Analysis of biosurfaces by neutron reflectometry: From simple to complex interfaces

Because of its high sensitivity for light elements and the scattering contrast manipulation via isotopic substitutions, neutron reflectometry (NR) is an excellent tool for studying the structure of soft-condensed material. These materials include model biophysical systems as well as in situ living tissue at the solid–liquid interface. The penetrability of neutrons makes NR suitable for probing thin films with thicknesses of 5–5000 Å at various buried, for example, solid–liquid, interfaces [J. Daillant and A. Gibaud, Lect. Notes Phys. 770, 133 (2009); G. Fragneto-Cusani, J. Phys.: Condens. Matter 13, 4973 (2001); J. Penfold, Curr. Opin. Colloid Interface Sci. 7, 139 (2002)]. Over the past two decades, NR has evolved to become a key tool in the characterization of biological and biomimetic thin films. In the current report, the authors would like to highlight some of our recent accomplishments in utilizing NR to study highly complex systems, including in-situ experiments. Such studies will result in a much better understanding of complex biological problems, have significant medical impact by suggesting innovative treatment, and advance the development of highly functionalized biomimetic materials

A Visual Stack Based Paradigm for Visualization Environments

We present a new visual paradigm for Visualization Systems, inspired by stack-based programming. Most current implementations of Visualization systems are based on directional graphs. However directional graphs as a visual representation of execution, though initially quite intuitive, quickly grow cumbersome and difficult to follow under complex examples. Our system presents the user with a simple and compact methodology of visually stacking actions directly on top of data objects as a way of creating filter scripts. We explore and address extensions to the basic paradigm to allow for: multiple data input or data output objects to and from execution action modules, execution thread jumps and loops, encapsulation, and overall execution control. We exploit the dynamic nature of current computer graphic interfaces by utilizing features such as drag-and-drop, color emphasis and object animation to indicate action, looping, message/parameter passing; to furnish an overall better understanding of the resulting laid out execution scripts

Bringing computational steering to the user

Computational steering is a technique that combines simulation and visualization. The user is continuously provided with visual feedback about the state of the simulation, and can change parameters on the fly. Designers can vary parameters to optimize their product, users can detect errors in the input early, researchers can do qualitative sensitivity analyses easily. The implementation of computational steering is very tedious. It requires knowledge of the simulation, visualization, user interfacing, and data communication. In this paper we discuss an environment that enables users to implement and use computational steering effectively without much support from user interface experts. We show how the environment is applied to various applications

Modeling noise experiments performed at AKR-2 and CROCUS zero-power reactors

CORTEX is a EU H2020 project (2017-2021) devoted to the analysis of ’reactor neutron noise’ in nuclear reactors, i.e. the small fluctuations occurring around the stationary state due to external or internal disturbances in the core. One important aspect of CORTEX is the development of neutron noise simulation codes capable of modeling the spatial variations of the noise distribution in a reactor. In this paper we illustrate the validation activities concerning the comparison of the simulation results obtained by several noise simulation codes with respect to experimental data produced at the zero-power reactors AKR-2 (operated at TUD, Germany) and CROCUS (operated at EPFL, Switzerland). Both research reactors are modeled in the time and frequency domains, using transport or diffusion theory. Overall, the noise simulators managed to capture the main features of the neutron noise behavior observed in the experimental campaigns carried out in CROCUS and AKR-2, even though computational biases exist close to the region where the noise-inducing mechanical vibration was located (the so-called ”noise source”). In some of the experiments, it was possible to observe the spatial variation of the relative neutron noise, even relatively far from the noise source. This was achieved through reduced uncertainties using long measurements, the installation of numerous, robust and efficient detectors at a variety of positions in the near vicinity or inside the core, as well as new post-processing methods. For the numerical simulation tools, modeling the spatial variations of the neutron noise behavior in zero-power research reactors is an extremely challenging problem, because of the small magnitude of the noise field; and because deviations from a point-kinetics behavior are most visible in portions of the core that are especially difficult to be precisely represented by simulation codes, such as experimental channels. Nonetheless the limitations of the simulation tools reported in the paper were not an issue for the CORTEX project, as most of the computational biases are found close to the noise source

Bringing computational steering to the user

Computational steering is a technique that combines simulation and visualization. The user is continuously provided with visual feedback about the state of the simulation, and can change parameters on the fly. Designers can vary parameters to optimize their product, users can detect errors in the input early, researchers can do qualitative sensitivity analyses easily. The implementation of computational steering is very tedious. It requires knowledge of the simulation, visualization, user interfacing, and data communication. In this paper we discuss an environment that enables users to implement and use computational steering effectively without much support from user interface experts. We show how the environment is applied to various applications

Softening of a flat phonon mode in the kagome ScV6_6Sn6_6

The long range electronic modulations recently discovered in the geometrically frustrated kagome lattice have opened new avenues to explore the effect of correlations in materials with topological electron flat bands. The observation of the lattice response to the emergent new phases of matter, a soft phonon mode, has remained elusive and the microscopic origin of charge density waves (CDWs) is still unknown. Here, we show, for the first time, a complete melting of the ScV$_ 6$Sn$_ 6$ (166) kagome lattice. The low energy phonon with propagation vector $\frac{1}{3} \frac{1}{3} \frac{1}{2}$ collapses at 98 K, without the emergence of long-range charge order, which sets in with a propagation vector $\frac{1}{3} \frac{1}{3} \frac{1}{3}$. The CDW is driven (but locks at a different vector) by the softening of an overdamped phonon flat plane at k$_z$=$\pi$. We observe broad phonon anomalies in momentum space, pointing to (1) the existence of approximately flat phonon bands which gain some dispersion due to electron renormalization, and (2) the effects of the momentum dependent electron-phonon interaction in the CDW formation. Ab initio and analytical calculations corroborate the experimental findings to indicate that the weak leading order phonon instability is located at the wave vector $\frac{1}{3} \frac{1}{3} \frac{1}{2}$ of a rather flat collapsed mode. We analytically compute the phonon frequency renormalization from high temperatures to the soft mode, and relate it to a peak in the orbital-resolved susceptibility, obtaining an excellent match with both ab initio and experimental results, and explaining the origin of the approximately flat phonon dispersion. Our data report the first example of the collapse of a softening of a flat phonon plane and promote the 166 compounds of the kagome family as primary candidates to explore correlated flat phonon-topological flat electron physics.Comment: 10 pages, 4 figure

Quality assessment of protein NMR structures

Biomolecular NMR structures are now routinely used in biology, chemistry, and bioinformatics. Methods and metrics for assessing the accuracy and precision of protein NMR structures are beginning to be standardized across the biological NMR community. These include both knowledge-based assessment metrics, parameterized from the database of protein structures, and model versus data assessment metrics. On line servers are available that provide comprehensive protein structure quality assessment reports, and efforts are in progress by the world-wide Protein Data Bank (wwPDB) to develop a biomolecular NMR structure quality assessment pipeline as part of the structure deposition process. These quality assessment metrics and standards will aid NMR spectroscopists in determining more accurate structures, and increase the value and utility of these structures for the broad scientific community

Machine Learning for Analysis of Real Nuclear Plant Data in the Frequency Domain

Machine Learning is used in this paper for detecting anomalies in nuclear plant reactor cores. The proposed approach first generates large amounts of simulated data with different types of perturbations occurring at various locations in the core. This is achieved using the CORE SIM+ modelling framework, which generates these data in the frequency domain. State-of-the-art machine and deep learning models are then extended and used to successfully perform semantic segmentation of the core, classification and localisation of perturbations. Actual plant data are then considered, provided by two different reactors, including no labels about perturbation existence. A domain adaptation methodology is then developed, which uses self-supervised, or unsupervised learning, so as to align the simulated data with the actual plant data and detect perturbations, whilst classifying their type and estimating their location. Experimental studies illustrate the successful performance of the developed approach and extensions are described that indicate a great potential for further research

An Application Perspective on High-Performance Computing and Communications

We review possible and probable industrial applications of HPCC focusing on the software and hardware issues. Thirty-three separate categories are illustrated by detailed descriptions of five areas -- computational chemistry; Monte Carlo methods from physics to economics; manufacturing; and computational fluid dynamics; command and control; or crisis management; and multimedia services to client computers and settop boxes. The hardware varies from tightly-coupled parallel supercomputers to heterogeneous distributed systems. The software models span HPF and data parallelism, to distributed information systems and object/data flow parallelism on the Web. We find that in each case, it is reasonably clear that HPCC works in principle, and postulate that this knowledge can be used in a new generation of software infrastructure based on the WebWindows approach, and discussed in an accompanying paper

Hydrogen in nonstoichiometric cubic titanium monoxides: X-ray and neutron diffraction, neutron vibrational spectroscopy and NMR studies

Hydrogen-induced changes in the properties of transition-metal oxides have attracted much recent attention due to numerous applications of these materials including catalysis, H2 production, low-temperature H2 sensing, solar cells, and air purification. However, basic properties of hydrogenated titanium monoxides have not been investigated so far. In the present work, we report the results of the first studies of the crystal structure, vibrational spectra, and mobility of H atoms in TiO0.72H0.30 and TiO0.96H0.14 using X-ray diffraction (XRD), neutron powder diffraction, neutron vibrational spectroscopy, and nuclear magnetic resonance (NMR). The hydrogenated compound TiO0.72H0.30 is found to retain the disordered cubic B1-type structure of the initial titanium monoxide, where H atoms exclusively occupy vacancies in the oxygen sublattice. It has been revealed that hydrogenation of the disordered cubic TiO0.96 leads to the formation of the two-phase compound TiO0.96H0.14, where the disordered B1-type phase coexists with the monoclinic phase of Ti5O5 type with an ordered arrangement of vacancies. In both phases, H atoms are found to occupy only vacancies in the oxygen sublattice. The low-temperature inelastic neutron scattering spectra of TiO0.72H0.30 and TiO0.96H0.14 in the energy transfer range of 40–180 meV exhibit a single peak due to optical oxygen vibrations (centered on about 60 meV) and a broad structure at 90–170 meV due to optical H vibrations. The unusual width of this structure can be attributed to the broken symmetry of hydrogen sites in the titanium monoxides: because of the presence of vacancies in the titanium sublattice, the actual point symmetry of these sites appears to be lower than octahedral. Proton NMR measurements have revealed that both hydrogenated compounds are metallic; no signs of hydrogen diffusive motion in TiO0.72H0.30 and TiO0.96H0.14 at the frequency scale of about 105 s-1 have been found up to 370 K. © 2021 Elsevier B.V.National Institute of Standards and Technology, NISTRussian Foundation for Basic Research, РФФИ, (19-03-00051a)Funding text 1: This work was performed within the assignment of the Russian Federal Scientific Program “Function” No. AAAA-A19-119012990095-0 (AVS). It was also carried out according to the state assignment for IMET UB RAS (AAR) and supported by the Russian Foundation for Basic Research, grant No. 19-03-00051a (AAV). The authors acknowledge the use of the high-resolution powder diffractometer and filter-analyzer neutron spectrometer at the NIST Center for Neutron Research in support of this work.Funding text 2: This work was performed within the assignment of the Russian Federal Scientific Program “Function” No. AAAA-A19-119012990095-0 (AVS). It was also carried out according to the state assignment for IMET UB RAS (AAR) and supported by the Russian Foundation for Basic Research, grant No. 19-03-00051a (AAV). The authors acknowledge the use of the high-resolution powder diffractometer and filter-analyzer neutron spectrometer at the NIST Center for Neutron Research in support of this work