Determination of symmetries and idealized cell parameters for simulated structures

Hundt, R.; Hannemann, A.; Jansen, Martin

doi:10.1107/s0021889898015763

Cited by 191 publications

(115 citation statements)

References 9 publications

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“…Furthermore the symmetries and space groups of the configurations are determined using the algorithms SFND (Symmetry FiNDer) [26] and RGS (Raum Gruppen Suchen = Space group search) [27], and the CMPZ (CoMPare Zelle = Compare cells) algorithm is used to eliminate duplicate structures [28]. We note that these symmetries allow us to propose possible transformation paths among different modifications, just as the principal coordinates hint at paths for transitions in large molecules.…”

Section: Methodsmentioning

confidence: 99%

Structure Prediction for PbS and ZnO at Different Pressures and Visualization of the Energy Landscapes

et al. 2011

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An important issue in modern solid state chemistry is the development of a general methodology to predict the possible (meta)-stable modifications of a solid. This requires the global exploration of the energy landscape of the chemical system, since each stable phase corresponds to a locally ergodic region of the landscape. The global search in the lead sulfide system has been performed with simulated annealing on the ab initio level, while zinc oxide was studied with an empirical potential using simulated annealing, both at standard and elevated pressure (up to 100 GPa). The local optimization of the modifications found in the PbS system was performed using various density functionals. Next, the energy E(V ) and enthalpy H(p) as function of volume and pressure, respectively, were computed for these modifications and their electronic structure was analyzed. The structures found for ZnO were locally optimized on ab initio level (DFT and Hartree-Fock). In both systems the structures found were in good agreement with the experiment. Furthermore, we employed the threshold algorithm to explore the barrier structure of the landscape of ZnO as function of the number of formula units in the simulation cell. Based on the barrier and minima information 2-D models of the energy landscape were constructed.

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Section: Methodsmentioning

confidence: 99%

Structure Prediction for PbS and ZnO at Different Pressures and Visualization of the Energy Landscapes

et al. 2011

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“…We tested our implementation with the materials (NaCl, La 2 O 3 , Cu 3 Au, PtS, Al 3 Ti, Mg, CoSn, αHg, and TlF) whose crystal parameters are obtained from [26], as well as MgF 2 and Ca 3 SiBr 2 structures [5,9,10]. Both ideal and noisy data for these materials are analysed.…”

Section: Experimental Results and Performance Analysismentioning

confidence: 99%

“…However, due to the limitations of the simulation, the primitive cells identified are always triclinic and exhibits no symmetry elements. Hundt et al [10] describe an algorithm to overcome the these limitations by employing some tolerance parameters, which are implemented in the program KPLOT.…”

Section: Introductionmentioning

confidence: 99%

Pattern information extraction from crystal structures

Okuyan¹,

Güdükbay²,

Gülseren³

2007

Computer Physics Communications

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Determining the crystal structure parameters of a material is an important issue in crystallography and material science. Knowing the crystal structure parameters helps in understanding the physical behavior of material. It can be difficult to obtain crystal parameters for complex structures, particularly those materials that show local symmetry as well as global symmetry. This work provides a tool that extracts crystal parameters such as primitive vectors, basis vectors and space groups from the atomic coordinates of crystal structures. A visualization tool for examining crystals is also provided. Accordingly, this work could help crystallographers, chemists and material scientists to analyze crystal structures efficiently.

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“…The general concept behind our approach is partly inspired by our algorithm for the comparison of two periodic structures, CMPZ (Hundt et al, 2006). We have to find a special inhomogeneous orthogonal transformation T, i.e.…”

Section: General Proceduresmentioning

confidence: 99%

“…As a simple illustrative example, we consider the structural relationship of the perovskite structure of CaTiO 3 and the structure of ReO 3 [note that this system had already been analyzed with an earlier version of UFRA (Hundt et al, 2006); we present it again for pedagogical reasons]. The structural data for CaTiO 3 and ReO 3 are taken from the ICSD (Bergerhoff et al, 1983;ICSD-FIZ-Karlsruhe, 2005) (Nos.…”

Section: Example 2: Presence Of a Polyhedron Inside A Large Clustermentioning

confidence: 99%

CCL: an algorithm for the efficient comparison of clusters

et al. 2013

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The systematic comparison of the atomic structure of solids and clusters has become an important task in crystallography, chemistry, physics and materials science, in particular in the context of structure prediction and structure determination of nanomaterials. In this work, an efficient and robust algorithm for the comparison of cluster structures is presented, which is based on the mapping of the point patterns of the two clusters onto each other. This algorithm has been implemented as the module CCL in the structure visualization and analysis program KPLOT.

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Determination of symmetries and idealized cell parameters for simulated structures

Cited by 191 publications

References 9 publications

Structure Prediction for PbS and ZnO at Different Pressures and Visualization of the Energy Landscapes

Structure Prediction for PbS and ZnO at Different Pressures and Visualization of the Energy Landscapes

Pattern information extraction from crystal structures

CCL: an algorithm for the efficient comparison of clusters

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