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At least 109 records · Page 6

Enantiomeric Excesses of Acid Labile Amino Acid Precursors of the Murchison Meteorite

Amino acids present in carbonaceous chondrite are extracted in water in part as free compounds and in approximately equal part as acid labile precursors. On the assumption that they would be free of contamination, the precursors of two Murchison amino acids that have terrestrial occurrence, alanine and glutamic acid, have been targeted for analysis of their enantiomeric ratios. Pyroglutamic acid, the precursor of glutamic acid, was found with an L-enantiomeric excess comparable to that of the free acid, while alanine's precursor, N-acetyl alanine, appears approximately racemic. Also alpha-imino propioacetic acid, a proposed end product of alanine synthesis in the meteorite, was analyzed and found racemic.

Pizzarello, Sandra↗

Experimental and computational studies on high-entropy carbide MoNbTaVWC 5 under high pressures

High-entropy carbide, MoNbTaVWC 5 , was synthesized from oxide precursors of the constituent metals, mixed with graphite powder in a microwave-generated hydrogen plasma at 26.66 kPa and 2100 °C. Ambient x-ray diffraction analysis confirms the full conversion of oxide precursors into a single-phase, face-centered cubic structure with a lattice parameter a = 4.3309 Å. Nanoindentation measured a hardness of 24.5 ± 1.3 GPa and an elastic modulus of 386 ± 22 GPa. The synthesized sample, mixed with a copper pressure marker, was studied by the radial x-ray diffraction technique with beryllium gasketing in a diamond anvil cell up to 70 GPa. The experimentally measured pressure–volume curve and shear strength were compared with theoretical predictions using the special quasi-random structure technique and density functional theory. MoNbTaVWC 5 achieved a 12% volume compression at 70 GPa and exhibited a high shear strength of 6.6 GPa. The present study demonstrates that the high-entropy carbide MoNbTaVWC 5 exhibits exceptional incompressibility and high strength under extreme conditions.

36 MATERIALS SCIENCE↗

An Effective Purification Process for the Nuclear Radiation Detector Tl 6 SeI 4

The semiconductor Tl6SeI4 was previously identified as a promising semiconductor for room temperature nuclear radiation detection. As the detection performance and carrier transport strongly depend on the concentration of impurity energy levels acting as scattering centers and carrier trapping, material purification is a crucial prerequisite step to obtain spectroscopic-grade detector performance. In this contribution, we present a highly efficient purification method using a bent ampule for evaporating Se, Tl2Se, and TlI precursors for Tl6Se4. On the basis of impurity analysis performed by glow discharge mass spectroscopy, the main impurities in Tl2Se were identified to be Pb, Bi, and Al, while in TlI the main impurities are Al and Sn. The bent-ampule method successfully reduces or removes the Cl, Pb, and Te impurities from the Se precursor, the Pb, Bi, and Al impurities from the Tl2Se precursor, and removes Sn from TU. Informed by the analysis results, density functional theory calculations were performed to study the identified impurities and related defects. The calculation results show that Bi and Al act as deep defect levels, which can be detrimental to the detector performance of Tl6SeI4. If the growth condition of Tl6SeI4 is Tl-rich/Se-poor, impurity of Si can introduce deep donors. However, it becomes electrically benign if growth conditions are Tl-poor/Se-rich, while Sn and Pb impurities are shallow donors. Centimeter-size Tl6SeI4 crystals were grown by the two-zone vertical Bridgman method using the purified precursors. The detector made of Tl6SeI4 crystal maintains the high resistivity on the order of 10(11) Omega.cm after purification, ideal for suppressing leakage current. The detector exhibits both full-energy and Tl escape photopeaks upon 122 keV gamma-ray from Co-57 radiation source. The electron mobility-lifetime product mu(e)tau(e) for TI6SeI4 detector is 8.1 X 10(-5) cm(2).V-1. On the basis of the carrier rise time measured from output pulses induced by 5.5 MeV alpha-particles from Am-241, the electron and hole mobilities were estimated to be 112 +/- 22 and 81 +/- 16 cm(2).V-1.s(-1), respectively, comparable to those of the leading detector materials HgI2 and TlBr. These results validate the potential of this compound for hard radiation detection, and the impurity analysis presented here allows future efforts to focus on reducing the concentration of the identified impurities.

Lin, Wenwen (ORCID:0000000216279558)↗

Dynamic Tracking of NiFe Smart Catalysts using In Situ X-Ray Absorption Spectroscopy for the Dry Methane Reforming Reaction

The exsolution of nanoparticles from perovskite precursors has been explored as a route to synthesize catalysts with sinter or coke resistance. The characteristics of these exsolved nanoparticles are highly dynamic depending on the redox nature of the environment to which they are subjected. To develop their properties for thermo- and electrocatalytic applications, it is necessary to track the states and behavior of exsolved catalysts with in situ and ex situ characterization. In this study, we conduct in situ X-ray absorption spectroscopy (XAS) along with ex situ scanning transmission electron microscopy high-angle annular dark-field (STEM-HAADF) and energy-dispersive X-ray spectroscopy analysis of the parent perovskite oxide precursor, LaFe 0.8 Ni 0.2 O 3 , as its structure forms bimetallic NiFe nanoparticles and evolves in oxidative, reductive, and dry methane reforming environments. We develop a theory that NiFe exsolution is a function of the reduction potential where LaFe 0.8 Ni 0.2 O 3 transforms to NiFe alloy supported on LaO x -LaFeO x . The Ni starts to exsolve at 268 °C, while most Fe exsolves at 700 °C. During dry methane reforming conditions, most of the Fe is oxidized by CO 2 during the reaction and re-enters the perovskite as LaFeO 3 , while Ni remains on the surface as nanoparticles in the metallic state. During the oxidative regeneration phase, most of the Fe re-enters the bulk perovskite phase, while Ni is partially regenerated with a small percentage oxidized to large NiO nanoparticles. Finally, this study sheds light on the exsolution and regeneration of bimetallic alloy nanoparticles and the influence of the reaction conditions on their catalyst performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Similarity of Precursors in Solid-State Synthesis as Text-Mined from Scientific Literature

Collecting and analyzing the vast amount of information available in the solid-state chemistry literature may accelerate our understanding of materials synthesis. However, one major problem is the difficulty of identifying which materials from a synthesis paragraph are precursors or are target materials. In this study, we developed a two-step chemical named entity recognition model to identify precursors and targets, based on information from the context around material entities. Using the extracted data, we conducted a meta-analysis to study the similarities and differences between precursors in the context of solid-state synthesis. To quantify precursor similarity, we built a substitution model to calculate the viability of substituting one precursor with another while retaining the target. From a hierarchical clustering of the precursors, we demonstrate that the “chemical similarity” of precursors can be extracted from text data. Quantifying the similarity of precursors helps provide a foundation for suggesting candidate reactants in a predictive synthesis model.

36 MATERIALS SCIENCE↗

Red light regulation of ethylene biosynthesis and gravitropism in etiolated pea stems

During gravitropism, the accumulation of auxin in the lower side of the stem causes increased growth and the subsequent curvature, while the gaseous hormone ethylene plays a modulating role in regulating the kinetics of growth asymmetries. Light also contributes to the control of gravitropic curvature, potentially through its interaction with ethylene biosynthesis. In this study, red-light pulse treatment of etiolated pea epicotyls was evaluated for its effect on ethylene biosynthesis during gravitropic curvature. Ethylene biosynthesis analysis included measurements of ethylene; the ethylene precursor 1-aminocyclopropane-1-carboxylic acid (ACC); malonyl-conjugated ACC (MACC); and expression levels of pea ACC oxidase (Ps-ACO1) and ACC synthase (Ps-ACS1, Ps-ACS2) genes by reverse transcriptase-polymerase chain reaction analysis. Red-pulsed seedlings were given a 6 min pulse of 11 micromoles m-2 s-1 red-light 15 h prior to horizontal reorientation for consistency with the timeline of red-light inhibition of ethylene production. Red-pulse treatment significantly reduced ethylene production and MACC levels in epicotyl tissue. However, there was no effect of red-pulse treatment on ACC level, or expression of ACS or ACO genes. During gravitropic curvature, ethylene production increased from 60 to 120 min after horizontal placement in both control and red-pulsed epicotyls. In red-pulsed tissues, ACC levels increased by 120 min after horizontal reorientation, accompanied by decreased MACC levels in the lower portion of the epicotyl. Overall, our results demonstrate that ethylene production in etiolated epicotyls increases after the initiation of curvature. This ethylene increase may inhibit cell growth in the lower portion of the epicotyl and contribute to tip straightening and reduced overall curvature observed after the initial 60 min of curvature in etiolated pea epicotyls.

Non-NASA Center↗

What Is the Smallest Zeolite That Could Be Synthesized?**

Abstract Zeolites with a few unit cells are promising as catalyst and adsorbents. The quest to synthesize the smallest zeolites has recently resulted in 4 to 8 nm nanozeolites, about 2 to 4 unit cells. These findings pose the question of what is the smallest zeolite that could be obtained by hydrothermal synthesis. Here we address this question using molecular simulations and thermodynamic analysis. The simulations predict that amorphous precursors as small as 4 nm can crystallize zeolites, in agreement with the experiments. We find that interfacial forces dominate the structure of smaller particles, resulting in size‐dependent compact isomers that have ring and pore distributions different from open framework zeolites. The instability of zeolites smaller than 3±0.5 nm precludes a classical mechanism of nucleation from solution or through assembly of small nanoslabs.

Dhabal, Debdas↗

What Is the Smallest Zeolite That Could Be Synthesized?**

Zeolites with a few unit cells are promising as catalyst and adsorbents. The quest to synthesize the smallest zeolites has recently resulted in 4 to 8 nm nanozeolites, about 2 to 4 unit cells. These findings pose the question of what is the smallest zeolite that could be obtained by hydrothermal synthesis. We address this question using molecular simulations and thermodynamic analysis. The simulations predict that amorphous precursors as small as 4 nm can crystallize zeolites, in agreement with the experiments. We find that interfacial forces dominate the structure of smaller particles, resulting in size-dependent compact isomers that have ring and pore distributions different from open framework zeolites. The instability of zeolites smaller than 3±0.5 nm precludes a classical mechanism of nucleation from solution or through assembly of small nanoslabs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Subtle penetrant size effects on separation of carbon molecular sieve membranes derived from $\mathrm{6FDA:BPDA}$-$\mathrm{DAM}$ polyimide

Economically scalable carbon molecular sieve (CMS) hollow fiber membranes rely upon a tunable bimodal pore morphology to separate gas pairs using angstrom-level size discrimination. Freshly formed CMS membranes experience self-retarding physical aging, reflected by permeance losses and selectivity gains that stabilize over short times compared to the lifetime of the membrane. Self-retarding morphology rearrangements are of special interest here due to tightening of the largest size range of ultramicropores, thereby causing aging for polyimide-derived CMS. We report effects of such aging for two A/B penetrant pairs, C 3 H 6 /C 3 H 8 and CO 2 /CH 4 . These two pairs not only have different average sizes, $\overline{d}_{A/B}$, but also different size differences,Δd A/B , between the members in each pair. We focus primarily on the C 3 H 6 /C 3 H 8 pair, which is the most difficult of the two pairs to separate, and use some CO 2 /CH 4 results as a comparison case. We study CMS derived from 6FDA:BPDA-DAM (1:1) polyimide by pyrolysis at 550 °C, 600 °C and 650 °C. Here we suggest conditions and physical causes that expedite, retard or even suppress the aging process within CMS membranes. Finally, we suggest how analysis of CMS derived from other precursors and other penetrant pairs can be generalized by understanding the results for the 6FDA:BPDA-DAM (1:1) polyimide derived CMS.

36 MATERIALS SCIENCE↗

Rubisco supplies pyruvate for the 2- C -methyl-D-erythritol-4-phosphate pathway

RIBULOSE-1,5-BISPHOSPHATE CARBOXYLASE/OXYGENASE (Rubisco) produces pyruvate in the chloroplast through β-elimination of the aci-carbanion intermediate. Here we show that this side reaction supplies pyruvate for isoprenoid, fatty acid and branched-chain amino acid biosynthesis in photosynthetically active tissue. 13 C labelling studies of intact Arabidopsis plants demonstrate that the total carbon commitment to pyruvate is too large for phosphoenolpyruvate to serve as a precursor. Low oxygen stimulates Rubisco carboxylase activity and increases pyruvate production and flux through the 2-C-methyl-d-erythritol-4-phosphate (MEP) pathway, which supplies the precursors for plastidic isoprenoid biosynthesis. Metabolome analysis of mutants defective in phosphoenolpyruvate or pyruvate import and biochemical characterization of isolated chloroplasts further support Rubisco as the main source of pyruvate in chloroplasts. Seedlings incorporated exogenous, 13 C-labelled pyruvate into MEP pathway intermediates, while adult plants did not, underscoring the developmental transition in pyruvate sourcing. Rubisco β-elimination leading to pyruvate constituted 0.7% of the product profile in in vitro assays, which translates to 2% of the total carbon leaving the Calvin–Benson–Bassham cycle. These insights solve the “pyruvate paradox”, improve the fit of metabolic models for central metabolism and connect the MEP pathway directly to carbon assimilation.

Plant physiology↗

Distributed Coordination of Networked Microgrids for Voltage Support in Bulk Power Grids

The increasing deployment of distributed energy resources (DERs) and microgrids (MGs) in power distribution systems has enabled the adjustment of reactive power consumption as seen at the substation, which can be used to provide voltage support for the bulk power system (BPS). Leveraging this new capability will provide greater resiliency to the power system as a whole. Here, the goal of this paper is to develop and compare three different algorithms, namely distributed optimal power flow, distributed consensus algorithm, and fully decentralized collaborative autonomy for unbalanced distribution systems for microgrid coordination. These algorithms use networked MGs to support the BPS voltage when a contingency at the bulk grid results in abnormally low voltages, which may be a precursor to voltage collapse. Our comparative analysis includes both qualitative and quantitative assessments of the three algorithms and a discussion of the trade-offs between the decentralized and distributed methods in normal and disrupted conditions. Each algorithm was evaluated on the modified IEEE 13-bus system and a real power distribution system at Chattanooga, Tennessee, that encompasses more than 4500 buses. Each algorithms excels differently and may be suited for different scenarios depending on the condition, operations, and priorities of the power and communication systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Integrating Machine Learning into a Methodology for Early Detection of Wellbore Failure [Slides]

Approximately 93% of US total energy supply is dependent on wellbores in some form. The industry will drill more wells in next ten years than in the last 100 years (King, 2014). Global well population is around 1.8 million of which approximately 35% has some signs of leakage (i.e. sustained casing pressure). Around 5% of offshore oil and gas wells “fail” early, more with age and most with maturity. 8.9% of “shale gas” wells in the Marcellus play have experienced failure (120 out of 1,346 wells drilled in 2012) (Ingraffea et al., 2014). Current methods for identifying wells that are at highest priority for increased monitoring and/or at highest risk for failure consists of “hand” analysis of multi-arm caliper (MAC) well logging data and geomechanical models. Machine learning (ML) methods are of interest to explore feasibility for increasing analysis efficiency and/or enhanced detection of precursors to failure (e.g. deformations). MAC datasets used to train ML algorithms and preliminary tests were run for “predicting” casing collar locations and performed above 90% in classification and identifying of casing collar locations.

54 ENVIRONMENTAL SCIENCES↗

Integrating Machine Learning into a Methodology for Early Detection of Wellbore Failure [Slides]

Approximately 93% of US total energy supply is dependent on wellbores in some form. The industry will drill more wells in next ten years than in the last 100 years (King, 2014). Global well population is around 1.8 million of which approximately 35% has some signs of leakage (i.e. sustained casing pressure). Around 5% of offshore oil and gas wells “fail” early, more with age and most with maturity. 8.9% of “shale gas” wells in the Marcellus play have experienced failure (120 out of 1,346 wells drilled in 2012) (Ingraffea et al., 2014). Current methods for identifying wells that are at highest priority for increased monitoring and/or at highest risk for failure consists of “hand” analysis of multi-arm caliper (MAC) well logging data and geomechanical models. Machine learning (ML) methods are of interest to explore feasibility for increasing analysis efficiency and/or enhanced detection of precursors to failure (e.g. deformations). MAC datasets used to train ML algorithms and preliminary tests were run for “predicting” casing collar locations and performed above 90% in classification and identifying of casing collar locations.

54 ENVIRONMENTAL SCIENCES↗

Structural and Chemical Evolution of Methylammonium Lead Halide Perovskites during Thermal Processing from Solution

Following the prominent success of CH3NH3PbI3 in photovoltaics and other optoelectronic applications, focus has been placed on better understanding perovskite crystallization from precursor and intermediate phases in order to facilitate improved crystallinity often desirable for advancing optoelectronic properties. Understanding of stability and degradation is also of critical importance as these materials seek commercial applications. In this study, we investigate the evolution of perovskites formed from targeted precursor chemistries by correlating in situ temperature-dependent X-ray diffraction, thermogravimetric analysis, and mass spectral analysis of the evolved species. This suite of analyses reveals important precursor composition-induced variations in the processes underpinning perovskite formation and degradation. The addition of Cl- leads to widely different precursor evolution and perovskite formation kinetics, and results in significant changes to the degradation mechanism, including suppression of crystalline PbI2 formation and modification of the thermal stability of the perovskite phase. This work highlights the role of perovskite precursor chemistry in both its formation and degradation.

14 SOLAR ENERGY↗

Microstructural pattern formation during liquid metal dealloying: Phase-field simulations and theoretical analyses

In recent years, liquid metal dealloying has emerged as a promising material processing method to generate micro- and nanoscale bicontinuous or porous structures. Most previous studies focused on the experimental characterization of the dealloying process and on the properties of the dealloyed materials, leaving the theoretical study incomplete to fully understand the fundamental mechanisms of the liquid metal dealloying process. In this paper, we use theoretical models and phase-field simulations to clarify the kinetics and pattern formation during liquid metal dealloying. Our investigation starts from a theoretical analysis of the 1D dissolution of a binary precursor alloy, which reveals that the 1D dissolution process involves two regimes. In the first regime, due to the low solubility of one of the elements in the melt, it accumulates at the solid-liquid interface, which reduces the dissolution kinetics. In the second regime, the interface kinetics reaches a stationary regime where both elements of the precursor alloy dissolve into the melt. Previous works revealed that in the early dealloying stage, the dealloying front is destabilized by an interfacial spinodal decomposition, which triggers the formation of interconnected ligaments. Here we extend this line of work by proposing a linear stability analysis able to predict the initial length scale of the ligaments formed in the initial stage of the dealloying. Combining this analysis with the 1D dissolution model proposed here enables us to better understand the initial conditions (composition of the precursor alloy and the melt) leading to a planar dissolution without interface destabilization. Finally, we report a strong influence of solid-state diffusion on dealloying. Although the solid-state diffusivity is four to five orders of magnitude smaller than in the liquid phase, it is found to affect both dissolution kinetics and ligament morphologies.

36 MATERIALS SCIENCE↗

Contributions to local- and regional-scale formaldehyde concentrations

Reducing ambient formaldehyde concentrations is a complex task because formaldehyde is both a primary and a secondary air pollutant, with significant anthropogenic and biogenic sources of volatile organic compound (VOC) precursor emissions. This work uses adjoint sensitivity analysis in a chemical transport model to identify emission sources and chemical reactions that influence formaldehyde mixing ratios in the San Francisco Bay Area and within three urbanized sub-areas. For each of these receptors, the use of the adjoint technique allows for efficient calculation of the sensitivity of formaldehyde to emissions of NO x , formaldehyde, and VOC precursors occurring at any location and time. Formaldehyde mixing ratios are found to be generally higher in summer than in winter. The opposite seasonal trend is observed for the sensitivities of these mixing ratios to formaldehyde emissions. In other words, even though formaldehyde is higher in summer, reducing formaldehyde emissions has a greater impact in winter. In winter, 85%–90% of the sensitivity to emissions is attributed to direct formaldehyde emissions. In summer, this contribution is smaller and more variable, ranging from 27% to 75% among the receptor areas investigated in this study. Higher relative contributions of secondary formation versus direct emissions are associated with receptors located farther away from heavily urbanized and emission-rich areas. In particular, the relative contribution of biogenic VOC emissions (15%–43% in summer) is largest for these receptors. Ethene and other alkenes are the most influential anthropogenic precursors to secondary formaldehyde. Isoprene is the most influential biogenic precursor. Sensitivities of formaldehyde to NO x emissions are generally negative but relatively small in magnitude compared to sensitivities to VOC emissions. The magnitude of anthropogenic emissions of organic compounds other than formaldehyde is found to correlate reasonably well with their influence on population-weighted formaldehyde mixing ratios at the air-basin scale. This correlation does not hold for ambient formaldehyde in smaller urbanized sub-areas. The magnitude of biogenic emissions does not correlate with their influence in either case.

Bastien, Lucas A. J.↗

Analysis of cardiomyocyte movement in the developing murine heart

The precise assemblage of several types of cardiac precursors controls heart organogenesis. The cardiac precursors show dynamic movement during early development and then form the complicated heart structure. However, cardiomyocyte movements inside the newly organized mammalian heart remain unclear. We previously established the method of ex vivo time-lapse imaging of the murine heart to study cardiomyocyte behavior by using the Fucci (fluorescent ubiquitination-based cell cycle indicator) system, which can effectively label individual G1, S/G2/M, and G1/S-transition phase nuclei in living cardiomyocytes as red, green, and yellow, respectively. Global analysis of gene expression in Fucci green positive ventricular cardiomyocytes confirmed that cell cycle regulatory genes expressed in G1/S, S, G2/M, and M phase transitions were upregulated. Interestingly, pathway analysis revealed that many genes related to the cell cycle were significantly upregulated in the Fucci green positive ventricular cardiomyocytes, while only a small number of genes related to cell motility were upregulated. Time-lapse imaging showed that murine proliferating cardiomyocytes did not exhibit dynamic movement inside the heart, but stayed on site after entering the cell cycle. - Highlights: • We directly visualized cardiomyocyte movement inside the developing murine heart. • Cell cycle related genes were upregulated in the proliferating cardiomyocytes. • Time-lapse imaging revealed that proliferating murine cardiomyocytes stayed in place. • Murine ventricular cardiomyocytes proliferate on site during development.

60 APPLIED LIFE SCIENCES↗