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At least 1,279 records · Page 71

Experimental Modal Analysis Using Phase Quantities from Phase-Based Motion Processing and Motion Magnification

Phase-based motion processing and the associated Motion Magnification that it enables has become popular not only for the striking videos that it can produce of traditionally stiff structures visualized with very large deflections, but also for its ability to pull information out of the noise floor of images so that they can be processed with more traditional optical techniques such as digital image correlation or feature tracking. While the majority of papers in the literature have utilized the Phase-based Image Processing approach as a pre-processor for more quantitative analyses, the technique itself can be used directly to extract modal parameters from an image, noting that the extracted phases are proportional to displacements in the image. Therefore, once phases are extracted, they can be fit using traditional experimental modal analysis techniques. This produces a mode “shape” where the degrees of freedom are phases instead of physical motions. These phases can be scaled to produce on-image visualizations of the mode shapes, rather than operational shapes produced by bandpass filtering. Modal filtering techniques can also be used to visualize motions from an environment on an image using the modal phases as a basis for the expansion.

47 OTHER INSTRUMENTATION↗

Controlled-Resonant Surface Tapping-Mode Scanning Probe Electrospray Ionization Mass Spectrometry Imaging

This paper reports on the advancement of a controlled-resonance surface tapping-mode single capillary liquid junction extraction/ESI emitter for mass spectrometry imaging. The basic instrumental setup and the general operation of the system were discussed and optimized performance metrics were presented. The ability to spot sample, lane scan and chemically image in an automated and controlled fashion were demonstrated. Rapid, automated spot sampling was demonstrated for a variety of compound types including the cationic dye basic blue 7, the oligosaccharide cellopentaose, and the protein equine heart cytochrome c. The system was used for lane scanning and chemical imaging of the cationic dye crystal violet in inked lines on glass and for lipid distributions in mouse brain thin tissue sections. Imaging of the lipids in mouse brain tissue under optimized conditions provided a spatial resolution of approximately 35 m based on the ability to distinguish between features observed both in the optical and mass spectral chemical images. The sampling spatial resolution of this system was comparable to the best resolution that has been reported for other types of atmospheric pressure liquid extraction-based surface sampling/ionization techniques used for mass spectrometry imaging.

Lorenz, Matthias↗

Multiple-core-hole resonance spectroscopy with ultraintense X-ray pulses

Understanding the interaction of intense, femtosecond X-ray pulses with heavy atoms is crucial for gaining insights into the structure and dynamics of matter. One key aspect of nonlinear light–matter interaction was, so far, not studied systematically at free-electron lasers—its dependence on the photon energy. Here, we use resonant ion spectroscopy to map out the transient electronic structures occurring during the complex charge-up pathways of xenon. Massively hollow atoms featuring up to six simultaneous core holes determine the spectra at specific photon energies and charge states. We also illustrate how different X-ray pulse parameters, which are usually intertwined, can be partially disentangled. The extraction of resonance spectra is facilitated by the possibility of working with a constant number of photons per X-ray pulse at all photon energies and the fact that the ion yields become independent of the peak fluence beyond a saturation point. Our study lays the groundwork for spectroscopic investigations of transient atomic species in exotic, multiple-core-hole states that have not been explored previously.

74 ATOMIC AND MOLECULAR PHYSICS↗

Microscopic theory, analysis, and interpretation of conductance histograms in molecular junctions

Molecular electronics break-junction experiments are widely used to investigate fundamental physics and chemistry at the nanoscale. Reproducibility in these experiments relies on measuring conductance on thousands of freshly formed molecular junctions, yielding a broad histogram of conductance events. Experiments typically focus on the most probable conductance, while the information content of the conductance histogram has remained unclear. Here we develop a microscopic theory for the conductance histogram by merging the theory of force-spectroscopy with molecular conductance. The procedure yields analytical equations that accurately fit the conductance histogram of a wide range of molecular junctions and augments the information content that can be extracted from them. Our formulation captures contributions to the conductance dispersion due to conductance changes during the mechanical elongation inherent to the experiments. In turn, the histogram shape is determined by the non-equilibrium stochastic features of junction rupture and formation. The microscopic parameters in the theory capture the junction’s electromechanical properties and can be isolated from separate conductance and rupture force (or junction-lifetime) measurements. The predicted behavior can be used to test the range of validity of the theory, understand the conductance histograms, design molecular junction experiments with enhanced resolution and molecular devices with more reproducible conductance properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Surface chemical defence of the eelgrass Zostera marina against microbial foulers

Plants rely on both mechanical and chemical defence mechanisms to protect their surfaces against microorganisms. The recently completed genome of the eelgrass Zostera marina , a marine angiosperm with fundamental importance for coastal ecosystems, showed that its re-adaptation from land to the sea has led to the loss of essential genes (for chemical communication and defence) and structural features (stomata and thick cuticle) that are typical of terrestrial plants. This study was designed to understand the molecular nature of surface protection and fouling-control strategy of eelgrass against marine epiphytic yeasts. Different surface extraction methods and comparative metabolomics by tandem mass spectrometry (LC-MS/MS) were used for targeted and untargeted identification of the metabolite profiles of the leaf surface and the whole tissue extracts. Desorption electrospray ionization-imaging mass spectrometry (DESI-IMS) coupled with traditional bioassays revealed, for the first time, the unique spatial distribution of the eelgrass surface-associated phenolics and fatty acids, as well as their differential bioactivity against the growth and settlement of epiphytic yeasts. This study provides insights into the complex chemical defence system of the eelgrass leaf surface. It suggests that surface-associated metabolites modulate biotic interactions and provide chemical defence and structural protection to eelgrass in its marine environment.

60 APPLIED LIFE SCIENCES↗

Phase Segmentation in Atom-Probe Tomography Using Deep Learning-Based Edge Detection

Abstract Atom-probe tomography (APT) facilitates nano- and atomic-scale characterization and analysis of microstructural features. Specifically, APT is well suited to study the interfacial properties of granular or heterophase systems. Traditionally, the identification of the interface between, for precipitate and matrix phases, in APT data has been obtained either by extracting iso-concentration surfaces based on a user-supplied concentration value or by manually perturbing the concentration value until the iso-concentration surface qualitatively matches the interface. These approaches are subjective, not scalable, and may lead to inconsistencies due to local composition inhomogeneities. We introduce a digital image segmentation approach based on deep neural networks that transfer learned knowledge from natural images to automatically segment the data obtained from APT into different phases. This approach not only provides an efficient way to segment the data and extract interfacial properties but does so without the need for expensive interface labeling for training the segmentation model. We consider here a system with a precipitate phase in a matrix and with three different interface modalities—layered, isolated, and interconnected—that are obtained for different relative geometries of the precipitate phase. We demonstrate the accuracy of our segmentation approach through qualitative visualization of the interfaces, as well as through quantitative comparisons with proximity histograms obtained by using more traditional approaches.

47 OTHER INSTRUMENTATION↗

Expediting field-effect transistor chemical sensor design with neuromorphic spiking graph neural networks

Improving the sensitive and selective detection of analytes in a variety of applications requires accelerating the rational design of field-effect transistor (FET) chemical sensors. Achieving high-performance detection relies on identifying optimal probe materials that can effectively interact with target analytes, a process traditionally driven by chemical intuition and time-consuming trial-and-error methods. To address the difficulties in probe screening for FET sensor development, this work presents a methodology that combines neuromorphic machine learning (ML) architectures, specifically a hybrid spiking graph neural network (SGNN), with an enriched dataset of physicochemical properties through semi-automated data extraction using large language models. Achieving a classification accuracy of 0.89 in predicting sensor sensitivity categories, the SGNN model outperformed traditional ML techniques by leveraging its ability to capture both global physicochemical properties and sparse topological features through a hybrid modeling framework. Next-generation sensor design was informed by the actionable insights into the connections between material properties and sensing performance offered by the SGNN framework. Through virtual screening for the detection of per- and polyfluoroalkyl substances (PFAS) as a use case, the effectiveness of the SGNN model was further validated. Density functional theory simulations confirmed graphene as a promising active material for PFAS detection as suggested by the SGNN framework. By bridging gaps in predictive modeling and data availability, this integrated approach provides a strong foundation for accelerating advancements in FET sensor design and innovation.

Ferreira, Rodrigo Pires [Univ. of Chicago, IL (Uni↗

Inductively driven surface-plasma negative ion source for N-NBI use (invited)

The long-pulse surface-plasma source prototype is developed at Budker Institute of Nuclear Physics for negative-ion based neutral beam injector use. The essential source features are (1) an active temperature control of the ion-optical system electrodes by circulation of hot thermal fluid through the channels, drilled in the electrode bodies, (2) the concaved transverse magnetic field in the extraction and acceleration gaps, preventing the electrons trapping and avalanching, and (3) the directed cesium deposition via distribution tubes adjacent to the plasma grid periphery. The long term effect of cesium was obtained just with the single cesium deposition. The high voltage strength of ion-optical system electrodes was improved with actively heated electrodes. A stable H{sup −} beam with a current ∼1 A and energy 90 keV was routinely extracted and accelerated.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Gas scintillation mitigation in gas Cherenkov detectors for inertial confinement fusion (invited)

Gas Cherenkov detectors provide a time resolved measurement of the fusion burn in inertial confinement fusion experiments. The fusion rate delivers critical benchmark figures, such as burn width and bang time. Recent detector improvements pushed temporal resolution to 10 ps to make burn width measurements on igniting targets possible. First high temporal resolution measurements using CO 2 gas fills had a background signal with a long decay length (tail), which was caused by gas scintillation. This gas scintillation limits the ability of the detector to resolve short burn width and high frequency features in the fusion rate measurements. A thorough investigation of the cause of the tail and mitigation options for gas scintillation is presented here. As a near-term resolution, neon gas is being used to extract fusion burn histories. Paths forward for the next generation of gas Cherenkov detectors are identified including the usage of oxygen as a Cherenkov medium.

47 OTHER INSTRUMENTATION↗

INTERPRETING THE GLOBAL 21 cm SIGNAL FROM HIGH REDSHIFTS. I. MODEL-INDEPENDENT CONSTRAINTS

The sky-averaged (global) 21 cm signal is a powerful probe of the intergalactic medium (IGM) prior to the completion of reionization. However, so far it has been unclear whether it will provide more than crude estimates of when the universe's first stars and black holes formed, even in the best case scenario in which the signal is accurately extracted from the foregrounds. In contrast to previous work, which has focused on predicting the 21 cm signatures of the first luminous objects, we investigate an arbitrary realization of the signal and attempt to translate its features to the physical properties of the IGM. Within a simplified global framework, the 21 cm signal yields quantitative constraints on the Lyα background intensity, net heat deposition, ionized fraction, and their time derivatives without invoking models for the astrophysical sources themselves. The 21 cm absorption signal is most easily interpreted, setting strong limits on the heating rate density of the universe with a measurement of its redshift alone, independent of the ionization history or details of the Lyα background evolution. In a companion paper, we extend these results, focusing on the confidence with which one can infer source emissivities from IGM properties.

79 ASTRONOMY AND ASTROPHYSICS↗

Energy dependence of polarized 𝛾⁢𝛾 → 𝑒 + ⁢ 𝑒− in peripheral Au+Au collisions at $\sqrt{s_{NN}}$ = 54.4 and 200 GeV with the STAR experiment at RHIC

We report the differential yields at mid-rapidity of the Breit-Wheeler process (𝛾⁢𝛾 → 𝑒 + ⁢𝑒 − ) in peripheral Au+Aucollisions at $\sqrt{s_{NN}}$ = 54.4 and 200 GeV with the STAR experiment at the Relativistic Heavy Ion Collider (RHIC), as a function of energy $\sqrt{s_{NN}}$, 𝑒 + ⁢𝑒 − transverse momentum 𝑝 T , 𝑝$^{2}_{T}$, invariant mass 𝑀 𝑒⁢𝑒 , and azimuthal angle. In the invariant mass range of 0.4 < 𝑀 𝑒⁢𝑒 < 2.6GeV/𝑐 2 at low transverse momentum (𝑝 T < 0.15GeV/𝑐), the yields increase while the pair √⟨𝑝$^{2}_{T}$⟩ decreases with increasing $\sqrt{s_{NN}}$, a feature that is correctly predicted by the QED calculation. Here, the energy dependencies of the measured quantities are sensitive to the nuclear form factor, infrared divergence and photon polarization. The data are compiled and used to extract the charge radius of the Au nucleus.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

HERCULES: Strong Patterns towards More Intelligent Predictive Modeling, In: 2014 43rd International Conference on Parallel Processing

Recent work has shown that program analysis techniques to select meaningful code features of programs are important in the task of deciding the best compiler optimizations. Although, there are many successful state-of-the-art program analysis techniques, they often do not provide a simple method to extract the most expressive information about loops, especially when a target program is computationally intensive with complex loops and data dependencies. In this paper, we introduce a static technique to characterize a program using a pattern-driven system named HERCULES. This characterization technique not only helps a user to understand programs by searching pattern-of-interests, but also can be used for a predictive model that effectively selects the proper compiler optimizations. We formulated 35 loop patterns, then evaluated our characterization technique by comparing the predictive models constructed using HERCULES to three other state-of-the-art characterization methods. We show that our models outperform three state-of-the-art program characterization techniques on two multicore systems in selecting the best optimization combination from a given loop transformation space. We achieved up to 67% of the best possible speedup achievable with the optimization search space we evaluated.

Computer Science↗

(U) A Theoretical Study of Asay Foil Trajectories (V.02)

We consider the trajectory of a generic Asay foil ejecta momentum diagnostic sensor, for scenarios where ejecta are produced at a planar surface and fly ballistically through a perfect vacuum to the sensor. To do so, we build upon a previously established mathematical formalism derived for the analytic study of stationary sensors (i.e., piezopins). First, we derive the momentum conservation equation for the problem, in a form amenable to accelerating sensors, in terms of a generic ejecta source areal mass function (“source model”). This defines an integro-differential equation (IDE) for the foil trajectory. When ejecta production is instantaneous - as is generally assumed in momentum diagnostic data analyses - the IDE leads to an implicit and easily calculable closed-form solution for the foil trajectory in a perfect system, as long as the ejecta particle velocity distribution is twice-integrable. General properties of the instant-production trajectory solution indicate the existence of a boundary condition the particle velocity distribution must satisfy in order for the analytically predicted foil trajectories to be compatible with certain features commonly observed in foil data. This boundary condition is identical to one derived previously from a consideration of piezopin data. Armed with the analytic solution for instant production, we also consider various techniques used to extract time-dependent cumulative ejecta masses from foil trajectories, and derive an expression for the error imposed by using an approximated equation of motion. This analytic trajectory solution furthermore makes it possible to examine the common practice of presenting inferred cumulative ejecta masses as a function of a normalized implied velocity; we derive conditions under which this methodology is and is not meaningful. We also propose a strategy for extending the instant-production trajectory solution to time-dependent source functions.

42 ENGINEERING↗

DEIMoS: An Open-Source Tool for Processing High-Dimensional Mass Spectrometry Data

We present DEIMoS: Data Extraction for Integrated Multidimensional Spectrometry, a Python application programming interface and command-line tool for high-dimensional mass spectrometry data analysis workflows, offering ease of development and access to efficient algorithmic implementations. Functionality includes feature detection, feature alignment, collision cross section calibration, isotope detection, and MS/MS spectral deconvolution, with the output comprising detected features aligned across study samples and characterized by mass, CCS, tandem mass spectra, and isotopic signature. Notably, DEIMoS operates on N-dimensional data, largely agnostic to acquisition instrumentation: algorithm implementations utilize all dimensions simultaneously to (i) offer greater separation between features, improving detection sensitivity, (ii) increase alignment/feature matching confidence among datasets, and (iii) mitigate convolution artifacts in tandem mass spectra. We demonstrate DEIMoS with LC-IMS-MS/MS data, demonstrating the advantages of a multidimensional approach in each data processing step.

Colby, Sean M↗

XAFS Investigation of Uranium Binding by Seawater-Contacted Amidoxime Adsorbents

Extraction of uranium from seawater constitutes an important avenue for ensuring nuclear fuel availability beyond the coming century. With a predicted 100 years of uranium remaining in terrestrial ores, efficient extraction of the 4.5 billion tons of uranium dissolved in ocean water would enable access to an effectively limitless supply. More near-term benefits include establishment of a backstop technology, preventing runaway price inflation for this critical resource. The current state-of-the-art material for seawater extraction of uranium is a polymeric adsorbent composed of a robust trunk material subsequently surface functionalized by copolymerization of polyacrylonitrile and a hydrophilic comonomer. Treatment of this material with hydroxylamine results in the formation of poly-amidoxime functionalities which have been known to bind strongly with uranium since the early 1980's. Despite more than three decades of investigation, many questions remain unanswered regarding how these adsorbents bind uranium in seawater. The physical characteristics of the polymer prohibit many classical characterization techniques, while most spectroscopic approaches are impeded by the relatively low concentration of uranium compared to the polymer itself and other metals extracted by the adsorbent. The traditional approach has been to investigate small molecule analogues of uranyl - dioxouranium (VI), the form of uranium present in seawater - as bound by amidoxime or amidoxime derivatives, and assert the findings to be representative of the larger polymer system. Computational efforts have also been recently leveraged to a similar end. This approach is not without difficulty, as it has been routinely proposed that the treatment with hydroxylamine and subsequent alkaline conditioning results in formation of a cyclic imide dioxime site, which is truly responsible for uranium binding, as opposed to the 'open chain' amidoxime. Further complications ensue from considering the possibility of cooperative binding interactions from the different hydrophilic comonomers which are known to be necessary for optimizing uranium capacity. Finally, application of different surface polymerization techniques has the potential to directly affect the morphology of the surface polymer by influencing the degree of grafting, extent of polymer crosslinking, and polymer density. The impact of these morphological considerations on the uranyl binding environment cannot be easily replicated with small molecule studies or by computation. Ultimately, the precise binding environment of uranium is unknown, but constitutes critical knowledge for the design and engineering of advanced adsorbent materials capable of selective extraction of uranium from seawater. Analysis of the EXAFS fits reveals three of the four polymer morphologies appear to bind uranium in different chemical environments, none of which were predicted by crystallographic study or computational investigation, challenging numerous long-held assumptions. Both AI-8 and AN/HEA spectra possess features which could be attributable to cooperative binding of uranium by comonomers, but this cannot be definitively determined by EXAFS without further investigation. Unlike AF-1, neither AI-8 or AN/HEA require an adjacent μ{sup 2}-oxo-bridged transition metal to obtain a reasonable fit. The fit for Cyclic AF-1 is refined to almost identical parameters to the fit of the original AF-1 adsorbent, with the only difference is the contracting of the light elements in the second coordination sphere. It is thus proposed that the DMSO and heat treatment of the AF-1 fiber does very little to change the uranium binding site, and any differences in uptake are more readily explained by changes in the morphology of the graft polymer. There is no evidence for cyclic amidoxime functionality contributing significantly to the extraction of uranium from seawater, and efforts to maximize the number of these binding sites should be discontinued. While molecular interactions necessarily occur in adsorption processes, these results clearly reveal physical phenomena at the mesoscale play a critical role in adsorbent behavior, even to the extent that the binding environment differs from those predicted by small molecule studies. In contrast to the current paradigm where chemical functionality is varied, improvements in the performance of polymer-based amidoxime-functionalized adsorbents for extraction of uranium from seawater need also be pursued through interrogation and modulation of bulk morphology and improvements in polymer hydrophilicity. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Local measurement of thermal conductivity and diffusivity

Simultaneous measurement of local thermal diffusivity and conductivity is demonstrated on a range of ceramic samples. This was accomplished by measuring the temperature field spatial profile of samples excited by an amplitude modulated continuous wave laser beam. A thin gold film is applied to the samples to ensure strong optical absorption and to establish a second boundary condition that introduces an expression containing the substrate thermal conductivity. The diffusivity and conductivity are obtained by comparing the measured phase profile of the temperature field to a continuum based model. A sensitivity analysis is used to identify the optimal film thickness for extracting the both substrate conductivity and diffusivity. Proof of principle studies were conducted on a range of samples having thermal properties that are representatives of current and advanced accident tolerant nuclear fuels. It is shown that by including the Kapitza resistance as an additional fitting parameter, the measured conductivity and diffusivity of all the samples considered agreed closely with the literature values. A distinguishing feature of this technique is that it does not require a priori knowledge of the optical spot size which greatly increases measurement reliability and reproducibility.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Enhancing metaproteomics-The value of models and defined environmental microbial systems

Metaproteomics - the large-scale characterization of the entire protein complement of environmental microbiota at a given point in time - added unique features and possibilities to study environmental microbial communities and to unravel these “black boxes”. New technical challenges arose which were not an issue for classical proteome analytics before and choosing the appropriate model system applicable to the research question can be difficult. Here, we reviewed different model systems for metaproteome analysis. Following a short introduction to microbial communities and systems, we discussed the most used systems ranging from technical systems over rhizospheric models to systems for the medical field. This includes acid mine drainage, anaerobic digesters, activated sludge, planted fixed bed reactors, gastrointestinal simulators and in vivo models. Model systems are useful to evaluate the challenges encountered within (but not limited to) metaproteomics, including species complexity and coverage, biomass availability or reliable protein extraction. The implementation of model systems can be considered as a step forward to better understand microbial responses and ecological distribution of member organisms. In the future, novel improvements are necessary to fully engage complex environmental systems.

54 ENVIRONMENTAL SCIENCES↗

An enhanced droplet-based liquid microjunction surface sampling system coupled with HPLC-ESI-MS/MS for spatially resolved analysis

Droplet-based liquid microjunction surface sampling coupled with high-performance liquid chromatography (HPLC)-electrospray ionization (ESI)-tandem mass spectrometry (MS/MS) for spatially resolved analysis provides the possibility of effective analysis of complex matrix samples and can provide a greater degree of chemical information from a single spot sample than is typically possible with a direct analysis of an extract. Described here is the setup and enhanced capabilities of a discrete droplet liquid microjunction surface sampling system employing a commercially available CTC PAL autosampler. The system enhancements include incorporation of a laser distance sensor enabling unattended analysis of samples and sample locations of dramatically disparate height as well as reliably dispensing just 0.5 μL of extraction solvent to make the liquid junction to the surface, wherein the extraction spot size was confined to an area about 0.7 mm in diameter; software modifications improving the spatial resolution of sampling spot selection from 1.0 to 0.1 mm; use of an open bed tray system to accommodate samples as large as whole-body rat thin tissue sections; and custom sample/solvent holders that shorten sampling time to approximately 1 min per sample. Lastly, the merit of these new features was demonstrated by spatially resolved sampling, HPLC separation, and mass spectral detection of pharmaceuticals and metabolites from whole-body rat thin tissue sections and razor blade (“crude”) cut mouse tissue.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗