole (MeIm) and methyl thiocyanate (MeSCN) is observed when the reaction is confined in the nanoscale silica pores of MCM41 and SBA15. The experiments in the silica pores are conducted without surrounding bulk reaction mixture. The influences of temperature, pore radius, and surface chemistry on the kinetics of the confined reaction are analyzed with time-dependent infrared spectroscopy, molecular dynamics simulations, and ab initio calculations. The rate constant of the pseudo-first order reaction increases with decreasing pore size, and the activation energy is found to decrease by 5.6 kJ/mol in the smallest pore studied (2.8 nm) relative to the bulk reaction. The rate constant dependence on pore size is accurately described by a two-state model in which molecules within the 4.6 Å interfacial layer experience a 2.4-fold rate constant increase relative to those reacting at the bulk rate further away from the interface. The removal of polar silanol groups from the silica surface via passivation with trimethylsilyl chloride results in bulk-like kinetics despite a reduction in the pore diameter, demonstrating the role of silanols as catalytic sites. Here, electronic structure calculations of the energy profile on a model silica surface confirm that silanol groups, particularly those of the vicinal type, can reduce the activation energy and reaction endothermicity through the donation of hydrogen bonds to the reactant, transition state, and product complexes.

36 MATERIALS SCIENCE↗

Editorial special issue: Advancing foundational sun-induced chlorophyll fluorescence science

The first research on the possibilities offered by chlorophyll-a fluorescence to track the daily course of CO 2 assimilation by leaves dates back to the last century (Kautsky and Hirsch, 1931). In the second half of the XXth Century, the development of the field of active fluorescence, which relies mainly on the pulse amplitude modulation (PAM) fluorimetry technique, allowed the unraveling of the relationship between the yield of chlorophyll-a fluorescence and photochemistry (linear electron transport), which is modulated by a third process known as non-photochemical quenching (Genty et al., 1989). Since then, active fluorescence has been regularly used in ecophysiology, forestry, and crop sciences to understand the plant response to stress (Schreiber, 2004). Since the beginning of the 2000s, the development of portable field spectrometers allows for measuring passive sun-induced fluorescence (SIF) at strong solar or telluric absorption features, which do not rely on the use of artificial excitation light (e.g., Meroni and Colombo, 2006; Meroni et al., 2009; Perez-Priego et al., 2005). Since then, the field has rapidly evolved, and now fluorescence is measurable with automated field spectrometers in the field (Grossmann et al., 2018; Gu et al., 2019b; Rossini et al., 2010), airborne platforms (Rascher et al., 2015; Zarco-Tejada et al., 2000), and satellites (Guanter et al., 2012; Sun et al., 2018). These advances offer the potential to couple ecosystem-scale measurements of CO 2 fluxes and SIF to probe new aspects related to ecosystem structural impacts on SIF andphotosynthesis processes at different time-scales and on different ecosystems (e.g., Damm et al., 2010; Magney et al., 2019; Porcar-Castell et al., 2021). While SIF has been proven as a good proxy of gross primary productivity (GPP), mainly across large spatial and temporal gradients, a series of studies showed that different factors could confound this relationship, namely different canopy structures (e.g., Dechant et al., 2020; Migliavacca et al., 2017), stress conditions (e.g., Martini et al., 2022; Wieneke et al., 2018; Wohlfahrt et al., 2018), nutritional conditions (Cendrero-Mateo et al., 2015; Martini et al., 2019), species-specific differences (e.g., Van Wittenberghe et al., 2013) and light regimes (e.g., Liu and Liu, 2018). At the same time, the modeling of SIF developed rapidly (Gu et al., 2019a; Han et al., 2022; Han et al., 2021; van der Tol et al., 2014; van der Tol et al., 2009) and with an increasing degree of realism, offering the possibility to retrieve important vegetation parameters from remote sensing (Pacheco-Labrador et al., 2019; Verrelst et al., 2015; Verrelst et al., 2016; Zhang et al., 2014). Excellent and comprehensive reviews of the field are by (Mohammed et al., 2019; Porcar-Castell et al., 2021; Porcar-Castell et al., 2014; Sun et al., 2023a; Sun et al., 2023b). Despite the exponential increase in the number of publications in the field, significant progress is still needed. Here, this special issue aims to report foundational SIF science, including theoretical modeling and measurement-based research that is urgently needed to unleash the full potential of SIF for physiological and ecological applications at scales spanning from leaf to globe. The 14 articles collected in this special issue reported on the following specific aspects: first, technical capabilities enabling spectrally resolved SIF observations and their inter-comparability in space and time; second, theoretical developments in SIF-photosynthesis relationships to correctly interpret the signal and extract mechanistic information on vegetation structure and function; third, evaluation of the potential of SIF to track process beyond photosynthesis, such as transpiration; fourth, large scale-applications of SIF observations; and finally, upscaling fluorescence from leaf to canopy scales.

54 ENVIRONMENTAL SCIENCES↗

Combined Heat Shield and Solar Thermal Propulsion System for an Oberth Maneuver

As humanity continues its exploration of space, many space missions are enabled by increases in speed. Examples include outer planet and dwarf planet exploration missions and missions that travel through our solar system into interstellar space. For many of these applications speeds of >10 astronomical units per year (AU/yr) are desired. A powered gravity assist around the Sun may offer the best option for reaching this goal; however, current heat shields and kick stages are too heavy or generate too little thrust. Solar thermal propulsion overcomes this tradeoff by converting the heat of the Sun into thrust. By tripling the specific impulse relative to chemical propulsion and by enabling a smaller perihelion through active cooling, this approach nearly doubles the escape velocity. Our team has designed and built working solar thermal propulsion prototypes out of materials that can survive 2700 K at a 30 x 30 cm scale. These benchtop-scale demonstrations have thus far validated the simplifying assumptions that underlie our thermal and propulsion models. Despite growing confidence that a full-scale heat shield/heat exchanger can survive an Oberth maneuver, many questions remain regarding the feasibility of long-term cryogenic storage of hydrogen propellant.

33 ADVANCED PROPULSION SYSTEMS↗

Ad-apoptin inhibits glycolysis, migration and invasion in lung cancer cells targeting AMPK/mTOR signaling pathway

Ad-apoptin is a recombinant oncolytic adenovirus constructed by our laboratory that can express apoptin. It can selectively kill tumor cells without damaging normal cells. This study investigated the effects of Ad-apoptin on glycolysis, migration and invasion of non-small cell lung cancer. Cell viability and apoptosis were detected by CCK-8 and flow cytometry, respectively. Glycolysis was investigated by glucose consumption, lactic acid production and glycolytic key enzyme protein levels. Migration and invasion were evaluated via wound healing, transwell assays and epithelial-mesenchymal transition (EMT) protein levels. The interaction between apoptin and AMPK was detected by Co-IP. A nude mice tumor model was established to investigate the anti-cancer role of Ad-apoptin in vivo. The results showed that Ad-apoptin inhibits cell viability and induces apoptosis of A549 and NCI–H23 cells. Ad-apoptin can reduce the glucose uptake and lactic production in lung cancer cells, and reduce the expression of related glycolysis-limiting enzymes. At the same time, Ad-apoptin inhibited the migration and invasion of lung cancer. Immunoprecipitation showed that apoptin and AMPK could interact directly. Moreover, knockdown of AMPK significantly attenuated the inhibitory effect of Ad-apoptin on glycolysis, migration and invasion of A549 and NCI–H23 cells. Ad-apoptin can inhibit the growth of tumors in nude mice. Compared with the control group, Ad-apoptin had a significant inhibitory effect on AMPK knockdown tumors. The immunohistochemical results of tumor tissues were consistent with those in vitro. Collectively, Ad-apoptin targets AMPK and inhibits glycolysis, migration and invasion of lung cancer cells through the AMPK/mTOR signaling pathway. This suggests that Ad-apoptin may have therapeutic potential for lung cancer by targeting AMPK activation.

60 APPLIED LIFE SCIENCES↗

Ni/Photoredox-Catalyzed C(sp 3 )–C(sp 3 ) Coupling between Aziridines and Acetals as Alcohol-Derived Alkyl Radical Precursors

Aziridines are readily available C(sp 3 ) precursors that afford valuable β-functionalized amines upon ring opening. In this article, we report a Ni/photoredox methodology for C(sp 3 )–C(sp 3 ) cross-coupling between aziridines and methyl/1°/2° aliphatic alcohols activated as benzaldehyde dialkyl acetals. Orthogonal activation modes of each alkyl coupling partner facilitate cross-selectivity in the C(sp 3 )–C(sp 3 ) bond-forming reaction: the benzaldehyde dialkyl acetal is activated via hydrogen atom abstraction and β-scission via a bromine radical (generated in situ from single-electron oxidation of bromide), whereas the aziridine is activated at the Ni center via reduction. Here, we demonstrate that an Ni(II) azametallacycle, conventionally proposed in aziridine cross-coupling, is not an intermediate in the productive cross-coupling. Rather, stoichiometric organometallic and linear free energy relationship studies indicate that aziridine activation proceeds via Ni(I) oxidative addition, a previously unexplored elementary step.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Phase segregation reversibility in mixed-metal hydroxide water oxidation catalysts

Achieving stable, low-cost electrocatalysts represents a daunting challenge towards practical water oxidation reactions. Here, we report that a degraded electrocatalyst can be revivified under catalytic operating conditions by manipulating reversible phase segregation. Under the oxygen evolution reaction conditions, Fe segregation develops in the Ni–Fe hydroxide host lat- tice, with the formation of FeOOH, resulting in an interface between the FeOOH and the host lattice. A dynamic metal dissolu- tion–redeposition process accelerates the Fe segregation and formation of the FeOOH secondary phase, resulting in catalyst deactivation. Operando synchrotron spectroscopic and microscopic analyses suggest that the phase segregation is revers- ible between the water oxidation potential and the catalyst reduction potential. Therefore, we have developed an intermittent reduction methodology to revivify the catalytic activity under the operating conditions, enhancing catalyst durability. The pres- ent study highlights that tailoring phase segregation at the catalyst/electrolyte interface constitutes an important strategy for revivifying and stabilizing catalytic activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Decontamination and Sterilization of Surfaces using Low Cost Ionic Liquids (CRADA Final Report)

The current study made a comprehensive literature review of the structure activity relationship (SAR) for microcidal and virucidal influence of ionic liquids. It summarized the key structure parameters that have close correlation to the antimicrobial and antiviral properties of the ILs. It proposed an experimental plan on developing and testing an effective ionic liquid from renewable lignocellulosic biomass. The goal is to understand the structure activity relationship (SAR) for virucidal influence of ionic liquids through comprehensive literature search and data analysis. A full experimental plan will be drafted based on the literature summary. Perform a comprehensive literature search to aid the development of an effective and easily deployable method to inactivate SARS-CoV-2 and decontaminate surfaces based on low-cost functional ionic liquids. These designer solvents have the potential to be a compelling and environmentally friendly alternative to common chemical disinfectants. Literature summary report including reported ionic liquid structures, synthesis and testing methods, and the structure activity relationship. Experimental plan on developing a low cost effective antiviral ionic liquid.

59 BASIC BIOLOGICAL SCIENCES↗

Selenium Migration and Local Structures in Cu‐Doped CdSeTe Solar Cells after Aging

Selenium grading plays a critical role in state-of-the-art Cadmium Telluride photovoltaic cells by enhancing long-wavelength absorption and extending minority carrier lifetimes —key to enabling the current performance record of 23.08%. However, very little is understood about selenium motion. In this study, a comprehensive, multimodal, and multiscale approach is employed to investigate Se migration and local structural changes in copper (Cu)-doped CdSeTe solar cells subjected to accelerated stress. X-ray fluorescence (XRF) microscopy shows unexpected levels of Se diffusion after 500 h under heat (75°C) and light (0.8 suns, 80 mW/cm 2 ), suggesting the coexistence of fast and slow diffusion channels even at low temperatures, with unexpectedly low activation energies (<0.85 eV). X-ray Absorption Near Edge Structure (XANES) analysis indicates a preferential migration of Se atoms to anionic lattice sites and a reduction in Se-Cl co-passivation at Te-terminated dislocation cores. Furthermore, these findings point to a reconfiguration of Se local environments and highlight the potential role of extended structural defects in enabling Se transport at low temperatures. Additionally, XANES results suggest that the presence of metallic Cu across the absorber layer may contribute to back-contact degradation and reduced hole density in both fresh and aged devices.

14 SOLAR ENERGY↗

C/2014 UN 271 (Bernardinelli-Bernstein): The Nearly Spherical Cow of Comets

Abstract Comet C/2014 UN 271 (Bernardinelli-Bernstein), incoming from the Oort cloud, is remarkable in having the brightest (and presumably largest) nucleus of any well-measured comet and having been discovered at the heliocentric distance r h ≈ 29 au, farther than any Oort cloud comet. In this work, we describe the discovery process and observations and the properties that can be inferred from images recorded until the first reports of activity in 2021 June. The orbit has i = 95°, with a perihelion of 10.97 au to be reached in 2031 and a previous aphelion at 40,400 ± 260 au. Backward integration of the orbit under a standard Galactic tidal model and known stellar encounters suggests a perihelion of q ≈ 18 au on its previous perihelion passage 3.5 Myr ago; hence, the current data could be the first ever obtained of a comet that has not been inside Uranus’s orbit in 4 Gyr. The photometric data show an unresolved nucleus with absolute magnitude H r = 8.0, colors that are typical of comet nuclei or Damocloids, and no secular trend as it traversed the range 34–23 au. For the r -band geometric albedo p r , this implies a diameter of 150 ( p r / 0.04 ) − 0.5 km. There is strong evidence of brightness fluctuations at the ±0.2 mag level, but no rotation period can be discerned. A coma, nominally consistent with a “stationary” 1/ ρ surface brightness distribution, grew in scattering cross section at an exponential rate from A f ρ ≈ 1 to ≈150 m as the comet approached from 28 to 20 au. The activity rate is consistent with a very simple model of sublimation of a surface species in radiative equilibrium with the Sun. The inferred enthalpy of sublimation matches those of CO 2 and NH 3 . More volatile species, such as N 2 , CH 4 , and CO, must be far less abundant on the sublimating surfaces.

79 ASTRONOMY AND ASTROPHYSICS↗

Machine learning in nuclear materials research

Nuclear materials are often demanded to function for extended time in extreme environments, including high radiation fluxes with associated transmutations, high temperature and temperature gradients, mechanical stresses, and corrosive coolants. They also have a wide range of microstructural and chemical makeups, resulting in multifaceted and often out-of-equilibrium interactions. Machine learning (ML) is increasingly being used to tackle these complex time-dependent interactions and aid researchers in developing models and making predictions, sometimes with better accuracy than traditional modeling that focuses on one or two parameters at a time. Conventional practices of acquiring new experimental data in nuclear materials research are often slow and expensive, limiting the opportunity for data-centric ML, but new methods are changing that paradigm. Here we review high-throughput computational and experimental data approaches, especially robotic experimentation and active learning that is based on Gaussian process and Bayesian optimization. We show ML examples in structural materials (e.g., reactor pressure vessel (RPV) alloys and radiation detecting scintillating materials) and highlight new techniques of high-throughput sample preparation and characterizations, and automated radiation/environmental exposures and real-time online diagnostics. Herein, this review suggests that ML models of material constitutive relations in plasticity, damage, and even electronic and optical responses to radiation are likely to become powerful tools as they develop. Finally, we speculate on how the recent trends of using natural language processing (NLP) to aid the collection and analysis of literature data, interpretable artificial intelligence (AI), and the use of streamlined scripting, database, workflow management, and cloud computing platforms that will soon make the utilization of ML techniques as commonplace as the spreadsheet curve-fitting practices of today.

36 MATERIALS SCIENCE↗

Quantum annealing-aided design of an ultrathin-metamaterial optical diode

Abstract Thin-film optical diodes are important elements for miniaturizing photonic systems. However, the design of optical diodes relies on empirical and heuristic approaches. This poses a significant challenge for identifying optimal structural models of optical diodes at given wavelengths. Here, we leverage a quantum annealing-enhanced active learning scheme to automatically identify optimal designs of 130 nm-thick optical diodes. An optical diode is a stratified volume diffractive film discretized into rectangular pixels, where each pixel is assigned to either a metal or dielectric. The proposed scheme identifies the optimal material states of each pixel, maximizing the quality of optical isolation at given wavelengths. Consequently, we successfully identify optimal structures at three specific wavelengths (600, 800, and 1000 nm). In the best-case scenario, when the forward transmissivity is 85%, the backward transmissivity is 0.1%. Electromagnetic field profiles reveal that the designed diode strongly supports surface plasmons coupled across counterintuitive metal–dielectric pixel arrays. Thereby, it yields the transmission of first-order diffracted light with a high amplitude. In contrast, backward transmission has decoupled surface plasmons that redirect Poynting vectors back to the incident medium, resulting in near attenuation of its transmission. In addition, we experimentally verify the optical isolation function of the optical diode.

36 MATERIALS SCIENCE↗