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Register a new userChemical short range order obtained from the atomic pair distribution function
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Authors
Th. Proffen
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Many crystalline materials show chemical short range order and relaxation of neighboring atoms. Local structural information can be obtained by analyzing the atomic pair distribution function (PDF) obtained from powder diffraction data. In this paper, we present the successful extraction of chemical short range order parameters from the x-ray PDF of a quenched Cu_3Au sample.
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The paper describes an extension of the Liga algorithm for structure solution from atomic pair distribution function (PDF), to handle periodic crystal structures with multiple elements in the unit cell. The procedure is performed in 2 separate steps - at first the Liga algorithm is used to find unit cell sites consistent with pair distances extracted from the experimental PDF. In the second step the assignment of atom species over cell sites is solved by minimizing the overlap of their empirical atomic radii. The procedure has been demonstrated on synchrotron x-ray PDF data from 16 test samples. The structure solution was successful for 14 samples including cases with enlarged super cells. The algorithm success rate and the reasons for failed cases are discussed together with enhancements that should improve its convergence and usability.
Group IV alloys have been long viewed as homogeneous random solid solutions since they were first perceived as Si-compatible, direct-band-gap semiconductors 30 years ago. Such a perception underlies the understanding, interpretation and prediction of alloys properties. However, as the race to create scalable and tunable device materials enters a composition domain far beyond alloys equilibrium solubility, a fundamental question emerges as to how random these alloys truly are. Here we show, by combining statistical sampling and large-scale ab initio calculations, that GeSn alloy, a promising group IV alloy for mid-infrared technology, exhibits a clear, short-range order for solute atoms within its entire composition range. Such short-range order is further found to substantially affect the electronic properties of GeSn. We demonstrate the proper inclusion of this short-range order through canonical sampling can lead to a significant improvement over previous predictions on alloys band gaps, by showing an excellent agreement with experiments within the entire studied composition range. Our finding thus not only calls for an important revision of current structural model for group IV alloy, but also suggests short-range order may generically exist in different types of alloys.
Neutron and x-ray total scattering measurements have been performed on powder samples of the iron chalcogenide superconductor FeSe. Using pair distribution function (PDF) analysis of the total scattering data to investigate short-range atomic correlations, we establish the existence of an instantaneous, local orthorhombic structural distortion attributable to nematic fluctuations that persists well into the high-temperature tetragonal phase, at least up to 300 K and likely to significantly higher temperatures. This short-range orthorhombic distortion is correlated over a length scale of about 1 nm at 300 K and grows to several nm as the temperature is lowered toward the long-range structural transition temperature. In the low-temperature nematic state, the local instantaneous structure exhibits an enhanced orthorhombic distortion relative to the average structure with a typical relaxation length of 3 nm. The quantitative characterization of these orthorhombic fluctuations sheds light on nematicity in this canonical iron-based superconductor.
We present a detailed study of the mechanism by which the INVERT method [Phys. Rev. Lett. 104, 125501] guides structure refinement of disordered materials. We present a number of different possible implementations of the central algorithm and explore the question of algorithm weighting. Our analysis includes quantification of the relative contributions of variance and fit-to-data terms during structure refinement, which leads us to study the roles of density fluctuations and configurational jamming in the RMC fitting process. We present a parametric study of the pair distribution function solution space for C60, a-Si and a-SiO2, which serves to highlight the difficulties faced in developing a transferable weighting scheme.
A new approach is presented to obtain candidate structures from atomic pair distribution function (PDF) data in a highly automated way. It fetches, from web-based structural databases, all the structures meeting the experimenters search criteria and performs structure refinements on them without human intervention. It supports both x-ray and neutron PDFs. Tests on various material systems show the effectiveness and robustness of the algorithm in finding the correct atomic crystal structure. It works on crystalline and nanocrystalline materials including complex oxide nanoparticles and nanowires, low-symmetry and locally distorted structures, and complicated doped and magnetic materials. This approach could greatly reduce the traditional structure searching work and enable the possibility of high-throughput real-time auto analysis PDF experiments in the future.
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