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At least 721 records · Page 40

Hydrogen Storage with Aluminum Formate, ALF: Experimental, Computational, and Technoeconomic Studies

Long-duration storage of hydrogen is necessary for coupling renewable H2 with stationary fuel cell power applications. In this presentation, I will discuss how aluminum formate, Al(HCOO)3 (ALF), which adopts an ReO3-type structure, is shown to have remarkable H2 storage performance at non-cryogenic (> 120 K) temperatures and low pressures. The most promising performance of ALF is found between 120 K and 160 K and at 10 bar to 20 bar. The talk will cover and illustrate the H2 adsorption performance of ALF over the 77 K to 296 K temperature range using gas isotherms, in situ neutron powder diffraction, and DFT calculations, as well as technoeconomic analysis (TEA), illustrating ALF’s competitive performance for long-duration storage versus compressed hydrogen and leading metal–organic frameworks. In the TEA, it is shown that ALF’s storage capacity, when combined with a temperature/pressure swing process, has advantages versus compressed H2 at a fraction of the pressure (15 bar versus 350 bar). Given ALF’s performance in the 10 bar to 20 bar regime under moderate cooling, it is particularly promising for use in safe storage systems serving fuel cells, and is currently the only MOF that works in this moderate temperature range/ low pressure regime to be cost competitive with compressed H2 gas for large scale H2 storage.[1]

Chemistry↗

Bibliometric review and recent advances in total scattering pair distribution function analysis: 21 years in retrospect

Global research activities have been driven by the quest to develop and characterize novel materials for technological advancements. The total scattering pair distribution function (TSPDF) is a powerful and versatile characterization technique for examining the structural details of diverse complex materials including liquid, amorphous, disordered crystalline, and nanostructured materials. Thus, it is critical to keep track of research progress, identify research gaps, and future research directions of the application of the TSPDF technique in materials development and discovery. In this work, a bibliometric analysis of literature regarding the TSPDF technique between 2000 and 2021 was conducted using datasets retrieved from the Web of Science database. The research trends based on publication outputs, research subject distribution, co-authorships among institutions, countries/regions, co-citation of referenced sources, and keyword co-occurrence are evaluated and discussed herein. The impact of the TSPDF technique is projected to increase due to its importance in probing emerging functional materials, and the advances in specialized facilities and instrumentation among the scientific communities engaged with it. Finally, current and emerging research hotspots related to TSPDF technique such as catalysis, computer modeling and simulation, pharmaceutics, machine learning, hydrogen storage, battery materials, and layered structured materials are also identified and discussed.

36 MATERIALS SCIENCE↗

Dynamic, Adaptive, Systems and Materials: Complex, Simple and Emergent Behaviors

This program has been funded by DoE/BES for twenty years. It has moved into and out of various subjects as it has developed, but it has retained its focus on complexity and complex systems. The project has evolved in the following way: Self-Assembly and Biomimetic Self-Assembly: All self-assembling systems depend upon a minimum of two types of interaction: a repulsion and an attraction. For the familiar molecular systems, attractive interactions are typically hydrogen bonds and electrostatic interactions. Repulsive interactions include steric effects, hydrophobic effects (in biological systems), and charge-charge repulsion. We have expanded this repertoire to include surface interactions, magnetic interactions, and others. I list these systems in the order in which we have explored them: i) A key emphasis in current work is in understanding how the movement of ions in a magnetic field (the Lorentz effect) interacts with catalytic systems. We have demonstrated that an acceleration in rate of reduction of CO 2 to CO can be accomplished by applying an external magnetic field. This acceleration is largely due to the application of the Lorentz effect on mass transport at the catalyst’s surface. ii) We have also extensively explored the influence of electrostatics, as exhibited in self-assembling systems, by tribocharging. iii) Another key system involves surface tension effects; examples include interactions between heavy particles floating at a liquid-air interface, and interacting by changes in surface area; interactions of bubbles and bubble rafts, behaviors of bubble trains in microfluidic networks, and behaviors of microorganisms in constraining environments. iv) This work has intentionally de-emphasized biological systems; but it does include some work on protein-ligand interactions and interactions among microorganisms. v) We have also explored applications of some of these effects, these explorations include bubble rafts as diffraction gratings, exploration of the structures that can be obtained by tribocharging and uses of these structures in exploring nucleation and melting of crystals. vi) Although not a major focus of this work, several other topics have emerged and offer opportunities for future work. These include the behavior of bubble trains and bubble rafts in microfluidic systems. A particularly interesting example is the formation of bubble trains that repeat in the alteration of large and small bubbles according to rules we do not presently understand, but are uniquely large-period oscillating systems. These systems offer a new route into understanding the instabilities of the type represented by oscillations. vii) We have also begun exploratory projects on magnetic levitation (especially to determine molecular density), and information storage (in molecules). Magnetic Levitation: Self-assembling and biomimetic systems require both attraction and repulsion. We have used electrostatics (tribocharging), interfacial free-energies (surface tension and related forces) and others. Potential uses include reconfigurable diffraction gratings and liquid lenses; exploration of mechanisms in tribocharging; tunneling in EGaIn junctions; and bubble trains (especially in micro-fluidic systems). Examples of systems representing these topics is included in the following papers: Complexity: Disks rotating at a water-air interface; Benard-Marangoni effects; Vortex-Crystals from spinning magnetic disks (Marangoni effects); EGaIn Electrode to study quantum tunneling; Self-Assembly of electrostatically-charged metallic spheres (electrets); Dynamically reconfigurable lens; Using computational designs of ligands for enzymes; Electrostatic self-assembly by tribocharging; Monodisperse bubble trains in microchannel systems; Inverted dripping faucet; Flames; Printing of micro-organisms to regenerate the “ink” of printing device; Using micro-organisms to move loads (“microoxen”); Motion of bacterial swarms near surfaces; Making monodisperse particles in microfluidic systems; Coding/decoding of information stored in droplet trains in microfluidic networks; Magnetic levitation; and Information storage. i) Tribocharging. The change in focus of this work on electrets from the fundamentals of charging to applications of these materials in studying self-assembly using electrostatic interactions. ii) Bubbles in Microchannels. The realization that systems of bubbles in microchannels represented a major opportunity to study complexity in a very tractable system, and the development of a semi-quantitative theory of this subject. iii) Flames. The growth of “flames” remains an exploratory subject for the research, although their currently relatively little active work involving it ongoing. iv) Systems with Microorganisms. The removal of work in biological systems from this project. Based on work supported in this program, we now have a significant project on the development of microfluidic tools for studying C. elegans (a nematode), but this work was not appropriate for a program focused on complexity, and we developed separate support for it. (It is, however, an example of successful seeding of a new area by BES.) The work on electrets has gone through a period in which a part of the program was the subject of a MURI; the focus of this work was to develop materials that did not charge electrostatically on friction or contact. The MURI is now over, and the work on dynamic self-assembly (supported by BES) is the major focus. “Flames” has also enjoyed synergistic support, in terms of a project supported by DARPA on flame suppression (in the absence of extinguishing agents, using acoustic and electrostatic interactions). This work was helpful in understanding some of the basics of flames, but is entirely distinct from the BES focus in complexity. A growing interest is in the Lorentz effect. The Lorentz effect is the force exerted on charged particles (electrons, ions, charged molecules) when they move through a perpendicular magnetic field. The Lorentz effect is almost ubiquitous in modern technology: examples of applications include electric motors, dynamos, cathode ray tubes, many batteries, and most systems that control electrical currents with magnetic forces. We have begun to explore the Lorentz effect in electrochemical systems and heterogeneous catalytic systems involving charged organic species and inorganic ions. This work is still at an early stage, but initial studies that Lorentz effects can be large when ions move through magnetic fields, or magnetic fields move in the presence of ions.

36 MATERIALS SCIENCE↗

Theoretical Prediction of Thermal Expansion Anisotropy for Y 2 Si 2 O 7 Environmental Barrier Coatings Using a Deep Neural Network Potential and Comparison to Experiment

Environmental barrier coatings (EBCs) are an enabling technology for silicon carbide (SiC)-based ceramic matrix composites (CMCs) in extreme environments such as gas turbine engines. However, the development of new coating systems is hindered by the large design space and difficulty in predicting the properties for these materials. Density Functional Theory (DFT) has successfully been used to model and predict some thermodynamic and thermo-mechanical properties of high-temperature ceramics for EBCs, although these calculations are challenging due to their high computational costs. In this work, we use machine learning to train a deep neural network potential (DNP) for Y 2 Si 2 O 7 , which is then applied to calculate the thermodynamic and thermo-mechanical properties at near-DFT accuracy much faster and using less computational resources than DFT. We use this DNP to predict the phonon-based thermodynamic properties of Y 2 Si 2 O 7 with good agreement to DFT and experiments. We also utilize the DNP to calculate the anisotropic, lattice direction-dependent coefficients of thermal expansion (CTEs) for Y 2 Si 2 O 7 . Molecular dynamics trajectories using the DNP correctly demonstrate the accurate prediction of the anisotropy of the CTE in good agreement with the diffraction experiments. In the future, this DNP could be applied to accelerate additional property calculations for Y 2 Si 2 O 7 compared to DFT or experiments.

36 MATERIALS SCIENCE↗

Synthesis, Isolation, and Study of Heterobimetallic Uranyl Crown Ether Complexes

Although crown ethers can selectively bind many metal cations, little is known regarding the solution properties of crown ether complexes of the uranyl dication, UO 2 2+ . Here, in this work, the synthesis and characterization of isolable complexes in which the uranyl dication is bound in an 18-crown-6-like moiety are reported. A tailored macrocyclic ligand, templated with a Pt(II) center, captures UO 2 2+ in the crown moiety, as demonstrated by results from single-crystal X-ray diffraction analysis. The U(V) oxidation state becomes accessible at a quite positive potential (E 1/2 ) of –0.18 V vs Fc +/0 upon complexation, representing the most positive U VI /U V potential yet reported for the UO 2 n+ core. Isolation and characterization of the U(V) form of the crown complex are also reported here; there are no prior reports of reduced uranyl crown ether complexes, but U(V) is clearly stabilized by crown chelation. Joint computational studies show that the electronic structure of the U(V) form results in significant weakening of U–O oxo bonding despite the quite positive reduction potential at which this species can be accessed, underscoring that crown-ligated uranyl species could demonstrate unique reactivity under only modestly reducing conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Analysis of airborne antenna patterns

The status of various efforts in support of the development of computer codes to analyze the radiation patterns of general aviation aircraft and simulate private aircraft is reported. Because of the significant amount of energy scattered by the windshield of private aircraft, a method is being developed to treat high frequency scattering by thin dielectric layers. To treat such aircraft at lower frequencies, i.e., where the aircraft surface area is less than 10 square wavelengths, a moment method code is being modified. The problem of plane (or surface) wave diffraction by the dielectric half plane is constructed and discussed.

Rojas, R. G.↗

Rotary encoding device using polygonal mirror with diffraction gratings on each facet

A device for position encoding of a rotating shaft in which a polygonal mirror having a number of facets is mounted to the shaft and a monochromatic light beam is directed towards the facets. The facets of the polygonal mirror each have a low line density diffraction grating to diffract the monochromatic light beam into a number of diffracted light beams such that a number of light spots are created on a linear array detector. An analog-to-digital converter is connected to the linear array detector for reading the position of the spots on the linear array detector means. A microprocessor with memory is connected to the analog-to-digital converter to hold and manipulate the data provided by the analog-to-digital converter on the position of the spots and to compute the position of the shaft based upon the data from the analog-to-digital converter.

Leviton, Douglas B.↗

High Angular Sensitivity, Absolute Rotary Encoding Device with Polygonal Mirror and Stand-Alone Diffraction Gratings

A device for position encoding of a rotating shaft in which a polygonal mirror having a number of facets is mounted to the shaft and a monochromatic light beam is directed towards the facets. The facets of the polygonal mirror direct the light beam to a stand-alone low line density diffraction grating to diffract the monochromatic light beam into a number of diffracted light beams such that a number of light spots are created on a linear array detector. An analog-to-digital converter is connected to the linear array detector for reading the position of the spots on the linear array detector means. A microprocessor with memory is connected to the analog-to-digital converter to hold and manipulate the data provided by the analog-to-digital converter on the position of the spots and to compute the position of the shaft based upon the data from the analog-lo-digital converter.

Leviton, Douglas B.↗

A High-Speed Rotational Diamond Anvil Cell for In Situ Analysis of Hierarchical Microstructural Evolution of Metallic Alloys during Extreme Shear Deformation

High speed shear deformation is ubiquitous in engineering applications, ranging from material processing methods such as friction stir processing/extrusion and in tribological contacts. However, analyzing the microstructural evolution of materials while they are undergoing high speed shear deformation have been a long-standing challenge. This led to predominant reliance on ex situ microscopy before and after shear deformation. But ex situ microscopy lacks the ability to analyze dynamic and transient hierarchical microstructural evolution mechanisms that could occur during shear deformation of materials. Therefore, to better understand the dynamic mechanisms of mass and energy transfer in materials under shear deformation, we developed a first of its kind high-speed rotational diamond anvil cell (HS-RDAC) for synchrotron-based in situ high-energy x-ray diffraction (XRD). We studied the time resolved lattice strain evolution, XRD peak broadening and changes in spatial variation of shear deformation induced alloying in pure metal and metal alloy sheets and powder mixture using the HS-RDAC. These in situ results were combined with detailed ex situ microstructural characterization before and after the shear deformation using transmission electron microscopy and atom probe tomography, which revealed the different stages of evolution of a shear deformation induced hierarchical nanostructure. Multiscale computational simulations including computational fluid dynamics, crystal plasticity, molecular dynamic simulation and density functional theory uncovered the mechanisms behind morphological changes, evolution of defect structures and changes in driving force for shear deformation induced intermixing. In conclusion, this in situ HS-RDAC capability, in combination with ex situ microstructural characterization and computational simulations, can provide new insights into the hierarchical microstructural evolution pathway during shear deformation.

36 MATERIALS SCIENCE↗

Exploring 2D X-ray diffraction phase fraction analysis with convolutional neural networks: Insights from kinematic-diffraction simulations

Abstract Deep-learning models are effective for analyzing the complex information in 2D X-ray diffraction (XRD) patterns. Accurately collecting parameters of the material sample is crucial during model training, significantly impacting model performance. In this study, we employ a kinematic-diffraction simulator to generate simulated 2D XRD patterns for Ti–6Al–4V alloy, allowing precise control of sample parameters. These simulated patterns are used to train convolutional neural networks, predicting $$\upbeta$$ β -phase volume fractions. The training data set consists exclusively of 2D XRD patterns with pure $$\upalpha$$ α - or pure $$\upbeta$$ β -phase, while the testing set incorporates patterns with intermediate phase volume fraction. In particular, we investigate how the architectures of the model influence prediction reliability and computational performance. Experimental results reveal that, with appropriate training, the convolutional neural network accurately detects intermediate phase volume fractions even trained with only pure-phase patterns, achieving a mean square error accuracy of $$9.4 \times 10^{-4}$$ 9.4 × 10 - 4 . Graphical abstract

Yue, Weiqi↗

Caustic Singularities Of High-Gain, Dual-Shaped Reflectors

Report presents study of some sources of error in analysis, by geometric theory of diffraction (GTD), of performance of high-gain, dual-shaped antenna reflector. Study probes into underlying analytic causes of singularity, with view toward devising and testing practical methods to avoid problems caused by singularity. Hybrid physical optics (PO) approach used to study near-field spillover or noise-temperature characteristics of high-gain relector antenna efficiently and accurately. Report illustrates this approach and underlying principles by presenting numerical results, for both offset and symmetrical reflector systems, computed by GTD, PO, and PO/GO methods.

Galindo, Victor↗

Universal Polarization Transformations: Spatial Programming of Polarization Scattering Matrices Using a Deep Learning‐Designed Diffractive Polarization Transformer

Abstract Controlled synthesis of optical fields having nonuniform polarization distributions presents a challenging task. Here, a universal polarization transformer is demonstrated that can synthesize a large set of arbitrarily‐selected, complex‐valued polarization scattering matrices between the polarization states at different positions within its input and output field‐of‐views (FOVs). This framework comprises 2D arrays of linear polarizers positioned between isotropic diffractive layers, each containing tens of thousands of diffractive features with optimizable transmission coefficients. After its deep learning‐based training, this diffractive polarization transformer can successfully implement N i N o = 10 000 different spatially‐encoded polarization scattering matrices with negligible error, where N i and N o represent the number of pixels in the input and output FOVs, respectively. This universal polarization transformation framework is experimentally validated in the terahertz spectrum by fabricating wire‐grid polarizers and integrating them with 3D‐printed diffractive layers to form a physical polarization transformer. Through this set‐up, an all‐optical polarization permutation operation of spatially‐varying polarization fields is demonstrated, and distinct spatially‐encoded polarization scattering matrices are simultaneously implemented between the input and output FOVs of a compact diffractive processor. This framework opens up new avenues for developing novel devices for universal polarization control and may find applications in, e.g., remote sensing, medical imaging, security, material inspection, and machine vision.

Optical neural networks↗

Computational and Experimental Investigation of Chiral and Achiral Two‐Dimensional Organic Lead Bromide Perovskites: Octahedral Distortions and Electronic and Optical Properties

A computational investigation is presented, in conjunction with synthesis and experimental characterization, into the structural, electronic, and optical properties of layered two-dimensional organic lead bromide perovskites. Materials based on the chiral (R/S)-4-fluoro-α-methylbenzylammonium (R/S-FMBA), which have been shown to lead to bright room-temperature circularly polarized luminescence, are contrasted with the similar achiral 4-fluorobenzylammonium (FBA). Using density functional theory (DFT) with van der Waals (vdW) corrections, relaxed structures (compared with X-ray diffraction, XRD) and optical absorption spectra (compared with experiments) are studied, as well as band structure and orbital character of transitions. A Python code is developed and provided to calculate octahedral distortions and compare DFT and XRD results, finding that vdW corrections are important for accuracy and that DFT overestimates octahedral tilt angles. (FMBA) 2 PbBr 4 shows among the largest tilt angle differences (often termed Δ β ) reported, 14°–15°, indicating strong inversion symmetry-breaking, which enables its chiral emission. A large resulting Dresselhaus spin-splitting effect is found. The lowest-energy optical transitions involve the perovskite only and are polarized within the layer. This work furthers understanding of structure-property relations with applications to optoelectronics and spintronics.

UV/vis spectroscopy↗

The role of precursor decomposition in the formation of samarium doped ceria nanoparticles via solid-state microwave synthesis

The impact on the final morphology of ceria (CeO 2 ) nanoparticles made from different precursors (commercial: cerium acetate/nitrate) and in house: cerium tri(methylsilyl)amide (Ce-TMSA)) via a microwave solid state reaction has been determined. In all instances, powder X-ray diffraction indicated that the cubic fluorite CeO 2 phase (PDF# 04–004-9150, with the space group Fm-3 m) had formed. Scanning electron microscopy (SEM) images revealed spherical nanoparticles were produced from the Ce-TMSA precursor. The commercial acetate and nitrate precursors produced particles with irregular morphology. The roles of the precursor decomposition and binding energy in the synthesis of the nanocrystals with various morphologies, as well as a possible growth mechanism, were evaluated based on experimental and computational data. The formation of spherical shaped nanoparticles was determined to be due to the preferential single-step decomposition of the Ce-TMSA as well as the low activation energy to overcome decomposition. Due to the complicated decomposition of the commercial precursors and high activation energy the resulting particles adopted an irregular morphology. Highly uniform samarium doped ceria (Sm x Ce 1-x O 2-δ ) nanospheres were also synthesized from Ce-TMSA and samarium tri(methylsilyl)amide (Sm-TMSA). The effects of reaction time and temperature, on the final morphology were observed through SEM. The rapid single-step decomposition of TMSA-based precursors as observed through thermogravimetric analysis (TGA) and confirmed through the calculation of potential energy surfaces and binding energies from density functional theory (DFT) calculations, indicated that nanoparticle formation follows LaMer’s classical nucleation theory.

36 MATERIALS SCIENCE↗

Actinide arene-metalates: ion pairing effects on the electronic structure of unsupported uranium–arenide sandwich complexes

Addition of [UI 2 (THF) 3 (μ-OMe)] 2 ·THF (2·THF) to THF solutions containing 6 equiv. of K[C 14 H 10 ] generates the heteroleptic dimeric complexes [K(18-crown-6)(THF) 2 ] 2 [U(η 6 -C 14 H 10 )(η 4 -C 14 H 10 )(μ-OMe)] 2 ·4THF (1 18C6 ·4THF) and {[K(THF) 3 ][U(η 6 -C 14 H 10 )(η 4 -C 14 H 10 )(μ-OMe)]} 2 (1 THF ) upon crystallization of the products in THF in the presence or absence of 18-crown-6, respectively. Both 1 18C6 ·4THF and 1 THF are thermally stable in the solid-state at room temperature; however, after crystallization, they become insoluble in THF or DME solutions and instead gradually decompose upon standing. X-ray diffraction analysis reveals 1 18C6 ·4THF and 1 THF to be structurally similar, possessing uranium centres sandwiched between bent anthracenide ligands of mixed tetrahapto and hexahapto ligation modes. Yet, the two complexes are distinguished by the close contact potassium-arenide ion pairing that is seen in 1 THF but absent in 1 18C6 ·4THF, which is observed to have a significant effect on the electronic characteristics of the two complexes. Structural analysis, SQUID magnetometry data, XANES spectral characterization, and computational analyses are generally consistent with U(IV) formal assignments for the metal centres in both 1 18C6 ·4THF and 1 THF , though noticeable differences are detected between the two species. For instance, the effective magnetic moment of 1 THF (3.74 μ B ) is significantly lower than that of 1 18C6 ·4THF (4.40 μ B ) at 300 K. Furthermore, the XANES data shows the U L III -edge absorption energy for 1 THF to be 0.9 eV higher than that of 1 18C6 ·4THF, suggestive of more oxidized metal centres in the former. Of note, CASSCF calculations on the model complex {[U(η 6 -C 14 H 10 )(η 4 -C 14 H 10 )(μ-OMe)] 2 } 2– (1*) shows highly polarized uranium–arenide interactions defined by π-type bonds where the metal contributions are primarily comprised by the 6d-orbitals (7.3 ± 0.6%) with minor participation from the 5f-orbitals (1.5 ± 0.5%). These unique complexes provide new insights into actinide–arenide bonding interactions and show the sensitivity of the electronic structures of the uranium atoms to coordination sphere effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nanoscale X-ray Imaging and Dynamics of Electronic and Magnetic Materials

This project supported cutting-edge nanoscale characterization developments including X-ray Imaging by utilizing the power of Coherent X-ray Diffractive Imaging (CXDI). This research pioneered new directions in studies of nanoscale dynamics using X-ray Photon Correlation Spectroscopy (XPCS) and Ultrafast X-ray Scattering (UXS), extending our understanding of science and technology at the limits of ultrasmall (atomic/nanoscale) and ultrafast (from seconds to femtosecond dynamics). The research funded by this award spans a wide range of condensed matter and materials physics systems, from correlated oxides and nanomaterials to energy-related materials, and quantum materials for neuromorphic computing.

25 ENERGY STORAGE↗

Physics of Acoustic Radiation from Jet Engine Inlets

Numerical simulations of acoustic radiation from a jet engine inlet are performed using advanced computational aeroacoustics (CAA) algorithms and high-quality numerical boundary treatments. As a model of modern commercial jet engine inlets, the inlet geometry of the NASA Source Diagnostic Test (SDT) is used. Fan noise consists of tones and broadband sound. This investigation considers the radiation of tones associated with upstream propagating duct modes. The primary objective is to identify the dominant physical processes that determine the directivity of the radiated sound. Two such processes have been identified. They are acoustic diffraction and refraction. Diffraction is the natural tendency for an acoustic wave to follow a curved solid surface as it propagates. Refraction is the turning of the direction of propagation of sound waves by mean flow gradients. Parametric studies on the changes in the directivity of radiated sound due to variations in forward flight Mach number and duct mode frequency, azimuthal mode number, and radial mode number are carried out. It is found there is a significant difference in directivity for the radiation of the same duct mode from an engine inlet when operating in static condition and in forward flight. It will be shown that the large change in directivity is the result of the combined effects of diffraction and refraction.

Tam, Christopher K. W.↗

Effect of Pressure on Crystal Structure and Phonon Density of States of FeSi

The strongly correlated material FeSi displays several unusual thermal, magnetic, and structural properties under varying pressure-temperature (P-T) conditions. It is a potential thermoelectric alloy and a material with several geochemical implications as a possible constituent at the Earth's core-mantle boundary (CMB). Previous theoretical studies predicted a pressure-induced B20-B2 transition at ambient temperature below 40 GPa; however, experimentally, the structural transition is observed only at high P-T conditions. In this study, we have performed high-pressure powder X-ray diffraction (XRD) up to 90 GPa and Nuclear Resonant Inelastic X-ray Scattering (NRIXS) measurements up to 120 GPa to understand the phase stability and lattice dynamics. Our study provides evidence for a non-hydrostatic stress-induced B20-B2 transition in FeSi at around 36 GPa. We deduced the Fe partial phonon density of states (PDOS) and thermal parameters from NRIXS measurements up to 120 GPa and compared them with density functional theory (DFT) calculations. Furthermore, the computations show pressure-induced metallization and the band gap closing around 12 GPa.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗