Detailed total scattering analysis of disorder in ZIF-8

This work investigates the X-ray scattering signatures of disorder in the zeolitic imidazolate framework ZIF-8. Two layer disorder models are examined in reciprocal space and compared with conventional Rietveld analysis. Stacking faults along the [001] direction of the cubic lattice are in poor agreement with experimental powder diffraction data, consistent with previously reported density functional theory studies showing that these defects are energetically unfavorable compared with amorphization. Meanwhile, fluctuation of layer position along the [110] direction of the cubic lattice shows a significant agreement with experimental data. This result is interpreted analogously to an anisotropic strain mechanism, suggesting links between elastic anisotropy and crystallographic imperfections found in metal–organic framework materials. In direct space, it is demonstrated that models accounting for the static position disorder amongst the linker and metal sublattices are required to fit the experimental pair distribution function data.

A real-space approach to the analysis of stacking faults in close-packed metals: G(r) modelling and Q-space feedback

An R-space approach to the simulation and fitting of a structural model to the experimental pair distribution function is described, to investigate the structural disorder (distance distribution and stacking faults) in close-packed metals. This is carried out by transferring the Debye function analysis into R space and simulating the low-angle and high-angle truncation for the evaluation of the relevant Fourier transform. The strengths and weaknesses of the R-space approach with respect to the usual Q-space approach are discussed.

Cluster-mining: an approach for determining core structures of metallic nanoparticles from atomic pair distribution function data

A novel approach for finding and evaluating structural models of small metallic nanoparticles is presented. Rather than fitting a single model with many degrees of freedom, libraries of clusters from multiple structural motifs are built algorithmically and individually refined against experimental pair distribution functions. Each cluster fit is highly constrained. The approach, called cluster-mining, returns all candidate structure models that are consistent with the data as measured by a goodness of fit. It is highly automated, easy to use, and yields models that are more physically realistic and result in better agreement to the data than models based on cubic close-packed crystallographic cores, often reported in the literature for metallic nanoparticles.

Analysis of stacking disorder in ice I using pair distribution functions

Stacking-disordered materials display crystalline order in two dimensions but are disordered along the direction in which layered structural motifs are stacked. Countless examples of stacking disorder exist, ranging from close-packed metals, ice I and diamond to open-framework materials and small-molecule pharmaceuticals. In general, the presence of stacking disorder can have profound consequences for the physical and chemical properties of a material. Traditional analyses of powder diffraction data are often complicated by the presence of memory effects in the stacking sequences. Here it is shown that experimental pair distribution functions of stacking-disordered ice I can be used to determine local information on the fractions of cubic and hexagonal stacking. Ice is a particularly challenging material in this respect, since both the stacking disorder and the orientational disorder of the water molecules need to be described. Memory effects are found to contribute very little to the pair distribution functions, and consequently, the analysis of pair distribution functions is the method of choice for characterizing stacking-disordered samples with complicated and high-order memory effects. In the context of this work, the limitations of current structure-reconstruction approaches are also discussed.

Effective interaction potential of dust particles in a plasma from experimental pair correlation functions

Interaction between dust particles in a plasma is investigated on the basis of experimental pair correlation functions of dust formation in a dc glow discharge and the Poisson equation. It is shown that the calculated effective potentials have an oscillating character and depend rather weakly on macroscopic parameters of the plasma. Existence of an attractive component in the interaction of dust particles is confirmed within the validity range of our model.

Testing the correspondence between map positions of quantitative trait loci

There are several instances in which quantitative trait locus (QTL) mapping experiments have been independently carried out for similar traits in different laboratories. We develop a permutation test of the correspondence between the test statistics obtained from genome-wide QTL scans in two such experiments to test whether the same QTLs are segregating in the experimental pair. In simulations, we show that the permutation test has the desired properties if chromosomes are of equal length, but bias can occur if chromosomes are of unequal length, a problem connected with autocorrelation of test statistic values. We apply the test to data from three recent mouse body weight QTL mapping experiments. The results from the test are non-significant, and imply a lack of overall concordance between the QTLs that were segregating in these experiments.

Effective Pair Potentials and Structure of Water

Classical Monte Carlo calculations have been performed in order to investigate the ability of the TIP4P, SPC, and SPCE water models to reproduce the structural features of liquid water. The simulations were carried out in the NPT ensemble at 4 thermodynamic conditions. The results are compared with recent neutron diffraction data. Essentially, the three models capture equally well the thermodynamic and structural features of water. Although they were parametrized to reproduce the water properties at ambient conditions, the agreement with the experimental pair correlation functions was even better at super-critical conditions. This is because the effective pair potentials have some difficulty to re-produce cooperative interactions, like hydrogen bonds. These interactions are less effective at super-critical conditions, where the liquid behaves roughly like a gas