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Occupational and dietary differences in hydroxylated and methoxylated PBDEs and metals in plasma from Puget Sound, Washington, USA region volunteers

BACKGROUND: Electronic waste (E-waste) recycling is a rapidly growing occupation in the USA with the potential for elevated exposure to flame retardants and metals associated with electronic devices. We previously measured polybrominated diphenyl ethers (PBDEs) in plasma from E-waste workers and found them similar to non-E-waste workers. OBJECTIVES: This study focused on structurally related PBDE derivatives, the hydroxylated (OH-PBDEs) and methoxylated (MeO-PBDEs) forms along with metals known to occur in E-waste. Humans can metabolize PBDEs and some MeO-PBDEs into OH-PBDEs, which is a concern due to greater health risks associated with OH-PBDEs METHODS: We measured 32 different OH-PBDEs and MeO-PBDEs in plasma samples provided by 113 volunteers living in the greater Puget Sound region of Washington State, USA. We measured 14 metals in a subset of 10 E-waste and 10 non-E-waste volunteers. Volunteers were classified based on occupational and dietary habits: work outdoors and weekly consume = 5 seafood servings (outdoor), electronic waste recycling (E-waste) or non-specific indoor occupations (indoor). A two-week food consumption diary was obtained from each volunteer prior to blood sampling. RESULTS: OH-PBDEs were detected in all volunteers varying between 0.27 – 102 ng/g/g-lipid. The MeO-PBDEs were detected in most, but not all volunteers varying between 0 – 60.4 ng/g/g-lipid. E-waste recyclers had OH-PBDE and MeO-PBDE plasma levels that were similar to the indoor group. The outdoor group had significantly higher levels of MeO-PBDEs, but not OH-PBDEs. Comparison of plasma concentrations of BDE-47 with its known hydroxylated metabolites suggested OH-PBDE levels were likely determined by biotransformation and at least two subpopulations identified differing in their apparent rates of OH-PBDE formation. The metals analysis indicated no significant differences between E-waste workers and non-E-waste workers. CONCLUSIONS: Our results indicate E-waste workers do not have elevated plasma levels of these contaminants relative to non-E-waste workers with similar dietary habits.

Schultz, Irvin↗

Listeria monocytogenes loss of cultivability on carrot is associated with the formation of mesosome-like structures

Raw carrot is known to have antimicrobial activity against Listeria monocytogenes, but the mechanism of action has not been fully elucidated. In this study, we examined carrot antilisterial activity against several strains of Listeria species (including L. grayi, L. innocua, L. seeligeri, and L. welshimeri) and L. monocytogenes. A representative strain of L. monocytogenes was subsequently used for further characterizing carrot antilisterial activity. Exposure to fresh-cut carrot for 15 min resulted in a similar loss of cultivability, ranging from 2.5 to 4.7 log units, across all Listeria strains evaluated. L. monocytogenes recovered from the fresh-cut surface of different raw carrots was 1.6 to 4.1 log lower than levels obtained from paired boiled carrot samples with abolished antilisterial activity. L. monocytogenes levels recovered from fresh-cut carrot were 2.8 to 3.1 log lower when enumerated by culture-dependent methods than by the culture-independent method of PMAxx-qPCR, a qPCR assay that is performed using DNA pre-treated to selectively sequester DNA from cells with injured membranes. These results suggested that L. monocytogenes loss of cultivability on fresh-cut carrot was not associated with a loss of L. monocytogenes cell membrane integrity and putative cell viability. Transmission electron microscopy imaging revealed that L. monocytogenes rapidly formed mesosome-like structures upon exposure to carrot fresh-cut surface but not upon exposure to boiled carrot surface, suggesting there may be an association between the formation of these mesosome-like structures and a loss of cultivability in L. monocytogenes. As a result, further research is necessary to conclude the causality of this association.

59 BASIC BIOLOGICAL SCIENCES↗

Transuranium Sulfide via the Boron Chalcogen Mixture Method and Reversible Water Uptake in the NaCu T S 3 Family

The behavior of 5f electrons in soft ligand environments makes actinides, and especially transuranium chalcogenides, an intriguing class of materials for fundamental studies. Due to the affinity of actinides for oxygen, however, it is a challenge to synthesize actinide chalcogenides using non-metallic reagents. Using the Boron Chalcogen Mixture (BCM) method, we achieved the synthesis of the transuranium sulfide NaCuNpS 3 starting from the oxide reagent, NpO 2 . Via the same synthetic route, the isostructural composition of NaCuUS 3 was synthesized and the material contrasted with NaCuNpS 3 . Single crystals of the U-analog, NaCuUS 3 , were found to undergo an unexpected reversible hydration process to form NaCuUS 3 ·xH 2 O (x ≈ 1.5). Here, a large combination of techniques was used to fully characterize the structure, hydration process, and electronic structures, specifically a combination of single crystal, powder, high temperature powder X-ray diffraction, extended X-ray ab-sorption fine structure, infrared, and inductively coupled plasma spectroscopies, thermogravimetric analysis, and density functional theory calculations. The outcome of these analyses enabled us to determine the composition of NaCuUS 3 ·xH 2 O and obtain a structural model that demonstrated the retention of the local structure within the [CuUS 3 ] – layers throughout the hydration-dehydration process. Band structure, density of states, and Bader charge calculations for NaCuUS 3 , NaCu-US 3 ·xH 2 O, and NaCuNpS 3 along with X-ray absorption near edge structure, UV-vis-NIR and work function measurements on ACuUS 3 (A = Na, K, and Rb) and NaCuUS 3 ·xH 2 O samples were carried out to demonstrate that electronic properties arise from the [CuTS 3 ] – layers and show surprisingly little dependence on the interlayer distance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Role of Eu-Doping in the Electron Transport Behavior in the Zintl Thermoelectric Ca 5-x-y Yb x Eu y Al 2 Sb 6 System

A series of Eu-doped Zintl compounds belonging to theCa 5-x-y Yb x Eu y Al 2 Sb 6 (x = 0, 1.12; 0 ≤ y ≤ 0.63(2)) system have been successfully synthesized by both the arc-melting and the molten Pb-flux methods. All of the five title compounds initially crystallized in the Ca 5 Ga 2 As 6 -type phase (space group Pbam, Z = 2, Pearson code oP26) and maintained their original structure even after the post-heat treatment, unlike the recently reported n-type Zintl analogues in the Ca 5-x-y Yb x RE y Al 2 Sb 6 (RE = Pr, Nd, Sm) systems, which underwent a phase transition from the Ca 5 Ga 2 As 6 -type to the Ca 5 Al 2 Bi 6 -type phase after annealing. This research aimed to understand the origin of the structural preference of the title Ca 5-x-y Yb x Eu y Al 2 Sb 6 system, whether it was affected by the valence electron count or the cationic size. Electrical transport property measurements showed an increase in electrical conductivities and a decrease of Seebeck coefficients for Ca 4.89(1) Eu 0.11 Al 2 Sb 6 , Ca 4.82(1) Eu 0.18 Al 2 Sb 6 , and Ca 4.62(1) Eu 0.38 Al 2 Sb 6 , compared to the parental compound Ca 5 Al 2 Sb 6 . Hole effect measurements proved that these changes should be attributed to the reduced carrier concentration and enhanced carrier mobility. The comprehensive density functional theory calculations including electron density map analysis for the hypothetical model Ca 4.5 Eu 0.5 Al 2 Sb 6 revealed that the polarity between Al and Sb forming the anionic frameworks decreased as the Eu-dopants were introduced, which eventually affected the carrier mobility in the anionic frameworks. Thermal conductivity measurements proved that the Eu-doping successfully lowered the lattice thermal conductivity because of the enhanced atomic disordering. In conclusion, the magnetization measurements for Ca 4.37(2) Eu 0.63 Al 2 Sb 6 showed a typical Curie–Weiss behavior with weak antiferromagnetic nearest-neighbor interactions with θ p = -5.07 K.

36 MATERIALS SCIENCE↗

Description of reaction and vibrational energetics of CO 2 –NH 3 interaction using quantum computing algorithms

CO 2 capture is critical to solving global warming. Amine-based solvents are extensively used to chemically absorb CO 2 . Thus, it is crucial to study the chemical absorption of CO 2 by amine-based solvents to better understand and optimize CO 2 capture processes. Here, we use quantum computing algorithms to quantify molecular vibrational energies and reaction pathways between CO 2 and a simplified amine-based solvent model—NH 3 . Molecular vibrational properties are important to understanding kinetics of reactions. However, the molecule size correlates with the strength of anharmonicity effect on vibrational properties, which can be challenging to address using classical computing. Quantum computing can help enhance molecular vibrational calculations by including anharmonicity. We implement a variational quantum eigensolver (VQE) algorithm in a quantum simulator to calculate ground state vibrational energies of reactants and products of the CO 2 and NH 3 reaction. The VQE calculations yield ground vibrational energies of CO 2 and NH 3 with similar accuracy to classical computing. In the presence of hardware noise, Compact Heuristic for Chemistry (CHC) ansatz with shallower circuit depth performs better than Unitary Vibrational Coupled Cluster. The “Zero Noise Extrapolation” error-mitigation approach in combination with CHC ansatz improves the vibrational calculation accuracy. Excited vibrational states are accessed with quantum equation of motion method for CO 2 and NH 3 . Using quantum Hartree–Fock (HF) embedding algorithm to calculate electronic energies, the corresponding reaction profile compares favorably with Coupled Cluster Singles and Doubles while being more accurate than HF. Our research showcases quantum computing applications in the study of CO 2 capture reactions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Influence of Methylammonium Chloride on Wide-Bandgap Halide Perovskites Films for Solar Cells

Wide-bandgap perovskites are of paramount importance as the photoactive layer of the top cell in high-efficiency tandem solar cells. Comparably high Br contents are required to widen the perovskite bandgap. However, the increase in Br content causes heterogeneous halide distribution and photoinstability. Here, in this study, the positive effect of the additive methylammonium chloride (MACl) on the optical and electronic properties of Br-rich perovskite, deposited using N-methyl-2-pyrrolidone (NMP) as co-solvent and the gas quenching method, is investigated. Simultaneous in situ grazing-incidence wide-angle X-ray scattering and photoluminescence spectroscopy are used to track the evolution of the structural and optoelectronic properties of the perovskites with different amounts of Br and MACl during the spin-coating and thermal annealing steps. The formation mechanism is elucidated in the presence of MACl. It is observed that chloride ions inhibit the intermediate phases, favoring the formation of a perovskite phase with higher crystallinity. Nano X-ray fluorescence mapping recognizes Br-richer and poorer nanometric domains, whose average sizes reduce for samples with MACl. In conclusion, it is demonstrated that adding MACl affects the formation of wide-bandgap perovskites via destabilization of the intermediate phases and acts on the homogenization of the halide distribution, leading to improved solar cell performances.

14 SOLAR ENERGY↗

Influence of thermal treatment on structure and catalytic performance of ceria-zirconia supported copper oxide (CuO x /Ce y Zr 1-y O 2 ) catalysts for CO oxidation

Copper oxide (CuO x ) supported on ceria-zirconia (Ce y Zr 1-y O 2 , y = 1.0, 0.5, 0.0) catalysts were investigated to elucidate the effects of thermal treatment on their physicochemical properties and catalytic performance in carbon monoxide (CO) oxidation. Here, the catalysts were synthesized via a one-pot chemical vapor deposition (OP-CVD) method at 700˚C and 900˚C with controlled Cu loading. Characterization techniques, including synchrotron X-ray diffraction (S-XRD), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), inductively coupled plasma spectroscopy (ICP), and N 2 adsorption-desorption, were implemented to probe the crystalline structure, molecular and electronic structure, oxygen vacancies, specific surface area (SSA) and metal loading. CO oxidation was chosen as a model reaction to explore the structure-catalytic performance relationship. A ∼100% CO conversion was achieved at < 150˚C, particularly with the CuO x /CeO 2 catalyst calcined at 700˚C. In contrast, calcination at 900˚C caused a ∼90% decrease in SSA and a ∼24% increase in T 50 . Activity tests revealed that increasing ZrO 2 content lowered CO oxidation activity despite generating more defect sites. In-situ measurement of the 700 °C calcined samples revealed the presence of stable and unstable defects in CuO x /Ce 0.5 Zr 0.5 O 2 and CeO 2 respectively, which play a key role in the activity of the catalysts. The results highlight that catalytic performance is closely related to the SSA. Furthermore, an optimum calcination temperature favor significant oxygen vacancy formation with required CuO x -support interactions, enhancing redox properties and catalytic performance.

36 MATERIALS SCIENCE↗

SPACE: 3D parallel solvers for Vlasov-Maxwell and Vlasov-Poisson equations for relativistic plasmas with atomic transformations

A parallel, relativistic, three-dimensional particle-in-cell code SPACE has been developed for the simulation of electromagnetic fields, relativistic particle beams, and plasmas. In addition to the standard second-order Particle-in-Cell (PIC) algorithm, SPACE includes efficient novel algorithms to resolve atomic physics processes such as multi-level ionization of plasma atoms, recombination, and electron attachment to dopants in dense neutral gases. SPACE also contains a highly adaptive particle-based method, called Adaptive Particle-in-Cloud (AP-Cloud), for solving the Vlasov-Poisson problems. It eliminates the traditional Cartesian mesh of PIC and replaces it with an adaptive octree data structure. The code's algorithms, structure, capabilities, parallelization strategy, and performance have been discussed. Additionally, typical examples of SPACE applications to accelerator science and engineering problems are described.

43 PARTICLE ACCELERATORS↗

Seed-Mediated Colloidal Synthesis of Multimetallic and High-Entropy Alloy Nanocrystal Libraries with Enhanced Catalytic Performance

Engineering colloidally stable multimetallic nanocrystals offers many benefits in a wide range of applications and allows manipulation of physical, chemical, and electronic properties of materials at the nanoscale. Synthesis routes are challenged by the chemical complexity required to temporally and spatially coordinate the reduction and alloying of multiple metal species, which has hampered the development of tunable libraries of colloidal materials to date. Here, in this work, we demonstrate a seed-mediated synthesis method to incorporate five or more metal elements into uniform, colloidally stable nanocrystals. By integrating machine learning-accelerated simulations, the synthesis of shortlisted high-entropy alloy nanocrystals was demonstrated. Multiple seed materials can be used, leading to a library of multimetallic nanocrystals with tunable electronic, physical, and alloy structures. The advantage of this synthetic protocol is highlighted in the preparation of catalytic materials that showed 2 orders of magnitude higher reaction rates than monometallic catalysts and outstanding thermal stability, thus highlighting the promise of this approach for high-performance materials in many areas.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Artificial intelligence in cryo-EM protein particle picking: recent advances and remaining challenges

Abstract Cryo-electron microscopy (cryo-EM) has revolutionized structural biology by enabling the determination of high-resolution 3-Dimensional (3D) structures of large biological macromolecules. Protein particle picking, the process of identifying individual protein particles in cryo-EM micrographs for building protein structures, has progressed from manual and template-based methods to sophisticated artificial intelligence (AI)-driven approaches in recent years. This review critically examines the evolution and current state of cryo-EM particle picking methods, with an emphasis on the impact of AI. We conducted a comparative evaluation of popular AI-based particle picking methods, using both general machine learning metrics and specific cryo-EM structure determination metrics. This analysis involved constructing the 3D density map from the picked protein particles and assessing the obtained resolution and particle orientation diversity, underscoring the significant impact of AI on cryo-EM particle picking. Despite the advancements, we also identified key obstacles, such as handling complex micrographs with small proteins. The analysis provides insights into the future development of more sophisticated and fully automated AI methods in cryo-EM particle recognition.

Biochemistry & Molecular Biology↗

Probing New Bosons and Nuclear Structure with Ytterbium Isotope Shifts

In this Letter, we present mass-ratio measurements on highly charged Yb 42+ ions with a precision of 4 ×10 -12 and isotope-shift measurements on Yb + on the 2 S 1/2 → 2 D 5/2 and 2 S 1/2 → 2 F 7/2 transitions with a precision of 4 ×10 -9 for the isotopes 168,170,172,174,176 Yb. We present a new method that allows us to extract higher-order changes in the nuclear charge distribution along the Yb isotope chain, benchmarking ab initio nuclear structure calculations. Additionally, we perform a King plot analysis to set bounds on a fifth force in the keV/c 2 to MeV/c 2 range coupling to electrons and neutrons.

74 ATOMIC AND MOLECULAR PHYSICS↗

Spectroscopy and Scattering Studies Using Interpolated Ab Initio Potentials

The Born–Oppenheimer potential energy surface (PES) has come a long way since its introduction in the 1920s, both conceptually and in predictive power for practical applications. Nevertheless, nearly 100 years later—despite astonishing advances in computational power—the state-of-the-art first-principles prediction of observables related to spectroscopy and scattering dynamics is surprisingly limited. For example, the water dimer, (H 2 O) 2 , with only six nuclei and 20 electrons, still presents a formidable challenge for full-dimensional variational calculations of bound states and is considered out of reach for rigorous scattering calculations. The extremely poor scaling of the most rigorous quantum methods is fundamental; however, recent progress in development of approximate methodologies has opened the door to fairly routine high-quality predictions, unthinkable 20 years ago. In this review, in relation to the workflow of spectroscopy and/or scattering studies, we summarize progress and challenges in the component areas of electronic structure calculations, PES fitting, and quantum dynamical calculations.

Chemistry↗

Holographic Quantum Simulation of Strongly Correlated Electron Systems

The project aimed to demonstrate a new holographic quantum simulation approach and co‐ designed quantum hardware to tackle three specific problems that fall within the broad umbrella of unraveling the physics of strongly correlated electron systems (SCES). These tasks were: (1) holographic preparation of ground‐ and thermal‐ states of correlated magnetic and electronic systems including quasi‐2d frustrated‐spin, Fermi‐Hubbard, and fractional quantum Hall (FQH) systems, (2) holographic‐simulation of long‐time out‐of‐equilibrium dynamics and (3) holographic analogs of embedding methods such as dynamical mean‐ field theory (DMFT) and density‐matrix embedding theory (DMET) to solve systems with complex structure or long‐range interactions. These tasks are prototypes for the kinds of material simulation problems of interest to BES, such as the simulation of multiferroic materials, perovskite photovoltaics and high‐temperature superconductors, that tax the capabilities of the most powerful classical supercomputers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Resilient Distributed Frequency Regulation of Renewable Generators under Communication Interruptions

Modern power systems (MPSs) face significant challenges due to the high penetration of renewable energy sources (RESs) and new types of loads such as electric vehicles (EVs). Traditional load frequency control (LFC) methods struggle with the intermittent, stochastic nature of RESs, the near-zero inertia of power-electronics-based generators, and the mobility of controllable loads and battery systems. This paper introduces a novel resilient distributed frequency regulation method to address these issues. The proposed method employs a state space model to represent the dynamic behavior of participating power sources while accounting for stochastic switching processes to model structural and parameter variations caused by disruptions such as generator connection/disconnection, communication interruptions, and physical faults. By integrating these dynamic and stochastic components, the method treats power grids as a comprehensive stochastic hybrid system. Our method enhances conventional frequency control by incorporating local stability control, neighborhood control decoupling, and coordination feedback. Theoretical analyses establish the stability, convergence, and resilience of the proposed method, and its effectiveness is validated through case studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Atomic-scale electronic inhomogeneity in single-layer iron chalcogenide alloys revealed by machine learning of STM/S data

Chemical pressure from the isovalent substitution of Se by a larger Te atom in the epitaxial film of iron chalcogenide FeSe can effectively tune its superconducting, topological, and magnetic properties. However, such substitution during epitaxial growth inherently leads to defects and structural inhomogeneity, making the determination of alloy composition and atomic sites for the substitutional Te atoms challenging. Here, we utilize machine learning to distinguish between Se and Te atoms in scanning tunneling microscopy images of single-layer FeSe1−xTex on SrTiO3(001) substrates. Defect locations are first identified by analyzing spatial-dependent dI/dV tunneling spectra using the K-means clustering method. After excluding the defect regions, the remaining dI/dV spectra are further analyzed using the singular value decomposition method to determine the Se/Te ratio. Our findings demonstrate an effective and reliable approach for determining alloy composition and atomic-scale electronic inhomogeneity in superconducting single-layer iron chalcogenide films.

Materials Science↗

Materials Challenges and Opportunities for Energy Generation, Conversion, Delivery, and Storage (Applied Energy Tri-Laboratory Consortium Workshop Report)

This report documents the outcomes of the Tri-Laboratory Materials Workshop that was held July 31 and August 1, 2019 to begin addressing the needs, opportunities, and challenges associated with the development, fabrication, and testing of the needed materials and components for integrated hybrid energy systems (i.e., incorporating nuclear, fossil, and renewables for electric and thermal applications). This was accomplished by assembling the research program leads and principal investigators at Idaho National Laboratory (INL), National Energy Technology Laboratory (NETL), and National Renewable Energy Laboratory (NREL), who support the research and development of new technology and system integration. The team then identified and prioritized key materials development needs. This effort was intended to enhance communications and synergy among the Tri-Lab partners. Advanced functional and structural materials are central to transformative energy technologies for energy generation, conversion, delivery, and storage. With that in mind, the workshop focused on identifying and assessing the foundational materials research needs at both the basic and applied levels. Materials challenges include the ability to withstand harsh environments, such as high temperatures and pressures, corrosion, oxidation, or irradiation while maintaining flexible mission profiles and long service lifespans. Advanced energy system material challenges and needs range from materials for the capture, upgrading/concentration, storage, and delivery of low-grade heat to materials for high temperature environments that involve liquid metals, molten salt, and very high temperature gas heat delivery and storage systems. Material improvements are needed for hybrid energy systems due to accelerated corrosion and stress-fatigue failure of materials and equipment, which results from increased frequency and amplitude of thermal, mechanical, and electrical cycling of systems components. Multifunctional materials are needed for high temperature solid-oxide fuel cells, advanced electrochemical reactors, and in-process separation. Relative to materials manufacturing, application of advanced additive and subtractive methods need to be understood to develop both thin-layer homogenous materials and materials of graded composition. Materials modeling and machine learning will be critical to accelerate the design and production of power electronics, and nuclear reactor materials and fuel, as well as to gain an understanding of beneficial materials phenomena or deleterious microstructure evolution. There is also a need for standardized models, computational structures, data reporting protocols and modeling tools across the three laboratories. This would allow consistent results, analysis, and data sharing. Combining computational capabilities between the three laboratories (e.g., hardware, software) would greatly increase computational capabilities and throughput. The workshop identified the need for laboratories to anticipate and address problems that will occur during scale-up. Laboratory work must connect with industry to ensure that research focuses on processes that are scalable and marketable. Industry input and perspective are essential to guide laboratory research to meet these requirements and deploy new technology in industrial demonstrations. Another aspect of scale-up is the integration of multiple systems since new challenges often arise at the subsystem interfaces. Establishing a scale-up manufacturing demonstration/pilot plant, potentially as an industrial user facility, would be beneficial to the laboratories and industry. That modular scale-up manufacturing demonstration/pilot plant would allow researchers to find and resolve interface problems that cannot be identified by focusing only on individual parts. Communication exchanges among the organizers, attendees, and workshop survey responses indicate that the workshop was successful in achieving its goal to identify key technology gaps and research needs. Strong positive feedback was received on the sharing of ideas, capabilities, talent, and passion to move forward on the materials-related action items.

36 MATERIALS SCIENCE↗

Optimal band structure for thermoelectrics with realistic scattering and bands

Abstract Understanding how to optimize electronic band structures for thermoelectrics is a topic of long-standing interest in the community. Prior models have been limited to simplified bands and/or scattering models. In this study, we apply more rigorous scattering treatments to more realistic model band structures—upward-parabolic bands that inflect to an inverted-parabolic behavior—including cases of multiple bands. In contrast to common descriptors (e.g., quality factor and complexity factor), the degree to which multiple pockets improve thermoelectric performance is bounded by interband scattering and the relative shapes of the bands. We establish that extremely anisotropic “flat-and-dispersive” bands, although best-performing in theory, may not represent a promising design strategy in practice. Critically, we determine optimum bandwidth, dependent on temperature and lattice thermal conductivity, from perfect transport cutoffs that can in theory significantly boost z T beyond the values attainable through intrinsic band structures alone. Our analysis should be widely useful as the thermoelectric research community eyes z T > 3.

97 MATHEMATICS AND COMPUTING↗

Crystal Structure of an Anisotropic Pyrope Garnet That Contains Two Cubic Phases

The crystal structure of two different samples of pyrope garnet, ideally Mg 3 Al 2 Si 3 O 12 , from South Africa was refined using the Rietveld method, space group Ia3¯d, and monochromatic synchrotron high-resolution powder X-ray diffraction (HRPXRD) data. Sample 1 from Wesselton Mine is a single cubic phase and is optically isotropic. Electron-probe microanalysis (EPMA) provided an average composition {Mg 2.30 Fe 2+ 0.26 Ca 0.42 Mn 2+ 0.02 } Σ3 [Al 1.53 Fe 3+ 0.06 Cr 3+ 0.40 Ti 4+ 0.01 Fe 2+ 0.01 ] Σ2 Si 3 O 12 , which contains a significant amount of Cr cations. The unit-cell parameter (Å) and bond distances (Å) are a = 11.56197(1) Å, average = 2.2985, Al-O = 1.9101(4), and Si-O = 1.6343(3) Å. Sample 2 from De Beers Diamond Mine has an average composition {Mg 2.33 Fe 2+ 0.33 Ca 0.33 Mn 2+ 0.01 } Σ3 [Al 1.73 Fe 3+ 0.12 Cr 3+ 0.06 Ti 4+ 0.05 Fe 2+ 0.05 ] Σ2 Si 3 O 12 and is a fine-scale intergrowth of two cubic phases. The weight percentage, unit-cell parameter (Å), and bond distances (Å) for phase 2a are 62.2(1)%, a = 11.56185(1) Å, average = 2.3006, Al-O = 1.9080(4), Si-O = 1.6334(4) Å. The corresponding values for phase 2b are 37.8(1)%, a = 11.53896(1) Å, average = 2.2954, Al-O = 1.9020(6), Si-O = 1.6334(6) Å. The two cubic phases in sample 2 cause the crystal to be optically anisotropic because of strain induce birefringence. The unit-cell parameter and bond distances for sample 1 are similar to those in phase 2a.

36 MATERIALS SCIENCE↗