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Spinel lithium ferrite magnetic and crystallographic properties, considering effects of Li and oxygen losses, sintering temperature and cooling rate
Effects of lithium and oxygen losses on magnetic and crystallographic properties of spinel lithium ferrite
Polycrystalline MnAsP crystallographic and magnetic properties over temperature range, discussing susceptibility anomaly, magnetic moment, distortion and metamagnetism
In this study, the structure and transport properties of two polymorphs, nanoparticles and nanorods, of the iron(II) triazole [Fe(Htrz) 2 (trz)](BF 4 ) spin crossover complex were compared. Conductive atomic force microscopy was used to map the electrical conductivity of individual nanoparticles and nanorods. The [Fe(Htrz) 2 (trz)](BF 4 ) nanorods showed significantly higher conductivity compared to nanoparticles. This difference in electrical conductivity is partially associated to the different Fe–N bond lengths in each of the polymorphs, with an inverse relationship between Fe–N bond length and conductivity. Transport measurements were done on the nanorods for both high spin (at 380 K) and low spin (at 320 K) states under dark and illuminated conditions. The conductance is highest for the low spin state under dark conditions. In illumination, the conductance change is much diminished.
We investigated and compared optoelectronic properties, crystallographic structures, 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)). Across all these deposition technologies, a similar trend is observed: higher diffusion temperatures yield films that are more crystalline but 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. Firstly, the LPCVD method yields the roughest surface and smallest degree of crystallinity on finished poly-Si films. In contrast, the PECVD method has the smoothest surface for both as-deposited Si and annealed poly-Si films. Secondly, as-deposited sputtered and PECVD Si films contain only an amorphous phase whereas as-deposited LPCVD films has already had some crystalline phase. Thirdly, 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.
Uranium mononitride (UN) is a promising nuclear fuel that combines the advantageous properties of readily used UO 2 and uranium alloys. Various properties of UN have been previously studied using different density functional theory (DFT) methodologies; however, there are still inconsistencies when it comes to the dynamical stability and defect properties of UN. We address these inconsistencies by studying the UN phonons and defect properties using DFT calculations employing two generalized gradient approximation (GGA) exchange-correlation functionals: PBE and AM05, with and without an added on-site Coulomb repulsion term (+U). Furthermore, we investigate the importance of spin-orbit coupling (SOC) when calculating the properties of UN. We use the different methodologies to determine the preference of UN to have antiferromagnetic (AFM) ordering, as seen in experiments, or ferromagnetic (FM) ordering of the uranium spins. We compare the crystallographic properties, density of states, the DFT X-ray photoelectron spectra and phonon dispersions calculated using the different methodologies. We demonstrate that GGA + U reproduces the AFM ordering in UN, but the crystal structure is dynamically unstable. We also show that magnetic ordering is important in finding the lowest energy defective structure, and that SOC has a distinct influence on the energy of the different uranium interstitial defects. Lastly, we discuss the point defect formation energies under U-rich and N-rich conditions, and the stoichiometric formation energies calculated with the different methodologies, providing insight into the observed tendency for forming hypostoichiometric UN.
Uranium mononitride (UN) is a promising nuclear fuel that combines the advantageous properties of readily used UO 2 and uranium alloys, such as high melting temperature and high uranium density, and thermal conductivity, respectively. A better understanding of UN behavior at operating temperatures can be obtained from finite temperature data, such as elastic properties. To get this information, ab initio molecular dynamics (AIMD) simulations were performed at five different temperatures using constant volume (NVT) and constant pressure (NPT) ensembles. Initially, the performance of PBE functional in reproducing experimental crystallographic properties and magnetic ordering is assessed. The finite temperature phonon dispersions are calculated using NVT simulation results, which show a softening of the phonon modes with increasing temperature. The NPT results are used to obtain the thermal expansion of UN and finite temperature electronic properties. The calculated thermal expansion is compared with our measurements using neutron diffraction. Additionally, the temperature dependent elastic properties of UN are evaluated using the strain-stress method in AIMD simulations, indicating that UN becomes softer and more compressible with increasing temperature. Also, the calculated Young’s modulus slope is in very good agreement with the experiment. The finite temperature heat capacity and electronic thermal conductivity are calculated from AIMD simulations, which are in better agreement with the experiment than the heat capacity and thermal conductivity calculated using the structures relaxed at 0K. Finally, the thermal diffusivity from AIMD has opposite temperature dependence compared to experimental results, which we argued comes from the underestimated electronic thermal conductivity.
The nature of hydrocarbons and properties of elemental carbon in circumstellar, interstellar, and interplanetary dust is a long standing problem in astronomy and meteorite research. The textures and crystallographical properties of poorly graphitized carbon (PGC) from carbonaceous chondrites and Chondritic Porous Aggregates (CPAs) are comparable with PGCs formed by dehydrogenation and carbonization of hydrocarbon precursors under natural terrestrial and experimental conditions. A multistage model of hydrocarbon diagenesis in CPA and carbonaceous chondrite (proto-) planetary parent bodies was proposed in which hydrocarbons are subjected to low temperature hydrous pyrolysis. Continued efforts to recognize hydrocarbons and elemental phases in CPAs may allow understanding of the multistage hydrocarbon/elemental carbon model.
Alloying is a common technique to optimize the functional properties of materials for thermoelectrics, photovoltaics, energy storage etc. Designing thermoelectric (TE) alloys is especially challenging because it is a multi-property optimization problem, where the properties that contribute to high TE performance are interdependent. In this work, we develop a computational framework that combines first-principles calculations with alloy and point defect modeling to identify alloy compositions that optimize the electronic, thermal, and defect properties. We apply this framework to design n-type Ba 2(1–x) Sr 2x CdP 2 Zintl thermoelectric alloys. Our predictions of the crystallographic properties such as lattice parameters and site disorder are validated with experiments. To optimize the conduction band electronic structure, we perform band unfolding to sketch the effective band structures of alloys and find a range of compositions that facilitate band convergence and minimize alloy scattering of electrons. Here, we assess the n-type dopability of the alloys by extending the standard approach for computing point defect energetics in ordered structures. Through the application of this framework, we identify an optimal alloy composition range with the desired electronic and thermal transport properties, and n-type dopability. Such a computational framework can also be used to design alloys for other functional applications beyond TE.
Shape memory alloys (SMA) exhibiting the superelastic or one-way effects can produce large recoverable strains upon application of a stress. In single crystals this stress and resulting strain are very orientation dependent. We show experimental stress/strain curves for a Ni-Al single crystal for various loading orientations. Also shown are model predictions; the open and closed circles indicate recoverable strains obtained at various stages in the transformation process. Because of the strong orientation dependence of shape memory properties, crystallographic texture can be expected to play an important role in the mechanical behavior of polycrystalline SMA. It is desirable to formulate a constitutive model to better understand and exploit the unique properties of SMA.
Hematite-rich spherules were discovered embedded in sulfate-rich outcrop rock and as lag deposits of whole and broken spherules by the Opportunity rover at Meridiani Planem [1-6]. The Mars Global Surveyor (MGS) Thermal Emission Spectrometer (TES), which has a wider spectral range compared to the Mars Exploration Rover Mini-TES, provided an important constraint that hematite-rich spherules are dominated by emission along the crystallographic c-axis [7-10]. We have previously synthesized hematite spherules whose mineralogic, chemical, and crystallographic properties are strikingly similar to those for the hematite-rich spherules at Meridiani Planum [11]. The spherules were synthesized in the laboratory along with hydronium jarosite and minor hydronium alunite from Fe-Al-Mg-S-Cl acid sulfate solutions under hydrothermal conditions. The reaction sequence was (1) precipitation of hydronium jarosite, (2) jarosite dissolution and precipitation of hematite spherules, and (3) precipitation of hydronium alunite upon depletion of hydronium jarosite. The spherules exhibit a radial growth texture with the crystallographic c-axis aligned along the radial direction, so that thermal emission spectra have no hematite emissivity minimum at approx.390/cm similar to the emission spectra returned by MGS TES. The objective of this paper is to expand on our initial studies [11] to examine the morphological evolution during growth of spherules starting from sub-micrometer crystals to spherules many orders of magnitude in size.
Ceramics, for the most part, do not have inherently good tribological properties. For example friction coefficients in excess of 0.7 have been reported for silicon nitride sliding on silicon nitride or on bearing steel (ref. 1). High friction is always accompanied by considerable wear. Despite their inherently poor tribological properties, the high strength and high toughness of silicon nitride (Si3N4) ceramics has led to their successful use in tribological applications (refs. 1 to 4). The upper temperature limit for the application of Si3N4 as wear-resistant material is limited by reaction with the tribological environment (ref. 3). Silicon nitride is known to produce a thin silicon dioxide film with easy shear capability that results in low friction and low wear in a moist environment (ref. 5). At elevated temperatures, the removal of the reaction product that acts as lubricant causes the friction coefficient to increase and, consequently, the wear performance to become poor. New materials are sought that will have wear resistance superior to that of Si3N4 at elevated temperatures and in harsh environments. A new class of oxide ceramic materials has been developed with potential for excellent high-temperature wear resistance. The new material consists of a multicomponent oxide with a two-phase microstructure, in which the wear resistance of the mixed oxide is significantly higher than that of the individual constituents. This is attributed to the strong constraining effects provided by the interlocking microstructures at different length scales, to the large aspect ratio of the phases, to the strong interphase bonding, and to the residual stresses. Fretting wear tests were conducted by rubbing the new ceramic material against boron carbide (B4C). The new ceramic material produced a wear track groove on B4C, suggesting significantly higher wear resistance for the oxide ceramic. The new material did not suffer from any microstructural degradation after the wear test. The wear rate of the new ceramic material at 600 C was determined to be on the order of 10-10 mm3/N-m, which is 3 to 5 orders of magnitude lower than that for the current state-of-theart wear-resistant materials (Si3N4and B4C). The friction coefficient of the new ceramic materials is on the order of 0.4, which is significantly lower than that of silicon nitride. This new class of oxide materials has shown considerable potential for applications requiring high wear resistance at high temperatures and in harsh environments. New understanding of the wear behavior of ceramic materials is emerging as a result of the surprisingly high wear resistance of two-phase oxide ceramics. There is excellent potential for further improvements in the wear resistance of oxide ceramics through optimizing the microstructure and altering the crystallographic properties of specific oxide materials as a second phase to reduce the coefficient of friction at elevated temperatures.
Abstract Crystallization by particle attachment (CPA) is a gradual process where each step has its own thermodynamic and kinetic constrains defining a unique pathway of crystal growth. An important example is biomineralization of calcium carbonate through amorphous precursors that are morphed into shapes and textural patterns that cannot be envisioned by the classical monomer‐by‐monomer approach. Here, a mechanistic link between the collective kinetics of mineral deposition and the emergence of crystallographic texture is established. Using the prismatic ultrastructure in bivalve shells as a model, a fundamental leap is made in the ability to analytically describe the evolution of form and texture of biological mineralized tissues and to design the structure and crystallographic properties of synthetic materials formed by CPA.
Mineral replacement reactions are essential solid-fluid interactions in natural and industrial processes including metasomatism, diagenesis, and metamorphism, and sequestration of metal toxins from polluted water. In this paper, we explore the morphological evolution of aragonite and calcite (polymorphs of CaCO 3 ) during their replacement by cerussite (PbCO 3 , an isomorph of aragonite) and otavite (CdCO 3 , an isomorph of calcite) in acidic aqueous solutions (with initial pH 3 to 4). Observations using scanning electron and synchrotron-based transmission X-ray microscopies reveal the formation of pseudomorphic shells (~5 to 10 µm thick) of cerussite and otavite when Pb 2+ is reacted with either calcite or aragonite and when Cd 2+ is reacted with aragonite. The formation of pore space at the substrate-precipitate interface and within the precipitate is found to be key in promoting chemical exchange between the dissolving phase and the solution. In contrast, minimal reactivity is observed when Cd 2+ is reacted with calcite. These results demonstrate that the lack of substrate-precipitate epitaxy (either because of inconsistent symmetries or due to large lattice constant mismatch) is a critical factor that enables replacement of primary CaCO 3 minerals by Pb- or Cd-bearing secondary minerals while the presence of epitaxial relationships inhibit those reactions. When calcite and aragonite coexist, the replacement of aragonite by cerussite and otavite occurs preferentially over calcite. We postulate that the relative reactivity of calcite and aragonite to Pb 2+ and Cd 2+ can be determined by interplay between morphological and crystallographic properties of CaCO 3 materials as well as solution chemistry. Our results demonstrate that coupled dissolution-precipitation processes of carbonate minerals play an important role in controlling mobility and bioavailability of lead and cadmium in environments where acidic metal-contaminated water interacts with carbonate-rich rocks and soils.
Here, in this paper, we demonstrate area-selective crystallization of amorphous Si into tunable crystal orientations enabled by atomic imprint crystallization (AIC), where an amorphous Si layer is crystallized by solid phase epitaxy (SPE) from an externally impressed single-crystalline Si template. Using micro-patterned single-crystalline Si templates, a limited area of an amorphous Si film, where the film surface and patterned template surface are in contact, is crystallized via SPE to create an array of crystallographically aligned dots embedded in amorphous matrix. Combining AIC from the top surface and conventional SPE from the substrate, we demonstrate the fabrication of an array of crystalline dots embedded in single-crystalline matrix with tunable in-plane rotation angle. The results indicate the high tunability of the crystallization process enabled by AIC, allowing precise control of crystallographic properties of thin films with area-selectivity; such capability opens opportunities for the design of new materials for a wide range of applications in materials science.
The approach based on atomic pair distribution function (PDF) has revolutionized structural investigations by X-ray/electron diffraction of nano or quasi-amorphous materials, opening up the possibility of exploring short-range order. However, the ab initio crystal structural solution by the PDF is far from being achieved due to the difficulty in determining the crystallographic properties of the unit cell. A method for estimating the crystal cell parameters directly from a PDF profile is presented, which is composed of two steps: first, the type of crystal cell is inferred using machine-learning approaches applied to the PDF profile; second, the crystal cell parameters are extracted by means of multivariate analysis combined with vector superposition techniques. The procedure has been validated on a large number of PDF profiles calculated from known crystal structures and on a small number of measured PDF profiles. The lattice determination step has been benchmarked by a comprehensive exploration of different classifiers and different input data. The highest performance is obtained using the k -nearest neighbours classifier applied to whole PDF profiles. Descriptors calculated from the PDF profiles by recurrence quantitative analysis produce results that can be interpreted in terms of PDF properties, and the significance of each descriptor in determining the prediction is evaluated. The cell parameter extraction step depends on the cell metric rather than its type. Monometric, dimetric and trimetric cells have top-1 estimates that are correct 40, 20 and 5% of the time, respectively. Promising results were obtained when analysing real nanocrystals, where unit cells close to the true ones are found within the top-1 ranked solution in the case of monometric cells and within the top-6 ranked solutions in the case of dimetric cells, even in the presence of a crystalline impurity with a weight fraction up to 40%.
Open-source release of the AlphaDiffract data generation and training system. Includes only the public Materials Project dataset retrievers.AlphaDiffract is a deep learning framework that achieves state-of-the-art performance in predicting the crystal system, space group, and lattice parameters directly from PXRD patterns. AlphaDiffract utilizes a 1D adaptation of the ConvNeXt architecture, a modern convolutional neural network that integrates key design principles from transformers, coupledwith dedicated prediction heads for each crystallographic property.