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Morphology, microstructure, and doping behaviour: A comparison between different deposition methods for poly-Si/SiO x passivating contacts

In this work, we study how crystallographic structures, optoelectronic properties, and nanoscale surface morphologies of ex situ phosphorus-doped polycrystalline silicon (poly-Si)/SiO x passivating contacts, formed by different deposition methods (sputtering, plasma-enhanced chemical vapour deposition [PECVD], and low-pressure chemical vapour deposition [LPCVD]), are investigated and compared. Across all these deposition technologies, we noted the same trend: higher diffusion temperatures yield films that are more crystalline but that have rougher surface morphologies due to bigger surface crystal grains. Also, the recrystallization process of the as-deposited Si films starts from the SiO x interface, rather than from the film surface and bulk. However, there are some distinct differences among these technologies. First, the LPCVD method yields the lowest deposition rate, roughest surfaces, and smallest degree of crystallinity on finished poly-Si films. In contrast, the PECVD method has the highest deposition rate and smoothest surfaces for both as-deposited Si and annealed poly-Si films. Second, as-deposited sputtered and PECVD Si films contain only an amorphous phase, whereas as-deposited LPCVD films already has some crystalline phase. Third, the LPCVD phosphorus in-diffusion into the substrate depends strongly on the initial film thickness, whereas for the other two methods, it is weakly dependent on thickness. Finally, the passivation quality of every poly-Si film type has different responses to the film thickness and diffusion temperature, suggesting that the ex situ doping optimization should be performed independently.

14 SOLAR ENERGY↗

One Structure, Two Elements—LuGe 2 Superconductor vs Ordinary Metallic Conductor LuSn 2 . A Case Study on How Site-Selective Germanium for Tin Atom Substitution Leads to Modulating of the Charge Distribution

The substitution of chemically similar elements in a given crystal structure is an effective way to enhance physical properties, but the understanding on such improvements is usually impeded because the substitutions are random, and the roles of the different atoms cannot be distinguished by crystallographic symmetry. Herein, we provide a detailed crystallographic analysis and property measurements for the continuous solid solutions LuGe x Sn 2–x (0 < x < 2). The results show that there is no apparent change of the global symmetry, with the end-members LuGe 2 and LuSn 2 , as well as the intermediate LuGe x Sn 2–x compositions adopting the ZrSi 2 type structure (space group Cmcm, Pearson index oC12). Yet, the refinements of the crystal structures from single-crystal X-ray diffraction data show that Ge–Sn atom substitutions are not random, but occur preferentially at the zig-zag chain. The patterned distribution of two group 14 elements leads to a significant variation in chemical bonding and charge ordering within the other structural fragment, the 2D square nets, thereby resulting in tuned electron transport. The enhancement is greater than the typical Bloch-Gruneisen model, and more akin to the parallel-resistor model. Magnetization measurements on single crystals show bulk superconductivity in all LuGe x Sn 2–x samples with shielding fractions as high as 90%. Specific heat data confirm the effect to originate from residual metallic tin in the material, indicating that Sn atom substitutions in the 2D square nets cause disruptions of the hypervalent bonding and local anisotropy, which ultimately leads to vanishing of the superconducting state in the end-member LuGe 2 . This work sheds light on how the complexity in chemical interactions by two different carbon congeners leads to changes in the physical properties and how they can be correlated with the induced charge distribution. Furthermore, these studies also provide a general approach to modulation of charge density, and thus, of emerging physical properties in other classes of intermetallic systems based on the main-group elements of groups 13 to 15.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Size Dependence of Lattice Parameter and Electronic Structure in CeO2 Nanoparticles

Intrinsic properties of a compound (e.g. electronic structure, crystallographic structure, optical and magnetic properties) define notably its chemical and physical behavior. In the case of nanomaterials, these fundamental properties depend on the occurrence of quantum mechanical size effects and on the considerable increase of the surface to bulk ratio. However, the literature on this size-dependence and on the involved mechanisms is quite elusive and scarce. Here, we explore the size-dependence of both crystal and electronic properties of CeO2 nanoparticles (NPs) with different sizes by state-of-the art spectroscopic techniques. XRD, XPS and HERFD-XANES demonstrate that the as-synthesized NPs crystallize in the fluorite structure and they are predominantly composed of CeIV ions. The strong dependence of the lattice parameter with the NPs size was attributed to the presence of adsorbed species at the NPs surface thanks to FTIR and TGA measurements. In addition, the size-dependence of the eg level in the Ce LIII XANES spectra was experimentally observed by HERFD-XANES and confirmed by theoretical calculations.

Lanthanide, CeO2, HEFRD-XANES, Electronic structur↗

Thallium-based scintillators for high-resolution gamma-ray spectroscopy: Ce 3+ - doped Tl 2 LaCl 5 and Tl 2 LaBr 5

In this paper we report on the crystallographic and scintillation properties of Tl 2 LaCl 5 :Ce 3 + and Tl 2 LaBr 5 :Ce 3 + , two novel thallium-containing high-resolution scintillators for gamma-ray spectroscopy. Crystals of Tl 2 LaCl 5 :Ce 3 + and Tl 2 LaBr 5 :Ce 3 + were grown by the Vertical Bridgman method up to 1-inch diameter and 1-inch long. Single crystals of Tl 2 LaCl 5 :Ce 3 + and Tl 2 LaBr 5 :Ce 3 + belong to the orthorhombic system with space group 62 and have a density of 5.16 and 5.98 g/cm 3 , respectively. The scintillators show high light yields of up to 68,000 photons/MeV, excellent gamma-ray energy resolution of ≤ 3% at 662 keV, a fast scintillation decay, and a proportional response over a wide range of energies from 32 keV up to 1275 keV. Density Functional Theory calculations show that the Ce 3 + energy levels are inside the bandgap despite the smaller bandgap of Tl 2 LaCl 5 and Tl 2 LaBr 5 compared to K 2 LaCl 5 and K 2 LaBr 5 . Finally, a systematic Ce 3 + concentration study was performed for Tl 2 LaCl 5 :Ce 3 + and trends observed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Crystal Chemistry and Thermodynamics of HREE (Er, Yb) Mixing in a Xenotime Solid Solution

Rare earth elements (REEs), the 15 naturally occurring lanthanides plus yttrium and scandium, are ubiquitously used in modern life as they are critical components of many advanced devices and technologies. However, the demand for REEs is not equal, with the heavy rare earth elements (HREEs) having a higher demand. Xenotime (HREEPO 4 ) is an important HREE ore mineral and globally is an economical source of HREE. Most of the crystallographic and thermodynamic properties of xenotime endmembers have been elucidated by calorimetric, solubility, and high-pressure studies. Yet, in natural systems, endmembers are rarely encountered, and instead, REE solid solutions are more commonly observed. Here, we characterize the crystal chemistry, thermodynamics of HREE mixing, and high-temperature material behaviors and thermochemistry of a synthetic erbium (Er)-ytterbium (Yb) binary xenotime solid solution (Er (x) Yb (1-x) PO 4 ) using a suite of experimental techniques, including X-ray fluorescence spectroscopy, synchrotron X-ray powder diffraction implemented with Rietveld analysis, Fourier transform infrared spectroscopy coupled with attenuated total reflectance, Raman spectroscopy, thermogravimetric analysis coupled with differential scanning calorimetry, and high-temperature oxide melt drop solution calorimetry. Our results shed light on the formation of natural xenotimes and lay the foundation for their industrial applications as thermal coating materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effect of Plutonium on Uranium Oxide Microstructural Fingerprint

The analysis of particulates from environmental sampling is routinely performed for nuclear forensics applications. In order to increase the tools available for nuclear forensics applications, capability development materials (CDMs), or reference particulates, are necessary for developing and benchmarking new analytical methods. Historically, these CDM particulates have been produced with highly controlled and characterized isotopic and size parameters for applications in developing and benchmarking particle sizers and mass spectrometry analytical methods [1- 4]. However, the development of CDMs with highly characterized particle morphology and phase of the particles is vital for aiding in the development and benchmarking of particle analytical methods for those parameters. In many cases, key properties such as crystallographic phase, morphology, and microstructure, may be correlated to processing history of environmental sampling particulates [5]. To that end, this work investigates determining the structural fingerprint of produced Pu-doped uranium oxide CDMs using transmission electron microscopy (TEM). The particulates, one of which shown in Figure 1, were synthesized to Fig. 1. Single particulate of uranium oxide fabricated using the THESEUS technique. develop capabilities for environmental sampling investigations. These particles are monodisperse at diameter of 1 μm and a range of plutonium concentrations from 0- 1,000 ppm. Given their small diameter, TEM analysis was ideal for studying the particulate structural fingerprint in detail. Previous investigations confirmed the external homogeneity of the particulates at different plutonium concentrations, however this analysis focuses on determining the grain structure, phase distribution, and porosity of the particulates.

Mayer, Jack [Univ. of Florida, Gainesville, FL (Un↗

A First Principles Approach to Spectral Phonon Transport in Heterostructures

Understanding thermal transport across interfaces which give rise to a thermal resistance (also known as Kapitza resistance) is a critical issue affecting the development of nanotechnologies. Much modern and emergent nanotechnology consist of adjacent materials, and phonon mediated heat transfer governs thermal behavior across internal interfaces in these devices. The physics of thermal transport in solids are governed both by phenomena occurring at the atomic scale and interactions with the material's microstructure. The forecasting of fundamental quantities such as temperature, heat flux and thermal conductivity typically employs the semi-classical Boltzmann transport equation to predict the macroscopic behavior of materials in terms of the microscopic dynamics of its heat carriers. Kapitza resistance was first discovered in liquid helium experiments and has led to a fundamental research thrust in micro and nano-scale heat transport, the behavior of thermal carriers across internal interfaces. Thermal interfacial resistance (TIR) is a widely studied phenomenon, first engaged by Swartz and Pohl through their development of the acoustic and diffuse mismatch methods, then continued through myriad efforts with varying methods and approaches in an attempt to resolve carrier behavior at thermal interfaces. Many of the fundamental approaches to TIR have been at the nanoscale, and research is conducted with molecular dynamics (MD) and density functional theory (DFT) methods. The limitations of these methods is system size; atomistic methods tend to be limited to system sizes of 100,000 atoms or less. Larger length-scale methods have also been pursued, based on the principles of acoustic or diffuse mismatch, but not all include simulation of TIR using a full phonon band spectrum, or temperature dependent methods. Our approach to enabling phonon transport in layered materials draws upon our previous work of demonstrating spectrally coupled phonon transport in homogeneous and heterogeneous materials. We use a semi-analytical approach in which the Bose-Einstein (B-E) statistics set the strength of the phonon radiance in a frequency group, but the B-E statistics are informed with information from the transport system. The B-E statistics in a single frequency group feels the influence of all the groups through the spatial temperature. We also include a new field term which is an indicator of the amount of non-equilibrium behavior of the phonon spectrum---this is added to the phonon source term in all groups to ensure closure and conservation of energy, as the phonon groups in the transport system and the analytical systems are coupled. This work builds upon our previous approach by adding a phonon coupling term at an internal interface, using the principles of the DMM through transmission and reflection coefficients. In this work, the coefficients are determined through computing a common temperature at the interface, influenced by the phonon band structure of both materials, in effect, providing mixing between the two material systems and using the common temperature to set the strength of the phonon radiance at the boundaries on either side of the interface. Our approach uses material properties computed along various crystallographic orientations, and while some isotropy is built into the interface condition, the material properties weight the phonon distributions in the proper crystalline direction. Greater resolution of phonon behavior in proximity to an interface, and more accurate predictions of TIR are obtained. While it is true the assumption of diffuse mismatch can yield inconsistent results compared to experiment especially at low temperatures, this work focuses on room temperature and beyond effects, for future applications in nuclear fuel, or thermoelectric devices; a modified mismatch approach may be feasible if applied properly. Additionally, our methods focus on bridging mesoscale to engineering scale

36 MATERIALS SCIENCE↗

Machine Learning for Prediction of Thermodynamic Descriptors

Our objective is to apply machine learning (ML) algorithms for the prediction of molecular catalysis descriptors from geometric properties derived from experimental crystallographic databases. Catalysis is often considered a “low-data” discipline that is poorly suited for ML methods. An exception is the extensive structural information that is available for molecular catalysts through the Cambridge Structural Database (CSD), which contains atomically precise molecular structures from X-ray diffraction analysis for >600K metal complexes. As a proof-of-principle, we targeted the prediction of hydricity, a thermodynamic property that provides understanding and control of catalytic hydride transfer. We built a training set composed of ~100 molecular complexes with a known hydricity and structural information from the CSD. This data set was converted into a machine-readable format using the smooth overlap of atomic positions (SOAP) representation and further labeled with simple electronic descriptors for the metal centers. Multiple different neural networks were trained on this data set, and the accuracy of the hydricity predictions ranged from < 2 kcal/mol to 20 kcal/mol. The accuracy of each model was highly sensitive to which compounds were in the train versus test set, underscoring the challenges associated with small and chemically diverse data sets. Finally, to further augment the data set, we attempted to experimentally measure several new hydricity values, however these experiments were unsuccessful due to undesired chemical reactivity of the selected complexes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Effects of Annealing after Equal Channel Angular Extrusion (ECAE) on Mechanical and Magnetic Properties of 49Fe-49Co-2V Alloy

Equal channel angular extrusion (ECAE) of 49Fe-49Co-2V, also known as Hiperco® 50A or Permendur-2V, greatly improves the strength and ductility of this alloy, while sacrificing soft magnetic performance. In this work, ECAE Hiperco specimens were subjected to post-ECAE annealing in order to improve soft magnetic properties. The microstructure, mechanical properties, and magnetic performance are summarized in this study. Annealing begins above 650°C and a steep decline in yield strength is observed for heat treatments between 700 and 840°C due to grain growth and the Hall-Petch effect, although some strength benefit is still observed in fully annealed ECAE material compared to conventionally processed bar. Soft magnetic properties were assessed through B-H hysteresis curves from which coercivity (Hc) values were extracted. Hc decreases rapidly with annealing above 650°C as well, i.e. improved soft magnetic behavior. The observed trend is attributed to annealing and grain growth in this temperature regime, which facilitates magnetic domain wall movement. The coercivity vs. grain size results generally follow the trend predicted in the literature. The magnetic behavior of annealed ECAE material compares favorably to conventional bar, possibly due to mild crystallographic texturing which enhances properties in the post-ECAE annealed material. Overall, this study highlights a definitive tradeoff between mechanical and magnetic properties brought about by post-ECAE annealing and grain growth.

annealing↗

Determining elastic anisotropy of textured polycrystals using resonant ultrasound spectroscopy

Abstract Polycrystalline materials can have complex anisotropic properties depending on their crystallographic texture and crystal structure. In this study, we use resonant ultrasound spectroscopy (RUS) to nondestructively quantify the elastic anisotropy in extruded aluminum alloy 1100-O, an inherently low-anisotropy material. Further, we show that RUS can be used to indirectly provide a description of the material’s texture, which in the present case is found to be transversely isotropic. By determining the entire elastic tensor, we can identify the level and orientation of the anisotropy originated during extrusion. The relative anisotropy of the compressive (c 11 /c 33 ) and shear (c 44 /c 66 ) elastic constants is 1.5% ± 0.5% and 5.7% ± 0.5%, respectively, where the elastic constants (five independent elastic constants for transversely isotropic) are those associated with the extrusion axis that defines the symmetry of the texture. These results indicate that the texture is expected to have transversely isotropic symmetry. This finding is confirmed by two additional approaches. First, we confirm elastic constants and the degree of elastic anisotropy by direct sound velocity measurements using ultrasonic pulse echo. Second, neutron diffraction (ND) data confirm the symmetry of the bulk texture consistent with extrusion-induced anisotropy, and polycrystal elasticity simulations using the elastic self-consistent model with input from ND textures and aluminum single-crystal elastic constants render similar levels of polycrystal elastic anisotropy to those measured by RUS. We demonstrate the ability of RUS to detect texture-induced anisotropy in inherently low-anisotropy materials. Therefore, as many other common materials have intrinsically higher elastic anisotropy, this technique should be applicable for similar levels of texture, providing an efficient general diagnostic and characterization tool.

36 MATERIALS SCIENCE↗

Quantifying Microstructure Variability in Laser Powder Bed Fusion 316 L Stainless Steel Microstructures with Spatial Statistics

Here, we have explored data-driven methods for material microstructure quantification that improve sensitivity to microstructural changes compared to traditional approaches. The methods integrate multiple microstructural properties, including grain morphology, crystallographic orientation, and material phase information. The simpler method employs maps of the Euclidean distance transformation metric to evaluate the morphology of grain boundary networks. The more intensive approach employs generalized spherical harmonic mapping for crystallographic orientations, per-pixel phase information, and a variational auto-encoder for dimensionality reduction and results in a multidimensional clustering of by microstructure similarity. Applied to an experimental dataset of additively manufactured steel, both methods detected slight variations in samples produced under nominally identical processing conditions. Both methods were able to distinguish between samples from multiple (nominally identical) builds, while the generalized spherical harmonics-based method could additionally cluster data samples rotated at two orientations on the build plate. The improved sensitivity of the methods, demonstrated through comparison with traditional microstructure characterization techniques, offers advantages for microstructure quantification and comparisons in advanced manufacturing applications.

SS316L↗

Boron carbide amorphous solid with tunable band gap

Boron carbide B x C (x = 1/6 – 10) powders were synthesized through a microwave-assisted carbothermic reduction reaction as a potential clean energy material. Their crystallographic structures and optical properties were characterized. X-ray diffraction and electron diffraction indicated that the synthesized B x C powders were amorphous. Electron energy-loss spectroscopy demonstrated that the composition of boron and carbon was in amorphous materials, and their chemical bonding were disclosed from Raman scattering spectroscopy. Here, UV-vis absorption spectroscopy indicated that the bandgap of the bulks varied from 2.30 eV to 3.90 eV, tuned by the boron/carbon element ratio.

36 MATERIALS SCIENCE↗

Spin–Flop and Metamagnetic Transition in Monoclinic Eu 4 Bi 6 Se 13

This study explores an investigation of the crystallographic, electronic, and magnetic properties of the europium-based bismuth selenide compound Eu 4 Bi 6 Se 13 , with particular focus on its magnetic anisotropy. This compound adopts a monoclinic crystal structure classified under the P2 1 /m space group (#11). It exhibits distinctive structural features, including substantial Eu–Se coordination numbers (6 and 8), Bi–Se ladders, and linear chains of Eu atoms that propagate along the b-axis. Electronic resistivity assessments indicate that Eu 4 Bi 6 Se 13 exhibits metallic behavior. As the magnetic field is oriented along the b-axis, magnetic characterization reveals uniaxial magnetic anisotropy, with metamagnetic transitions appearing at approximately 12 kOe and a lower field. In the field below 10 kOe, the spin-flop transition is observed with possible domain-induced hysteresis. This behavior supports the identification of metamagnetic features in field-dependent measurements attributable to the europium spins.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Defect Diffusion Graph Neural Networks for Materials Discovery in High-Temperature Energy Applications

Here, the migration of crystallographic defects dictates material properties and performance for a plethora of technological applications. Density functional theory (DFT)-based nudged elastic band (NEB) calculations are a powerful computational technique for predicting defect migration activation energy barriers, yet they become prohibitively expensive for high-throughput screening of defect diffusivities. Without introducing hand-crafted (i.e., chemistry- or structure-specific) descriptors, we propose a generalized deep learning approach to train surrogate models for NEB energies of vacancy migration by hybridizing graph neural networks with transformer encoders and simply using pristine host structures as input. With sufficient training data, computationally efficient and simultaneous inference of vacancy defect thermodynamics and migration activation energies can be obtained to compute temperature-dependent vacancy diffusivities and to down-select candidates for more thorough DFT analysis or experiments. Thus, as we specifically demonstrate for potential water-splitting materials, candidates with desired defect thermodynamics, kinetics, and host stability properties can be more rapidly targeted from open-source databases of experimentally validated or hypothetical materials.

14 SOLAR ENERGY↗

A-type antiferromagnetic order in semiconducting EuMg 2 Sb 2 single crystals

Eu-based Zintl-phase materials EuA 2 Pn 2 (A = Mg, In, Cd, Zn; Pn = Bi, Sb, As, P) have generated significant recent interest owing to the complex interplay of magnetism and band topology. Here, we investigated the crystallographic, magnetic, and electronic properties of the layered Zintlphase single crystals of EuMg 2 Sb 2 with the trigonal CaAl 2 Si 2 crystal structure (space group $P\bar{3}m1$). Electrical resistivity measurements complemented with angle-resolved photoemission spectroscopy (ARPES) studies and density functional theory (DFT) calculations find an activated behavior with intrinsic conductivity at high temperatures indicating a semiconducting electronic ground state with a narrow energy gap of 370 meV. Magnetic susceptibility and zero-field heat capacity measurements indicate that the compound undergoes antiferromagnetic (AFM) ordering at the Néel temperature T N = 8.0(2) K. Here, zero-field neutron-diffraction measurements reveal that the AFM ordering is A-type where the Eu spins (Eu 2+ , S = 7/2) arranged in ab-plane layers are aligned ferromagnetically in the ab plane and the Eu spins in adjacent layers are aligned antiferromagnetically. Eu-moment reorientation within the ab planes in the trigonal AFM domains associated with a very weak inplane magnetic anisotropy is also evident below T N at low fields < 0.05 T. Although isostructural semimetallic EuMg 2 Bi 2 is reported to host Dirac surface states, the observation of narrow-gap semiconducting behavior in EuMg 2 Sb 2 implies a strong role of spin-orbit coupling (SOC) in tuning the electronic states of these materials. Our DFT studies also suggest, besides the SOC, the more electronegative and smaller Sb than Bi shifts the low-lying conduction bands along the Γ-A direction to higher energy, resulting in an indirect bulk band gap between the Γ and M points for EuMg 2 Sb 2 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Modeling Time-Dependent Surrogates of Additive-Manufactured Nuclear Fuels Processes

Additive manufacturing (AM) technology is being increasingly adopted in a wide variety of application areas for its ability to rapidly produce, prototype, and customize designs. Recently, a hybrid AM technique was successfully developed at Idaho National Laboratory (INL) to manufacture nuclear fuels [1]. Despite the advantages, this AM technique needs optimization due to defects from a highly complex melting and sintering process. The complex metallurgical phenomena during AM processes are strongly related to parameters such as applied laser power, traveling speed, and scan style, which could lead to differences in density, residual stress, crystallographic texture, and mechanical properties. In addition, stochastic variations in laser energy interaction and associated multiscale/multiphysics phenomena cause variations in microstructure evolution and mechanical properties. Currently, researchers at INL are focusing on developing a comprehensive modeling framework, leveraging INL’s simulation tools MOOSE/MARMOT/BISON/RAVEN [2-4] to describe all steps of this AM process across multiple length scales. Although this advanced framework plays a critical role in enabling enhancements to traditional trial and error approaches for design and optimization of nuclear fuel materials, it remains computationally intense, limiting its use in sensitivity and optimization analysis. In this case, an accurate and inexpensive surrogate becomes an effective tool for providing a tractable approximation of the underlying underline physics. Surrogate models generally not based on the physics of a system are purely mathematical models used to capture the relationships between specific system inputs and outputs. Popular approaches, including neural networks [5], response surfaces [6], and subspace-based reduced order models [7], have been applied to a wide range of disciplines, such as nuclear reactor design, aerospace design and automotive design. In this summary, we employ advanced time-dependent surrogate models such as high-dimensional model representation (HDMR) [8] and physics-informed deep neural network (PINNs) [9] to accelerate the design and optimization of AM process.

42 ENGINEERING↗

Developing an experimental-computational framework to investigate the deformation mechanisms and mechanical properties of Al-8Ce-10Mg alloys at micro and macroscales

There is a promising future for the use of aluminum-cerium-magnesium alloys in a broad range of applications, including devices that operate at high temperatures. With cerium currently considered a waste product of rare earth mining validation studies of possible applications are essential to reduce the environmental waste. Here, a computational-experimental framework is developed to investigate the role both the intermetallic and matrix have on the mechanical properties of these alloys. A set of experiments, including SEM/EBSD imaging, nanoindentation, in-situ SEM tensile testing, and in-situ SEM-DIC tests are performed to characterize the microstructure and mechanical properties of these alloys. Furthermore, the elastic, plastic, and failure deformation mechanisms of the microstructure, and their correlation with the bulk scale mechanical properties are investigated. Experimental results are also used to calibrate parameters for a crystal plasticity finite element model, by performing a computational framework that minimizes the error between the computational and experimental results. This model is then utilized to investigate how the area percentage of intermetallics and the crystallographic texture control the mechanical properties of the alloy. Simulation results show that an increase in the percentage of intermetallics increase the strength but decrease the ductility of the alloy. Also, a change in material texture improves strength and reduces damage that leads to material failure. The development of the crystal plasticity model, as discussed in this work, opens opportunities for future investigations of similar aluminum-cerium-magnesium alloys.

36 MATERIALS SCIENCE↗

The anion exchange properties of AFm (hydrocalumite-group) minerals defined from solubility experiments and crystallographic information

Solubility experiments with binary series of OH-, Cl-, SO{sub 4}- and CO{sub 3}-AFm were re-examined with a non-ideal, multicomponent solid solution model. The electrical double layer on the mineral's outer surface, which neutralizes about 5% of the anionic charge, can be included. The choice of the end-members in the solid solution and the reaction formulation can help to eliminate the ‘non-ideality’ for OH-SO{sub 4} and Cl-OH exchange. CO{sub 3}-Cl-OH exchange is not ideal in the solubility experiments, nor can it be, because the mineral volume is not a linear combination of the end-members. The solubilities of the end-members are related to the anion charge and inversely to the anion-layer thickness. OH is part of the anion-charge, even when a pure, other anion form is the target of the synthesis. Pure OH-AFm is unstable and converts into hydrogarnet and portlandite, depending on the precipitation rate of hydrogarnet.

36 MATERIALS SCIENCE↗