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At least 217 records · Page 12

Reflectance and Thermal Infrared Spectroscopy of Mars: Relationship Between ISM and TES for Compositional Determinations

Reflectance spectroscopy has demonstrated that high albedo surfaces on Mars contain heavily altered materials with some component of hematite, poorly crystalline ferric oxides, and an undefined silicate matrix. The spectral properties of many low albedo regions indicate crystalline basalts containing both low and high calcium pyroxene, a mineralogy consistent with the basaltic SNC meteorites. The Thermal Emission Spectrometer (TES) experiment on the Mars Geochemical Surveyor has acquired critical new data relevant to surface composition and mineralogy, but in a wavelength region that is complementary to reflectance spectroscopy. The essence of the completed research was to analyze TES data in the context of reflectance data obtained by the French ISM imaging spectrometer experiment in 1989. This approach increased our understanding of the complementary nature of these wavelength regions for mineralogic determinations using actual observations of the martian surface. The research effort focused on three regions of scientific importance: Syrtis Major-Isidis Basin, Oxia Palus-Arabia, and Valles Marineris. In each region distinct spatial variations related to reflectance, and in derived mineralogic information and interpreted compositional units were analyzed. In addition, specific science questions related to the composition of volcanics and crustal evolution, soil compositions and pedogenic processes, and the relationship between pristine lithologies and weathering provided an overall science-driven framework for the work. The detailed work plan involved colocation of TES and ISM data, extraction of reflectance and emissivity spectra from areas of known reflectance variability, and quantitative analysis using factor analysis and statistical techniques to determine the degree of correspondence between these different wavelength regions. Identified coherent variations in TES spectroscopy were assessed against known atmospheric effects to validate that the variations are due to surface properties. With this new understanding of reflectance and emission spectroscopy, mineralogic interpretations were derived and applied to the science objectives of the three regions.

Boyce, Joseph↗

Verb Sense Disambiguation for Densifying Knowledge Graphs in Earth Science

We begin with an ambitious goal: to create a knowledge graph that spans the entire discipline of Earth science. In order to achieve this, we need to apply Natural Language Processing (NLP) techniques on Earth science journal articles to extract their semantic components for the graph. When sentences from Earth science journal articles are broken down into their semantic components and loaded onto a graph, the relationships among these semantic components are represented by the verbs in the sentences. However, since there are multiple verbs in English that can be used to denote the same meaning, the knowledge graph can become sparse and so can the results when we query the graph. In order to ensure quality results, it would be desirable to consolidate similar verbs into a single "class". So, this is the problem at hand: how do we make sure that multiple verbs that mean the same thing are represented as a single class of verb in the knowledge graph? Or in other words, how do we distinguish which meaning a particular verb takes given a particular sentence? In this poster, we demonstrate a potential technique to solve this problem.

Ashish Acharya↗

Phenomenology of TMD parton distributions in Drell-Yan and 𝑍 0 boson production in a hadron structure oriented approach

We present a first practical implementation of a recently proposed hadron structure oriented (HSO) approach to transverse momentum dependent (TMD) phenomenology applied to Drell-Yan-like processes, including lepton pair production at moderate 𝑄 2 and 𝑍 0 boson production. We compare and contrast general features of our methodology with other common practices and emphasize aspects that we view as improvements. Separately, we discuss the importance of treatments that preserve various theoretical properties of the nonperturbative parts of TMD parametrizations for future applications that have the extraction of hadron structure as a primary goal. These include the HSO’s preservation of a basic TMD parton-model-like framework even while accounting for full TMD factorization and evolution, explicit preservation of the integral relationship between TMD and collinear parton density functions, and the ability to meaningfully compare different theoretical models of nonperturbative TMD parton distributions. In our examples, we show that there is significant sensitivity at moderate 𝑄 2 to both the form of the nonperturbative transverse momentum dependence and the parametrization of collinear parton densities. However, we also find that evolving to 𝑄 2 =𝑀$^2_𝑍$, without fitting, results in a satisfactory postdiction of existing data for 𝑍0 production, nearly independently of the modeling of nonperturbative transverse momentum behavior. We argue that this demonstrates that moderate 𝑄 measurements should be given greater weight than high 𝑄 measurements in extractions of nonperturbative transverse momentum dependence. We also obtain new extractions of the nonperturbative Collins-Soper kernel within the HSO approach. We discuss its features and compare with some earlier extractions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The Effects of Herbarium Specimen Characteristics on Short-Read NGS Sequencing Success in Nearly 8000 Specimens: Old, Degraded Samples Have Lower DNA Yields but Consistent Sequencing Success

Phylogenetic datasets are now commonly generated using short-read sequencing technologies unhampered by degraded DNA, such as that often extracted from herbarium specimens. The compatibility of these methods with herbarium specimens has precipitated an increase in broad sampling of herbarium specimens for inclusion in phylogenetic studies. Understanding which sample characteristics are predictive of sequencing success can guide researchers in the selection of tissues and specimens most likely to yield good results. Multiple recent studies have considered the relationship between sample characteristics and DNA yield and sequence capture success. Here we report an analysis of the relationship between sample characteristics and sequencing success for nearly 8,000 herbarium specimens. This study, the largest of its kind, is also the first to include a measure of specimen quality (“greenness”) as a predictor of DNA sequencing success. We found that taxonomic group and source herbarium are strong predictors of both DNA yield and sequencing success and that the most important specimen characteristics for predicting success differ for DNA yield and sequencing: greenness was the strongest predictor of DNA yield, and age was the strongest predictor of proportion-on-target reads recovered. Surprisingly, the relationship between age and proportion-on-target reads is the inverse of expectations; older specimens performed slightly better in our capture-based protocols. We also found that DNA yield itself is not a strong predictor of sequencing success. Most literature on DNA sequencing from herbarium specimens considers specimen selection for optimal DNA extraction success, which we find to be an inappropriate metric for predicting success using next-generation sequencing technologies.

54 ENVIRONMENTAL SCIENCES↗

Integrated package of electron cyclotron emission imaging data processing and forward modeling in OMFIT

An Electron Cyclotron Emission Imaging (ECEI) data analysis module has been developed for the OMFIT platform to accommodate the needs of users at the DIII-D tokamak for physics applications. The user can easily access the ECEI spatial observation windows in the plasma that are calculated based on the automatically retrieved hardware setup and available DIII-D equilibria, perform spectral analysis, and make 2D electron temperature fluctuation images. The module provides a powerful data post processing package for extracting important physics parameters from the 2D measurements, including the radial structure and poloidal mode number of Alfven Eigenmodes, as well as the frequency-vs-wavenumber dispersion relationship of broadband MHD. Lastly, the module propagates characterized synthetic fluctuations for the user, so one can perform forward modeling tasks with simple analytical fluctuations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Climatological occurrences of hail and tornadoes associated with mesoscale convective systems in the United States

Hail and tornadoes are hazardous weather events responsible for significant property damage and economic loss worldwide. The most devastating occurrences of hail and tornadoes are commonly produced by supercells in the United States. However, these supercells may also grow upscale into mesoscale convective systems (MCSs) or be embedded within them. The relationship between hail and tornado occurrences with MCSs in the long-term climatology has not been thoroughly examined. In this study, radar features associated with MCSs are extracted from a 14-year MCS tracking database across the contiguous United States, and hazard reports are mapped to these MCS features. We investigate the characteristics of hail and tornadoes in relation to MCSs, considering seasonal and regional variabilities. On average, 8 %–17 % of hail events and 17 %–32 % of tornado events are associated with MCSs, depending on the criteria used to define MCSs. The highest total and MCS-associated hazard events occur from March to May, while the highest MCS-associated portion (23 % for hail and 45 % for tornadoes) is observed in winter (December–February) due to the dominance of MCSs caused by strong synoptic forcing. As hailstone size increases, the fraction associated with MCS decreases, but there is an increasing trend for tornado severity from EF0 to EF3 (Enhanced Fujita Scale). Violent tornadoes at EF4 and EF5 associated with MCSs were also observed, which are generated by supercells embedded within MCSs.

54 ENVIRONMENTAL SCIENCES↗

Analysis of interface cracks in adhesively bonded lap shear joints, part 4

Conservation laws of elasticity for nonhomogeneous materials were developed and were used to study the crack behavior in adhesively bonded lap shear joints. By using these laws and the fundamental relationships in fracture mechanics of interface cracks, the problem is reduced to a pair of linear algebraic equations, and stress intensity solutions can be determined directly by information extracted from the far field. The numerical results obtained show that: (1) in the lap-shear joint with a given adherend, the opening-mode stress intensity factor, (K sub 1) is always larger than that of the shearing-mode (K sub 2); (2) (K sub 1) is not sensitive to adherent thickness abut (K sub 2) increases rapidly with increasing thickness; and (3) (K sub 1) and (K sub 2) increase simultaneously as the interfacial crack length increases.

Wang, S. S.↗

Positron annihilation lifetime spectroscopy study of polyvinylpyrrolidone‐added polyvinylidene fluoride membranes: Investigation of free volume and permeation relationships

ABSTRACT Polyvinylidene fluoride (PVDF) membranes were prepared via the phase inversion method from casting solutions containing PVDF, dimethylformamide (DMF), and polyvinylpyrrolidone (PVP) as pore former. PVP was used in the casting solution in a range of 0–5 wt % and extracted. The effect on membranes of using PVP in the casting process was analyzed by X‐ray diffraction, differential scanning calorimetry, scanning electron microscopy, viscosity, and water permeability techniques. With an increase of PVP from 0 to 5 wt %, the PVDF casting solution viscosities increased from 858 to 1148 cP; the resulting PVDF membrane thickness increased; and the crystallinity of PVDF membranes decreased from 40.0 to 33.3%, which indicates that the addition of PVP inhibits the degree of crystallization in the PVDF membranes. SEM results revealed the shape and size of macropores in the membranes; these macropores changed after PVP addition to the casting solutions. The impact of structural changes on free‐volume properties was evaluated using positron annihilation lifetime spectroscopy (PALS) studies. PALS analysis indicated no effect on the average radius (~3.4 Å) of membrane free‐volume holes from the addition of PVP to the casting solution. However, the percentage of o ‐Ps pick‐off annihilation intensity, I 3 , increased from 1.7 to 5.1% with increased PVP content. Further, increasing the PVP content from 0.5 to 5% resulted in an increased final pure water permeability flux. For instance, the 210 min flux for a 14% PVDF + 0.5% PVP membrane was found to be 3.3 times greater than a control membrane having the same PVDF concentration. © 2020 Wiley Periodicals, Inc. J. Polym. Sci. 2020 , 58 , 589–598

Eren, Bilge↗

Dialing in Direct Air Capture of CO 2 by Crystal Engineering of Bis-iminoguanidines

Direct air capture (DAC) technologies that extract carbon dioxide from the atmosphere via chemical processes have the potential to restore the atmospheric CO 2 concentration to an optimal level. This study elucidates structure-property relationships in DAC by crystallization of bis-iminoguanidine (BIG) carbonate salts. Here, their crystal structures are analyzed by X-ray and neutron diffraction to accurately measure key structural parameters including molecular conformations, hydrogen bonding, and π-stacking. Experimental measurements of key properties, such as aqueous solubilities and regeneration energies and temperatures, are complemented by first-principles calculations of lattice and hydration free energies, as well as free energies of reactions with CO 2 , and BIG regenerations. Minor structural modifications in the molecular structure of the BIGs are found to result in major changes in the crystal structures and the aqueous solubilities within the series, leading to enhanced DAC.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The use of aerial photography to quantitatively delineate mixing zones - A progress report

Aerial photography has been used to characterize and model the mixing zones which result from waste effluent discharges at seven river sites throughout the state of Wisconsin. The mixing zone is defined as the portion of the river where the waste effluent is totally mixed with the ambient receiving water. An integrated program of field sampling, mathematical modeling, laboratory modeling, and remote sensing was conducted to develop a quantitative relationship for the volumetric configuration of the mixing zone as a function of the measurable characteristics of various effluents, outfalls, and receiving water bodies. Analysis of scanning microdensitometer data extracted from 9-in. color IR transparencies has confirmed the utility of employing image density measurements to quantitatively delineate surficial concentration patterns within the mixing zone.

Lillesand, T. M.↗

The scatterometer - Data and applications

The techniques used to extract oceanographic and meteorological parameters from satellite radar scatterometer data are described and demonstrated, primarily on the basis of Seasat data. The principles of backscatter measurement and the general relationships between wind and wave fields are summarized, and the construction of geophysical data records from scatterometer swaths is explained. Particular attention is given to surface-layer dynamics and stresses; planetary-boundary-layer dynamics; averaging methods; the estimation of heat, moisture, and CO2 flux coefficients; the determination of pressure fields; storm monitoring; synoptic-scale analysis; climate analysis; and ocean dynamics. The capabilities and potential applications of the planned ERS-1, NSCAT, and SCANSCAT satellite scatterometers are briefly indicated.

Brown, R. A.↗

Integration of the Biot–Gassmann Fluid Substitution Method and Machine Learning-Based Velocity–Stress Relationship for Estimating In Situ Stresses

Recent advancements have shown that in situ stresses can be reliably estimated through an integrated machine/deep learning (ML/DL)-based framework, which relies on models trained and validated using true triaxial ultrasonic velocity (TUV) experimental data that involve measurements of ultrasonic velocity in saturated rocks under varying stress configurations. However, when the goal is to interpret lower frequency measurements, it may be more appropriate to run experiments on dry rocks and then obtain Biot–Gassmann-derived equivalent saturated velocities (low-frequency approximation) and employ these quantities for training ML/DL models to predict in situ stress. Whether the dispersion effect of frequency on the velocity–stress relationship substantially impacts in situ stress prediction is an important and unresolved question. This work presents an enhancement of ML/DL-based workflow by training and implementing ML/DL models using equivalent saturated acoustic velocities (low-frequency) obtained by applying Biot–Gassmann fluid substitution on the ultrasonic velocities of dry cores. The models were trained on TUV data sets derived from three subsurface cores extracted from the geothermal well 16B(78)-32 at the Utah FORGE site. Each core was subjected to 75 unique stress configurations for velocity measurement in the dry state. The ML/DL trained on the TUV data set with equivalent saturated velocities demonstrated promising performance to predict in situ stress in subsurface geological rocks using velocity–stress relationships with R 2 of 0.86, 0.971, and 0.975 and root mean squared error (RMSE) of 2.59, 1.92, and 1.80 for validation/testing phases of vertical, minimum horizontal, and maximum horizontal stress models, respectively. Additionally, interpretation and explanation by Shapley additive explanations (SHAP) analysis further improved scientific validation and model reliability for estimating in situ stresses.

colloids↗

Third-order photon correlations extract single-nanocrystal multiexciton properties in solution

Colloidal semiconductor nanocrystals are considered promising materials for high-flux optical applications, including lasing, light-emitting diodes, biological imaging, and quantum optics. In high-flux applications, multiexcitons can significantly contribute to emission, influencing its brightness, spectral purity, and kinetics. As a result, understanding and controlling multiexciton emission in colloidal nanocrystal materials is of the utmost importance. In the past, single-nanocrystal photon correlation methods have been applied to understand biexciton and triexciton efficiencies, lifetimes, and spectra. While powerful, such methods suffer from user selection bias and require stable emission from single nanocrystals. To compensate for this shortcoming, second-order correlation methods were developed to extract sample-averaged biexciton properties from a solution of nanocrystals. Until now, however, the analogous third-order solution photon correlation methods remained unexplored. In this work, we present a pair of third-order photon correlation techniques to obtain the sample-averaged single-nanocrystal triexciton quantum yield and lifetime in a solution-phase experiment. These techniques derive from the relationship between the Poisson probability of nanocrystal photon absorption and the intrinsic probability of nanocrystal photon emission. We validate the theoretical background of these techniques by creating a numerical model to simulate the diffusion and emission of many nanocrystals in solution. Our simulations confirm that the average triexciton quantum yield and triexciton lifetime can be extracted from a solution of nanocrystals. These techniques will enable researchers to gain a better understanding of the fundamental multiexciton properties of colloidal nanocrystals.

Horowitz, Jonah R. [Massachusetts Institute of Tec↗

Molecular and Topographical Organization: Influence on Cicada Wing Wettability and Bactericidal Properties

Numerous natural surfaces have micro/nanostructures that result in extraordinary functionality, such as superhydrophobicity, self-cleaning, antifogging, and antimicrobial properties. One such example is the cicada wing, where differences in nanopillar geometry and composition among species can impact and influence the degree of exhibited properties. To understand the relationships between surface topography and chemical composition with multifunctionality, the wing properties of Neotibicen pruinosus (superhydrophobic) and Magicicada cassinii (hydrophobic) cicadas are investigated at time points after microwave-assisted extraction of surface molecules to characterize the chemical contribution to nanopillar functionality. Electron microscopy of the wings throughout the extraction process illustrates nanoscale topographical changes, while concomitant changes in hydrophobicity, bacterial fouling, and bactericidal properties are also measured. Extract analysis reveals the major components of the nanostructures to be fatty acids and saturated hydrocarbons ranging from C17 to C44. Effects on the antimicrobial character of a wing surface with respect to the extracted chemicals suggest that the molecular composition of the nanopillars plays both a direct and an indirect role in concert with nanopillar geometry. The data presented not only correlates the nanopillar molecular organization to macroscale functional properties, but it also presents design guidelines to consider during the replication of natural nanostructures onto engineered substrates to induce desired properties.

59 BASIC BIOLOGICAL SCIENCES↗

Microscopic and Macroscopic Characterization of Grain Boundary Energy and Strength in Silicon Carbide via Machine-Learning Techniques

Predicting the properties of grain boundaries poses a challenge because of the complex relationships between structural and chemical attributes both at the atomic and continuum scales. Grain boundary systems are typically characterized by parameters used to classify local atomic arrangements in order to extract features such as grain boundary energy or grain boundary strength. The present work utilizes a combination of high-throughput atomistic simulations, macroscopic and microscopic descriptors, and machine-learning techniques to characterize the energy and strength of silicon carbide grain boundaries. Additionally, a diverse data set of symmetric tilt and twist grain boundaries are described using macroscopic metrics such as misorientation, the alignment of critical low-index planes, and the Schmid factor, but also in terms of microscopic metrics, by quantifying the local atomic structure and chemistry at the interface. These descriptors are used to create random-forest regression models, allowing for their relative importance to the grain boundary energy and decohesion stress to be better understood. Results show that while the energetics of the grain boundary were best described using the microscopic descriptors, the ability of the macroscopic descriptors to reasonably predict grain boundaries with low energy suggests a link between the crystallographic orientation and the resultant atomic structure that forms at the grain boundary within this regime. For grain boundary strength, neither microscopic nor macroscopic descriptors were able to fully capture the response individually. However, when both descriptor sets were utilized, the decohesion stress of the grain boundary could be accurately predicted. These results highlight the importance of considering both macroscopic and microscopic factors when constructing constitutive models for grain boundary systems, which has significant implications for both understanding the fundamental mechanisms at work and the ability to bridge length scales.

36 MATERIALS SCIENCE↗

Nanoscale covariance magnetometry with diamond quantum sensors

Nitrogen vacancy (NV) centers in diamond are atom-scale defects that can be used to sense magnetic fields with high sensitivity and spatial resolution. Typically, the magnetic field is measured by averaging sequential measurements of single NV centers, or by spatial averaging over ensembles of many NV centers, which provides mean values that contain no nonlocal information about the relationship between two points separated in space or time. In this work, we propose and implement a sensing modality whereby two or more NV centers are measured simultaneously, and we extract temporal and spatial correlations in their signals that would otherwise be inaccessible. We demonstrate measurements of correlated applied noise using spin-to-charge readout of two NV centers and implement a spectral reconstruction protocol for disentangling local and nonlocal noise sources.

47 OTHER INSTRUMENTATION↗

Hierarchical classification in high dimensional numerous class cases

As progress in new sensor technology continues, increasingly high resolution imaging sensors are being developed. These sensors give more detailed and complex data for each picture element and greatly increase the dimensionality of data over past systems. Three methods for designing a decision tree classifier are discussed: a top down approach, a bottom up approach, and a hybrid approach. Three feature extraction techniques are implemented. Canonical and extended canonical techniques are mainly dependent upon the mean difference between two classes. An autocorrelation technique is dependent upon the correlation differences. The mathematical relationship between sample size, dimensionality, and risk value is derived.

Kim, Byungyong↗