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At least 109 records · Page 6

Rapid macrovoid characterization in membranes prepared via nonsolvent-induced phase separation: A comparison between 2D and 3D techniques

Optimizing the performance of asymmetric membranes prepared via nonsolvent-induced phase separation (NIPS) requires a quantitative understanding of how processing variables influence membrane morphology. Presently, the most useful structural quantification techniques require 3D visualization of the membrane structure and are best suited for studies seeking detailed information on small datasets. This study proposes and validates a rapid and accurate technique for quantifying macroporosity (i.e., D m ), a simple descriptor of sublayer macrovoid content in asymmetric membranes D m . values measured from segmented cross-sectional imaging performed via X-ray computed tomography (XCT) and scanning electron microscopy (SEM) are presented and compared for three asymmetric membranes prepared from commercial polymers. Importantly, analyses of 3D XCT membrane reconstructions reveal that D m is described by a single, centralized mean, which demonstrates that macrovoid content is spatially homogenous. Thus, D m can be approximated from limited sampling of the 2D cross-sectional membrane structure via SEM. A proposed 2D SEM sampling method provides D m estimates within ±6% of corresponding 3D XCT values with 30 independent measurements for the three membranes. Further sensitivity is achieved using complementary descriptors such as macrovoid count density (i.e., C m ). This technique is thus a useful tool for characterizing macroporosity from a broad selection of membrane samples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Accelerated radiation transport modeling techniques for pencil beam computed tomography using gamma rays

Monte Carlo radiation transport modeling studies were performed for a compact, and high-resolution gamma-ray computed tomography system designed for imaging irradiated nuclear fuel. The system comprises a 60 Co source – chosen for its highly penetrating 1173 keV and 1332 keV gamma rays – a pair of high-aspect-ratio pencil beam collimators, and an inorganic scintillator detector. Here two acceleration methods are proposed to rapidly model a transmission type gamma-ray tomography system. The first, a variance reduction technique, is based on performing Monte Carlo simulations with a monodirectionally-biased source, sampled from a characteristic sub-volume of the full source volume. The second acceleration method is based on the deterministic calculations using the Beer–Lambert law and detector response characteristics. Comparison of simulations using acceleration approaches with analog simulations of the fully isotropic, full-volume equivalent, show that the Monte Carlo variance reduction technique gives quantitatively accurate predictions for large collimator aspect ratios while the deterministic calculations are semi-quantitative but converge close to the correct result as the collimator aspect ratio increases. As such, these techniques can be used to reduce the computational cost in generating simulated radiographs and tomographs by several orders of magnitude. Experimental validation efforts are currently underway and will be demonstrated in future work.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Use of a deuterium-deuterium neutron generator for the Add-A-Source waste matrix correction technique

Neutron generators offer an alternative to radioactive sources in the application of active techniques for nondestructive assay of nuclear materials. The Add-A-Source technique has enabled improvements in the ability to accurately measure waste bearing nuclear materials by measuring and correcting for the non-nuclear matrix effect. The technique has historically been performed with a Cf-252 spontaneous fission source. Here, in this work, we have demonstrated the use of a Deuterium-deuterium neutron generator in place of the Cf-252 source. A DD generator enables operational advantages and allows the simplification of the instrument design, while offering equivalent corrective performance as a Cf-252 source.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Gas stopping and reacceleration techniques at the Facility for Rare Isotope Beams (FRIB)

The Facility for Rare Isotope Beams (FRIB) at Michigan State University provides a wide range of beams and energies for science with fast, stopped and reaccelerated rare-isotope beams. FRIB was commissioned in 2022 with the science program beginning in May 2022. Here, the combination of fast beams followed by gas stopping of rare-isotope beams together with reacceleration is unique to FRIB. Stopping techniques and beam manipulation at very-low energies are important to slow down fast beams for use in either stopped-beam experimental devices, or subsequent injection in the reaccelerator for experiments at energies ranging from 0.3 MeV/u to 12 MeV/u, depending on the Q/A of the ion. Innovative stopped-beam techniques to optimize the stopping and extraction efficiencies across a wide range of atomic numbers, as well as to reduce contamination and increase extraction speed, were developed. Reacceleration of those beams involve cooling, bunching, charge breeding and acceleration by a state-of-the-art superconducting reaccelerator, ReA. In this contribution we present the latest results of various gas stoppers and techniques to eliminate contaminants after reacceleration by the ReA.

43 PARTICLE ACCELERATORS↗

An adaptive knowledge-based data-driven approach for turbulence modeling using ensemble learning technique under complex flow configuration: 3D PWR sub-channel with DNS data

This work describes a new approach to increase the accuracy of Reynolds-averaged Navier–Stokes (RANS) in modeling turbulence flow leveraging the machine learning technique. Traditionally, different turbulence models for Reynolds stress are developed for different flow patterns based on human knowledge. Each turbulence model has a certain application domain and prediction uncertainty. In recent years, with the rapid improvements of machine learning techniques, researchers start to develop an approach to compensate for the prediction discrepancy of traditional turbulence models with statistical models and data. However, the approach has deficiencies in several aspects. For example, the amount of human knowledge introduced to the statistical model couldn’t be controlled, which makes the statistical model learn from a very naïve stage and limits its application. In this work, a new approach is developed to address those deficiencies. Here, the new approach uses the “ensemble learning” technique to control the amount of human knowledge introduced into the statistical model. Therefore, the new approach could be adaptive to the multiple application domains. In conclusion, according to the results of case study, the new approach shows higher accuracy than both traditional turbulence models and the previous machine learning approach.

42 ENGINEERING↗

Modeling simultaneous particle shrinkage, dissolution and breakage using the modified moving grid technique

Simultaneous shrinkage, dissolution and breakage are important particle size reduction phenomena that characterize processes like the reactive degradation of solid chemicals. The dynamics of the particle size distribution (PSD) for such processes are non-trivial to model due to the number expending processes brought about by the eventual dissolution of particles. To this end, Population Balance Model (PBM) resolved through the sectional techniques is the natural approach. Here, we introduce a modified Moving Grid technique (m-MGT) to accurately resolve the particle size reduction phenomena. Our technique mimics the perpetual particle shrinkage through a continuously left-moving size grid and incorporates a strategic grid removal routine to capture the disappearance of particles. Coupled with the Fixed Pivot (FP) discretization for breakage, our m-MGT not only preserves the moment-related properties, but also benchmarked very well against the analytical number densities and exhibited a minimum of first-order convergence in all assessed case studies.

97 MATHEMATICS AND COMPUTING↗

Formation and degradation mechanism of methylammonium lead iodide perovskite thin film fabricated by electrospray technique

Electrospray deposition technique has been reported previously for fabricating effective and stable perovskite thin film, leading to efficient perovskite solar cells. Here, in this work, a comprehensive investigation of the formation mechanism of methylammonium lead iodide perovskite (CH 3 NH 3 PbI 3 ) film by electrospray technique is demonstrated and compared to the formation mechanism through the conventional spin coating technique. In the electrospray process, charged MAI nanoparticles are gradually introduced onto the PbI 2 film, intercalating within the PbI 2 structure to produce the perovskite film. In contrast, the spin-coating method involves supplying the MAI solution in bulk, leading to perovskite crystal formation through the dissolution of the PbI 2 layer by the MAI solution, followed by recrystallization into perovskite oriented in the [110] direction, 30° inclined to the substrate. The impact of charge and the electric field on the formation of perovskite film using the electrospray is explored. Furthermore, the intrinsic stability of perovskite films is monitored in real-time in a highly humid environment (≥80 % relative humidity (RH)) using in-situ Grazing Incidence Wide Angle X-ray Scattering (GIWAXS), and a degradation mechanism is proposed to enhance the durability of the perovskite-based devices. The study further delves into the comparison of the stability of electrosprayed and spin-coated perovskite film, and the impact of humidity level and the presence of a hole-transporting layer on the stability of the perovskite layer. Overall, this work provides a detailed understanding of the formation and humidity-induced degradation mechanism of electrosprayed perovskite films, offering insights that can extend to various applications of perovskite materials.

14 SOLAR ENERGY↗

A Deep Learning-Driven Sampling Technique to Explore the Phase Space of an RNA Stem-Loop

The folding and unfolding of RNA stem-loops are critical biological processes; however, their computational studies are often hampered by the ruggedness of their folding landscape, necessitating long simulation times at the atomistic scale. Here, we adapted DeepDriveMD (DDMD), an advanced deep learning-driven sampling technique originally developed for protein folding, to address the challenges of RNA stem-loop folding. Although tempering- and order parameter-based techniques are commonly used for similar rare-event problems, the computational costs or the need for a priori knowledge about the system often present a challenge in their effective use. DDMD overcomes these challenges by adaptively learning from an ensemble of running MD simulations using generic contact maps as the raw input. DeepDriveMD enables on-the-fly learning of a low-dimensional latent representation and guides the simulation toward the undersampled regions while optimizing the resources to explore the relevant parts of the phase space. We showed that DDMD estimates the free energy landscape of the RNA stem-loop reasonably well at room temperature. Our simulation framework runs at a constant temperature without external biasing potential, hence preserving the information on transition rates, with a computational cost much lower than that of the simulations performed with external biasing potentials. Here, we also introduced a reweighting strategy for obtaining unbiased free energy surfaces and presented a qualitative analysis of the latent space. This analysis showed that the latent space captures the relevant slow degrees of freedom for the RNA folding problem of interest. Finally, throughout the manuscript, we outlined how different parameters are selected and optimized to adapt DDMD for this system. We believe this compendium of decision-making processes will help new users adapt this technique for the rare-event sampling problems of their interest.

Gupta, Ayush↗

Lithium–Sulfur Batteries: 3D Printed Tools and Assembly Techniques for Repeatable Lab-Scale Coin Cell Manufacturing

The coin cell form factor has become a standard in energy storage research owing to its relatively low cost, low quantity of requisite electroactive material, fast experimental turnover, and capability to generate publishable quality data. Coin cell assembly at the lab-scale requires precise manual alignment of the many internal components of a cell to yield a properly functioning device. Truly repeatable device assembly presents a significant challenge to the acquisition of reliable data. In this report, we present a three-dimensional (3D) printable design for a coin cell alignment device and describe techniques for a generalized workflow to achieve reproducible coin cell assembly of lithium-based batteries. Standardized assembly techniques using readily accessible, purpose-built tools were demonstrated for labscale production of lithium−sulfur (Li−S) coin cells. Li−S batteries fabricated using the alignment device as well as conductive adhesive incorporated workflows afforded coin cells with up to 35% reduction of assembly times, comparable or better functional cell yields, and improved electrochemical device performance with more consistent and up to 150 mAh/g higher average discharge capacities coupled with Coulombic efficiency increases of up to 2.0% over manually aligned cell assembly techniques.

Batteries↗

How May the Choice of Downscaling Techniques and Meteorological Reference Observations Affect Future Hydroclimate Projections?

Abstract We present an intercomparison of a suite of high‐resolution downscaled climate projections based on a six‐member General Circulation Model (GCM) ensemble from Coupled Models Intercomparison Project (CMIP6). The CMIP6 GCMs have been downscaled using dynamical and statistical downscaling techniques based on two meteorological reference observations over the conterminous United States. We use the regional climate model, RegCM4, for dynamical downscaling, double bias correction constructed analogs method for statistical downscaling, and Daymet and Livneh datasets as the reference observations for statistical training and bias‐correction. We evaluate the performances of downscaled data in both historical and future periods under the SSP585 scenario. While dynamical downscaling improves the simulation of some performance evaluation indices, it adds an extra bias in others, highlighting the need for statistical correction before its use in impact assessments. Downscaled datasets after bias‐correction compare exceptionally well with observations. However, the choice of downscaling techniques and the underlying reference observations influence the hydroclimate characteristics of downscaled data. For instance, the statistical downscaling generally preserves the GCMs climate change signal but overestimates the frequency of hot extremes. Similarly, simulated future changes are sensitive to the choice of reference observations, particularly for precipitation extremes that exhibit a higher projected increase in the ensembles trained and/or corrected by Daymet than Livneh. Overall, these results demonstrate that multiple factors, including downscaling techniques and reference observations, can substantially influence the outcome of downscaled climate projections and stress the need for a comprehensive understanding of such method‐based uncertainties.

54 ENVIRONMENTAL SCIENCES↗

Techniques for studying materials under extreme states of high energy density compression

The properties of materials under extreme conditions of pressure and density are of key interest to a number of fields, including planetary geophysics, materials science, and inertial confinement fusion. In geophysics, the equations of state of planetary materials, such as hydrogen and iron, under ultrahigh pressure and density provide a better understanding of their formation and interior structure [Celliers et al., “Insulator-metal transition in dense fluid deuterium,” Science 361, 677–682 (2018) and Smith et al., “Equation of state of iron under core conditions of large rocky exoplanets,” Nat. Astron. 2, 591–682 (2018)]. The processes of interest in these fields occur under conditions of high pressure (100 GPa–100 TPa), high temperature (>3000 K), and sometimes at high strain rates (>103 s−1) depending on the process. With the advent of high energy density (HED) facilities, such as the National Ignition Facility (NIF), Linear Coherent Light Source, Omega Laser Facility, and Z, these conditions are reachable and numerous experimental platforms have been developed. To measure compression under ultrahigh pressure, stepped targets are ramp-compressed and the sound velocity, measured by the velocity interferometer system for any reflector diagnostic technique, from which the stress-density of relevant materials is deduced at pulsed power [M. D. Knudson and M. P. Desjarlais, “High-precision shock wave measurements of deuterium: Evaluation of exchange-correlation functionals at the molecular-to-atomic transition,” Phys. Rev. Lett. 118, 035501 (2017)] and laser [Smith et al., “Equation of state of iron under core conditions of large rocky exoplanets,” Nat. Astron. 2, 591–682 (2018)] facilities. To measure strength under high pressure and strain rates, experimenters measure the growth of Rayleigh–Taylor instabilities using face-on radiography [Park et al., “Grain-size-independent plastic flow at ultrahigh pressures and strain rates,” Phys. Rev. Lett. 114, 065502 (2015)]. The crystal structure of materials under high compression is measured by dynamic x-ray diffraction [Rygg et al., “X-ray diffraction at the national ignition facility,” Rev. Sci. Instrum. 91, 043902 (2020) and McBride et al., “Phase transition lowering in dynamically compressed silicon,” Nat. Phys. 15, 89–94 (2019)]. Medium range material temperatures (a few thousand degrees) can be measured by extended x-ray absorption fine structure techniques, Yaakobi et al., “Extended x-ray absorption fine structure measurements of laser-shocked V and Ti and crystal phase transformation in Ti,” Phys. Rev. Lett. 92, 095504 (2004) and Ping et al., “Solid iron compressed up to 560 GPa,” Phys. Rev. Lett. 111, 065501 (2013), whereas more extreme temperatures are measured using x-ray Thomson scattering or pyrometry. This manuscript will review the scientific motivations, experimental techniques, and the regimes that can be probed for the study of materials under extreme HED conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A super-resolution technique to analyze single-crystal inelastic neutron scattering measurements using direct-geometry chopper spectrometers

Direct-geometry time-of-flight chopper neutron spectroscopy is instrumental in studying dynamics in liquid, powder, and single crystal systems. We report here that real-space techniques in optical imagery can be adapted to obtain reciprocal-space super resolution dispersion for phonon or magnetic excitations from single-crystal neutron spectroscopy measurements. The procedure to reconstruct super-resolution energy dispersion of excitations relies on an accurate determination of the momentum and energy-dependent point spread function and a dispersion correction technique inspired by an image disparity calculation technique commonly used in stereo imaging. Here by, applying these methods to spinwave dispersion data from a virtual neutron experiment demonstrates ~5-fold improvement over nominal energy resolution.

47 OTHER INSTRUMENTATION↗

An updated technique to obtain explosive kinetics data on microsecond timescales

There are few techniques available for chemists to obtain time-to-explosion data with known temperature inputs at the early stages of the design and synthesis of new explosives. In the 1960s, a technique was developed to rapidly heat milligram-quantities of confined explosives to ~1000 K on microsecond timescales. Wenograd loaded explosives inside stainless steel hypodermic needles, connected them to a fireset and rapidly discharged a capacitor through the steel. He obtained the temperature by measuring the needle resistance in a Wheatstone bridge arrangement and the time to explosion from a needle rupture. However, owing to the narrow-gauge needles used in the original research, the experiment was only possible with melt-castable explosives; it was never replicated, and modern diagnostics are now available with advances beyond the 1960s. Here, we report the development of the High Explosives Initiation Time (HEIT) test, which utilizes a 250 J pulsed power system to heat the needles. This work extends the Wenograd approach by using optical diagnostics, computational modeling, and advanced techniques to measure needle resistance and needle rupture. Preliminary rate information for pentaerythritol tetranitrate (PETN) will be presented.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Optimization techniques in self-similar compressible flow

We investigate the one-dimensional (1D) inviscid compressible flow equations for an ideal gas through the lens of optimization techniques. It is the case that, to our knowledge, optimization analysis applied to the so-called “linear velocity” solutions of the Euler compressible flow equations has not been previously conducted. Through both gradient-based and variational techniques, new variants of well-studied flow scenarios, i.e., self-similar, 1D, linear velocity solution class to idealized inviscid compressible flow equations, are determined, as encoded in both the kinematic and thermodynamic properties of this self-similar solution class. With the kinematics of the said solutions being driven by a self-similar “scale radius” and the thermodynamics being driven separately through the appearance of an arbitrary function, a myriad of new solution classes is possible. Acting as a guide to more realistic physical circumstances as well as discovery, it is the hope that the presented cases serve as the framework for future investigations into the intersection of self-similarity and optimization techniques. Fields of study that may find this work to be of interest include aerodynamic design, flow control, inertial confinement fusion, physics-informed neural networks, and other related areas of interest.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Interfacial solvation-structure regulation for stable Li metal anode by a desolvation coating technique

Rechargeable lithium (Li) metal batteries face challenges in achieving stable cycling due to the instability of the solid electrolyte interphase (SEI). The Li-ion solvation structure and its desolvation process are crucial for the formation of a stable SEI on Li metal anodes and improving Li plating/stripping kinetics. This research introduces an interfacial desolvation coating technique to actively modulate the Li-ion solvation structure at the Li metal interface and regulate the participation of the electrolyte solvent in SEI formation. Through experimental investigations conducted using a carbonate electrolyte with limited compatibility to Li metal, the optimized desolvation coating layer, composed of 12-crown-4 ether-modified silica materials, selectively displaces strongly coordinating solvents while simultaneously enriching weakly coordinating fluorinated solvents at the Li metal/electrolyte interface. This selective desolvation and enrichment effect reduce solvent participation to SEI and thus facilitate the formation of a LiF-dominant SEI with greatly reduced organic species on the Li metal surface, as conclusively verified through various characterization techniques including XPS, quantitative NMR, operando NMR, cryo-TEM, EELS, and EDS. The interfacial desolvation coating technique enables excellent rate cycling stability (i.e., 1C) of the Li metal anode and prolonged cycling life of the Li||LiCoO 2 pouch cell in the conventional carbonate electrolyte (E/C 2.6 g/Ah), with 80% capacity retention after 333 cycles.

42 ENGINEERING↗

Novel fabrication technique for high-resolution spherical crystal analyzers using a microporous aluminium base

Modern inelastic X-ray spectrometers employ curved, bent and diced analyzers to capture sufficiently large solid angles of radially emitted scattered radiation emanating from the sample. Fabricating these intricate analyzers, especially when a high energy resolution of a few millielectronvolts is required, is very time-consuming, expensive and often a hit-or-miss affair. A novel fabrication technique is introduced, utilizing a concave-spherical, microporous aluminium base to hold an assembly of a thin glass substrate with a diced crystal wafer bonded to it. Under uniform vacuum forces, the glass substrate is drawn into the aluminium base, achieving the desired bending radius, while dicing of the diffracting crystal layer prevents bending strain from being imposed on the individual crystal pixels. This technique eliminates the need for permanently bonding the crystal assembly to the concave lens, offering the opportunity for correcting figure errors, avoiding long-term degradation of the permanent bond, and making both lens and crystal reusable. Process and material costs are thus substantially decreased. Two analyzers, Si(844) and Ge(337) with intrinsic resolutions of 14.6 meV and 36.5 meV, respectively, were produced in this fashion and characterized in resonant inelastic X-ray scattering (RIXS) measurements. The achieved overall energy resolutions for both analyzers were 29.4 meV for Si(844) and 56.6 meV for Ge(337). Although the RIXS technique is veru sensitive to analyzer imperfections, the analyzers were found to be equal, if not superior, in quality to their traditional, permanently bonded counterparts.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Rapid Prototyping Techniques for Organic Direct-Bonded-Copper Power Modules

Organic Direct-Bonded-Copper (ODBC) is a novel packaging technology for power modules which allows higher flexibility in layout design. In this work, a set of rapid prototyping techniques are developed for ODBC modules based on a polyimide dielectric material. These techniques enable fast and low-cost fabrication of modules with 3-Dimensional (3D) layout features. An example half-bridge (HB) silicon carbide (SiC) metal oxide semiconductor field effect transistor (MOSFET) module is designed and prototyped using the proposed techniques aiming at ultra-low power loop inductance. Finite element analysis (FEA)-circuit co-simulations results and experimental results validate an approximately 0.71nH power loop inductance for the example module design.

36 MATERIALS SCIENCE↗

Comparative Analysis of ML Techniques for Data-Driven Anomaly Detection, Classification and Localization in Distribution System

High penetration of Distributed Energy Resources (DERs), fundamental load behavior changes, controllable loads, and significant increase in Electrical Vehicles (EVs) lead to complex dynamic behavior of the electric distribution system. Increasing number of components also means more measurements, more data and more data anomalies. Detecting, classifying and localizing these anomalies are important for situational awareness, and at the same time, very challenging given increasing complexity of the system. Highly accurate and high-resolution analytical techniques are needed to support anomaly detection, classification and localization (AD-C-L) for monitoring, root cause analysis and decision making. This paper provides comprehensive review and analysis of the existing spatio-temporal AD-C-L techniques within the distribution system. Challenges for specific problems in AD-C- L have been also discussed in this paper. Existing AD-C- L techniques have been categorized and synthesized for specific merits and limitations of multiple Machine Learning (ML) methodologies using common developed metrics of performance. The comparative analysis is summarized and presented with the open research challenges and path forward for future research needs.

24 POWER TRANSMISSION AND DISTRIBUTION↗