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At least 613 records · Page 34

GAS41 Recognizes Diacetylated Histone H3 through a Bivalent Binding Mode

GAS41 is a chromatin-associated protein that belongs to the YEATS family and is involved in the recognition of acetyl-lysine in histone proteins. A unique feature of GAS41 is the presence of a C-terminal coiled-coil domain, which is responsible for protein dimerization. Here, we characterized the specificity of the GAS41 YEATS domain and found that it preferentially binds to acetylated H3K18 and H3K27 peptides. Interestingly, we found that full-length, dimeric GAS41 binds to diacetylated H3 peptides with an enhanced affinity when compared to those for monoacetylated peptides, through a bivalent binding mode. We determined the crystal structure of the GAS41 YEATS domain with H3K23acK27ac to visualize the molecular basis of diacetylated histone binding. Furthermore, our results suggest a unique binding mode in which full-length GAS41 is a reader of diacetylated histones.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Defect-driven selective metal oxidation at atomic scale

Nanoscale materials modified by crystal defects exhibit significantly different behaviours upon chemical reactions such as oxidation, catalysis, lithiation and epitaxial growth. However, unveiling the exact defect-controlled reaction dynamics (e.g. oxidation) at atomic scale remains a challenge for applications. Here, using in situ high-resolution transmission electron microscopy and first-principles calculations, we reveal the dynamics of a general site-selective oxidation behaviour in nanotwinned silver and palladium driven by individual stacking-faults and twin boundaries. The coherent planar defects crossing the surface exhibit the highest oxygen binding energies, leading to preferential nucleation of oxides at these intersections. Planar-fault mediated diffusion of oxygen atoms is shown to catalyse subsequent layer-by-layer inward oxide growth via atomic steps migrating on the oxide-metal interface. These findings provide an atomistic visualization of the complex reaction dynamics controlled by planar defects in metallic nanostructures, which could enable the modification of physiochemical performances in nanomaterials through defect engineering.

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A portable fiber optic sensor for the luminescent sensing of cobalt ions using carbon dots

Cobalt is critical to energy-relevant technologies, and demand for cobalt will increase significantly with growing global adoption of renewables. However, supply chain stability is threatened by economic and geopolitical factors, incentivizing domestic cobalt production from alternative resources such as coal, coal utilization byproducts (e.g., ash, acid mine drainage) and electronic waste. Rapid, inexpensive, and portable characterization techniques are needed to reduce production costs associated with cobalt prospecting and process monitoring. Here, in this research, we develop a compact, portable fiber optic luminescent probe for cobalt using phosphorus and nitrogen co-doped carbon dots as the sensing material. The carbon dot emission overlaps well with the cobalt absorption band at ~510 nm, leading to a selective decrease in emission as a function of cobalt concentration. The system responds nearly instantly to the presence of cobalt, with detection limits of 0.7 and 3.5 ppm in water and pH 1.68 buffer, respectively, providing comparable performance to a commercial spectrometer at a significantly lower cost. Moreover, the sensor is selective for cobalt in the presence of 13 of the most common metal ions encountered in coal utilization byproducts and is responsive to cobalt when spiked into an acid mine drainage leachate sample, highlighting the sensor's potential for real-world deployment in challenging matrices. In addition, integrating the carbon dots with a filter paper substrate produced ‘test strip’ sensors that exhibited a selective and sensitive visual response to cobalt using a handheld UV lamp. Taken together, the sensing system represents a significant step forward in the development of low-cost practical sensors for high-value metals in complex streams.

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Direct atomic-level insight into the active sites of a high-performance PGM-free ORR catalyst

Platinum group metal–free (PGM-free) metal-nitrogen-carbon catalysts have emerged as a promising alternative to their costly platinum (Pt)–based counterparts in polymer electrolyte fuel cells (PEFCs) but still face some major challenges, including (i) the identification of the most relevant catalytic site for the oxygen reduction reaction (ORR) and (ii) demonstration of competitive PEFC performance under automotive-application conditions in the hydrogen (H 2 )–air fuel cell. We demonstrate H 2 -air performance gains achieved with an iron-nitrogen-carbon catalyst synthesized with two nitrogen precursors that developed hierarchical porosity. In current densities recorded in the kinetic region of cathode operation, at fuel cell voltages greater than ~0.75 V, were the same as those obtained with a Pt cathode at a loading of 0.1 milligram of Pt per centimeter squared. The catalytic active site we proposed, carbon-embedded nitrogen-coordinated iron (FeN 4 ), was directly visualized with aberration-corrected scanning transmission electron microscopy, and the contributions of these active sites associated with specific lattice-level carbon structures were explored computationally.

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Evaluation of the spline reconstruction technique for PET

Purpose: The spline reconstruction technique (SRT), based on the analytic formula for the inverse Radon transform, has been presented earlier in the literature. In this study, the authors present an improved formulation and numerical implementation of this algorithm and evaluate it in comparison to filtered backprojection (FBP). Methods: The SRT is based on the numerical evaluation of the Hilbert transform of the sinogram via an approximation in terms of “custom made” cubic splines. By restricting reconstruction only within object pixels and by utilizing certain mathematical symmetries, the authors achieve a reconstruction time comparable to that of FBP. The authors have implemented SRT in STIR and have evaluated this technique using simulated data from a clinical positron emission tomography (PET) system, as well as real data obtained from clinical and preclinical PET scanners. For the simulation studies, the authors have simulated sinograms of a point-source and three digital phantoms. Using these sinograms, the authors have created realizations of Poisson noise at five noise levels. In addition to visual comparisons of the reconstructed images, the authors have determined contrast and bias for different regions of the phantoms as a function of noise level. For the real-data studies, sinograms of an{sup 18}F-FDG injected mouse, a NEMA NU 4-2008 image quality phantom, and a Derenzo phantom have been acquired from a commercial PET system. The authors have determined: (a) coefficient of variations (COV) and contrast from the NEMA phantom, (b) contrast for the various sections of the Derenzo phantom, and (c) line profiles for the Derenzo phantom. Furthermore, the authors have acquired sinograms from a whole-body PET scan of an {sup 18}F-FDG injected cancer patient, using the GE Discovery ST PET/CT system. SRT and FBP reconstructions of the thorax have been visually evaluated. Results: The results indicate an improvement in FWHM and FWTM in both simulated and real point-source studies. In all simulated phantoms, the SRT exhibits higher contrast and lower bias than FBP at all noise levels, by increasing the COV in the reconstructed images. Finally, in real studies, whereas the contrast of the cold chambers are similar for both algorithms, the SRT reconstructed images of the NEMA phantom exhibit slightly higher COV values than those of FBP. In the Derenzo phantom, SRT resolves the 2-mm separated holes slightly better than FBP. The small-animal and human reconstructions via SRT exhibit slightly higher resolution and contrast than the FBP reconstructions. Conclusions: The SRT provides images of higher resolution, higher contrast, and lower bias than FBP, by increasing slightly the noise in the reconstructed images. Furthermore, it eliminates streak artifacts outside the object boundary. Unlike other analytic algorithms, the reconstruction time of SRT is comparable with that of FBP. The source code for SRT will become available in a future release of STIR.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Enhancing Clean Energy Innovation Ecosystem Discovery Tool

During March 2016, the DOE’s Office of Energy Policy and Systems Analysis (EPSA) sought a methodology to identify and quantify the strength of the existing clean energy innovation ecosystems (IE) in the U.S. and their characteristics. Oak Ridge National Lab (ORNL) did a pilot study (Phase 1) and demonstrated the feasibility of an application comprised of natural language processing, link analysis, and other computational techniques to transform text and numerical data into metrics on clean energy innovation activity and geography. The data-collection, ingest and analytics pipelines were combined with an advanced user interface, together known as the Ecosystem Discovery Tool, to enhance DOE’s understanding of existing geographic innovation clusters. During Phase 2 of this project, this tool has been further enhanced by integrating new data sets and through backend software architecture changes, validation and bug fixing, making it a much more robust and powerful application. The tool’s user interface is a lot more intuitive, which enables a user to visualize the IE rankings for various geographic regions(CBSA, state level) for different clean energy technologies and seek automated insights. ORNL also created a DOE-specific dashboard that allows the user to visualize and analyze federal funding from various offices including Energy Efficiency and Renewable Energy(EERE), Office of Electricity(OE), Fossil Energy(FE), and Nuclear Energy(NE). During Phase 1 of this project, EPSA defined a clean energy innovation ecosystem as the overlap of five Ecosystem Components: 1) nascent clean energy Indicators, 2) investors, 3) enabling environment, 4) networking assets and 5) large companies. EPSA and ORNL worked together to collect data for each component: 1) small and medium companies, ARPA-E awardees, SBIR awardees, patents, publications, ERCs for Nascent Clean Energy Indicators; 2) qualified investors; 3) the Clean Edge Policy Index/DSIRE for the Enabling Environment; 4) universities, national laboratories, ERCs and incubators for Networking Assets; and 5) large companies and a subset of the Russell 1000 list for Large Companies. The ORNL team created a visual tool based on Tableau that integrated ecosystem component data to score, rank and map IEs. The tool was created with the flexibility to allow the user to choose the weights of each of the five ecosystem components and the subcomponents. This flexibility allows the user to visualize different subsets and to use the underlying data for different types of analysis. During Phase 2 of this project, the backend database and computation process have undergone major changes to provide a much more refined user-interface and added new features into the scoring algorithm. This phase also involved addition of newer databases such as a list of Energy Research Centers (ERC) ,DSIRE, and funding data from EERE, FE, NE, and OE to provide more granular information and more accurate/better quantification.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Impact of dissolved salts on two-phase flow and boiling heat transfer in a natural circulation loop

Two-phase natural circulation and boiling experiments are conducted in this study with artificial seawater as a heat transfer fluid or process coolant. This experimental work is focused on understanding the role of dissolved salts in water on the steady state two-phase natural circulation flow rates. Mass flow rates were measured at different heat flux levels with artificial seawater, deionized water and tap water in the experimental loop. It was found that the average quasi-steady state mass flow rates were the same at any particular heat flux level regardless of the fluid being used. Artificial seawater coolant exhibited more stable natural circulation at higher heat flux as compared to the other two coolants. Mass flow measurements recorded at 2 s intervals show that magnitude of flow oscillations are much higher in case of tap water and deionized water. Also, high speed camera images revealed that the bubble departure diameters are smaller in seawater compared to tap or deionized water. This can be attributed to the increased local wettability due to the presence of dissolved salts in the fluid. Visual observations of the riser section showed that bubble coalescence and formation of slugs is inhibited in the seawater. These observations also explain the reduced pressure drop across test section when seawater was used as a coolant.

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9Cr steel visualization and predictive modeling

The goals of this work were to develop tools to visualize and characterize materials information, to explore new alloy compositions and/or processing, to better predict tensile strength and other mechanical properties. The 9–12 wt% Cr (9Cr) steel test data were compiled from several sources. About 3000 records with 30 predictor variables represent 82 unique steel alloy compositions, variations of thermo-mechanical processing steps and temperatures (homogenization, normalization and tempering cycles), test conditions and outcomes. Detailed data processing steps such as visualization and exploratory analysis, including univariate and bivariate analysis, different clustering techniques used to segment the data, statistical post-hoc analysis to verify significance of the findings, feature engineering to identify predictors of importance, and predictive modeling with cross-validation were performed. The outcome of analysis at each step was reviewed in the context of the domain knowledge of this class of steel, to see if there were underlying physical mechanisms that explain statistical relationships. Data analytics techniques and their parameters were fine-tuned to facilitate interpretation of the results as aligned with the insights from domain experts. Here, the ensemble predictive modeling using Random Forest regressor and post-hoc means comparison corroborated domain knowledge on the role of Co which is known to increase strength of steel alloys through solid-solution strengthening and to affect diffusion of alloying elements and precipitates. Alloys with Co content of 0.7–8 wt% had significantly higher mean strength than the ones without (while having Cr locked within 10–11 wt% range in either group and keeping other compositional element ratios fixed). End products of the computational techniques exploration are presented as the tools that can be used in iterative workflow of materials development and testing.

36 MATERIALS SCIENCE↗

Development of high-affinity nanobodies specific for Na V 1.4 and Na V 1.5 voltage-gated sodium channel isoforms

Voltage-gated sodium channels, Na V s, are responsible for the rapid rise of action potentials in excitable tissues. Na V channel mutations have been implicated in several human genetic diseases, such as hypokalemic periodic paralysis, myotonia, and long-QT and Brugada syndromes. Here, we generated high-affinity anti-NaV nanobodies (Nbs), Nb17 and Nb82, that recognize the Na V 1.4 (skeletal muscle) and Na V 1.5 (cardiac muscle) channel isoforms. These Nbs were raised in llama (Lama glama) and selected from a phage display library for high affinity to the C-terminal (CT) region of Na V 1.4. The Nbs were expressed in Escherichia coli, purified, and biophysically characterized. Development of high-affinity Nbs specifically targeting a given human Na V isoform has been challenging because they usually show undesired crossreactivity for different Na V isoforms. Our results show, however, that Nb17 and Nb82 recognize the CTNa V 1.4 or CTNa V 1.5 over other CTNav isoforms. Kinetic experiments by biolayer interferometry determined that Nb17 and Nb82 bind to the CTNa V 1.4 and CTNa V 1.5 with high affinity (K D ~ 40–60 nM). In addition, as proof of concept, we show that Nb82 could detect Na V 1.4 and Na V 1.5 channels in mammalian cells and tissues by Western blot. Furthermore, human embryonic kidney cells expressing holo Na V 1.5 channels demonstrated a robust FRET-binding efficiency for Nb17 and Nb82. Our work lays the foundation for developing Nbs as anti-Na V reagents to capture Na V s from cell lysates and as molecular visualization agents for Na V s.

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InteraChem: Virtual Reality Visualizer for Reactive Interactive Molecular Dynamics

Interactive molecular dynamics in virtual reality (IMD-VR) simulations provide a digital molecular playground for students as an alternative or complement to traditional molecular modeling kits or 2D illustrations. Previous IMD-VR studies have used molecular mechanics to enable simulations of macromolecules such as proteins and nanostructures for the classroom setting with considerable success. Here, we present the InteraChem molecular visualizer, intended for reactive IMD-VR simulation using semiempirical and ab initio methods. InteraChem visualizes not only the molecular geometry but also (1) isosurfaces such as molecular orbitals and electrostatic potentials and (2) two-dimensional graphs of time-varying simulation quantities such as kinetic/potential energy, internal coordinates, and user-applied force. Additionally, InteraChem employs speech recognition to facilitate user interaction and introduces a novel “atom happiness” visualization using emojis to indicate the energetic feasibility of a particular bonding arrangement. Furthermore, we include a set of accompanying exercises that we have used to teach chemical reactivity in small molecular systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multi-matrix, dual polarity, tandem mass spectrometry imaging strategy applied to a germinated maize seed: toward mass spectrometry imaging of an untargeted metabolome

Mass spectrometry imaging (MSI) provides high spatial resolution information that is unprecedented in traditional metabolomics analyses; however, the molecular coverage is often limited to a handful of compounds and is insufficient to understand overall metabolomic changes of a biological system. Here, we propose an MSI methodology to increase the diversity of chemical compounds that can be imaged and identified, in order to eventually perform untargeted metabolomic analysis using MSI. We use the desorption/ionization bias of various matrixes for different metabolite classes along with dual polarities and a tandem MSI strategy. The use of multiple matrixes and dual polarities allows us to visualize various classes of compounds, while data-dependent MS/MS spectra acquired in the same MSI scans allow us to identify the compounds directly on the tissue. In a proof of concept application to a germinated corn seed, a total of 166 unique ions were determined to have high-quality MS/MS spectra, without counting structural isomers, of which 52 were identified as unique compounds. According to an estimation based on precursor MSI datasets, we expect over five hundred metabolites could be potentially identified and visualized once all experimental conditions are optimized and an MS/MS library is available. Finally, metabolites involved in the glycolysis pathway and tricarboxylic acid cycle were imaged to demonstrate the potential of this technology to better understand metabolic biology.

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Vibrational modes of ultrathin carbon nanomembrane mechanical resonators

We report measurements of vibrational mode shapes of mechanical resonators made from ultrathin carbon nanomembranes (CNMs) with a thickness of approximately 1 nm. CNMs are prepared from electron irradiation induced cross-linking of aromatic self-assembled monolayers and the variation of membrane thickness and/or density can be achieved by varying the precursor molecule. Single- and triple-layer freestanding CNMs were made by transferring them onto Si substrates with square/rectangular orifices. The vibration of the membrane was actuated by applying a sinusoidal voltage to a piezoelectric disk on which the sample was glued. The vibrational mode shapes were visualized with an imaging Mirau interferometer using a stroboscopic light source. Several mode shapes of a square membrane can be readily identified and their dynamic behavior can be well described by linear response theory of a membrane with negligible bending rigidity. By applying Fourier transformations to the time-dependent surface profiles, the dispersion relation of the transverse membrane waves can be obtained and its linear behavior verifies the membrane model. By comparing the dispersion relation to an analytical model, the static stress of the membranes was determined and found to be caused by the fabrication process.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Time-resolved in situ visualization of the structural response of zeolites during catalysis

Zeolites form an important class of materials that are widely used in various fields. Their unique properties come primarily from their size, shape, and connectivity of their sub-nm crystalline voids, the Si/Al ratio of the anionic framework, and the number and the nature of charge-balancing cations.The inhomogeneous distribution of the Si/Al ratio within crystals, and hence the cation density, the presence of organic residues, and their inhomogeneous distribution within crystals sensitively affect their performances because these factors influencethe intra-crystalline diffusion rates of the reactants and products. However, the information regarding these inhomogeneities in zeolite crystals cannot be obtained by conventional analytical tools because they only provide information regardingthe average properties of zeolite crystals. Here we employin situX-ray free electron laser-based time-resolved coherent X-ray diffraction imaging to investigate the internal deformations originating from the inhomogeneous Cu ion distributions in Cu-exchanged ZSM-5 zeolite crystals during the deoxygenation of nitrogen oxides with propene. We show that the interactions between the reactants and the active sites lead to an unusual strain distribution,which is confirmed by density functional theory simulations. Moreover, this elucidates the factors responsible for distinct active regions,which are essential to maximizing some applications with enhanced performances. These observations provide insights into the role of structural inhomogeneity in zeolites during a catalytic processand will assist the future design of zeolites for their applications.

36 MATERIALS SCIENCE↗

Mapping of Heterogeneous Catalyst Degradation in Polymer Electrolyte Fuel Cells

Pt catalysts in polymer electrolyte fuel cells degrade heterogeneously as the catalyst particles are exposed to local variations throughout the catalyst layer during operation. State-of-the-art analytical techniques for studying degradation of Pt catalysts do not possess fine spatial resolution to elucidate such non-uniform degradation behavior at a large electrode level. A new methodology is developed to spatially resolve and quantify the heterogeneous Pt catalyst degradation over a large area (several cm ) of aged MEAs based on synchrotron X-ray microdiffraction. PEFC single cells are aged using voltage cycling as an accelerated stress test and the degradation heterogeneity at a micrometer length scale is visualized by mapping Pt catalyst particle size after voltage cycling. It is demonstrated in detail that the Pt catalyst particle size growth is non-uniform and follows the flow field geometry. The Pt particle size growth is greater in the area under the flow field land, while it is minimal in the area under the flow field channel. Additional non-uniformity is observed with the Pt particle size increasing more rapidly at the air outlet area than the Pt particle size at the inlet area.

36 MATERIALS SCIENCE↗

Spontaneous Aerosol Ejection: Origin of Inorganic Particles in Biomass Pyrolysis

At high thermal flux and temperatures of approximately 500 °C, lignocellulosic biomass transforms to a reactive liquid intermediate before evaporating to condensable bio-oil for downstream upgrading to renewable fuels and chemicals. However, the existence of a fraction of nonvolatile compounds in condensed bio-oil diminishes the product quality and, in the case of inorganic materials, catalyzes undesirable aging reactions within bio-oil. In this study, ablative pyrolysis of crystalline cellulose was evaluated, with and without doped calcium, for the generation of inorganic-transporting aerosols by reactive boiling ejection from liquid intermediate cellulose. Further, aerosols were characterized by laser diffraction light scattering, inductively coupled plasma spectroscopy, and high-speed photography. Pyrolysis product fractionation revealed that approximately 3 % of the initial feed (both organic and inorganic) was transported to the gas phase as aerosols. Large bubble-to-aerosol size ratios and visualization of significant late-time ejections in the pyrolyzing cellulose suggest the formation of film bubbles in addition to the previously discovered jet formation mechanism.

09 BIOMASS FUELS↗

Biodegradation in Soil of PLA/PBAT Blends Compatibilized with Chain Extender

This paper presents a study of biodegradation, in soil, of samples of poly(butylene adipate-co-terephthalate)(PBAT), poly(lactic acid) (PLA) and blends of these materials prepared in torque rheometer with the addition of a chain extender. Film samples of these materials were buried in soil under controlled laboratory conditions. The degraded samples were regularly taken from soil and analyzed by visual inspection, size exclusion chromatography, differential scanning calorimetry and infrared spectroscopy. Respirometry biodegradation tests were conducted to assess samples mineralization degree. Blends showed higher degree of crystallinity compared to pure polymers. Crystallinity degree enhanced during the biodegradation process in all samples, being able to causing the samples to degrade slowly. The study showed the great complexity of the biodegradation process of PLA and PBAT blends when compatibilized with a chain extender. The biodegradation rate showed different results depending on the characteristic applied to evaluate it: visual, molecular weight or mineralization. The chain extender had strong influence in PBAT and blends degradation, slowing the process as observed by the variation of molecular weight and carbonyl index. Blends showed an intermediate behavior compared to the original polymers.

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