scholarly journals Experimental charge density studies: Discard valid data and overfit?

2014 ◽  
Vol 70 (a1) ◽  
pp. C282-C282 ◽  
Author(s):  
Regine Herbst-Irmer
Keyword(s):  
Charge Density ◽  
Data Sets ◽  
Resolution Limit ◽  
Quality Of Data ◽  
Refinement Method ◽  
Scaling Methods ◽  
First Results ◽  
Refinement Process ◽  
Refinement Strategy ◽  
Experimental Charge Density

In experimental charge density investigation it is indispensable to use the highest possible quality of data. Therefore the multiplicity should be as high as possible, but poor data should be omitted. To decide about resolution limit and discarding outlier data often limits for Rint or I/σ(I) are used. A better approach is the `paired refinement method' [1] comparing two data sets by the fit of the models derived by the same refinement protocol to both data sets. For macromolecular data sets it could be shown that a higher resolution should be used than normally derived from the above mentioned criteria. First results for charge density data seem to show the same tendency but of course on a different level. The paired refinement strategy can also be used to investigate the influence of different scaling methods. In a recent version of SADABS [2] a new error model and a 3λ correction is implemented. With the paired refinement strategy the improvement in data quality gets obvious. A further concern in charge density investigation is the question of overfitting. In macromolecular refinement this is answered by the Rfree concept [3]. Here a refinement protocol is developed by refining against a work set of reflections, e.g. 90 % of the data. The remaining reflections are untouched in the whole refinement process but an Rfree value is calculated using only this test set of reflections. An overfitting can clearly be identified by a decrease in Rwork but an increase in Rfree. This refinement protocol is then used for a final refinement against all data. It will be discussed how this method could support charge density studies.

Charge Density of L-Alanyl-glycyl-L-alanine Based on X-Ray Data Collection Periods from 4 to 130 Hours

2007 ◽  
Vol 62 (5) ◽  
pp. 696-704 ◽  
Author(s):  
Diana Förster ◽  
Armin Wagner ◽  
Christian B. Hübschle ◽  
Carsten Paulmann ◽  
Peter Luger
Keyword(s):  
Synchrotron Radiation ◽  
Low Temperature ◽  
Charge Density ◽  
Data Sets ◽  
Data Set ◽  
X Ray ◽  
Atomic Properties ◽  
Multipole Refinement ◽  
Refinement Strategy ◽  
Experimental Charge Density

Abstract The charge density of the tripeptide L-alanyl-glycyl-L-alanine was determined from three X-ray data sets measured at different experimental setups and under different conditions. Two of the data sets were measured with synchrotron radiation (beamline F1 of Hasylab/DESY, Germany and beamline X10SA of SLS, Paul-Scherer-Institute, Switzerland) at temperatures around 100 K while a third data set was measured under home laboratory conditions (MoKα radiation) at a low temperature of 20 K. The multipole refinement strategy to derive the experimental charge density was the same in all cases, so that the obtained charge density properties could directly be compared. While the general analysis of the three data sets suggested a small preference for one of the synchrotron data sets (Hasylab F1), a comparison of topological and atomic properties gave in no case an indication for a preference of any of the three data sets. It follows that even the 4 h data set measured at the SLS performed equally well compared to the data sets of substantially longer exposure time.

scholarly journals Validation of experimental charge-density refinement strategies: when do we overfit?

IUCrJ ◽  
2017 ◽  
Vol 4 (4) ◽  
pp. 420-430 ◽  
Author(s):  
Lennard Krause ◽  
Benedikt Niepötter ◽  
Christian J. Schürmann ◽  
Dietmar Stalke ◽  
Regine Herbst-Irmer
Keyword(s):  
Standard Deviation ◽  
Charge Density ◽  
Cross Validation ◽  
Data Sets ◽  
Topological Parameters ◽  
Visualization Tools ◽  
Multipole Refinement ◽  
The Given ◽  
Experimental Charge Density ◽  
Parameter Distributions

A cross-validation method is supplied to judge between various strategies in multipole refinement procedures. Its application enables straightforward detection of whether the refinement of additional parameters leads to an improvement in the model or an overfitting of the given data. For all tested data sets it was possible to prove that the multipole parameters of atoms in comparable chemical environments should be constrained to be identical. In an automated approach, this method additionally delivers parameter distributions ofkdifferent refinements. These distributions can be used for further error diagnostics,e.g.to detect erroneously defined parameters or incorrectly determined reflections. Visualization tools show the variation in the parameters. These different refinements also provide rough estimates for the standard deviation of topological parameters.

Revisiting the charge density analysis of 2,5-dichloro-1,4-benzoquinone at 20 K

2017 ◽  
Vol 73 (4) ◽  
pp. 654-659 ◽  
Author(s):  
Zhijie Chua ◽  
Bartosz Zarychta ◽  
Christopher G. Gianopoulos ◽  
Vladimir V. Zhurov ◽  
A. Alan Pinkerton
Keyword(s):  
Charge Density ◽  
Electron Density ◽  
Topological Analysis ◽  
Diffraction Measurement ◽  
X Ray Diffraction ◽  
Total Electron Density ◽  
Total Electron ◽  
Structure Factors ◽  
Density Analysis ◽  
Experimental Charge Density

A high-resolution X-ray diffraction measurement of 2,5-dichloro-1,4-benzoquinone (DCBQ) at 20 K was carried out. The experimental charge density was modeled using the Hansen–Coppens multipolar expansion and the topology of the electron density was analyzed in terms of the quantum theory of atoms in molecules (QTAIM). Two different multipole models, predominantly differentiated by the treatment of the chlorine atom, were obtained. The experimental results have been compared to theoretical results in the form of a multipolar refinement against theoretical structure factors and through direct topological analysis of the electron density obtained from the optimized periodic wavefunction. The similarity of the properties of the total electron density in all cases demonstrates the robustness of the Hansen–Coppens formalism. All intra- and intermolecular interactions have been characterized.

Characterization of the B⋯π-system interaction via topology of the experimental charge density distribution in the crystal of 3-chloro-7α-phenyl-3-borabicyclo[3.3.1]nonane

2004 ◽  
Vol 384 (1-3) ◽  
pp. 40-44 ◽  
Author(s):  
Konstatin A Lyssenko ◽  
Mikhail Yu Antipin ◽  
Mikhail E Gurskii ◽  
Yurii N Bubnov ◽  
Anna L Karionova ◽  
...  
Keyword(s):  
Density Distribution ◽  
Charge Density ◽  
Charge Density Distribution ◽  
Experimental Charge Density

Experimental Charge Density Study of a Silylone

2014 ◽  
Vol 53 (10) ◽  
pp. 2766-2770 ◽  
Author(s):  
Benedikt Niepötter ◽  
Regine Herbst-Irmer ◽  
Daniel Kratzert ◽  
Prinson P. Samuel ◽  
Kartik Chandra Mondal ◽  
...  
Keyword(s):  
Charge Density ◽  
Density Study ◽  
Experimental Charge Density

Experimental charge-density analysis towards predictive materials science

2021 ◽  
Vol 4 (03) ◽  
pp. 50-71
Author(s):  
Leonardo Dos Santos ◽  
Bernardo L. Rodrigues ◽  
Camila B. Pinto
Keyword(s):  
Physical Properties ◽  
Charge Density ◽  
Materials Science ◽  
New Materials ◽  
Wide Applicability ◽  
Density Analysis ◽  
Properties Of Materials ◽  
A Charge ◽  
Experimental Charge Density

The ongoing increase in the number of experimental charge-density studies can be related to both the technological advancements and the wide applicability of the method. Regarding materials science, the understanding of bonding features and their relation to the physical properties of materials can not only provide means to optimize such properties, but also to predict and design new materials with the desired ones. In this tutorial, we describe the steps for a charge-density analysis, emphasizing the most relevant features and briefly discussing the applications of the method.

Experimental charge density distribution and its correlation to structural and optical properties of Sm 3+ doped Nd 2 O 3 nanophosphors

2017 ◽  
Vol 35 (11) ◽  
pp. 1102-1114 ◽  
Author(s):  
Morris Marieli Antoinette ◽  
S. Israel ◽  
G. Sathya ◽  
Arlin Jose Amali ◽  
John L. Berchmans ◽  
...  
Keyword(s):  
Optical Properties ◽  
Density Distribution ◽  
Charge Density ◽  
Structural And Optical Properties ◽  
Charge Density Distribution ◽  
Experimental Charge Density
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