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At least 973 records · Page 54

Evidence for a higher-order topological insulator in a three-dimensional material built from van der Waals stacking of bismuth-halide chains

Low-dimensional van der Waals materials have been extensively studied as a platform with which to generate quantum effects. Advancing this research, topological quantum materials with van der Waals structures are currently receiving a great deal of attention. Here, we use the concept of designing topological materials by the van der Waals stacking of quantum spin Hall insulators. Most interestingly, we find that a slight shift of inversion centre in the unit cell caused by a modification of stacking induces a transition from a trivial insulator to a higher-order topological insulator. Based on this, we present angle-resolved photoemission spectroscopy results showing that the real three-dimensional material Bi4Br4 is a higher-order topological insulator. Our demonstration that various topological states can be selected by stacking chains differently, combined with the advantages of van der Waals materials, offers a playground for engineering topologically non-trivial edge states towards future spintronics applications.

36 MATERIALS SCIENCE↗

Building Neutron Scattering Infrastructure in Louisiana for Advanced Materials (Final Report)

The main objective of the Louisiana Consortium for Neutron Scattering (LaCNS) is to build a major neutron scattering infrastructure capable of treating both soft and hard materials. The goal is to create a sustainable effort having the quality, breadth, and depth necessary to produce competitive proposals including collaborative and center type proposals. Our scientific aim is to understand the role of coupling in emergent complex materials and its impact on the structure/property relationship and to explore how to tune the key couplings to guide the design of materials with the desired properties. This naturally includes building a base of users of the Spallation Neutron Source (SNS) and the High Flux Isotope Reactor (HFIR) in Louisiana; to train highly talented graduate and post-doctoral students in synthesis, neutron scattering, and simulation and modeling techniques, thereby helping to produce the next generation of scientist who use neutron scattering techniques as a crucial part of their research. The goal of our hard matter program is to understand the interplay between spin, charge, orbital, and lattice degrees of freedom in carefully selected complex materials. We have made considerable progress on number of complex systems including the oxide Sr3(Ru1-xMnx)2O7 where short-range magnetic ordering with anisotropic spin texture is initiated at the metal-insulator transition that clearly indicates a strong spin-charge coupling. Another critical area is in quantum materials. For example, in the topological semimetal BaMnSb2, we found a 3D canted antiferromagnetic Weyl semimetal with a 2D electronic structure and a nontrivial Berry phase. In addition, in the hexagonal chiral Mn1/3NbS2 system, we found soliton/soliton and soliton/antisoliton domain walls where the application of small fields or small currents can be used to control nanoscopic magnetic domains where the control of domain walls is crucially important for information storage. In addition, chemical transformation investigations were performed on the VISION instrument at Spallation Neutron Source (SNS). The soft matter effort was focused on understanding the role of non-covalent interactions on the structure and dynamics of fluid-based soft matter. One key focus was on sequence-defined (SD) amphiphilic peptoid polymers that allow encoding of molecular interactions and thereby systematic investigations of how charge directs the solution self-assembly of amphiphilic polymers in water. Another important area was on the dynamics of lipids self-assembled into membranes for exploring the permeability and mechanical using both neutron spin echo (NSE) spectroscopy and quasielastic neutron scattering (QENS) to distinguished between viscoelasticity and permeability at the molecular scale. Overall, the LaCNS project was quite successful, generating 145 publications and 245 presentations. Our graduate and post-doctoral students were well trained resulting in positions in national laboratories (Oak Ridge National Laboratory (ORNL), Argonne National Laboratory and Los Alamos National Laboratory), major research universities, and industry. We also developed a uniaxial pressure cell along with ORNL for SNS. A critical goal of this project was to establish a foundation for competing nationally in federally funded research programs. To this end, we were quite successful in generating over twenty-two federally and non-federally funded grants including awards from NSF, DOE, and DOD, and two early career awards. Equally important, we were able to secure a key major piece of instrumentation via a large ARO grant for a state-of-the-art electron microscope.

36 MATERIALS SCIENCE↗

A materials data framework and dataset for elastomeric foam impact mitigating materials

The availability of materials data for impact-mitigating materials has lagged behind applications-based data. For example, data describing on-field helmeted impacts are available, whereas material behaviors for the constituent impact-mitigating materials used in helmet designs lack open datasets. Here, we describe a new FAIR (findable, accessible, interoperable, reusable) data framework with structural and mechanical response data for one example elastic impact protection foam. The continuum-scale behavior of foams emerges from the interplay of polymer properties, internal gas, and geometric structure. This behavior is rate and temperature sensitive, therefore, describing structure-property characteristics requires data collected across several types of instruments. Data included are from structure imaging via micro-computed tomography, finite deformation mechanical measurements from universal test systems with full-field displacement and strain, and visco-thermo-elastic properties from dynamic mechanical analysis. These data facilitate modeling and design efforts in foam mechanics, e.g., homogenization, direct numerical simulation, or phenomenological fitting. The data framework is implemented using data services and software from the Materials Data Facility of the Center for Hierarchical Materials Design.

36 MATERIALS SCIENCE↗

Multifunctional approaches for safe structural batteries

Recent advancements in Li and Li-ion based energy storage resulted in development of novel electrode materials for higher energy density which are finding their applications in transportation. There appears to be a limitation in improvement of specific energy of the system based solely on design of material compositions for multivalent intercalation compounds. In addition, higher energy stored by the system implies need for addressing safety concerns especially when it comes to large automotive battery packs. New approaches for improvement of both energy density and safety of batteries are emerging, where multifunctionality of the materials and/or architectures is utilized. Here, we present a review for such approaches from multifunctional current collectors to design of batteries capable of supporting mechanical loads and thus possessing ability to be used as a structural component.

25 ENERGY STORAGE↗

Foaming prediction in pure liquids from dimensionless numbers inspired by the theory of fluid behavior for drops

Foaming prediction is critical for selecting materials and designing processes in industries such as bioprocessing and gas processing. Existing models lack the generality needed for a wide range of materials and overlook the foaming behavior in pure liquids. Here, this work presents a novel method for predicting foaming in pure liquids based on their density, surface tension, and viscosity, using Reynolds ( Re ) and Ohnesorge ( Oh ) numbers. A foaming prediction map, leveraging the theory of fluid drop behavior, was developed by plotting these numbers. This map delineates distinct non-foaming and foaming regions, functioning as a binary classifier for foaming predictions. The map was fitted and validated through shake test experiments on 46 liquids, demonstrating reliable predictions, except for a specific region characterized by small Oh and large Re numbers. This region corresponded to relatively low foam stability and high turbulence, making foaming predictions challenging for liquids in this category.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A technoeconomic analysis of poly- and single-crystalline NMCxyz from material synthesis to battery pack design

A process model was developed for estimating the cost of manufacturing lithium nickel manganese cobalt oxide (LiNi x Mn y Co z O 2 , NMCxyz), the main cathode active material in lithium-ion batteries used for electric vehicles in the United States. The model was used to estimate the prices of NMC622, NMC811, and NMC955 with poly- and single-crystalline morphologies. The Battery Performance and Cost Model (BatPaC) was used to translate the NMC prices into battery pack prices. A decrease in cobalt content from NMC622 (20% Co) to NMC955 (5% Ni) decreases the material price by $\$$0.85/kg (−3%) due to a decrease in the cost of battery materials, which account for >60% of the total price. NMC622 only produce cheaper packs if the nickel sulfate cost is > 4 × its baseline, indicating higher nickel materials will lower pack cost under normal market conditions. Single-crystalline materials are $\$$2/kg (+8%) more expensive than their polycrystalline counterparts due to higher manufacturing costs from longer, hotter calcinations in less densely packed saggars. This increases the pack price by ∼$\$$3/kWh, assuming identical electrochemical properties. In conclusion, the single-crystalline materials could yield cheaper packs if cycled to higher upper cutoff voltages (i.e., 4.35 to 4.43 V for the single-crystalline material vs. 4.25 V for their polycrystalline counterparts).

Cost modeling↗

Application of the van der Pauw method for electrical conductivity measurements at high temperatures using an insulating compressing ring

High quality data on the high temperature electrical properties of ceramics, particularly oxides, is of great value for material selection, design, and modeling for a broad range of emerging applications. Utilizing the mismatch in the coefficient of thermal expansion between two materials, a purely mechanical method for establishing electrical contact in the van der Pauw geometry to measure the bulk resistivity of ceramic disks at high temperatures is presented. Measurements of a reference material, 20 mol. % Gd-doped cerium oxide, are presented up to 1000 °C. The viability of electrical measurements up to a maximum temperature of 1600 °C is also considered. Measurements are performed using multiple techniques and compared to literature values finding excellent agreement. Finally, the approach described in this work enables the van der Pauw method to be applied to many ceramic materials over a wide range of temperatures and environments.

47 OTHER INSTRUMENTATION↗

First-Principles Understanding of Optical Excitations within Low-Dimensional Materials

The objective of this project is to utilize first-principles computational approaches to understand optical excitations within two-dimensional monolayers and heterostructures, with the ultimate goal of designing new materials by modifying the chemical and physical structure on the nanoscale. In 2D heterostructures, the nature and movement of the exciton is determined to a large extent by the electron-electron and electron-phonon strengths within individual monolayers, as well as the coupling between layers, all of which in turn depend on chemistry, solid-state screening properties, and quantum confinement. Controlling the nature and migration properties of excitons requires an understanding of the complex relationship between electrons, phonons, defects, disorder, and dynamics. The aim of this project is to determine, by analysis of highly accurate density functional theory (DFT) and many-body perturbation theory (MBPT) calculations, how these complexities can be decomposed into simple, tunable parameters. The specific goals of this project are to 1) understand electron conductivity, absorption and transparency of monolayer semiconductors and metals; 2) develop a theory of excitons near defects in low dimensions; and 3) understand the influence of inter-layer interactions in heterostructures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Manufacturing and Additive Design of Electric Machines by 3D Printing (MADE3D) (Final Technical Report)

As the U.S clean energy transition hinges on the growth of offshore wind, this is expected to be a major driver for innovations in manufacturing, material and design advancements to enable robust and cost-competitive wind turbines. The race to build larger and taller turbines rated 10 megawatts (MW) and beyond, has intensified pressure on OEMs in terms of logistics of handling and transporting large wind components, securing critical raw material as well as scaling up necessary domestic production infrastructure to meet the demand. There is increased interest in building lightweight, more efficient, and high-power dense drivetrains that will ease the burden on installation, minimize the raw material demand, increasing domestic sourceability. Despite good efficiency and reliability, existing drivetrain technologies such as direct-drive permanent magnet generators are heavy (> 300 tons), expensive, and often rely on large quantities of rare-earth permanent magnets (PMs), steel and copper.

17 WIND ENERGY↗

Inverse Design of Ultralow Lattice Thermal Conductivity Materials via Materials Database Screening of Lone Pair Cation Coordination Environment

The presence of lone pair (LP) electrons is strongly associated with the disruption of lattice heat transport, which is a critical component of strategies to achieve efficient thermoelectric energy conversion. By exploiting an empirical relationship between lattice thermal conductivity, κ L , and the bond angles of pnictogen group LP cation coordination environments, we develop an inverse design strategy based on a materials database screening to identify chalcogenide materials with ultralow κ L for thermoelectrics. Screening the ~635 000 real and hypothetical inorganic crystals of the Open Quantum Materials Database based on the constituent elements, nominal electron counting, LP cation coordination environment, and synthesizability, we identify 189 compounds expected to exhibit ultralow κ L . As a validation, we explicitly compute the lattice dynamical properties of two of the compounds (Cu 2 AgBiPbS 4 and MnTl 2 As 2 S 5 ) using first-principles calculations and successfully find both achieve ultralow κ L values at room temperature of ~0.3-0.4 W/(m·K) corresponding to the amorphous limit. Furthermore, our data-driven approach provides promising candidates for thermoelectric materials and opens new avenues for the design of phononic properties of materials.

36 MATERIALS SCIENCE↗

DENNIS: a design and analysis tool for dynamic material x-ray diffraction experiments

We present DENNIS (Diffraction Experiment desigN and aNalysiS): a graphical software tool useful for the design and analysis of dynamic x-ray diffraction experiments, such as those performed on the Z Pulsed Power Facility, Thor Pulsed Power Generator, and Dynamic Compression Sector (DCS) of the Advanced Photon Source. DENNIS provides rapid powder and single-crystal diffraction pattern predictions and powder diffraction pattern image integration in three-dimensional geometries. Additional features include crystallographic information file reading, image processing, and synthetic diffraction pattern image generation. We overview the software's capabilities, detail the prediction and integration methodologies, and provide example implementations on Z and DCS experiments.

47 OTHER INSTRUMENTATION↗

Toward high laser power beam manipulation with nanophotonic materials: evaluating thin film damage performance

Nanophotonic materials enable unprecedented control of light-matter interactions, including the ability to dynamically steer or shape wavefronts. Consequently, nanophotonic systems such as metasurfaces have been touted as promising candidates for free-space optical communications, directed energy and additive manufacturing, which currently rely on slow mechanical scanners or electro-optical components for beam steering and shaping. However, such applications necessitate the ability to support high laser irradiances (> kW/cm 2 ) and systematic studies on the high-power laser damage performance of nanophotonic materials and designs are sparse. Here, we experimentally investigate the pulsed laser-induced damage performance (at λ ∼ 1 µm) of model nanophotonic thin films including gold, indium tin oxide, and refractory materials such as titanium nitride and titanium oxynitride. We also model the spatio-thermal dissipation dynamics upon single-pulse illumination by anchoring experimental laser damage thresholds. Our findings show that gold exhibits the best laser damage resistance, but we argue that alternative materials such as transparent conducting oxides could be optimized to balance the tradeoff between damage resistance and optical tunability, which is critical for the design of thermally robust nanophotonic systems. We also discuss damage mitigation and ruggedization strategies for future device-scale studies and applications requiring high power beam manipulation.

36 MATERIALS SCIENCE↗

Learning two-phase microstructure evolution using neural operators and autoencoder architectures

Abstract Phase-field modeling is an effective but computationally expensive method for capturing the mesoscale morphological and microstructure evolution in materials. Hence, fast and generalizable surrogate models are needed to alleviate the cost of computationally taxing processes such as in optimization and design of materials. The intrinsic discontinuous nature of the physical phenomena incurred by the presence of sharp phase boundaries makes the training of the surrogate model cumbersome. We develop a framework that integrates a convolutional autoencoder architecture with a deep neural operator (DeepONet) to learn the dynamic evolution of a two-phase mixture and accelerate time-to-solution in predicting the microstructure evolution. We utilize the convolutional autoencoder to provide a compact representation of the microstructure data in a low-dimensional latent space. After DeepONet is trained in the latent space, it can be used to replace the high-fidelity phase-field numerical solver in interpolation tasks or to accelerate the numerical solver in extrapolation tasks.

36 MATERIALS SCIENCE↗

Cooled Gas Turbine and Combined Cycle Analysis for H 2 -CH 4 Fuel Mixes (Up to 100% H 2 )

In this study, a cooled gas turbine analysis was conducted for varying levels of hydrogen (H 2 ) blends with the natural gas. The ultimate goal is to have a gas turbine design that can be used for all the fuel blends (including 100% H 2 ) without any changes to the system. The technological developments in the cooling system, gas turbine design and materials that will be required for H 2 combustion were identified and analyzed in this study to develop an advanced gas turbine design for H 2 fuels. The study includes a combined cycle performance analysis with the H 2 fuel blends using the advanced gas turbine design developed in this study. A techno-economic analysis was conducted for analyzing the impact of the H 2 fuels on the levelized cost of electricity and cost sensitivities to fuel price and capacity factor.

03 NATURAL GAS↗

Cooled Gas Turbine and Combined Cycle Analysis for NH 3 -CH 4 Fuel Mixes (Up to 100% NH 3 )

In this study, a cooled gas turbine (GT) analysis was conducted for varying levels of ammonia (NH 3 ) blends with methane. The ultimate goal is to have a gas turbine design that can be used for all the fuel blends (including 100% NH 3 ) without any changes to the system. The technological developments in the cooling system, gas turbine design, and materials that will be required for NH 3 combustion were identified and analyzed in this study to develop an advanced gas turbine design for NH 3 fuels. The study includes a combined cycle performance analysis with the NH 3 fuel blends using the advanced gas turbine design developed in this study. A techno-economic analysis was conducted for analyzing the impact of the NH 3 fuels on the levelized cost of electricity and cost sensitivities to fuel price and capacity factor.

20 FOSSIL-FUELED POWER PLANTS↗

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↗

High Inlet Temperature Combustor for Direct-Fired Supercritical Oxy-Combustion

It is envisioned that supercritical CO 2 (sCO 2 ) electric power plant efficiencies can exceed 52% with 99% carbon capture using direct-fired oxy-combustion. Such efficiencies would be competitive with Natural Gas Combined Cycles (NGCC) and operate with nearly zero carbon emissions. To achieve high plant efficiencies, turbine inlet conditions must approach 1,200 °C at 250 bar. Such conditions, while desirable from a systems perspective, exceed the current state of the art in turbine design and materials qualification. The team of Southwest Research Institute ® (SwRI ® ), Georgia Institute of Technology (Georgia Tech), Spectral Energies, LLC (Spectral), GE Global Research (GE-GRC), and the University of Central Florida (UCF) sought to demonstrate an intermediate step toward these high efficiency plants with the development of a 1 MWth, subscale direct-fired oxy-fuel combustor. The efforts focused largely on the development of an auto-ignition based combustion system capable of providing the targeted 1200 °C and the pilot-scale plant to operate the combustor. While the project was stopped short of the commissioning and demonstration work, the advances made in this effort will reduce risks associated with chemical kinetics, thermal management, water separation, flue gas cleanup, materials selection, and corrosion in future demonstration efforts for the direct-fired oxy-fuel combustion cycles. The following report documents the design, analysis, and installation efforts completed during the project periods of performance.

03 NATURAL GAS↗

Luminescence from Self‐Trapped Excitons and Energy Transfers in Vacancy‐Ordered Hexagonal Halide Perovskite Cs 2 HfF 6 Doped with Rare Earths for Radiation Detection

Abstract Compared to halides Cs 2 HfX 6 (X = Cl, Br, I) with a vacancy‐ordered cubic double perovskite structure, the halide Cs 2 HfF 6 (CHF), with a hexagonal Bravais lattice, possesses a higher mass density and chemical stability for radiation detection. Luminescence properties and energy transfer mechanisms of rare‐earths‐doped CHF materials are studied here. The structure of CHF is identified as a new type of vacancy‐ordered hexagonal perovskite, with the same type of building blocks of the double perovskite but stacked with single layers. Density‐functional theory calculations reveal a large bandgap of CHF. A broad emission is observed from the pristine CHF host, which is suggested to be associated with self‐trapped excitons (STEs). A series of rare‐earths‐doped materials are designed utilizing the STE emissions, and efficient energy transfers from STEs and Tb 3+ to Eu 3+ are achieved for tunable emissions. The codoped material shows stable emission under X‐ray irradiation, with 10.2% reduction from its initial emission intensity, associated with possible structural evolution by radiation‐induced deformation of the soft host. The radiation responses of singly and codoped materials are evaluated, and the codoped material is found to be more sensitive to the radiation energy than the singly doped or pristine CHF for radiation detection.

36 MATERIALS SCIENCE↗