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At least 127 records · Page 7

Significant slowdown of plasma-optimized surface energy deactivation by vacuum sealing for efficient adhesive bonding

This work proposes an approach to minimize surface energy deactivation of plasma-treated metal and carbon fiber-reinforced polymer (CFRP) surfaces by vacuum sealing. Plasma treatments enhance adhesive wettability on post-treated surfaces for adhesive joints, but the treated surfaces deactivate quickly in air. The surface energy of aluminum alloy AA6061 and carbon fiber-reinforced polymer-polyamide (CFRP-PA66) optimally treated by a blown air plasma instrument returns to the original surface energy within one hour. Vacuum sealing of AA6061 and CFRP-PA66 reduced the surface energy deactivation over 7 days by at least 230 times and 970 times compared to in air. Double Cantilever Beam (DCB) tests performed on adhesively-bonded AA6061/CFRP-PA66 joints showed that the total energy release and energy dissipation before failure of plasma-treated and vacuum-sealed materials was up to 60% more than plasma-treated materials without vacuum sealing and up to 125% more than non-plasma-treated materials.

42 ENGINEERING↗

Modeling Ring Current Proton Fluxes Using Artificial Neural Network and Van Allen Probe Measurements

Abstract Terrestrial ring current dynamics are a critical part of the near‐space environment, in that they directly drive geomagnetic field variations that control particle drifts, and define geomagnetic storms. The present study aims to specify a global and time‐varying distribution of ring current proton using geomagnetic indices and solar wind parameters with their history as input. We train an artificial neural network (ANN) model to reproduce proton fluxes measured by the Radiation Belt Storm Probes Ion Composition Experiment instrument onboard Van Allen Probes. By choosing optimal feature parameters and their history length, the model results show a high correlation and a small error between model specifications and satellite measurements. The modeled results well capture energy‐dependent proton dynamics in association with geomagnetic storms, including inward radial diffusion, acceleration and decay. Our ANN model produces proton fluxes with their corresponding 3D spatiotemporal variations, capturing the latitudinal distribution and local time asymmetry that are consistent with observations and that can further inform theory.

Li, Jinxing↗

High frequency beam oscillation keyhole dynamics in laser melting revealed by in-situ x-ray imaging

The metal additive manufacturing industry is actively developing instruments and strategies to enable higher productivity, optimal build quality, and controllable as-built microstructure. A beam controlling technique, laser oscillation has shown potential in all these aspects in laser welding; however, few attempts have been made to understand the underlying physics of the oscillating keyholes/melt pools which are the prerequisites for these strategies to become a useful tool for laser-based additive manufacturing processes. Here, to address this gap, we utilized a synchrotron-based X-ray operando technique to image the dynamic keyhole oscillation in Ti-6Al-4V using a miniature powder bed fusion setup. We found good agreement between the experimental observations and simulations performed with a validated Lattice Boltzmann multiphysics model. The study revealed the continuous and periodic fluctuations in the characteristic keyhole parameters that are unique to the oscillating laser beam processing and responsible for the chevron pattern formation at solidification. In particular, despite the intrinsic longer-range fluctuation, the oscillating technique displayed potential for reducing keyhole instability, mitigating porosity formation, and altering surface topology. These insights on the oscillating keyhole dynamics can be useful for the future development and application of this technique.

36 MATERIALS SCIENCE↗

The clustering of Lyman Alpha Emitting galaxies at 𝗓=2–3

Here, we measure the clustering of Lyman Alpha Emitting galaxies (LAEs) selected from the One-hundred-square-degree DECam Imaging in Narrowbands (ODIN) survey, with spectroscopic follow-up from Dark Energy Spectroscopic Instrument (DESI). We use DESI spectroscopy to optimize our selection and to constrain the interloper fraction and redshift distribution of our narrow-band selected sources. We select samples of 4000 LAEs at z = 2.45 and 3.1 in 9 sq. deg. centered on the COSMOS field with median Lyα fluxes of ≈ 10 -16 erg s -1 cm -2 . Covariances and cosmological inferences are obtained from a series of mock catalogs built upon high-resolution N-body simulations that match the footprint, number density, redshift distribution and observed clustering of the sample. We find that both samples have a correlation length of r 0 = 3.0 ± 0.2 h -1 Mpc. Within our fiducial cosmology these correspond to 3D number densities of ≈ 10 -3 h 3 Mpc -3 and, from our mock catalogs, biases of 1.7 and 2.0 at z= 2.45 and 3.1, respectively. We discuss the implications of these measurements for the use of LAEs as large-scale structure tracers for high-redshift cosmology.

79 ASTRONOMY AND ASTROPHYSICS↗

Discovering the 3D Structure and Dynamics of the Sun-Interstellar Medium System on a Global Scale Los Alamos LDRD Report

We discover the 3D plasma structure of the Sun-interstellar medium interaction region, called the heliosheath. This is enabled by (1) the completion of a full solar cycle of observations of hydrogen energetic neutral atoms (ENAs) emanating from this region and detected by the Los Alamos-led IBEX-Hi ENA imager on NASA’s Interstellar Boundary Explorer (IBEX) mission, and (2) the development of tools to fully exploit all data from the IBEX-Hi imager, leading to a significant increase in the effective instrument sensitivity. This effort prepares us for optimizing the design and data exploitation of the IMAP-Hi imager, the Los Alamos-led next generation imager that will fly on the Interstellar Mapping and Acceleration Probe (IMAP) mission, currently under production. This project realized its goals as evidenced by two main outcomes: (1) The publication of the first-ever empirical 3D map of the interstellar boundary, and (2) the development and release of a new validated ENA data set that has tripled the amount of data available for scientific analysis of the outer heliosphere.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Improving Self-Driving Labs: Quantifying System-Level Experiment Repeatability and Broadening Instrument-Level Compatibility

Modular Autonomous Research System (MARS) is a self-driving laboratory (SDL) which performs wet-lab science with peptide-lanthanide combinations in an automated and, ultimately, an autonomous manner to aid in soil analysis for domestic lithium mining. Autonomous experimentation involves automated experimentation, experiment planning, and active learning. MARS consists of a 6-axis robotic arm (UR5e) on a linear rail, pipette robots (Opentrons 2), and microplate readers. These components transport, operate on, and collect data with chemical solutions in standard labware. For effective autonomy, MARS must perform system-level labware operations repeatably, plan experiments autonomously, and be portable between research-domains. Repeatability is evaluated by labware placement precision, such that future operations can properly locate labware, as well as the elapsed time, so that low variance mean estimates of experiment duration can inform high-level researcher decision making. Autonomous experiment planning is the next step to decouple experimentation from human management; however, there is a conflict between the ideal system-level experiment goals and the constraints imposed by instruments’ limitations. Sub-domain portability is a long-term goal to extend MARS’ research beyond the chemistry of peptide-lanthanide binding to other sub-domains without having to invest significant overhead to system retrofitting. To address these goals, we manually trained the robotic arm labware placement and modelled statistical failurerate and uncertainty Additionally, we benchmarked the duration and variance of each experiment sub-operation as a heuristic for research decision making. Next, we use a parameterized geometric program (PGP) approach to design experiments that optimize system-level objectives and satisfy instrument-level constraints. Lastly, we proposed a Python framework to maximize MARS’ extensibility to other scientific sub-domains through a JSON-based experiment specification.

36 MATERIALS SCIENCE↗

Correlation-aware binning for small-angle neutron scattering via Gaussian-process inference

Binning in small-angle neutron scattering (SANS) is typically performed empirically, with fixed parameters chosen for convenience rather than statistical optimality. Such practices often fail to balance statistical precision and spatial resolution, leading to inconsistencies across instruments and datasets. Here we establish a correlation-aware framework that determines the optimal bin width from first principles by extending the classical Freedman–Diaconis (FD) rule to account for inter-bin correlations with a Gaussian process. In this formulation, the scattering intensity is treated as a smooth stochastic field whose statistical coherence is described by a covariance matrix. Analytical expressions of errors derived from this model yield closed-form criteria that separate the total deviation into contributions from counting noise, aliasing distortion and curvature-dependent correlation effects. Expressed in reduced variables, the resulting dimensionless error surface reveals a continuous transition from the uncorrelated FD regime to the correlation-dominated limit, providing a unified description of noise suppression and resolution control. Because the formulation depends only on the profile characteristics of scattering intensity I(Q), specifically its average intensity and first- and second-order derivatives, it applies generally to any SANS measurement regardless of sample, instrument or geometry. Experimental validation using small- and ultra-small-angle neutron scattering data confirms the predicted scaling behavior, demonstrating that correlation-aware inference systematically reduces mean-squared error and enables information-efficient reproducible data reduction across materials and instruments.

Tung, Chi-Huan [ORNL] (ORCID:0000000221972074)↗

Fast Neutron Radiography Simulations

Conclusions: Elements other than detector array can heavily impact performance; Must consider a variety of alterations to an imaging array to determine an optimal system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Design and simulation of multilayer coatings for a multi-channel Wolter-like x-ray imager with large field of view and high resolution

X-ray diagnostics are key instruments for understanding the physics behind inertial confinement fusion experiments. We report on the multilayer design optimization for the Toroidal X-ray Imager (TXI), a hard x-rays microscope instrument designed by Commissariat à l’énergie atomique (CEA) and Laboratoire Charles Fabry (LCF) to be installed on the National Ignition Facility. TXI includes six channels designed for three different energy bands centered on 8.7, 13, and 17.5 keV. Each channel is made up of two toroidal mirrors arranged in a Wolter-like configuration. The required field of view is 800 × 400 µm2, and the resolution should be better than 5 µm. In addition, we seek to estimate the spatial distribution of the temperature, which requires no spectral overlap of the different energy bands and a good spectral homogeneity of the image produced. The development of the multilayer coatings was performed in a two-step method. First, the coatings were optimized to obtain proper energy bands. Then, an x-ray tracing code was used to calculate the integrated optical response of each channel and adjust the response of the mirror to fulfill the requirements. To fulfill all the specifications, we propose an original design using a combination of two aperiodic coatings, one with a narrow bandwidth and the other one with a larger bandwidth.

hard x-rays↗

A high transmission tender X-ray monochromator employing a matched pair of multilayer grating and mirror

It is now well established that multilayer coated gratings may offer high diffraction efficiencies over the tender X-ray range, from about 1 keV to 5 keV, covering the gap between single layer coated grating monochromators and crystal monochromators. Nevertheless, few beamlines in the world are using such gratings in their monochromator. The successful implementation of a multilayer grating monochromator requires producing a matched pair of a multilayer grating and a multilayer mirror, and this matching is not straightforward as it must account for different incidence angles and refraction effects on each element. Here we review the realization of the multilayer grating monochromator of the SIRIUS beamline which has been successfully in service for several years. We show how, by alternating computer simulation with our diffraction code and measurements, we could optimize the monochromator transmission on a very wide energy range. After the grating was coated, it was found that the angle of optimal efficiency versus photon energy was significantly different from what was predicted by a simple conformal model of binary layers. Layer interdiffusion and profile smoothing during the deposition process must be added to the multilayer model to reproduce the measured data. The critical adjustment of the mirror multilayer period is achieved by the lateral translation of the mirror, which was given a small transverse period gradient. The monochromator is thus providing high transmission efficiency in the 1 to 5 keV energy range, more than 30% over 2.5 keV and up to 46% at 4.6 keV.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Optimization of neutron chopper and optics for CENTAUR, the SANS/WANS diffractometer at the spallation neutron source second target station

Herein this report presents the physics design and optimization of the neutron chopper and optics systems for the CENTAUR instrument, a multifunctional small-angle and wide-angle neutron scattering diffractometer for the Spallation Neutron Source Second Target Station. This instrument will offer a wide range of capabilities, including small-angle neutron scattering with wide Q coverage (e.g., 0.001–20 Å –1 ), providing a tool to investigate structures from atomic to mesoscopic scales simultaneously. To efficiently transport desired neutrons from the compact high-brightness cold source, several innovative designs are utilized: a time-zero chopper with a straight guide system for short-wavelength neutrons, octagonal guides for higher flux, and a correlation chopper to reduce inelastic scattering. The optimization process considers factors such as useable time-integrated flux, instrument resolution, brilliance transfer, divergence, and acceptance diagram uniformity. The overall design prioritizes flexibility to accommodate diverse user requirements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

AEcroscopy: A Software–Hardware Framework Empowering Microscopy Toward Automated and Autonomous Experimentation

Microscopy has been pivotal in improving the understanding of structure-function relationships at the nanoscale and is by now ubiquitous in most characterization labs. However, traditional microscopy operations are still limited largely by a human-centric click-and-go paradigm utilizing vendor-provided software, which limits the scope, utility, efficiency, effectiveness, and at times reproducibility of microscopy experiments. Here, in this work, a coupled software–hardware platform is developed that consists of a software package termed AEcroscopy (short for Automated Experiments in Microscopy), along with a field-programmable-gate-array device with LabView-built customized acquisition scripts, which overcome these limitations and provide the necessary abstractions toward full automation of microscopy platforms. The platform works across multiple vendor devices on scanning probe microscopes and electron microscopes. It enables customized scan trajectories, processing functions that can be triggered locally or remotely on processing servers, user-defined excitation waveforms, standardization of data models, and completely seamless operation through simple Python commands to enable a plethora of microscopy experiments to be performed in a reproducible, automated manner. This platform can be readily coupled with existing machine-learning libraries and simulations, to provide automated decision-making and active theory-experiment optimization to turn microscopes from characterization tools to instruments capable of autonomous model refinement and physics discovery.

47 OTHER INSTRUMENTATION↗

A nearsighted force-training approach to systematically generate training data for the machine learning of large atomic structures

A challenge of atomistic machine-learning (ML) methods is ensuring that the training data are suitable for the system being simulated, which is particularly challenging for systems with large numbers of atoms. Most atomistic ML approaches rely on the nearsightedness principle (“all chemistry is local”), using information about the position of an atom’s neighbors to predict a per-atom energy. Here, in this work, we develop a framework that exploits the nearsighted nature of ML models to systematically produce an appropriate training set for large structures. We use a per-atom uncertainty estimate to identify the most uncertain atoms and extract chunks centered around these atoms. It is crucial that these small chunks are both large enough to satisfy the ML’s nearsighted principle (that is, filling the cutoff radius) and are large enough to be converged with respect to the electronic structure calculation. We present data indicating when the electronic structure calculations are converged with respect to the structure size, which fundamentally limits the accuracy of any nearsighted ML calculator. These new atomic chunks are calculated in electronic structures, and crucially, only a single force—that of the central atom—is added to the growing training set, preventing the noisy and irrelevant information from the piece’s boundary from interfering with ML training. The resulting ML potentials are robust, despite requiring single-point calculations on only small reference structures and never seeing large training structures. We demonstrated our approach via structure optimization of a 260-atom structure and extended the approach to clusters with up to 1415 atoms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Going mobile to address emerging climate equity needs in the heterogeneous urban environment

We report the Brookhaven National Laboratory Center for Multiscale Applied Sensing (CMAS) aims to address environmental equity needs in the context of a changing climate. As a first step towards this goal, the center developed a one-of-a-kind observatory tailored to the study of highly heterogeneous urban environments. This article describes the features of the mobile observatory that enable its rapid deployment either on or off the power grid, as well as its instrument payload. Beyond its unique design, the observatory optimizes data collection within the obstacle-laden urban environment using a new smart sampling paradigm. This setup facilitated the collection of previously poorly documented environmental properties including wind profiles throughout the atmospheric column. The mobile observatory captured unique observations during its first few intensive observation periods (IOPs).. Vertical air motion and infrared temperature measurements collected along the faces of the supertall One Vanderbilt skyscraper in Manhattan, NY reveal how solar and anthropogenic heating affect wind flow and thus the venting of heat, pollution, and contaminants in urban street canyons. Also, air temperature measurements collected during travel along a 150-km transect between Upton and Manhattan, NY offer a high-resolution view of the urban heat island and reveal that temperature disparities also exist within the city across different neighborhoods. Ultimately, the datasets collected by CMAS are poised to help guide equitable urban planning by highlighting existing disparities and characterizing the impact of urban features on the urban microclimate with the goal of improving human comfort.

54 ENVIRONMENTAL SCIENCES↗

Predicting ptychography probe positions using single-shot phase retrieval neural network

Ptychography is a powerful imaging technique that is used in a variety of fields, including materials science, biology, and nanotechnology. However, the accuracy of the reconstructed ptychography image is highly dependent on the accuracy of the recorded probe positions which often contain errors. These errors are typically corrected jointly with phase retrieval through numerical optimization approaches. When the error accumulates along the scan path or when the error magnitude is large, these approaches may not converge with satisfactory result. We propose a fundamentally new approach for ptychography probe position prediction for data with large position errors, where a neural network is used to make single-shot phase retrieval on individual diffraction patterns, yielding the object image at each scan point. The pairwise offsets among these images are then found using a robust image registration method, and the results are combined to yield the complete scan path by constructing and solving a linear equation. We show that our method can achieve good position prediction accuracy for data with large and accumulating errors on the order of 10 2 pixels, a magnitude that often makes optimization-based algorithms fail to converge. For ptychography instruments without sophisticated position control equipment such as interferometers, our method is of significant practical potential.

47 OTHER INSTRUMENTATION↗

Leveraging Calibration Transfer Techniques for Remote Monitoring of Samarium and Europium in LiCl Using Laser-Induced Florescence Spectroscopy for Radioisotope Production Applications

Radioisotope production relies on complex chemical processes that must be performed in radiological hot cells or glove boxes because of the radioactive and otherwise hazardous materials being used. In these situations, optical sensors can provide real-time monitoring to users, which is unobtainable by more traditional methods. This study explores the use of calibration transfer methods to train a model on one instrument and date and then transfer it to another instrument of the same or different configuration on a different date. By performing laser-induced fluorescence measurements of Eu(III) and Sm(III) in 10 M LiCl over the course of 6 months using two disparate spectrometers and two different training sets, a strategy for calibrating and deploying models for online monitoring was established. Three transfer techniques were compared: direct standardization (DS), piecewise direct standardization (PDS), and external parameter orthogonalization (EPO). DS and PDS outperformed EPO for day-to-day transfers, and EPO was not effective for instrument-to-instrument transfers. Transferring the initial date’s full factorial model provided better prediction performance compared with retraining models the day of measurements using a D-optimal designed calibration set. For both day-to-day and instrument-to-instrument transfers, five Kennard–Stone selected samples were sufficient. Based on this choice, the initial-date, high-resolution spectrometer model was transferred to a lower-resolution, compact spectrometer 6 months later to monitor a simulated, real-time demonstration. Here, the combined predictions of the DS and PDS transferred models were able to accurately track the anticipated concentration profiles, maintaining root-mean-square error of prediction values below 10 ppm.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Material and Design Optimization of Printed Melt Wire Arrays

Recent work conducted by the Advanced Sensors and Instrumentation (ASI) program at Idaho National Laboratory resulted in the establishment of in-house capabilities for fabricating and testing new advanced manufactured sensors for measuring irradiation temperatures inside a nuclear test reactor. Though current methods of real-time temperature monitoring (e.g., thermocouples) can still be used, the complexity of the feedthroughs and attachments needed for collecting real time measurements greatly increases the experiment-related costs. On the other hand, passive monitoring techniques can be used for collecting post irradiation temperature measurements by inferring reactor temperatures, based on the melting points of well-characterized materials (i.e., standard melt wires). However, challenges have arisen due to the limited space available for including instrumentation in experiments. To resolve this issue, the ASI program expanded its temperature detection capabilities to include advance manufactured melt wires for post-irradiation temperature measurements. These melt wires can determine reactor temperatures while also accommodating space limitations in irradiation experiments. To improve performance reliability and enhance melt wire readability following irradiation, FY-22 efforts have focused on optimizing the materials used in the encapsulation and printed melt wire array. This report details the design and fabrication tasks, along with the subsequent x ray computed tomography (XCT) evaluation process. The melt wire array consisted of indium with a melting point of 157°C, indium/silver (96/4 at%) with a melting point of 219°C, and tin with a melting point of 230°C. The encapsulation disc was made of vanadium due to its low activation properties and radiation resistance when deployed in nuclear reactors. Additionally, the melt wire design consisted of a ceramic sublayer (alumina disc) to further enhance the XCT post melting images of the printed melt wires. However, when sealing the vanadium container, all three melt wires melted, reflecting the temperature limitations that must be considered when employing metal containers in the sealing process.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Binary pseudorandom array test standard optimized for characterization of large field-of-view optical interferometers

Recently, a technique for calibrating the modulation transfer function (MTF) of a broad variety of metrology instrumentation has been demonstrated. This technique is based on test samples structured as one-dimensional binary pseudo-random (BPR) sequences and two-dimensional BPR arrays (BPRAs). The inherent power spectral density of BPR gratings (sequences) and arrays has a deterministic white-noise-like character that allows direct determination of the MTF with uniform sensitivity over the entire spatial frequency range and field-of-view of an instrument. As such, the BPR samples satisfy the characteristics of a test standard: functionality, ease of specification and fabrication, reproducibility, and low sensitivity to manufacturing error. Here we discuss our recent developments directed to the optimization of the sample design, fabrication, application, and data processing procedures, suitable for thorough characterization of large aperture optical interferometers. Compared with the previous coded-aperture based design, the improved, 'highly randomized' BPRA pattern of the new test standard provides better accuracy and reliability of instrument MTF and aberration characterization, and enables operation optimization of large aperture optical interferometers. We describe the pattern generation algorithm and tests to verify the compliance to desired BPRA topography. The data acquisition and analysis procedures for different applications of the technique are also discussed.

Yashchuk, Valeriy V.↗