CalcOPP: a program for the calculation of one-particle potentials (OPPs)

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Dennis Wiedemann
Keyword(s):  
Maximum Entropy Method ◽  
Three Dimensional ◽  
Entropy Method ◽  
Probability Density Functions ◽  
Free Form ◽  
Density Functions ◽  
Command Line Interface ◽  
Ion Migration ◽  
Density Maps ◽  
Microsoft Windows

Abstract In recent years, one-particle potentials (OPPs) derived from neutron-diffraction data have become a popular means to estimate activation energies of ion migration in solids. Computer programs for their calculation, however, have mostly been private in-house solutions. The software CalcOPP presented herein permits calculating two- or three-dimensional OPPs either from probability density functions put out by the crystallographic suite Jana2006/ Jana2020 (including error maps) or from scattering-density maps reconstructed using the maximum entropy method (MEM) implementation Dysnomia. The title program is open-source, written in modern free-form Fortran and Python 3, and available free of charge under the permissive MIT License. Executables are published for 64-bit Microsoft Windows and Linux platforms and can be controlled via an intuitive graphical user interface or via command-line interface. Depending on the kind of input, CalcOPP’s output is readily visualized with standard crystallographic software or plotting applications. The release of the program not only makes the rather powerful OPP method more transparent, but it also opens it up to a broader, less programming-oriented public.

scholarly journals Joint Delay Doppler Probability Density Functions for Air-to-Air Channels

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Michael Walter ◽  
Dmitriy Shutin ◽  
Uwe-Carsten Fiebig
Keyword(s):  
Probability Density ◽  
Channel Model ◽  
Three Dimensional ◽  
Doppler Frequency ◽  
Probability Density Functions ◽  
Density Functions ◽  
Wide Sense ◽  
Channel Measurements ◽  
Vector Calculus ◽  
Air Channels

Recent channel measurements indicate that the wide sense stationary uncorrelated scattering assumption is not valid for air-to-air channels. Therefore, purely stochastic channel models cannot be used. In order to cope with the nonstationarity a geometric component is included. In this paper we extend a previously presented two-dimensional geometric stochastic model originally developed for vehicle-to-vehicle communication to a three-dimensional air-to-air channel model. Novel joint time-variant delay Doppler probability density functions are presented. The probability density functions are derived by using vector calculus and parametric equations of the delay ellipses. This allows us to obtain closed form mathematical expressions for the probability density functions, which can then be calculated for any delay and Doppler frequency at arbitrary times numerically.

Electron densities by the maximum entropy method (MEM) for various types of prior densities: a case study on three amino acids and a tripeptide

2013 ◽  
Vol 69 (2) ◽  
pp. 203-213 ◽  
Author(s):  
Siriyara Jagannatha Prathapa ◽  
Swastik Mondal ◽  
Sander van Smaalen
Keyword(s):  
Maximum Entropy ◽  
Dynamic Model ◽  
Maximum Entropy Method ◽  
Entropy Method ◽  
Topological Descriptors ◽  
Acta Cryst ◽  
Density Maps ◽  
Large Spread ◽  
Better Than

Dynamic model densities according to Mondalet al.[(2012),Acta Cryst.A68, 568–581] are presented for independent atom models (IAM), IAMs after high-order refinements (IAM-HO), invariom (INV) models and multipole (MP) models of α-glycine, DL-serine, L-alanine and Ala–Tyr–Ala atT≃ 20 K. Each dynamic model density is used as prior in the calculation of electron density according to the maximum entropy method (MEM). We show that at the bond-critical points (BCPs) of covalent C—C and C—N bonds the IAM-HO and INV priors produce reliable MEM density maps, including reliable values for the density and its Laplacian. The agreement between these MEM density maps and dynamic MP density maps is less good for polar C—O bonds, which is explained by the large spread of values of topological descriptors of C—O bonds in static MP densities. The density and Laplacian at BCPs of hydrogen bonds have similar values in MEM density maps obtained with all four kinds of prior densities. This feature is related to the smaller spatial variation of the densities in these regions, as expressed by small magnitudes of the Laplacians and the densities. It is concluded that the use of the IAM-HO prior instead of the IAM prior leads to improved MEM density maps. This observation shows interesting parallels to MP refinements, where the use of the IAM-HO as an initial model is the accepted procedure for solving MP parameters. A deconvolution of thermal motion and static density that is better than the deconvolution of the IAM appears to be necessary in order to arrive at the best MP models as well as at the best MEM densities.

Syntheses and crystal structures of Li(Ta0.89Ti0.11)O2.945 and (Li0.977Eu0.023)(Ta0.89Ti0.11)O2.968

2013 ◽  
Vol 28 (3) ◽  
pp. 178-183 ◽  
Author(s):  
Tomohiro Uchida ◽  
Shiho Suehiro ◽  
Toru Asaka ◽  
Hiromi Nakano ◽  
Koichiro Fukuda
Keyword(s):  
Crystal Structures ◽  
Maximum Entropy Method ◽  
Rietveld Method ◽  
Three Dimensional ◽  
Structural Models ◽  
Entropy Method ◽  
Density Distributions ◽  
Cell Dimensions ◽  
Conventional Structure ◽  
Unit Cell Dimensions

Crystal structures of Li(Ta0.89Ti0.11)O2.945 and (Li0.977Eu0.023)(Ta0.89Ti0.11)O2.968 were investigated by laboratory X-ray powder diffraction. Both title compounds were trigonal with space group R3c and Z = 6. The hexagonal unit-cell dimensions were a = 0.514 82 9(2) nm, c = 1.377 61 2(4) nm, and V = 0.316 21 6(2) nm3 for the former compound and a = 0.517 71 2(2) nm, c = 1.373 50 0(6) nm, and V = 0.318 81 2(3) nm3 for the latter. The initial structural models, being isostructural with LiTaO3, were refined by the Rietveld method. The maximum-entropy method-based pattern fitting (MPF) method was subsequently used to confirm the validity of the structural models, in which conventional structure bias caused by assuming intensity partitioning was minimized. Atomic arrangements of the final structural models were in excellent agreement with the three-dimensional electron-density distributions determined by MPF.

Transient electron density maps from femtosecond x-ray powder diffraction

2014 ◽  
Vol 70 (a1) ◽  
pp. C100-C100
Author(s):  
Vincent Juvé ◽  
Flavio Zamponi ◽  
Marcel Holtz ◽  
Michael Woerner ◽  
Thomas Elsaesser
Keyword(s):  
Charge Transfer ◽  
Electron Density ◽  
Powder Diffraction ◽  
Maximum Entropy Method ◽  
Entropy Method ◽  
X Rays ◽  
X Ray ◽  
Density Maps ◽  
Structure Factors ◽  
Diffraction Angle

Ultrashort hard x-ray pulses are sensitive probes of structural dynamics on the picometer length and femtosecond time scales of electronic and atomic motions. Using short hard x-ray pulses as probe in a pump-probe scheme allow to do femtosecond x-ray diffraction experiments [1], which provide transient electron density maps at a femtosecond timescale with a sub-angstrom spatial resolution. In a typical femtosecond x-ray powder diffraction experiment many Debye-Scherrer rings, up to a maximum diffraction angle 2θmax, are recorded for each time delay between the optical pump and the hard x-ray probe. From the diffraction pattern, the change of the diffracted intensity of each rings are monitored. The interference of diffracted x-rays from the many unexcited cells, with known structure factors coming from steady-state measurement, and diffracted x-rays from the few excited cells allows for the detection of the transients structure factors. Problems could arise if the 3D-Fourier transform is directly used because of the abrupt end of the collected information in the reciprocal space (maximum diffraction angle 2θmax). In order to overcome this problem, the Maximum Entropy Method is apply to the data and the transient electron density maps are derived. We apply the femtosecond x-ray powder diffraction technique and the Maximum Entropy Method to study the induced transient polarization by high optical fields on ionic crystals. Such polarizations are connected to a spatial redistribution of electronic charge, which corresponds to a charge transfer between the two ionic compounds [2]. While the charge transfer originates from the anion to the cation in the LiBH and the NaBH4, the LiH exhibits a peculiar behavior: the charge transfer occurs from the cation to the anion. As result from comparison with calculations in the COHSEX framework, this behavior is due to the strong electronic correlations in the LiH [3].

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