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At least 595 records · Page 33

Unleashing the Power of Knowledge Extraction from Scientific Literature in Catalysis

Valuable knowledge of catalysis is often hidden in a large amount of scientific literature. There is an urgent need to extract useful knowledge to facilitate scientific discovery. Here this work takes the first step toward the goal in the field of catalysis. Specifically, we construct the first information extraction benchmark data set that covers the field of catalysis and also develop a general extraction framework that can accurately extract catalysis-related entities from scientific literature with 90% extraction accuracy. We further demonstrate the feasibility of leveraging the extracted knowledge to help users better access relevant information in catalysis through an entity-aware search engine and a correlation analysis system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dynamics of Charged Species in Ionic-Neutral Block Copolymer and Surfactant Complexes [Structural Relaxation and Dynamics of Ionic-Neutral Block Copolymer Surfactant Complexes]

Structure–property relationships of ionic block copolymer (BCP) surfactant complexes are critical toward the progress of favorable engineering design of efficient charge-transport materials. In this paper, molecular dynamics simulations are used to understand the dynamics of charged-neutral BCP and surfactant complexes. The dynamics are examined for two different systems: charged-neutral double-hydrophilic and hydrophobic–hydrophilic block copolymers with oppositely charged surfactant moieties. The dynamics of the surfactant head, tails, and charges are studied for five different BCP volume fractions. We observe that the dynamics of the different species solely depend on the balance between electrostatic and entropic interactions between the charged species and the neutral monomers. The favorable hydrophobic–hydrophobic interactions and the unfavorable hydrophobic–hydrophilic interactions determine the mobilities of the monomers. The dynamical properties of the charge species influence complex formation. Structural relaxations exhibit length-scale dependent behavior, with slower relaxation at the radius of gyration length-scale and faster relaxation at the segmental length-scale, consistent with previous results. The dynamical analysis correlates ion-exchange kinetics to the self-assembly behavior of the complexes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mapping Molecular Adsorption Configurations with < 5 nm Spatial Resolution through Ambient Tip-Enhanced Raman Imaging

We interrogate para-mercaptobenzoic acid (MBA) molecules chemisorbed onto plasmonic silver nanocubes through tip-enhanced Raman (TER) spectral nano-imaging. Through a detailed examination of the spectra, aided by correlation analysis and density functional theory calculations, we find that MBA chemisorbs onto the plasmonic particles with at least two distinct configurations: S- and CO2-bound. High spatial resolution TER mapping allows us to distinguish between the distinct adsorption geometries with a pixel-limited (< 5 nm) spatial resolution under ambient laboratory conditions.

Gabel, Matthew L.↗

Effects of the Grazing Incidence Geometry on X-ray Photon Correlation Spectroscopy Measurements

X-ray photon correlation spectroscopy (XPCS) is a versatile tool to measure dynamics on the nanometer to micrometer scale in bulk samples. XPCS has also been applied in grazing incidence (GI) geometry to examine the dynamics of surface layers. However, considering GI scattering experiments more universally, the GI geometry leads to a superposition of signals due to reflection and refraction effects, also known from the distorted-wave Born approximation (DWBA). In this paper, the impact of these reflection and refraction effects on the correlation analysis is determined experimentally by measuring grazing incidence transmission XPCS (GT-XPCS) and grazing incidence XPCS (GI-XPCS) simultaneously for a thin film sample, showing non-equilibrium dynamics. Here the results of the GI and GT geometry comparisons are combined within the framework of the standardly applied, simplified DWBA. These calculations allow identifying the main contributions of the detected signal from the leading scattering terms along the out-of-plane direction q z , which dominate the measured intensity pattern on the detector. In combination with the calculation of the non-linear effect of refraction in GTSAXS and GISAXS, it is possible to identify experimental conditions that can be chosen to run experiments and data analysis as close as possible to transmission XPCS and to explain which limitations for data interpretations are observed. Consequently, the beam exposure can be significantly reduced by using GI geometry only. Calculations of experimental settings prior to experiments are detailed to determine suitable q z regions for a variety of material systems measured in bulk-sensitive GI-XPCS experiments, allowing us to determine the scaling behavior of typical decay times as a function of q that is comparable to the scaling behavior obtained in distortion-free GT-XPCS or transmission XPCS experiments.

36 MATERIALS SCIENCE↗

Mapping mechanical force propagation through biomolecular complexes

In this paper, we employ single-molecule force spectroscopy with an atomic force microscope (AFM) and steered molecular dynamics (SMD) simulations to reveal force propagation pathways through a mechanically ultrastable multidomain cellulosome protein complex. We demonstrate a new combination of network-based correlation analysis supported by AFM directional pulling experiments, which allowed us to visualize stiff paths through the protein complex along which force is transmitted. Finally, the results implicate specific force-propagation routes nonparallel to the pulling axis that are advantageous for achieving high dissociation forces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantifying the Correlation between Coordination Chemistry, Interfacial Formation, and Electrochemical Performances for Mg Battery Electrolytes

Here, the rise of magnesium batteries as promising post-Li-ion energy storage technologies has sparked considerable attention toward understanding the fundamental aspects of coordination chemistry concerning Mg cations in multivalent electrolytes. This exploration includes investigating how coordination influences crucial electrolyte properties like solubility, electroreduction stability, and the formation of the interphase, all of which are pivotal for practical battery applications. Despite recent progress in developing a few functional electrolytes, a comprehensive understanding of the solvation structure that can facilitate efficient Mg deposition performance and the formulation of general design rules based on the solvation structure is still lacking. In our study, we endeavor to establish a connection between solvent and anion interactions with Mg 2+ , interface formation, and cycling performance through a series of organic ether solvents (tetrahydrofuran, glyme, diglyme, and triglyme) and amine solvents (dimethylamine, 3-methoxypropylamine, and dimethoxyethylamine). Our findings reveal a distinct coordination trend for solvent/Mg 2+ and (Mg-TFSI):solvent across various solvents, which dictates the extent of ion pairing for TFSI salts with increasing solvent molecule size and denticity. The solvated species in the bulk electrolyte across different solvents lead to diverse interfacial chemistries with varying decomposition components. We also explore the cycling efficiency as well as Mg deposition overpotentials for different solvents. A correlation analysis was conducted to assess the interplay between the structure and performance. Lastly, we apply the insights gained from these results to tailor the relative anion/Mg 2+ coordination structures using cosolvent systems, aiming for improved cell performance.

25 ENERGY STORAGE↗

Strongly Modified Scaling of CO Hydrogenation in Metal Supported TiO Nanostripes

The boundary between a metal-oxide and its metal support (metal-oxide|support) provides an intriguing structural interface for heterogeneous catalysis. The hydrogenation of CO is a reaction step believed to be rate limiting in electro-chemical CO2 reduction. Density functional theory (DFT) calculations were performed to study this reaction step for a class of catalytic material: metal supported TiO nanostripe. The most stable adsorption sites were identified for all metal supports which showed a striking difference in adsorbate geometry between the strong and weak binding metal supports. The modified CO hydrogenation scaling shows a significant strengthening over (111) and (211) transition metal surfaces. Such enhancement can be attributed to a combination of geometrical effects and metal-oxide|support electronic interactions. A correlation analysis was performed to identify the key features needed to accurately predict *CO and *CHO adsorption energies on the TiO nanostripes and to further validate our physical analysis of the results. This structural motif seems to be a promising avenue to explore scaling modification in other metal-oxide materials and reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Surface Chemistry and Particle Morphology Changes in Pine Biomass under Indirect Thermal Gradients: Implications for Feed Screw Design

The conversion of biomass feedstocks into fuels and chemicals using fast pyrolysis is a promising approach to renewable energy. Feed screws that convey biomass to pyrolysis reactors, however, often encounter plugging. Indirect heating of the feed screw occurs due to contact with the pyrolysis chamber, resulting in a heating gradient ranging from ambient temperature (22 °C) to reactor temperature (500 °C). Given that major cell wall macromolecules, such as lignin, cellulose, and hemicellulose, begin to produce bio-oils and volatile resin acid compounds within this temperature gradient, we hypothesized that indirect heating during feed screw conveyance is sufficient to cause premature degradation of biomass. We characterized this degradation by observing increases in surface roughness, changes in overall particle morphology, and the production and deposition of bio-oils on biomass particle surfaces. Correlative analysis between optical in situ hot-stage microscopy, confocal Raman spectroscopy, and SEM analysis revealed that heating at temperatures as low as 375 °C caused significant increases in surface roughness, with large fissures forming between and within cell walls. Additionally, droplets of bio-oil were observed on particles, especially in the bark and cambium samples. This work suggests that these phenomena contribute to particle agglomeration, leading to feed screw plugging, and that engineering a solution to cool the feed screw could prevent particle agglomeration and reduce plugging incidents, thereby increasing biomass processing efficiency.

09 BIOMASS FUELS↗

Evidence of Aerosols as a Media for Rapid Daytime HONO Production over China

Current knowledge of daytime HONO sources remains incomplete. A large missing daytime HONO source has been found in many places around the world, including polluted regions in China. Conventional understanding and recent studies attributed this missing source mainly to ground surface processes or gas-phase chemistry, while assuming aerosols to be an insignificant media for HONO production. We analyze in situ observations of HONO and its precursors at an urban site in Beijing, China, and report an apparent dependence of the missing HONO source strength on aerosol surface area and solar ultraviolet radiation. Based on extensive correlation analysis and process-modeling, we propose that the rapid daytime HONO production in Beijing can be explained by enhanced hydrolytic disproportionation of NO2 on aqueous aerosol surfaces due to catalysis by dicarboxylic acid anions. The combination of high abundance of NO2, aromatic hydrocarbons, and aerosols over broad regions in China likely leads to elevated HONO levels, rapid OH production, and enhanced oxidizing capacity on a regional basis. Our findings call for attention to aerosols as a media for daytime heterogeneous HONO production in polluted regions like Beijing. This study also highlights the complex and uncertain heterogeneous chemistry in China, which merits future efforts of reconciling regional modeling and laboratory experiments, in order to understand and mitigate the regional particulate and O3 pollutions over China.

Liu, Zhen↗

Oxidation of Volatile Organic Compounds as the Major Source of Formic Acid in a Mixed Forest Canopy

Formic acid (HCOOH) is among the most abundant carboxylic acids in the atmosphere, but its budget is poorly understood. We present eddy flux, vertical gradient, and soil chamber measurements from a mixed forest and apply the data to better constrain HCOOH source/sink pathways. While the cumulative above-canopy flux was downward, HCOOH exchange was bidirectional, with extended periods of net upward and downward flux. Net above-canopy fluxes were mostly upward during warmer/drier periods. The implied gross canopy HCOOH source corresponds to 3% and 38% of observed isoprene and monoterpene carbon emissions and is 15× underestimated in a state-of-science atmospheric model (GEOS-Chem). Gradient and soil chamber measurements identify the canopy layer as the controlling source of HCOOH or its precursors to the forest environment; below-canopy sources were minor. A correlation analysis using an ensemble of marker volatile organic compounds suggests that secondary formation, not direct emission, is the major source driving ambient HCOOH.

58 GEOSCIENCES↗

Characterizing the Atmospheric Mn Cycle and Its Impact on Terrestrial Biogeochemistry

Abstract The role of manganese (Mn) in ecosystem carbon (C) biogeochemical cycling is gaining increasing attention. While soil Mn is mainly derived from bedrock, atmospheric deposition could be a major source of Mn to surface soils, with implications for soil C cycling. However, quantification of the atmospheric Mn cycle, which comprises emissions from natural (desert dust, sea salts, volcanoes, primary biogenic particles, and wildfires) and anthropogenic sources (e.g., industrialization and land‐use change due to agriculture), transport, and deposition, remains uncertain. Here, we use compiled emission data sets for each identified source to model and quantify the atmospheric Mn cycle by combining an atmospheric model and in situ atmospheric concentration measurements. We estimated global emissions of atmospheric Mn in aerosols (<10 μm in aerodynamic diameter) to be 1,400 Gg Mn year −1 . Approximately 31% of the emissions come from anthropogenic sources. Deposition of the anthropogenic Mn shortened Mn “pseudo” turnover times in 1‐m‐thick surface soils (ranging from 1,000 to over 10,000,000 years) by 1–2 orders of magnitude in industrialized regions. Such anthropogenic Mn inputs boosted the Mn‐to‐N ratio of the atmospheric deposition in non‐desert dominated regions (between 5 × 10 −5 and 0.02) across industrialized areas, but that was still lower than soil Mn‐to‐N ratio by 1–3 orders of magnitude. Correlation analysis revealed a negative relationship between Mn deposition and topsoil C density across temperate and (sub)tropical forests, consisting with atmospheric Mn deposition enhancing carbon respiration as seen in in situ biogeochemical studies.

Environmental Sciences & Ecology↗

Tidally Modulated Glacial Slip and Tremor at Helheim Glacier, Greenland

Numerical modeling of ice sheet motion and hence projections of global sea level rise require information about the evolving subglacial environment, which unfortunately remains largely unknown due to its difficulty of access. Here we advance such subglacial observations by reporting multi–year observations of seismic tremor likely associated with glacier sliding at Helheim Glacier. This association is confirmed by correlation analysis between tremor power and multiple environmental forcings on different timescales. Variations of the observed tremor power indicate that different factors affect glacial sliding on different timescales. Effective pressure may control glacial sliding on long (seasonal/annual) timescales, while tidal forcing modulates the sliding rate and tremor power on short (hourly/daily) timescales. Polarization results suggest that the tremor source comes from an upstream subglacial ridge. This observation provides insights on how different factors should be included in ice sheet modeling and how their timescales of variability play an essential role.

54 ENVIRONMENTAL SCIENCES↗

Charge density wave memory in a cuprate superconductor

Although CDW correlations are a ubiquitous feature of the superconducting cuprates, their disparate properties suggest a crucial role for pinning the CDW to the lattice. Here, we report coherent resonant X-ray speckle correlation analysis, which directly determines the reproducibility of CDW domain patterns in La 1.875 Ba 0.125 CuO 4 (LBCO 1/8) with thermal cycling. While CDW order is only observed below 54 K, where a structural phase transition creates inequivalent Cu-O bonds, we discover remarkably reproducible CDW domain memory upon repeated cycling to far higher temperatures. That memory is only lost on cycling to 240(3) K, which recovers the four-fold symmetry of the CuO 2 planes. We infer that the structural features that develop below 240 K determine the CDW pinning landscape below 54 K. This opens a view into the complex coupling between charge and lattice degrees of freedom in superconducting cuprates.

36 MATERIALS SCIENCE↗

Iron mineral dissolution releases iron and associated organic carbon during permafrost thaw

It has been shown that reactive soil minerals, specifically iron(III) (oxyhydr)oxides, can trap organic carbon in soils overlying intact permafrost, and may limit carbon mobilization and degradation as it is observed in other environments. However, the use of iron(III)-bearing minerals as terminal electron acceptors in permafrost environments, and thus their stability and capacity to prevent carbon mobilization during permafrost thaw, is poorly understood. We have followed the dynamic interactions between iron and carbon using a space-for-time approach across a thaw gradient in Abisko (Sweden), where wetlands are expanding rapidly due to permafrost thaw. We show through bulk (selective extractions, EXAFS) and nanoscale analysis (correlative SEM and nanoSIMS) that organic carbon is bound to reactive Fe primarily in the transition between organic and mineral horizons in palsa underlain by intact permafrost (41.8 ±10.8 mg carbon per g soil, 9.9 to 14.8% of total soil organic carbon). During permafrost thaw, water-logging and O 2 limitation lead to reducing conditions and an increase in abundance of Fe(III)-reducing bacteria which favor mineral dissolution and drive mobilization of both iron and carbon along the thaw gradient. By providing a terminal electron acceptor, this rusty carbon sink is effectively destroyed along the thaw gradient and cannot prevent carbon release with thaw.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Application of pan-sharpening algorithm for correlative multimodal imaging using AFM-IR

The coupling of atomic force microscopy with infrared spectroscopy (AFM-IR) offers the unique capability to characterize the local chemical and physical makeup of a broad variety of materials with nanoscale resolution. However, in order to fully utilize the measurement capability of AFM-IR, a three-dimensional dataset (2D map with a spectroscopic dimension) needs to be acquired, which is prohibitively time-consuming at the same spatial resolution of a regular AFM scan. In this paper, we provide a new approach to process spectral AFM-IR data based on a multicomponent pan-sharpening algorithm. This approach requires only a low spatial resolution spectral and a limited number of high spatial resolution single wavenumber chemical maps to generate a high spatial resolution hyperspectral image, greatly reducing data acquisition time. As a result, we are able to generate high-resolution maps of component distribution, produce chemical maps at any wavenumber available in the spectral range, and perform correlative analysis of the physical and chemical properties of the samples. We highlight our approach via imaging of plant cell walls as a model system and showcase the interplay between mechanical stiffness of the sample and its chemical composition. We believe our pan-sharpening approach can be more generally applied to different material classes to enable deeper understanding of that structure-property relationship at the nanoscale.

36 MATERIALS SCIENCE↗

Coupling physics in machine learning to predict properties of high-temperatures alloys

Abstract High-temperature alloy design requires a concurrent consideration of multiple mechanisms at different length scales. We propose a workflow that couples highly relevant physics into machine learning (ML) to predict properties of complex high-temperature alloys with an example of the 9–12 wt% Cr steels yield strength. We have incorporated synthetic alloy features that capture microstructure and phase transformations into the dataset. Identified high impact features that affect yield strength of 9Cr from correlation analysis agree well with the generally accepted strengthening mechanism. As a part of the verification process, the consistency of sub-datasets has been extensively evaluated with respect to temperature and then refined for the boundary conditions of trained ML models. The predicted yield strength of 9Cr steels using the ML models is in excellent agreement with experiments. The current approach introduces physically meaningful constraints in interrogating the trained ML models to predict properties of hypothetical alloys when applied to data-driven materials.

36 MATERIALS SCIENCE↗

Data analytics approach to predict high-temperature cyclic oxidation kinetics of NiCr-based Alloys

Abstract Although of practical importance, there is no established modeling framework to accurately predict high-temperature cyclic oxidation kinetics of multi-component alloys due to the inherent complexity. We present a data analytics approach to predict the oxidation rate constant of NiCr-based alloys as a function of composition and temperature with a highly consistent and well-curated experimental dataset. Two characteristic oxidation models, i.e., a simple parabolic law and a statistical cyclic oxidation model, have been chosen to numerically represent the high-temperature oxidation kinetics of commercial and model NiCr-based alloys. We have successfully trained machine learning (ML) models using highly ranked key input features identified by correlation analysis to accurately predict experimental parabolic rate constants ( k p ). This study demonstrates the potential of ML approaches to predict oxidation kinetics of alloys over wide composition and temperature ranges. This approach can also serve as a basis for introducing more physically meaningful ML input features to predict the comprehensive cyclic oxidation behavior of multi-component high-temperature alloys with proper constraints based on the known underlying mechanisms.

36 MATERIALS SCIENCE↗

Genetic loci simultaneously controlling lignin monomers and biomass digestibility of rice straw

Lignin content and composition are crucial factors affecting biomass digestibility. Exploring the genetic loci simultaneously affecting lignin-relevant traits and biomass digestibility is a precondition for lignin genetic manipulation towards energy crop breeding. In this study, a high-throughput platform was employed to assay the lignin content, lignin composition and biomass enzymatic digestibility of a rice recombinant inbred line population. Correlation analysis indicated that the absolute content of lignin monomers rather than lignin content had negative effects on biomass saccharification, whereas the relative content of p-hydroxyphenyl unit and the molar ratio of p-hydroxyphenyl unit to guaiacyl unit exhibited positive roles. Eight QTL clusters were identified and four of them affecting both lignin composition and biomass digestibility. Here, the additive effects of clustered QTL revealed consistent relationships between lignin-relevant traits and biomass digestibility. Pyramiding rice lines containing the above four positive alleles for increasing biomass digestibility were selected and showed comparable lignin content, decreased syringyl or guaiacyl unit and increased molar percentage of p-hydroxyphenyl unit, the molar ratio of p-hydroxyphenyl unit to guaiacyl unit and sugar releases. More importantly, the lodging resistance and eating/cooking quality of pyramiding lines were not sacrificed, indicating the QTL information could be applied to select desirable energy rice lines.

59 BASIC BIOLOGICAL SCIENCES↗