scholarly journals Structure of the amorphous titania precursor phase of N-doped photocatalysts

RSC Advances ◽  
2021 ◽  
Vol 11 (15) ◽  
pp. 8619-8627
Author(s):  
I. E. Grey ◽  
P. Bordet ◽  
N. C. Wilson

Amorphous titania samples prepared by ammonia solution neutralization of titanyl sulphate have been characterized by chemical and thermal analyses, and with reciprocal-space and real-space fitting of wide-angle synchrotron X-ray scattering data.

2020 ◽  
Vol 76 (11) ◽  
pp. 1145-1156
Author(s):  
Lili Cao ◽  
Ulf Ryde

X-ray crystallography is the main source of atomistic information on the structure of proteins. Normal crystal structures are obtained as a compromise between the X-ray scattering data and a set of empirical restraints that ensure chemically reasonable bond lengths and angles. However, such restraints are not always available or accurate for nonstandard parts of the structure, for example substrates, inhibitors and metal sites. The method of quantum refinement, in which these empirical restraints are replaced by quantum-mechanical (QM) calculations, has previously been suggested for small but interesting parts of the protein. Here, this approach is extended to allow for multiple conformations in the QM region by performing separate QM calculations for each conformation. This approach is shown to work properly and leads to improved structures in terms of electron-density maps and real-space difference density Z-scores. It is also shown that the quality of the structures can be gauged using QM strain energies. The approach, called ComQumX-2QM, is applied to the P-cluster in two different crystal structures of the enzyme nitrogenase, i.e. an Fe8S7Cys6 cluster, used for electron transfer. One structure is at a very high resolution (1.0 Å) and shows a mixture of two different oxidation states, the fully reduced PN state (Fe8 2+, 20%) and the doubly oxidized P2+ state (80%). In the original crystal structure the coordinates differed for only two iron ions, but here it is shown that the two states also show differences in other atoms of up to 0.7 Å. The second structure is at a more modest resolution, 2.1 Å, and was originally suggested to show only the one-electron oxidized state, P1+. Here, it is shown that it is rather a 50/50% mixture of the P1+ and P2+ states and that many of the Fe—Fe and Fe—S distances in the original structure were quite inaccurate (by up to 0.8 Å). This shows that the new ComQumX-2QM approach can be used to sort out what is actually seen in crystal structures with dual conformations and to give locally improved coordinates.


IUCrJ ◽  
2019 ◽  
Vol 6 (2) ◽  
pp. 259-266 ◽  
Author(s):  
Po-Ting Chiu ◽  
Yu-Cheng Chien ◽  
Prokopios Georgopanos ◽  
Ya-Sen Sun ◽  
Apostolos Avgeropoulos ◽  
...  

The development of well ordered nanonetwork materials (in particular gyroid-structured materials) has been investigated using a block-copolymer template for templated electroless plating as an example system for the examination of network formation using X-ray scattering. By taking advantage of the nucleation and growth mechanism of templated electroless plating, gyroid-structured Au was successfully fabricated through the development of Au nanoparticles, then tripods and branched tripods, and finally an ordered network. Each stage in the development of the network phase could then be examined by combining real-space transmission electron microscopy observations with reciprocal-space small-angle X-ray scattering results. The fingerprint scattering profile of the building block for the network (i.e. the tripod of the gyroid) could be well fitted with the form factor of an effective sphere, and the diffraction results from the ordered network could thus be reasonably addressed. As a result, the examination of well ordered network materials can be simplified as the scattering from the form factor of a sphere convoluted with the nodes of its structure factor, providing a facile method of identifying the network phases from X-ray scattering data.


2018 ◽  
Vol 122 (45) ◽  
pp. 10320-10329 ◽  
Author(s):  
Amin Sadeghpour ◽  
Marjorie Ladd Parada ◽  
Josélio Vieira ◽  
Megan Povey ◽  
Michael Rappolt

1995 ◽  
Author(s):  
Yibin Zheng ◽  
Peter C. Doerschuk ◽  
John E. Johnson

2017 ◽  
Vol 50 (3) ◽  
pp. 951-958 ◽  
Author(s):  
Sen Chen ◽  
Juncheng E ◽  
Sheng-Nian Luo

SLADS(http://www.pims.ac.cn/Resources.html), a parallel code for direct simulations of X-ray scattering of large anisotropic dense nanoparticle systems of arbitrary species and atomic configurations, is presented. Particles can be of arbitrary shapes and dispersities, and interactions between particles are considered. Parallelization is achieved in real space for the sake of memory limitation. The system sizes attempted are up to one billion atoms, and particle concentrations in dense systems up to 0.36. Anisotropy is explored in terms of superlattices. One- and two-dimensional small-angle scattering or diffraction patterns are obtained.SLADSis validated self-consistently or against cases with analytical solutions.


2020 ◽  
Author(s):  
Steve P. Meisburger ◽  
Da Xu ◽  
Nozomi Ando

AbstractMixtures of biological macromolecules are inherently difficult to study using structural methods, as increasing complexity presents new challenges for data analysis. Recently, there has been growing interest in studying evolving mixtures using small-angle X-ray scattering (SAXS) in conjunction with time-resolved, high-throughput, or chromatography-coupled setups. Deconvolution and interpretation of the resulting datasets, however, are nontrivial when neither the scattering components nor the way in which they evolve are known a priori. To address this issue, we introduce the REGALS method (REGularized Alternating Least Squares), which incorporates simple expectations about the data as prior knowledge and utilizes parameterization and regularization to provide robust deconvolution solutions. The restraints used by REGALS are general properties such as smoothness of profiles and maximum dimensions of species, which makes it well-suited for exploring datasets with unknown species. Here we apply REGALS to analyze experimental data from four types of SAXS experiment: anion-exchange (AEX) coupled SAXS, ligand titration, time-resolved mixing, and time-resolved temperature jump. Based on its performance with these challenging datasets, we anticipate that REGALS will be a valuable addition to the SAXS analysis toolkit and enable new experiments. The software is implemented in both MATLAB and python and is available freely as an open-source software package.


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