Massimo Ladisa

Ab initio GW many-body effects in graphene

We present an ab initio numerical many-body GW calculation of the band plot in freestanding graphene. We consider the full ionic and electronic structure introducing e-e interaction and correlation effects via a self-energy containing non-Hermitian and dynamical terms. With respect to the density-functional theory local-density approximation, the Fermi velocity is renormalized with an increase of 17%, in better agreement with the experiment. Close to the Dirac point the linear dispersion is modified by the presence of a kink, as observed by angle-resolved photoemission spectroscopy. We demonstrate that the kink is due to low-energy pi-->pi* single-particle excitations and to the pi plasmon. The GW self-energy does not open the band gap.

Nanoparticle size distribution estimation by a full-pattern powder diffraction analysis

The increasing scientific and technological interest in nanoparticles has raised the need for fast, efficient, and precise characterization techniques. Powder diffraction is a very efficient experimental method, as it is straightforward and nondestructive. However, its use for extracting information regarding very small particles brings some common crystallographic approximations to and beyond their limits of validity. Powder pattern diffraction calculation methods are critically discussed, with special focus on spherical particles with log-normal distributions, with the target of determining size distribution parameters. A 20-nm

Debye function analysis and 2D imaging of nanoscaled engineered bone

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Folding a two-dimensional powder diffraction image into a one-dimensional scan: a new procedure

sample is analyzed as an example.

Momentum distribution and Compton profile by the ab initio GW approximation

The Debye Function Analysis of diffraction patterns from nanosized mineral crystals showing different average degrees of maturity was carried out on engineered bone samples. The analysis relied on a bivariate family of atomistic hydroxyapatite nanocrystal models and provided information about crystal structure, size and shape distributions of the mineral component of the newly formed bone. An average rod-like shape of nanocrystals was found in all samples, with average sizes well matching the collagen I gap region. The diffraction patterns investigated through the Debye Function Analysis were used as signal models to perform the Canonical Correlation Analysis of high resolution X-ray micro-diffraction patterns collected on porous and resorbable hydroxyapatite/silicon-stabilized tricalcium phosphate (Si-TCP) implants. The nosologic maps clearly showed a size gradient in the new formed bone that validates the mechanism (mimicking the bone remodelling in orthotopic bones) of a continuous deposition of bone by osteoblasts, an increasing mineralization of the newly deposited bone, a growth of the new crystals, at the same time that osteoclasts adhere to the scaffold surface and resorb the bioceramic. The comparison of samples at different implantation times proved that the selective resorption of Si-TCP component from the scaffold was already evident after two and almost complete after six months.

Canonical correlation and quantitative phase analysis of microdiffraction patterns in bone-tissue engineering

A new procedure aimed at folding a two-dimensional powder diffraction pattern into a one-dimensional scan is presented. The sample-to-detector distance is the only parameter that, in this approach, needs to be adjusted in a separate step by using the `standard sample. The technique consists of three steps: tracking the beam centre by means of simulated annealing of the diffraction rings along the same axis, detector tilt and rotation determination by a Hankel Lanczos singular value decomposition and intensity integration by an adaptive binning algorithm. The X-ray powder diffraction (XRPD) intensity profile of the standard NIST Si 640c sample is used to test the performance. Results show the robustness of the method and its capability of efficiently tagging the pixels in a two-dimensional readout system by matching the ideal geometry of the detector to the real beam–sample–detector frame. The technique is a versatile and user-friendly tool for the one-dimensional folding of two-dimensional XRPD images.

Disentangling instrumental broadening

We present two possible approaches to calculate the momentum distribution n(p) and the Compton profile within the framework of the ab initio GW approximation on the self-energy. The approaches are based on integration of the Green’s function along either the real or the imaginary axes. Examples will be presented on the jellium model and on real bulk sodium. Advantages and drawbacks of both methods are discussed in comparison with accurate quantum Monte Carlo (QMC) calculations and x-ray Compton scattering experiments. We illustrate the effect of many-body correlations and disentangle them from band-structure and anisotropy effects by a comparison with density functional theory in the local density approximation. Our results suggest the use of G0W0 momentum distributions as reference for future experiments and theory developments.

Unfolding a two-dimensional powder diffraction image: conformal mapping

A novel method is described that combines high-resolution scanning microdiffraction techniques, Rietveld quantitative phase analysis and a statistical method known as canonical correlation analysis (CCA). The method has been applied to a sample taken from a bone-tissue-engineered bioceramic porous scaffold implanted in a mouse for six months. The CCA technique allows the detection of those pixels throughout the investigated sample that best correlate with signal models. Besides the standard usage of this approach, which requires theoretical profiles as signal models, a novel application is presented here, which consists of picking the model spectra out of the experimental data set. Patterns representative of a reasonable range of phase compositions were selected among the huge number of two-dimensional patterns (folded in one-dimensional profiles) to extract quantitative phase fractions. At this stage, the CCA approach was also used to overcome the low Poisson statistic of signal models, so making Rietveld quantitative analysis more reliable. These patterns have been used as profile models for CCA. The final classification map, obtained by assigning the considered pixel to the model spectrum with the highest canonical coefficient, provides the spatial variation of phase concentration.

Classification of crystallographic data using canonical correlation analysis

A new procedure aimed at disentangling the instrumental profile broadening and the relevant X-ray powder diffraction (XRPD) profile shape is presented. The technique consists of three steps: de-noising by means of wavelet transforms, background suppression by morphological functions and deblurring by a Lucy–Richardson damped deconvolution algorithm. Real XRPD intensity profiles of ceria samples are used to test the performance. Results show the robustness of the method and its capability of efficiently disentangling the instrumental broadening affecting the measurement of the intrinsic physical line profile. These features make the whole procedure an interesting and user-friendly tool for the pre-processing of XRPD data.

Blind source separation and automatic tissue typing of microdiffraction data by hierarchical nonnegative matrix factorization

A new procedure aimed at unfolding a two-dimensional powder diffraction image into both a one-dimensional azimuthal and a radial scan is presented. In this approach, the sample-to-detector distance is the only parameter that must be adjusted in a separate step by using a standard sample. The technique consists of three steps: tracking the beam centre as the local maximum of the self-convolution of the original two-dimensional map, detector tilt and rotation determination by an intensity-tensor diagonalization, and azimuthal/radial intensity integration by a conformal mapping of the original two-dimensional powder diffraction image. The X-ray powder diffraction (XRPD) intensity profile of the NIST Si 640c standard sample is used to test the performance. The results show the robustness of the method and its capability of efficiently tagging the pixels in a two-dimensional readout system by matching the ideal geometry of the detector to the real beam–sample–detector frame. The technique is a fast, versatile and user-friendly tool for the simultaneous analysis of both azimuthal and radial spectra of two-dimensional XRPD images.