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At least 487 records · Page 27

Do Flashing and Sealant Materials Need to be Exposed to Extreme Cycling?

In the U.S., over 50% of homes were built before 1980, when minimal building codes existed. The aging of building envelopes can significantly contribute to the air leakage, moisture intrusion, and durability of buildings leading to higher energy demands. Although the durability of building materials and envelope systems has been studied extensively, the durability of specific components like window-wall flashing and sealants remains underexplored. Current standards such as ASTM, NIST, and AAMA primarily focus on durability testing considering the high temperatures only and require sealant testing on anodized aluminum panels, leaving questions about performance in cold or fluctuating temperatures unanswered. Current ASTM and AAMA standards provide guidelines for durability testing but predominantly focus on exposure to higher temperature conditions. It remains unclear how exposure to cold temperatures, or cycles of both hot and cold conditions, affect the durability of these materials. Furthermore, AAMA standards mandate that flashing materials be tested on anodized aluminum panels, which may not reflect real-world applications. Therefore, this initial study aims to explore this concern through testing by constructing two window-wall interface prototypes and applying five different flashing and sealant materials to their joints. These samples were subjected to extreme temperatures, ranging from −34 ℃ (−30 °F) to 50 ℃ (122 °F), over a 28-day period (fourteen cycles of 24 hours), with daily visual inspections to document any signs of deterioration such as wrinkling, distortion, or warping. The study has two main objectives: (1) to determine whether flashing and sealant materials lose their durability and strength when exposed to varying climate conditions, specifically cold climates, and (2) to assess whether the interaction of these materials with different substrates (e.g., lumber, PVC, insulation) affects their durability and strength under varying climate conditions. The findings demonstrate how aging impacts the durability of window-wall systems interfaces, justifying future research that potentially could lead to the development of new testing protocols if significant defects are identified.

Palani, Hevar [ORNL] (ORCID:0000000220211994)↗

FREDA: A Web Application for the Processing, Analysis, and Visualization of Fourier‐Transform Mass Spectrometry Data

The high-resolution measurement capability of Fourier-transform mass spectrometry (FT-MS) has made it a necessity for exploring the molecular composition of complex organic mixtures, like soil, plant, aquatic, and petroleum samples. This demand has driven a need for informatics tools to explore and analyze FT-MS data in a robust and reproducible manner. FREDA is an interactive web application developed to enable spectrometrists to format, process, and explore their FT-MS data without the need for statistical programming expertise. FREDA was built to explore outputs from a molecular identification tool, like CoreMS, and provide a suite of methods to filter data, compute chemical properties of peaks, statistically compare samples and groups of samples, conduct exploratory data analysis, and download the results with a report detailing all steps conducted. To demonstrate the utility of FREDA, an example analysis was conducted using FT-MS data from a soil microbiology study of samples collected in two different soil depths at the Sphagnum bog forest north of Grand Rapids, Minnesota. Differences between the two depths are observed using Kendrick, Gibbs free energy, and van Krevelen plots. G-tests are used to quantify a significant difference between the groups. All analyses and plotting are conducted using only the FREDA application. FREDA is an open-source and readily available web application that allows users to explore and make statistically valid conclusions about their FT-MS data. The application is available online (https://map.emsl.pnnl.gov/app/freda) with a tutorial web series (https://youtu.be/k5HLE2kNSBY?si=yB6sGoyvzxrFf5MP) and freely accessible code on Github (https://github.com/EMSL-Computing/FREDA).

47 OTHER INSTRUMENTATION↗

Processes in DNA damage response from a whole-cell multi-omics perspective

Technological advances have made it feasible to collect multi-condition multi-omic time courses of cellular response to perturbation, but the complexity of these datasets impedes discovery due to challenges in data management, analysis, visualization, and interpretation. Here, we report a whole-cell mechanistic analysis of HL-60 cellular response to bendamustine. We integrate both enrichment and network analysis to show the progression of DNA damage and programmed cell death over time in molecular, pathway, and process-level detail using an interactive analysis framework for multi-omics data. Our framework, Mechanism of Action Generator Involving Network analysis (MAGINE), automates network construction and enrichment analysis across multiple samples and platforms, which can be integrated into our annotated gene-set network to combine the strengths of networks and ontology-driven analysis. Taken together, our work demonstrates how multi-omics integration can be used to explore signaling processes at various resolutions and demonstrates multi-pathway involvement beyond the canonical bendamustine mechanism.

59 BASIC BIOLOGICAL SCIENCES↗

Ultrafast relaxation of lattice distortion in two-dimensional perovskites

Direct visualization of ultrafast coupling between charge carriers and lattice degrees of freedom in photoexcited semiconductors has remained a long-standing challenge and is critical for understanding the light-induced physical behaviour of materials under extreme non-equilibrium conditions. Here we obtain a direct visualization of the structural dynamics in monocrystalline 2D perovskites. We achieve this by monitoring the evolution of wavevector-resolved ultrafast electron diffraction intensity following above-bandgap high-density photoexcitation. Our analysis reveals a light-induced ultrafast reduction in antiferro-distortion resulting from a strong interaction between the electron–hole plasma and perovskite lattice, which induces an in-plane octahedra rotation towards a more symmetric phase. Correlated ultrafast spectroscopy performed at the same carrier density as ultrafast electron diffraction reveals that the creation of a dense electron–hole plasma triggers the relaxation of lattice distortion at shorter timescales by modulating the crystal cohesive energy. Then we show that the interaction between carrier gas and lattice can be altered by tailoring the rigidity of the 2D perovskite by choosing an appropriate organic spacer layer.

36 MATERIALS SCIENCE↗

An automated fast neutron computed tomography instrument with on-line focusing for non-destructive evaluation

A fast neutron tomography imaging instrument has been designed, built, and tested at The Ohio State University 500 kW Research Reactor on a fast neutron beamline with a peak neutron flux ≈5.4 × 107 n·cm−2·s−1 at 1.6 MeV median neutron energy. The instrument and beamline are also configurable for thermal neutron imaging. The imaging apparatus is composed of a lens coupled, water-cooled Electron Multiplying Charge Coupled Device camera, a front-surface mirror, and a high light yield plastic Polyvinyl toluene scintillator. The instrument sits on a mobile cart. A total of 5 motion-control stages are built into the system for XYZ and rotational degrees of freedom for sample positioning; the fifth stage fine tunes the focal distance between the camera and the scintillator to achieve on-line focusing. A Python code with a user-friendly graphical user interface controls the fully automated image acquisition, not requiring user interaction, yet facilitating tracking of the image acquisition. A complete fast neutron computed tomography dataset with 360 projections requires less than 3 h, with 30 s per projection. On-line focusing is accomplished with a commercial, off-the-shelf, dielectrically actuated liquid lens. Finally, tomographic reconstructions are visualized using the Livermore Tomography Tools software package. The effective pixel size (width and height) is ≈0.1058 mm, yielding a minimum voxel size of 0.1058 × 0.1058 × 0.1058 mm3, and produces a spatial resolution of 231 μm when calculated from knife-edge measurements.

Bisbee, M. G. (ORCID:0000000313466697)↗

Integrated multi-wavelength microscope combining TIRFM and IRM modalities for imaging cellulases and other processive enzymes

We describe a multimodal microscope for visualizing processive enzymes moving on immobilized substrates. The instrument combines interference reflection microscopy (IRM) with multi-wavelength total internal reflectance fluorescence microscopy (TIRFM). The microscope can localize quantum dots with a precision of 2.8 nm at 100 frames/s, and was used to image the dynamics of the cellulase, Cel7a interacting with surface-immobilized cellulose. The instrument, which was built with off-the-shelf components and is controlled by custom software, is suitable for tracking other degradative enzymes such as collagenases, as well as motor proteins moving along immobilized tracks.

09 BIOMASS FUELS↗

High tide: a systematic search for ellipsoidal variables in ASAS-SN

ABSTRACT The majority of non-merging stellar mass black holes are discovered by observing high energy emission from accretion processes. Here, we pursue the large, but still mostly unstudied population of non-interacting black holes and neutron stars by searching for the tidally induced ellipsoidal variability of their stellar companions. We start from a sample of about 200 000 rotational variables, semiregular variables, and eclipsing binary stars from the All-Sky Automated Survey for Supernovae. We use a χ2 ratio test followed by visual inspection to identify 369 candidates for ellipsoidal variability. We also discuss how to combine the amplitude of the variability with mass and radius estimates for observed stars to calculate a minimum companion mass, identifying the most promising candidates for high mass companions.

79 ASTRONOMY AND ASTROPHYSICS↗

Fluid structure interaction of a subaqueous pendulum: Analyzing the effect of wake correction via large eddy simulations

The dynamic behavior of a subaqueous cylindrical pendulum and corresponding flow dynamics are investigated. The objectives were twofold: (i) to examine whether the two-dimensional model equations sufficiently capture the three-dimensional dynamics and (ii) to investigate the emerging three-dimensional vortical flow structures. Large eddy simulations with two-way coupling fluid structure interaction were carried out using the immersed boundary method to simulate the motion of the pendulum and its interactions with the initially stagnant water. The resulting pendulum motion is compared against measured data obtained in a series of experimental tests to validate the simulation results and the model equations with and without wake corrections. An analysis of the flow vorticity revealed the development of a vortex ring during the first swing and the formation of tip vortices. The evolution of the vortex rings emerging from the motion of the subaqueous cylindrical pendulum was visualized using Q-criteria showing a reasonable agreement with vortical structures observed in the experiment using particle imaging velocimetry. The hydrodynamic moments acting on the simulated pendulum and the moments calculated from the model equations are analyzed. Using the insights from these numerical simulations, a modification of the wake correction is proposed to enhance the accuracy of the rate of decay and period. The transient effect of coherent flow on pendulum dynamics, especially the added mass effect, is discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Experimental study of three-dimensional CO 2 -water drainage and fracture-matrix interactions in fractured porous media

Estimation of CO 2 storage capacity in fractured porous reservoirs requires a better understanding of the CO 2 -water flow fundamentals in fracture-matrix systems. There are few core-flood experiments on three-dimensional CO 2 -water drainage in a fracture-matrix system, yet none have examined the impacts of the capillary continuity of fractures and fracture-matrix interactions. In this study, twelve drainage experiments were conducted in four fracture-matrix columns, each comprising a vertical stack of a cylindrical rock core, a filter paper serving as an analogue to a horizontal fracture, and a ceramic plate. Here, the core sample was surrounded by open space at the top and circumferential sides to model fractures, allowing for 3-D CO 2 -water drainage in the rock core and displaced water draining across the horizontal fracture. X-ray computed tomography was conducted to visualize the dynamic invasion/drainage processes in four rock core samples showing contrasts in anisotropy, permeability, and heterogeneity. Experimental results show (1) the equilibrium CO 2 saturations in the rock matrix vary from 0.10 to 0.60 at controlled capillary pressures up to 200 kPa, (2) the CO 2 saturations in the matrix increase with water saturation in the horizontal fracture resulting in better capillary continuity for water to drain across the fracture, and (3) the fracture water saturation can be enhanced by the non-uniform fracture capillary pressure and countercurrent flow of CO 2 and water across the fracture-matrix interface. In the case of high fracture water saturation, matrix CO 2 saturation largely depends on matrix anisotropy and heterogeneity. The core-scale experimental results contribute to understand the fracture-matrix interactions and CO 2 storage efficiency in fractured porous media.

54 ENVIRONMENTAL SCIENCES↗

New tool for kinematic regime estimation in semi-inclusive deep-inelastic scattering

We introduce a new phenomenological tool based on momentum region indicators to guide the analysis and interpretation of semi-inclusive deep-inelastic scattering measurements. The new tool, referred to as “affinity”, is devised to help visualize and quantify the proximity of any experimental kinematic bin to a particular hadron production region, such as that associated with transverse momentum dependent factorization. We apply the affinity estimator to existing HERMES and COMPASS data and expected data from Jefferson Lab and the future Electron-Ion Collider. We also provide an interactive notebook based on Machine Learning for fast evaluation of affinity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Deep learning approaches for instantaneous laser absorptance prediction in additive manufacturing

Abstract The quantification of absorbed light is essential for understanding laser-material interactions and melt pool dynamics in order to minimize defects in additively manufactured metal components. The geometry of a vapor depression formed during laser melting is closely related to laser energy absorption. This relationship has been observed by the state-of-the-art in situ high-speed synchrotron X-ray visualization and integrating sphere radiometry. These two techniques create a temporally resolved dataset consisting of vapor depression images and corresponding laser absorptance. In this work, we propose two different approaches to predict instantaneous laser absorptance. The end-to-end approach uses deep convolutional neural networks to learn implicit features of X-ray images automatically and predict the laser energy absorptance. The two-stage approach uses a semantic segmentation model to engineer geometric features and predict absorptance using classical regression models. While having distinct advantages, both approaches achieved a consistently low mean absolute error of less than 3.3%.

Chemistry↗

The DREAM Endstation at the Linac Coherent Light Source

Free-electron lasers (FEL), with their ultrashort pulses, ultrahigh intensities, and high repetition rates at short wavelength, have provided new approaches to Atomic and Molecular Optical Science. One such approach is following the birth of a photo electron to observe ion dynamics on an ultrafast timescale. Such an approach presents the opportunity to decipher the photon-initiated structural dynamics of an isolated atomic and molecular species. It is a fundamental step towards understanding single- and non-linear multi-photon processes and coherent electron dynamics in atoms and molecules, ultimately leading to coherent control following FEL research breakthroughs in pulse shaping and polarization control. A key aspect for exploring photoinduced quantum phenomena is visualizing the collective motion of electrons and nuclei in a single reaction process, as dynamics in atoms/ions proceed at femtosecond (10 –15 s) timescales while electronic dynamics take place in the attosecond timescale (10 –18 s). Here, we report on the design of a Dynamic Reaction Microscope (DREAM) endstation located at the second interaction point of the Time-Resolved Molecular and Optical (TMO) instrument at the Linac Coherent Light Source (LCLS) capable of following the photon–matter interactions by detecting ions and electrons in coincidence. The DREAM endstation takes advantage of the pulse properties and high repetition rate of LCLS-II to perform gas-phase soft X-ray experiments in a wide spectrum of scientific domains. With its design ability to detect multi-ions and electrons in coincidence while operating in step with the high repetition rate of LCLS-II, the DREAM endstation takes advantage of the inherent momentum conservation of reaction product ions with participating electrons to reconstruct the original X-ray photon–matter interactions. In this report, we outline in detail the design of the DREAM endstation and its functionality, with scientific opportunities enabled by this state-of-the-art instrument.

47 OTHER INSTRUMENTATION↗

Classification of Intensity Distributions of Transmission Eigenchannels of Disordered Nanophotonic Structures Using Machine Learning

Light-matter interaction optimization in complex nanophotonic structures is a critical step towards the tailored performance of photonic devices. The increasing complexity of such systems requires new optimization strategies beyond intuitive methods. For example, in disordered photonic structures, the spatial distribution of energy densities has large random fluctuations due to the interference of multiply scattered electromagnetic waves, even though the statistically averaged spatial profiles of the transmission eigenchannels are universal. Classification of these eigenchannels for a single configuration based on visualization of intensity distributions is difficult. However, successful classification could provide vital information about disordered nanophotonic structures. Emerging methods in machine learning have enabled new investigations into optimized photonic structures. In this work, we combine intensity distributions of the transmission eigenchannels and the transmitted speckle-like intensity patterns to classify the eigenchannels of a single configuration of disordered photonic structures using machine learning techniques. Specifically, we leverage supervised learning methods, such as decision trees and fully connected neural networks, to achieve classification of these transmission eigenchannels based on their intensity distributions with an accuracy greater than 99%, even with a dataset including photonic devices of various disorder strengths. Simultaneous classification of the transmission eigenchannels and the relative disorder strength of the nanophotonic structure is also possible. Our results open new directions for machine learning assisted speckle-based metrology and demonstrate a novel approach to classifying nanophotonic structures based on their electromagnetic field distributions. These insights can be of paramount importance for optimizing light-matter interactions at the nanoscale.

79 ASTRONOMY AND ASTROPHYSICS↗

Role of the Solvent–Surfactant Duality of Ionic Liquids in Directing Two-Dimensional Particle Assembly

Nanoparticle self-assembly plays a key role in formation of superlattices, which exhibit remarkable physical and chemical properties. However, controlling assembly remains a challenge partly due to a lack of understanding of the assembly dynamics and the difficulty in linking interfacial solution properties to interparticle forces. In this study, using liquid-cell transmission electron microscopy, self-assembly of gold nanoparticles (NPs) into superlattices in mixtures of water and ionic liquid (IL) was visualized, revealing a dual role of the IL in the assembly process. At intermediate concentrations, the IL acts as a surfactant stabilizing the particles at a well-defined equilibrium separation corresponding to the length of hydrogen bonded IL cations adsorbed onto neighboring NPs. Analysis of the interparticle forces reveals attractive long-range interactions of a van der Waals nature. At separations of 1-3 nm, interactions are dominated by attractive ion correlation and repulsive hydration forces giving rise to an energy minimum at 1.5 nm separation. The superlattice is further stabilized by hydrogen bonding, which shifts the equilibrium interparticle distance to 1.1 nm. In contrast, at higher concentrations, IL accumulates and forms a structured network in the gap between nanoparticles, where it acts as a solvent that eliminates the repulsive barrier and thus promotes particle coalescence. This solvent-surfactant duality of IL opens new opportunities for their use in directing particle assembly.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bioimaging Science Program Principal Investigator Meetings Proceedings (2021)

As part of the 2021 Biological Systems Science Division (BSSD) Principal Investigator (PI) Meeting, the Bioimaging Science program (BSP), within BSSD's Biomolecular Characterization and Imaging Science portfolio, held its annual PI meeting virtually February 22–23. BSP's mission is to understand the translation of genomic information into the mechanisms that power living cells, communities of cells, and whole organisms. The goal of BSP is to develop new imaging and measurement technologies to visualize the spatial and temporal relationships of key metabolic processes governing phenotypic expression in plants and microbes. BSP convenes annual PI meetings to bring together its contributing investigators to review progress and current state-of-the-art bioimaging research. Holding the BSP meeting as part of the broader BSSD PI meeting allowed researchers to interact with the extended Genomic Science program community. This convergence provided a platform for networking and exchange of ideas, helping to forge new multidisciplinary collaborations among investigators from the two sister programs. An important highlight of the BSP meeting was the keynote presentation “Enhancing Fluorescence Microscopy with Computation” by Dr. Hari Shroff of the NIH National Institute of Biomedical Imaging and Bioengineering. All the BSP PIs made presentations describing their research focus and progress, and these were followed by roundtable discussions of each project. The meeting’s proceedings provide an outline of the program’s current state and potential future directions and opportunities.

59 BASIC BIOLOGICAL SCIENCES↗

Interacting with the COVID virus model in VR environment

The Disaster Response Complex at Idaho State University (ISU) hosts an annual Disaster Preparedness and Response Conference which will give a bird's eye view of disasters and pandemics in the U.S. We'll demonstrate virtual reality (VR) and augmented reality (AR) capabilities at the conference. This VR demo displays the structure and components of the COVID virus model, and let users to interact with it in an immersive environment. The 3D model used in this demo is open source and downloaded from this site: https://sketchfab.com/GLS.

3D↗

Time-domain study of coupled collective excitations in quantum materials

Quantum materials hold immense promises for future applications due to their intriguing electronic, magnetic, thermal, and mechanical properties that often arise from a complex interplay between microscopic degrees of freedom. Important insights of such interactions come from studying the collective excitations of electrons, spins, orbitals, and lattice, whose cooperative motions play a crucial role in determining the novel behavior of these systems and offer us a key tuning knob to modify material properties on-demand through external perturbations. In this regard, ultrafast light-matter interaction has shown great potential in controlling the couplings of collective excitations, and rapid progress in a plethora of time-resolved techniques down to the attosecond regime has significantly advanced our understanding of the coupling mechanisms and guided us in manipulating the dynamical properties of quantum materials. This review aims to highlight recent experiments on visualizing collective excitations in the time domain, focusing on the coupling mechanisms between different collective modes such as phonon-phonon, phonon-magnon, phonon-exciton, magnon-magnon, magnon-exciton, and various polaritons. We introduce how these collective modes are excited by an ultrashort laser pulse and probed by different ultrafast techniques, and we explain how the coupling between collective excitations governs the ensuing nonequilibrium dynamics. We also provide some perspectives on future studies that can lead to discoveries of the emergent properties of quantum materials both in and out of equilibrium.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Guiding the choice of informatics software and tools for lipidomics research applications

Progress in mass spectrometry lipidomics has led to a rapid proliferation of studies across biology and biomedicine. These generate extremely large raw datasets requiring sophisticated solutions to support automated data processing. To address this, numerous software tools have been developed and tailored for specific tasks. However, for researchers, deciding which approach best suits their application relies on ad hoc testing, which is inefficient and time consuming. Here we first review the data processing pipeline, summarizing the scope of available tools. Next, to support researchers, LIPID MAPS provides an interactive online portal listing open-access tools with a graphical user interface. This guides users towards appropriate solutions within major areas in data processing, including (1) lipid-oriented databases, (2) mass spectrometry data repositories, (3) analysis of targeted lipidomics datasets, (4) lipid identification and (5) quantification from untargeted lipidomics datasets, (6) statistical analysis and visualization, and (7) data integration solutions. Detailed descriptions of functions and requirements are provided to guide customized data analysis workflows.

59 BASIC BIOLOGICAL SCIENCES↗