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At least 19 records

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↗

Multifunctional application of nanoscratch technique to characterize cementitious materials

This study aims to further explore the multifunctional applicability of nanoscratch technique to cementitious materials for comprehensive characterization. Based on the investigation of deformation, applied force, and fracture toughness of hardened cement paste during scratching, the methods of phase identification, fracture toughness of individual phase, and the interfacial transition zone (ITZ) thickness quantification were proposed and discussed. After redefining the vertical loading rate of scratching, the slope of the square scratching depth vs. scratching length is recognized as a reliable parameter to distinguish the individual phases for the first time. A fracture toughness-based method is proposed to quantify the thickness of ITZ between clinker and hydrates. Meanwhile, the applicability of phase identification by the scratch method is discussed for different transverse scratching speeds and the vertical loading rates. The findings will benefit the investigation and mechanism understanding of cementitious materials at the microscale by utilizing nanoscratch technique.

36 MATERIALS SCIENCE↗

Terahertz EPR spectroscopy using a 36-tesla high-homogeneity series-connected hybrid magnet

Electron Paramagnetic Resonance (EPR) is a powerful technique to study materials and biological samples on an atomic scale. High-field EPR in particular enables extracting very small g-anisotropies in organic radicals and half-filled 3d and 4f metal ions such as Mn II (3d 5 ) or Gd III (4f 7 ), and resolving EPR signals from unpaired spins with very close g-values, both of which provide high-resolution details of the local atomic environment. Before the recent commissioning of the high-homogeneity Series Connected Hybrid magnet (SCH, superconducting + resistive) at the National High Magnetic Field Laboratory (NHMFL), the highest-field, high-resolution EPR spectrometer available was limited to 25 T using a purely resistive “Keck” magnet at the NHMFL. Herein, we report the first EPR experiments performed using the SCH magnet capable of reaching the field of 36 T, corresponding to an EPR frequency of 1 THz for g = 2. The magnet’s intrinsic homogeneity (25 ppm, that is 0.9 mT at 36 T over 1 cm diameter, 1 cm length cylinder) was previously established by NMR. We characterized the magnet’s temporal stability (5 ppm, which is 0.2 mT at 36 T over one-minute, the typical acquisition time) using 2,2-diphenyl-1-picrylhydrazyl (DPPH). This high resolution enables resolving the weak g-anisotropy of 1,3-bis(diphenylene)-2-phenylallyl (BDPA), Δg = 2.5 × 10 –4 obtained from measurements at 932 GHz and 33 T. Subsequently, we recorded EPR spectra at multiple frequencies for two Gd III complexes with potential applications as spin labels. In conclusion, we demonstrated a significant reduction in line broadening in Gd[DTPA], attributed to second order zero field splitting, and a resolution enhancement of g-tensor anisotropy for Gd[sTPATCN]-SL.

47 OTHER INSTRUMENTATION↗

Machine-learning-assisted automation of single-crystal neutron diffraction

Neutron scattering is a powerful but expensive technique to study materials and discover new matter. Advanced detector technology has significantly improved the efficiency of neutron experiments, increasing the complexity of neutron data reduction and analysis. Machine learning (ML) brings new directions for neutron diffraction data reduction and experiment operation. Here, this work presents an ML-assisted data reduction and analysis method for precise recognition of Bragg peaks and the corresponding regions of interest; it can then automatically screen and align a measured crystal using the recognized peaks, and subsequently plan and optimize the data collection with user-provided information and uncertainty quantification values of detected peaks. This method shows robust performance in different complex sample environments and enables automated single-crystal neutron diffraction.

47 OTHER INSTRUMENTATION↗

Designing an impedance-based technique for studying corrosion on cladding materials

In nuclear cladding materials, changes in structure and chemistry over the lifetime of claddings can have a significant impact on fuel and reactor performance. Currently, chemical evolution over the lifetime of the fuel and cladding materials can only be inferred using post-irradiation examination. As an alternative to post-irradiation measurements, electrochemical impedance spectroscopy (EIS) can provide an in-pile measurement of changes in chemistry in oxides and hydrides. The objective of this study is to develop an impedance based sensing technology for measuring spatial- and time-resolved in-pile changes in cladding chemistry in order to understand the mechanisms of hydride formation, hydride dealloying and associated cladding corrosion so that a mitigation strategy and technology can be developed for reactor safe operation. Two prototype impedance-based sensors were designed and assembled using Zr-4 as working electrode and Pt as counter and reference electrode. One sensor is tubular type and the other one is plate-type. These sensors will be tested in static autoclave to investigate the effects of various environmental conditions (including temperature, pressure, and water chemistry) on cladding material corrosion mechanisms. These in-situ EIS sensors would provide corrosion-layer parameters in high-temperature water, such as (1) total layer thickness, (2) the evolution of oxide structures as uniform layer dielectric or sublayer(s), and (3) the possible electrochemistry of the volume corrosion process and the solid/liquid interface, such as the cyclic nature of corrosion of Zr alloys in high-temperature water. This work was focused on electrochemical sensor development, targeting cladding oxides/hydrides under thermodynamic equilibria; characterization of samples using Kelvin probe force microscopy (SKPFM), Raman spectroscopy, and scanning electron microscopy (SEM) with energy-dispersive X-ray spectroscopy (EDS) to provide high-resolution co-localized characterization of zirconium oxide and metal/oxide interface.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Nonlinear ultrasonic technique for the characterization of microstructure in additive materials

This study employs nonlinear ultrasonic techniques to track microstructural changes in additively manufactured metals. The second harmonic generation technique based on the transmission of Rayleigh surface waves is used to measure the acoustic nonlinearity parameter, β. Stainless steel specimens are made through three procedures: traditional wrought manufacturing, laser-powder bed fusion, and laser engineered net shaping. The β parameter is measured through successive steps of an annealing heat treatment intended to decrease dislocation density. Dislocation density is known to be sensitive to manufacturing variables. In agreement with fundamental material models for the dislocation-acoustic nonlinearity relationship in the second harmonic generation, β drops in each specimen throughout the heat treatment before recrystallization. Geometrically necessary dislocations (GNDs) are measured from electron back-scatter diffraction as a quantitative indicator of dislocations; average GND density and β are found to have a statistical correlation coefficient of 0.852 showing the sensitivity of β to dislocations in additively manufactured metals. Moreover, β shows an excellent correlation with hardness, which is a measure of the macroscopic effect of dislocations.

42 ENGINEERING↗

Process Optimization of Carbon Electrode Materials Manufacturing by Experimental Study and Machine Learning Techniques

Electrospun carbon fibers from coal have been investigated as electrodes for batteries and supercapacitors. Despite the excellent properties of coal-derived carbon fibers (CCNF) for energy storage devices, there still lacks systematic understanding on how various process parameters affect final electrode performances, which poses challenges to scale from pilot to high volume manufacturing. The goals of this project are twofold. First, we focuse on process optimization for converting a new precursor from powder river basin (PRB) coal, referred to as coal-based polyurethane (CPU) to CCNF using electrospinning. Second, different machine learning techniques will be examined using experimental data from this work and open literature. Specifically, for CPU the following process parameters need to be characterized and optimized in order to produce CCNFs with desirable mechanical integrity and physiochemical properties: precursor composition and viscosity, operating voltage and distance, oxidation and carbonization temperature and duration. Consequently, physiochemical properties of the fibers were characterized to correlate these process parameters with desirable electrochemical performance. Given the complex nature of the fiber production process, ML models are assessed for their ability to capture the nonlinear relationship between process parameters and the electrochemical properties in applications including supercapacitors. As such, we applied various machine learning techniques, to determine which technique produces a model that best predicts device function.

Cincotta, Robert E.F.↗

Atomic Resolution Cryogenic 4D-STEM Imaging via Robust Distortion Correction

Cryogenic four-dimensional scanning transmission electron microscopy (4D-STEM) imaging is a useful technique for studying quantum materials and their interfaces by simultaneously probing charge, lattice, spin, and chemistry on the atomic scale with the sample held at temperatures ranging from room to cryogenic. However, its applications are currently limited by the instabilities of cryo-stages and electronics. To overcome this challenge, we develop an algorithm to effectively correct the complex distortions present in atomic resolution cryogenic 4D-STEM data sets. This method uses nonrigid registration to identify localized distortions in a 4D-STEM and relate them to an undistorted experimental STEM image, followed by a series of affine transformations for distortion corrections. This method allows a minimum loss of information in both reciprocal and real spaces, enabling the reconstruction of sample information from 4D-STEM data sets. This method is computationally cheap, fast, and applicable for on-the-fly data analysis in future in situ cryogenic 4D-STEM experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Failure Analysis of a New Polyamide-Based Fluoropolymer-Free Backsheet After Combined-Accelerated Stress Testing

The viability of novel coextruded, fluoropolymer-free backsheets for photovoltaic (PV) modules has been questioned as a result of a large number of early-life backsheet failures in PV installations containing one of the earliest co-extruded polyamide (PA)-based backsheet to reach the market, “AAA.” New PV reliability testing protocols have been recently developed and applied to backsheets to reproduce failures observed in the field and evaluate the durability of novel backsheet materials and designs prior to commercialization. A new co-extruded PA-based backsheet was tested using combined-accelerated stress testing (C-AST) and demonstrated a greater lifetime than AAA, and some other fluoropolymer-based backsheets such as polyvinylidene fluoride. The improved PA-based backsheet also eventually failed by through-thickness cracking. Using surface and bulk material characterization techniques, we performed a comprehensive study of material properties before and after the stress testing. Aging of the backsheet resulted in an increase of surface roughness by erosion of the outer PA layer. However the failure is more likely related to an increase in crystallinity of the polyolefin core layer reducing the backsheet tearing energy. The analysis can ultimately inform on the specific weaknesses of the materials so that the manufacturer can improve the backsheet design to extend its lifetime.

14 SOLAR ENERGY↗

Measurement and Simulation of Vacancy Formation in 2-MeV Self-irradiated Pure Fe

Positron annihilation spectroscopy is a powerful tool to quantify the amount of vacancies and vacancy clusters in materials. The technique has been utilized to study the induced defects in materials after ion beam and neutron irradiations. Here we make the case for how the technique can and should be utilized to quantify the defects created by irradiation in situ during irradiation to foster a more thorough understanding of the surviving defects after initial collision cascades. This paper outlines a future experimental approach and its meaning for the nuclear materials community, being able to benchmark commonly used rate theory models of damage evolution.

36 MATERIALS SCIENCE↗

Reaction heterogeneity in practical high-energy lithium–sulfur pouch cells

The lithium–sulfur (Li–S) battery is a promising next-generation energy storage technology because of its high theoretical energy and low cost. Extensive research efforts have been made on new materials and advanced characterization techniques for mechanistic studies. However, it is uncertain how discoveries made on the material level apply to realistic batteries due to limited analysis and characterization of real high-energy cells, such as pouch cells. Evaluation of pouch cells (>1 A h) (instead of coin cells) that are scalable to practical cells provides a critical understanding of current limitations which enables the proposal of strategies and solutions for further performance improvement. Herein, we design and fabricate pouch cells over 300 W h kg -1 , compare the cell parameters required for high-energy pouch cells, and investigate the reaction processes and their correlation to cell cycling behavior and failure mechanisms. Spatially resolved characterization techniques and fluid-flow simulation reveal the impacts of the liquid electrolyte diffusion within the pouch cells. We found that catastrophic failure of high-energy Li–S pouch cells results from uneven sulfur/polysulfide reactions and electrolyte depletion for the first tens of cycles, rather than sulfur dissolution as commonly reported in the literature. The uneven reaction stems from limited electrolyte diffusion through the porous channels into the central part of thick cathodes during cycling, which is amplified both across the sulfur electrodes and within the same electrode plane. A combination of strategies is suggested to increase sulfur utilization, improve nanoarchitectures for electrolyte diffusion and reduce consumption of the electrolytes and additives.

25 ENERGY STORAGE↗

Emergent properties of magnons coupled to microwave photons (Final Technical Report)

Studying the emergent properties of hybrid quantum material platforms holds great promise for advancing quantum technologies and transforming our ability to control quantum mechanical interactions. A key development in recent years is the recognition that magnons – the elementary quanta of spin waves – can serve as fundamental building blocks in quantum systems. Understanding the mechanisms behind the generation and control of hybrid quasiparticles based on magnons could pave the way for engineering new materials for quantum coherent processing and quantum computing. This research project focused on the precise control of light-matter interactions in magnetic hybrid systems and nanostructures, where light is carried by microwave photons and matter by magnons in engineered magnetic metamaterials. Furthermore, we investigated hybridized magnon interactions in magnetic nanostructures and devices. To this end, the project has developed new measurement techniques and systematically studied novel material systems for efficient magnon-photon coupling. A key focus was uncovering the fundamental mechanisms governing magnon-photon and magnon-phonon interactions – critical for utilizing magnons as coherent information transducers between carriers. Specifically, this research addressed: 1. Investigate the dispersion and collective properties of magnon hybrid systems in new material systems. 2. Develop magnonic hybrids with non-zero wavevectors and achieve effective control of magnon-polariton properties through engineered magnonic behaviors. 3. Determine how spin-orbit torques interact with electromagnetic fields in the strong coupling regime. This work generated new insights into the physics of magnonic hybrid systems and their emergent properties by broadening the range of material platforms and measurement techniques used to study magnon-photon and magnon-magnon coupling. The findings deepen our understanding of magnon-polaritons and lay the groundwork for novel spintronic devices with potential applications in quantum information science.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Computational Exploration of High Entropy Alloys as Promising Materials for Future Beam Windows

With the ever-increasing demand for high beam power, the currently used beam-intercepting devices (BIDs) such as targets, and beam windows may not be able to handle the high power required for future accelerator complexes or the lifetime may be reduced drastically. As beam power increases, the damage incurred by BIDs, including thermal shock, fatigue, and irradiation damage, also rises. Therefore, it is imperative to design materials that can withstand high beam power for longer lifetimes. High entropy alloys (HEAs) have emerged as potential alternative materials for designing next-generation BIDs. In this study, we primarily focus on materials for developing beam windows for next-generation accelerator complexes. We propose an integrated approach that combines various computational techniques to study and design new materials. Specifically, we use CALPHAD, density functional theory (DFT), and molecular dynamics (MD) to comprehensively investigate the defect properties of suitable HEAs, offering potential alternatives for future beam windows. We begin by scanning the extensive phase space provided by Cr-Mn-V-Ti-Al-Co HEAs, selecting 8 compositions after evaluating approximately 120,000 unique compositions using CALPHAD. We, then employ DFT-informed machine learning techniques to develop force-field parameters. Finally, MD simulations using these developed force-field parameters will be used to study the effects of radiation damage on the defect and mechanical properties of the selected alloys. This research explains the use of the CALPHAD approach and shows how critical modeling (DFT and MD) is in developing novel material such as HEAs. It also highlights the promising role of machine learning in this field. The results from this study will greatly improve the novel materials development to be used in next-generation accelerator components, leading to higher beam power and longer operational times of BIDs.

43 PARTICLE ACCELERATORS↗

Crystallography of low Z material at ultrahigh pressure: Case study on solid hydrogen

Diamond anvil cell techniques have been improved to allow access to the multimegabar ultrahigh-pressure region for exploring novel phenomena in condensed matter. However, the only way to determine crystal structures of materials above 100 GPa, namely, X-ray diffraction (XRD), especially for low Z materials, remains nontrivial in the ultrahigh-pressure region, even with the availability of brilliant synchrotron X-ray sources. In this work,we perform a systematic study, choosing hydrogen (the lowest X-ray scatterer) as the subject, to understand how to better perform XRD measurements of low Z materials at multimegabar pressures. The techniques that we have developed have been proved to be effective in measuring the crystal structure of solid hydrogen up to 254 GPa at room temperature [C. Ji et al.,Nature 573, 558–562 (2019)]. We present our discoveries and experiences with regard to several aspects of this work, namely, diamond anvil selection, sample configuration for ultrahigh-pressure XRD studies,XRD diagnostics for low Z materials, and related issues in data interpretation and pressure calibration.We believe that these methods can be readily extended to other low Z materials and can pave the way for studying the crystal structure of hydrogen at higher pressures, eventually testing structural models of metallic hydrogen.

36 MATERIALS SCIENCE↗

Chapter 10.02 - Neutron Scattering Studies of Materials for Hydrogen Storage

Hydrogen storage presents a significant barrier to the widespread adaptation of hydrogen as an energy source in mobile and stationary applications. The development of new candidate hydrogen storage materials is therefore an outstanding goal in the field of inorganic chemistry. Neutron scattering techniques - including diffraction, inelastic, and quasielastic scattering - are integral in investigating these materials. Here, we review some of the key studies of candidate hydrogen storage materials which have employed neutron scattering techniques. We begin with a brief discussion of hydrogen's current position in the global energy landscape. Next, we provide a brief description of the theory and practical aspects of the neutron scattering techniques germane to the study of hydrogen storage. Then we enumerate the neutron scattering studies of candidate hydrogen storage materials, including metal hydrides, chemical hydrides, and porous compounds. We focus on the studies which helped develop our understanding of hydrogen storage by revealing the underlying fundamental physics and chemistry of hydrogen sorption in these systems. Finally, we provide an outlook to the future of hydrogen storage research.

chemical hydrides↗

Ab initio molecular dynamics on quantum computers

Ab initio molecular dynamics (AIMD) is a valuable technique for studying molecules and materials at finite temperatures where the nuclei evolve on potential energy surfaces obtained from accurate electronic structure calculations. In this work, we present an approach to running AIMD simulations on noisy intermediate-scale quantum (NISQ)-era quantum computers. The electronic energies are calculated on a quantum computer using the variational quantum eigensolver (VQE) method. Algorithms for computation of analytical gradients entirely on a quantum computer require quantum fault-tolerant hardware, which is beyond NISQ-era. Therefore, we compute the energy gradients numerically using finite differences, the Hellmann-Feynman theorem, and a correlated sampling technique. This method only requires additional classical calculations of electron integrals for each degree of freedom without any additional computations on a quantum computer beyond the initial VQE run. As a proof of concept, AIMD simulations are demonstrated for the H-2 molecule on IBM quantum devices. In addition, we demonstrate the validity of the method for larger molecules using full configuration interaction wave functions. As quantum hardware and noise mitigation techniques continue to improve, the method can be utilized for studying larger molecular systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

CASM Monte Carlo: Calculations of the thermodynamic and kinetic properties of complex multicomponent crystals

Monte Carlo techniques play a central role in statistical mechanics approaches that connect macroscopic thermodynamic and kinetic properties to the electronic structure of a material. This paper describes the implementation of Monte Carlo techniques for the study of multicomponent crystalline materials within the Clusters Approach to Statistical Mechanics (CASM) software suite, and demonstrates their use in model systems to calculate free energies and kinetic coefficients, study phase transitions, and construct phase diagrams from first principles. Many crystal structures are complex, with multiple sublattices occupied by differing sets of chemical species, along with the presence of vacancies or interstitial species. This imposes constraints on concentration variables, the form of thermodynamic potentials, and the values of kinetic transport coefficients. The framework used by CASM to formulate thermodynamic potentials and kinetic transport coefficients accounting for arbitrarily complex crystal structures is presented and demonstrated with examples of increasing complexity. Additionally, an overview of the capabilities of the CASM software specific to Monte Carlo methods is given, and a new CASM software package is introduced, casm-flow, which helps automate the setup, submission, management, and analysis of Monte Carlo simulations.

Cluster expansion↗

High throughput structure–property relationship for additively manufactured 316L/IN625 alloy mixtures leveraging 2-step Bayesian estimation

While the fabrication of graded materials by directed energy deposition (DED) has led to accelerated materials discovery, the ability to rapidly explore sufficiently large material composition spaces is limited due to the time-intensive nature of conventional materials characterization techniques. The present study investigates the viability of small punch test (SPT) protocols for rapidly evaluating DED-fabricated alloy mixtures of stainless steel 316L (316L) and Inconel 625 (IN625). The SPT protocols evaluated in this study include both the recently established two-step Bayesian estimation framework as well as the empirical relationships established in prior literature. It is shown that these protocols are capable of reliably and quantitatively tracking the changes in the mechanical properties of the alloy mixtures studied. Enhancement of mechanical properties was observed with the addition of IN625 to 316L, which is attributed to the austenite stabilization in the matrix and the formation of fine δ - Ni3Nb precipitates. It is shown that CALPHAD-based Scheil model simulations predicted the formation of different precipitate phases for each composition. The novel protocols presented in this paper open new avenues for high throughput material explorations for additive manufacturing.

2-step Bayesian estimation↗