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At least 325 records · Page 18

Disorderly Conduct of Benzamide IV: Crystallographic and Computational Analysis of High Entropy Polymorphs of Small Molecules

Benzamide, a simple derivative of benzoic acid and a common intermediate of pharmaceutical compounds, was reported to form two polymorphs in 1832, but the single crystal structure of the more stable form was not solved until 1959. Nearly 50 years later, the second form was characterized by powder diffraction, followed shortly thereafter by characterization of a third form, a polytype of the most thermodynamically stable Form I. These two new forms, Forms II and III, are metastable. Herein, we describe a fourth polymorph, Form IV, discovered by melt crystallization concurrently with its crystallization under confinement at small length scales (<10 nm), where it is stable indefinitely. Form III exists under confinement in larger pores, and melting point data for different pore sizes corroborate the existence of Form IV below 10 nm. Form IV is highly disordered, precluding indexing of powder diffraction data other than hk0 reflections. Nonetheless, a combination of powder X-ray diffraction and computational crystal structure prediction reveals that Form IV contains a 2D motif resembling that of Form II, but with longrange order in the third dimension masked by ubiquitous stacking faults. This approach relies on distilling a large number of candidate structures to a few possible disorder models based on benzamide tetrads that organize in 2D parquet-like tiles, with organization along the third dimension, that can be modeled with various stacking fault configurations having distinct intermolecular interactions and translations in the dimension orthogonal to the tiling planes. These observations reveal a bewildering crystallographic complexity for such a simple molecule. Nonetheless, the approach described herein demonstrates that challenging structures that may be abandoned prematurely because of poor crystallinity, twinning, or disorder can be solved.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Regional Moment Tensor Inversion Using Rotational Observations

There are benefits from the addition of rotational motions to translational displacements for moment tensor (MT) inversions. The rotational radiation pattern is orthogonal to the shear radiation pattern, thus incorporating rotations is equivalent to gaining another observation point on the focal sphere. We demonstrated this by simulating curl and displacement wavefields for a regional distance station. Thus, one 6-C station (3-Component translational + 3-Component rotational) gathers the same information on radiation pattern as two 3-C stations at 90° azimuth from one another along the focal plane axis, which is sometimes difficult to obtain when restricted to surface sensors. We added rotational Green's functions to a regional MT inversion scheme (long-period, time-domain, and linear inversion) by computing spatial gradients from f-κ reflectivity synthetics. For rotational data, we used Array Derived Rotations (ADR) from Piñon Flats Observatory Array and Golay array deployed during IRIS Community Wavefield Demonstration Experiment. The hope is to ultimately use compact and field deployable broadband rotational seismometers instead of ADRs. Rotational motions were predicted from well-constrained deviatoric MT solutions of nine earthquakes recorded by the arrays and other seismic networks. Additionally, we formed three station sparse datasets with (3-C and 6-C) and without rotational ground motions (3-C only) for eight earthquakes testing the benefits of including rotational waveforms in MT inversions when they are equally weighted with translational waveforms. Adding rotational motions improved the double-couple components and reduced compensated-linear-vector-dipole and isotropic components in full-MT solutions using sparse datasets with poor coverage.

58 GEOSCIENCES↗

Ex situ metrology and data analysis for optimization of beamline performance of aspherical pre-shaped x-ray mirrors at the advanced light source

Super high quality aspherical x-ray mirrors with a residual slope error of ~100 nrad (root-mean-square) and a height error of ~1-2 nm (peak-to-valley), and even lower, are now available from a number of the most advanced vendors utilizing deterministic polishing techniques. The mirror specification for the fabrication is based on the simulations of the desired performance of the mirror in the beamline optical system and is normally given with the acceptable level of deviation of the mirror figure and finish from the desired ideal shape. For example, in the case of aspherical x-ray mirrors designed for the Advanced Light Source (ALS) QERLIN beamline, the ideal shape is defined with the beamline application (conjugate) parameters and their tolerances. Here, we first introduce an original procedure and dedicated software developed at the ALS X-Ray Optics Laboratory (XROL) for optimization of beamline performance of pre-shaped hyperbolic and elliptical mirrors. The optimization is based on results of ex situ surface slope metrology and consists in minimization of the mirror shape error by determining the conjugate parameters of the best-fit ideal shape within the specified tolerances. We describe novel optical metrology instrumentation, measuring techniques, and analytical methods used at the XROL for acquisition of surface slope data and optimization of the optic’s beamline performance. The high efficacy of the developed experimental methods and data analysis procedures is reflected in results of measurements with and performance optimization of hyperbolic and elliptical cylinder mirrors designed and fabricated for the ALS QERLIN beamline.

47 OTHER INSTRUMENTATION↗

Design Considerations for Secure Wireless Sensor Communication Systems in Harsh Electromagnetic Environments of Nuclear Reactor Facilities

Wireless sensors can potentially play a significant role in safety, efficiency, and reliability of the instrumentation and control process in current and next generation nuclear power reactors. While conventional narrowband wireless sensors have shown a certain level of success in some nuclear power plants (NPPs), the radio frequency (RF) propagation challenges posed by the heavy metallic and cluttered environment of NPPs has prevented their widespread use in such operations. Furthermore, these challenges include RF wave propagation in harsh (reflective, absorptive, cluttered) environments, data security issues, and RF interference to and from other devices in the vicinity of a nuclear reactor core. In this paper, first we address how ultrawideband (UWB) RF technology can complement the narrowband (i.e., WiFi) solutions that have been used in some NPPs by providing an alternative solution in addressing the signal propagation issues in such electromagnetically harsh environments. Second, we discuss and present the UWB software simulation results on multipath harsh environments, and then address the data security issues. In the final sections of the paper, we present the experimental results of using UWB signaling in a representative harsh environment conducted at the Massachusetts Institute of Technology research reactor site. We plan to develop the UWB communications hardware based on the results of this paper and report on its performance in the field with emphasis on the security aspects of the system in a subsequent paper.

42 ENGINEERING↗

Refinements for Bragg coherent X-ray diffraction imaging: electron backscatter diffraction alignment and strain field computation

Bragg coherent X-ray diffraction imaging (BCDI) allows the 3D measurement of lattice strain along the scattering vector for specific microcrystals. If at least three linearly independent reflections are measured, the 3D variation of the full lattice strain tensor within the microcrystal can be recovered. However, this requires knowledge of the crystal orientation, which is typically attained via estimates based on crystal geometry or synchrotron microbeam Laue diffraction measurements. Presented here is an alternative method to determine the crystal orientation for BCDI measurements using electron backscatter diffraction (EBSD) to align Fe–Ni and Co–Fe alloy microcrystals on three different substrates. The orientation matrix is calculated from EBSD Euler angles and compared with the orientation determined using microbeam Laue diffraction. The average angular mismatch between the orientation matrices is less than ∼6°, which is reasonable for the search for Bragg reflections. The use of an orientation matrix derived from EBSD is demonstrated to align and measure five reflections for a single Fe–Ni microcrystal via multi-reflection BCDI. Using this data set, a refined strain field computation based on the gradient of the complex exponential of the phase is developed. This approach is shown to increase accuracy, especially in the presence of dislocations. The results demonstrate the feasibility of using EBSD to pre-align BCDI samples and the application of more efficient approaches to determine the full lattice strain tensor with greater accuracy.

42 ENGINEERING↗

FTLADS: Object-Logging Based Fault-Tolerant Big Data Transfer System Using Layout Aware Data Scheduling

The layout-aware data scheduling (LADS) data movement framework optimizes congestion for end-to-end data transfers. During data transfer, LADS can avoid congested storage elements by exploiting the underlying storage layout at each endpoint. This improves the I/O bandwidth and hence the data transfer rate across high-speed networks. However, the absence of fault tolerance (FT) in LADS results in data retransmission overhead and may lead to possible data integrity issues upon faults. In this paper, we propose object-logging FT mechanisms to avoid transmitting the objects that are successfully written into the parallel file system (PFS) at the sink end. Depending on the number of log files created for the whole dataset, we have classified our FT mechanisms into three different categories: file logger, transaction logger, and universal logger. Also, to address the space overhead, we have proposed different methods of populating the log files with the information of the successfully transferred objects. We have evaluated the data transfer performance and recovery time overhead of the proposed object-logging-based FT mechanisms on the LADS data transfer framework. Our experimental results reflect that FT mechanisms exhibit negligible overhead (<; 1%) with respect to the data transfer time. Yet, the fault recovery time is 10% higher than the total data transfer time at any fault point.

97 MATHEMATICS AND COMPUTING↗

Measurement and Reporting Guidelines for Solar Mirror Aging Tests Using Xenon Arc Lamp Exposure (XALE)

This technical report provides a guideline for accelerated aging tests on solar reflectors. Solar reflectors must have a high durability, with goal lifespans reaching 30 years. To test and develop state-of-the-art solar reflectors, relevant durability tests must be conducted. Existing guidelines for materials testing include isothermal testing, humidity testing, corrosion, etc., but many tests do not specify to include solar irradiance or address its relevance to solar reflector durability. The guideline focuses on test design and reporting guidelines for using Xenon Arc Lamp Exposure (XALE). The XALE environmental chambers can subject samples to a combination of relevant environmental factors including concentrated solar irradiance, heat, humidity, and weathering cycles. The guideline is meant to provide information on developing relevant test conditions, exposure times, reflectance characterization procedures, and data reporting.

14 SOLAR ENERGY↗

2023 Standard Scenarios Report: A U.S. Electricity Sector Outlook

This report, originally published in December 2023, has been revised in January 2024. There were three changes in the revision. First, Anthony Lopez was added as a contributing author, as he had been erroneously omitted in the original publication. Second, in appendix section A.1 the cost of upgrading a hydrogen combustion turbine from a natural gas turbine was erroneously reported as 20% when it should have been 33%. Lastly, appendix Figure A-8 was erroneously a duplication of the same figure from the Standard Scenarios 2022, it has now been updated to reflect this year’s data.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Patterns of Bacterial and Archaeal Gene Expression through the Lower Amazon River

Analysis of metatranscriptomic and metagenomic datasets from the lower reaches of the Amazon River between Obidos and the river mouth revealed microbial transcript and gene pools dominated by Actinobacteria, Thaumarchaeota, Bacteroidetes, Acidobacteria, Betaproteobacteria, and Planctomycetes. Three mainstem stations spanning a 625 km reach had similar gene expression patterns (transcripts gene copy-1) across a diverse suite of element cycling genes, but two tributary-influenced stations at the mouth of the Tapajos River and near the Tocantins River at Belem had distinct transcriptome composition and expression ratios, particularly for genes encoding light-related energy capture (higher) and iron acquisition and ammonia oxidation (lower). Environmental parameters that were useful predictors of gene expression ratios included concentrations of lignin phenols, suspended sediments, nitrate, phosphate, and particulate organic carbon and nitrogen. Similar to the gene expression data, these chemical properties reflected highly homogeneous mainstem stations punctuated by distinct tributary- influenced stations at Tapajos and Belem. Although heterotrophic processes were expected to dominate in the lower Amazon, transcripts from photosynthetic bacteria were abundant in tributary-influenced regions, and transcripts from Thaumarcheota taxa genetically capable of chemosynthetic ammonia oxidation accounted for up to 21% of the transcriptome at others. Based on regressions of transcript numbers against gene numbers, expression ratios of Thaumarchaeota populations were largely unchanged within the mainstem, suggesting a relatively minor role for gene regulation. These quantitative gene and transcript inventories detail a diverse array of energy acquisition strategies and metabolic capabilities for bacteria and archaea populations of the world’s largest river system.

59 BASIC BIOLOGICAL SCIENCES↗

A robust wireless communication system for electromagnetically harsh environments of nuclear facilities - 155

Wireless sensors could play a significant role in safety, efficiency, and reliability of instrumentation and control process in current and next generation nuclear power reactors. While conventional narrowband wireless sensors have successfully been used in numerous industrial applications, the RF propagation challenges posed by the heavy metallic and cluttered environment of Nuclear Power Plants (NPPs) has prevented their use in such operations. These challenges include: RF propagation in harsh (reflective, absorptive, cluttered) environments, data security issues, and RF interference to and from other devices in a nuclear reactor. In this introductory paper, first we address how Ultra-wideband (UWB) technology can provide a viable solution for the signal propagation issues in such electromagnetically harsh environments. Second, we present a novel UWB remote powering scheme that allows for battery-free operation of sensors to increase their lifetime. We finalize the paper by presenting the experimental results of using UWB signaling in a representative harsh environment conducted at MIT research reactor. We plan to address the security issues through an innovative UWB communications scheme for sensor data communications in a subsequent paper. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Determining fast-S and slow-S propagation directions with SV-P data produced by buried explosives and recorded with vertical geophones

We have evaluated the concept of practicing S-wave reflection seismology with legacy 3D seismic data generated by a P-wave source and recorded with only vertical geophones. This type of S-wave imaging is based on the principle that seismic P-wave sources not only produce a downgoing illuminating P wavefield, but they also simultaneously produce a downgoing illuminating SV wavefield that, in almost all cases, is suitable for S-wave reflection imaging. The S-mode used in this study is the SV-P, or converted-P, mode. This mode involves a downgoing illuminating SV wavefield and an upgoing reflected P-mode that is recorded by vertical geophones. In flat-layered stratigraphy, the lengths of the SV and P raypaths in SV-P imaging are identical to the lengths of the SV and P raypaths in P-SV imaging with P-sources and 3C geophones. P-SV imaging of deep rocks has been practiced for more than two decades; SV-P imaging is a new concept. SV-P data should provide the same options for investigating deep rocks as do P-SV data. We have determined one of the equivalences between SV-P data extracted from vertical-geophone data and P-SV data extracted from horizontal geophones: that both modes react to azimuth-dependent variations in the S velocity in anisotropic rocks. Azimuthal variations in the SV-P traveltime can be used to define the polarization direction of the fast-S-wave mode, which is also the azimuth of the maximum horizontal stress (SHmax). Our investigation demonstrates a noninvasive method for monitoring changes in the SHmax azimuth across a CO 2 storage reservoir, or any targeted porous rock, as fluids are cycled into, and then out of, that rock’s pore space.

Geochemistry & Geophysics↗

Geothermal Play Fairway Analysis of the Snake River Plain: Phase 2

Play Fairway Analysis (PFA) is a methodology adapted from the petroleum industry that integrates data at the regional or basin scale to define favorable plays for exploration in a systematic fashion. Phase 2 of our Play Fairway Analysis of the Western Snake River Plain (WSRP) province in southern Idaho had three primary goals: first, to fill data gaps in critical areas in order to better define potential prospects, second, to integrate these data into new thermal and structural models, and finally, to infer the location of potential resources and drilling targets that could be validated during Phase 3. Prospects in the WSRP identified as potential target resources for Phase 3 validation include the Mountain Home region close to the Air Force Base, and the Camas Prairie. The Mountain Home region represents a blind geothermal resource in an area of high heat flow and young volcanism. The Camas Prairie is a semi-blind, structurally controlled resource in an area with indicators of magmatic heat. New geophysical data acquired at these sites includes reflection seismic, gravity and magnetic surveys, and a magnetotelluric field survey. New geochemical data collection focused on the Camas Prairie, and included the aqueous and isotope geochemistry of hot springs, cold springs, and wells (geothermal, groundwater, and irrigation). New field mapping, sampling, and basalt flow chronology was also conducted at Camas Prairie. Integrated results from Phase 1 and 2 studies suggest that the blind system near the Mountain Home Air Force Base is located at ~1.5– 2.3 km depth, and the structurally-controlled system at Camas Prairie is shallower, with upper reservoir depths perhaps only ~0.5–0.7 km.

15 GEOTHERMAL ENERGY↗

Thermal model to quantify the impact of sub-bandgap reflectance on operating temperature of fielded PV modules

Minimizing module heating is an effective way to increase the lifetime energy output of photovoltaic systems. Maximizing the reflection of light that is unusable for energy conversion is one of the most promising ways to reduce the operating temperature of fielded modules. We derive a model based on a steady-state energy balance to quantify the temperature benefit of cell or module optical modifications aimed at improving reflection of light with photon energies below the photovoltaic cell bandgap energy. This more detailed model is then simplified so that, from outdoor measured data, temperature differences arising from reflectance can be isolated from those arising from irradiance, wind speed, and module standard-test-condition efficiency.

14 SOLAR ENERGY↗

Human Factors in Streaming Data Analysis: Challenges and Opportunities for Information Visualization: Human Factors in Streaming Data Analysis

State-of-the-art visual analytics models and frameworks mostly assume a static snapshot of the data, while in many cases it is a stream with constant updates and changes. Exploration of streaming data poses unique challenges as machine-level computations and abstractions need to be synchronized with the visual representation of the data and the temporally evolving human insights. In the visual analytics literature, we lack a thorough characterization of streaming data and analysis of the challenges associated with task abstraction, visualization design, and adaptation of the role of human-in-the-loop for exploration of data streams. We aim to fill this gap by conducting a survey of the state-of-the-art in visual analytics of streaming data for systematically describing the contributions and shortcomings of current techniques and analyzing the research gaps that need to be addressed in the future. Our contributions are: i) problem characterization for identifying challenges that are unique to streaming data analysis tasks, ii) a survey and analysis of the state-of-the-art in streaming data visualization research with a focus on the visualization design space for dynamic data and the role of the human-in-the-loop, and iii) reflections on the design-trade-offs for streaming visual analytics techniques and their practical applicability in real-world application scenarios.

streaming data↗

Polar Liquid Cloud Base Detection Algorithms for High Spectral Resolution or Micropulse Lidar Data

Liquid layers in clouds affect their microphysical processes, as well as the atmospheric energy budget. However, explicit liquid cloud base height (LCBH) detection algorithms using ground-based instruments (e.g., lidars) are currently absent in the literature. Most studies use either fixed lidar parameter thresholds or cloud base height data products that do not distinguish between ice and liquid, all of which might introduce inconsistencies and errors in the resolved LCBHs. In this paper, two LCBH detection algorithms are presented; the first algorithm uses the high spectral resolution lidar (HSRL) data, and yields satisfactory results. The second algorithm incorporates micropulse lidar (MPL) data for the LCBH detection. A 1-year long comparison of data gathered at Barrow, Alaska, and McMurdo Station, Antarctica, which includes other cloud base detection methodologies (ceilometer, MPL value-added product cloud base height, LCBHs detected using a fixed MPL depolarization threshold) emphasize the merits of the MPL algorithm.

Silber, Israel↗

vdisquants: Video Distrometer derived radar equivalent quantities. Retrievals from the VDIS instrument providing radar equivalent quantities, including dual polarization radar quantities (e.g., Z, Differential Reflectivity ZDR).

1. Provide cleaned and filtered data stream from multiple ARM disdrometers; 2. Estimate commonly-used physical parameters of the Drop Size Distribution (DSD). 3. Calculate radar equivalent quantities such as the Radar Reflectivity Factor Z.

54 ENVIRONMENTAL SCIENCES↗

SAD phasing of XFEL data depends critically on the error model

A nonlinear least-squares method for refining a parametric expression describing the estimated errors of reflection intensities in serial crystallographic (SX) data is presented. This approach, which is similar to that used in the rotation method of crystallographic data collection at synchrotrons, propagates error estimates from photon-counting statistics to the merged data. Here, it is demonstrated that the application of this approach to SX data provides better SAD phasing ability, enabling the autobuilding of a protein structure that had previously failed to be built. Estimating the error in the merged reflection intensities requires the understanding and propagation of all of the sources of error arising from the measurements. One type of error, which is well understood, is the counting error introduced when the detector counts X-ray photons. Thus, if other types of random errors (such as readout noise) as well as uncertainties in systematic corrections (such as from X-ray attenuation) are completely understood, they can be propagated along with the counting error, as appropriate. In practice, most software packages propagate as much error as they know how to model and then include error-adjustment terms that scale the error estimates until they explain the variance among the measurements. If this is performed carefully, then during SAD phasing likelihood-based approaches can make optimal use of these error estimates, increasing the chance of a successful structure solution. In serial crystallography, SAD phasing has remained challenging, with the few examples of de novo protein structure solution each requiring many thousands of diffraction patterns. Here, the effects of different methods of treating the error estimates are estimated and it is shown that using a parametric approach that includes terms proportional to the known experimental uncertainty, the reflection intensity and the squared reflection intensity to improve the error estimates can allow SAD phasing even from weak zinc anomalous signal.

59 BASIC BIOLOGICAL SCIENCES↗

Filling data analysis gaps in time-resolved crystallography by machine learning

There is a growing understanding of the structural dynamics of biological molecules fueled by x-ray crystallography experiments. Time-resolved serial femtosecond crystallography (TR-SFX) with x-ray Free Electron Lasers allows the measurement of ultrafast structural changes in proteins. Nevertheless, this technique comes with some limitations. One major challenge is the quality of data from TR-SFX measurements, which often faces issues like data sparsity, partial recording of Bragg reflections, timing errors, and pixel noise. To overcome these difficulties, conventionally, large volumes of data are collected and grouped into a few temporal bins. The data in each bin are then averaged and paired with the mean of their corresponding jittered timestamps. This procedure provides one structure per bin, resulting in a limited number of averaged structures for the entire time interval spanned by the experiment. Therefore, the information on ultrafast structural dynamics at high temporal resolution is lost. This has initiated research for advanced methods of analyzing experimental TR-SFX data beyond the standard binning and averaging method. To address this problem, we use a machine learning algorithm called Nonlinear Laplacian Spectral Analysis (NLSA), which has emerged as a promising technique for studying the dynamics of complex systems. In this work, we demonstrate the power of this algorithm using synthetic x-ray diffraction snapshots from a protein with significant data incompleteness, timing uncertainties, and noise. Our study confirms that NLSA is a suitable approach that effectively mitigates the effects of these artifacts in TR-SFX data and recovers accurate structural dynamics information hidden in such data.

Trujillo, Justin (ORCID:0000000285505360)↗