In situ dehydration behavior of zeolite-like cavansite: A single-crystal X-ray study

To track dehydration behavior of cavansite, Ca(VO)(Si4O10)·4H2O space group Pnma, a = 9.6329(2), b = 13.6606(2), c = 9.7949(2) Å, V = 1288.92(4) Å3 single-crystal X-ray diffraction data on a crystal from Wagholi quarry, Poona district (India) were collected up to 400 °C in steps of 25 °C up to 250 °C and in steps of 50 °C between 250 and 400 °C. The structure of cavansite is characterized by layers of silicate tetrahedra connected by V4+O5 square pyramids. This way a porous framework structure is formed with Ca and H2O as extraframework occupants. At room temperature, the hydrogen bond system was analyzed. Ca is eightfold coordinated by four bonds to O of the framework structure and four bonds to H2O molecules. H2O linked to Ca is hydrogen bonded to the framework and also to adjacent H2O molecules. The dehydration in cavansite proceeds in four steps.At 75 °C, H2O at O9 was completely expelled leading to 3 H2O pfu with only minor impact on framework distortion and contraction V = 1282.73(3) Å3. The Ca coordination declined from originally eightfold to sevenfold and H2O at O7 displayed positional disorder.At 175 °C, the split O7 sites approached the former O9 position. In addition, the sum of the three split positions O7, O7a, and O7b decreased to 50% occupancy yielding 2 H2O pfu accompanied by a strong decrease in volume V = 1206.89(8) Å3. The Ca coordination was further reduced from sevenfold to sixfold.At 350 °C, H2O at O8 was released leading to a formula with 1 H2O pfu causing additional structural contraction (V = 1156(11) Å3). At this temperature, Ca adopted fivefold coordination and O7 rearranged to disordered positions closer to the original O9 H2O site.At 400 °C, cavansite lost crystallinity but the VO2+ characteristic blue color was preserved. Stepwise removal of water is discussed on the basis of literature data reporting differential thermal analyses, differential thermo-gravimetry experiments and temperature dependent IR spectra in the range of OH stretching vibrations.

The macromolecular complex of ICP and falcipain-2 from Plasmodium: preparation, crystallization and preliminary X-ray diffraction analysis

The malaria parasite Plasmodium depends on the tight control of cysteine-protease activity throughout its life cycle. Recently, the characterization of a new class of potent inhibitors of cysteine proteases (ICPs) secreted by Plasmodium has been reported. Here, the recombinant production, purification and crystallization of the inhibitory C-terminal domain of ICP from P. berghei in complex with the P. falciparum haemoglobinase falcipain-2 is described. The 1:1 complex was crystallized in space group P4(3), with unit-cell parameters a = b = 71.15, c = 120.09 A. A complete diffraction data set was collected to a resolution of 2.6 A.

Quantitative 3D strain analysis in analogue experiments: Integration of X-ray computed tomography and digital volume correlation techniques

The combination of scaled analogue experiments, material mechanics, X-ray computed tomography (XRCT) and Digital Volume Correlation techniques (DVC) is a powerful new tool not only to examine the 3 dimensional structure and kinematic evolution of complex deformation structures in scaled analogue experiments, but also to fully quantify their spatial strain distribution and complete strain history. Digital image correlation (DIC) is an important advance in quantitative physical modelling and helps to understand non-linear deformation processes. Optical non-intrusive (DIC) techniques enable the quantification of localised and distributed deformation in analogue experiments based either on images taken through transparent sidewalls (2D DIC) or on surface views (3D DIC). X-ray computed tomography (XRCT) analysis permits the non-destructive visualisation of the internal structure and kinematic evolution of scaled analogue experiments simulating tectonic evolution of complex geological structures. The combination of XRCT sectional image data of analogue experiments with 2D DIC only allows quantification of 2D displacement and strain components in section direction. This completely omits the potential of CT experiments for full 3D strain analysis of complex, non-cylindrical deformation structures. In this study, we apply digital volume correlation (DVC) techniques on XRCT scan data of “solid” analogue experiments to fully quantify the internal displacement and strain in 3 dimensions over time. Our first results indicate that the application of DVC techniques on XRCT volume data can successfully be used to quantify the 3D spatial and temporal strain patterns inside analogue experiments. We demonstrate the potential of combining DVC techniques and XRCT volume imaging for 3D strain analysis of a contractional experiment simulating the development of a non-cylindrical pop-up structure. Furthermore, we discuss various options for optimisation of granular materials, pattern generation, and data acquisition for increased resolution and accuracy of the strain results. Three-dimensional strain analysis of analogue models is of particular interest for geological and seismic interpretations of complex, non-cylindrical geological structures. The volume strain data enable the analysis of the large-scale and small-scale strain history of geological structures.

Automatic X-ray landmark detection and shape segmentation via data-driven joint estimation of image displacements

In this paper, we propose a new method for fully-automatic landmark detection and shape segmentation in X-ray images. To detect landmarks, we estimate the displacements from some randomly sampled image patches to the (unknown) landmark positions, and then we integrate these predictions via a voting scheme. Our key contribution is a new algorithm for estimating these displacements. Different from other methods where each image patch independently predicts its displacement, we jointly estimate the displacements from all patches together in a data driven way, by considering not only the training data but also geometric constraints on the test image. The displacements estimation is formulated as a convex optimization problem that can be solved efficiently. Finally, we use the sparse shape composition model as the a priori information to regularize the landmark positions and thus generate the segmented shape contour. We validate our method on X-ray image datasets of three different anatomical structures: complete femur, proximal femur and pelvis. Experiments show that our method is accurate and robust in landmark detection, and, combined with the shape model, gives a better or comparable performance in shape segmentation compared to state-of-the art methods. Finally, a preliminary study using CT data shows the extensibility of our method to 3D data.