Jožef Stefan Institute

About: Jožef Stefan Institute is a facility organization based out in Ljubljana, Slovenia. It is known for research contribution in the topics: Liquid crystal & Dielectric. The organization has 3828 authors who have published 12614 publications receiving 291025 citations.

Rapid and Controllable Flame Reduction of TiO2 Nanowires for Enhanced Solar Water-Splitting

Abstract: We report a new flame reduction method to generate controllable amount of oxygen vacancies in TiO2 nanowires that leads to nearly three times improvement in the photoelectrochemical (PEC) water-splitting performance. The flame reduction method has unique advantages of a high temperature (>1000 °C), ultrafast heating rate, tunable reduction environment, and open-atmosphere operation, so it enables rapid formation of oxygen vacancies (less than one minute) without damaging the nanowire morphology and crystallinity and is even applicable to various metal oxides. Significantly, we show that flame reduction greatly improves the saturation photocurrent densities of TiO2 nanowires (2.7 times higher), α-Fe2O3 nanowires (9.4 times higher), ZnO nanowires (2.0 times higher), and BiVO4 thin film (4.3 times higher) in comparison to untreated control samples for PEC water-splitting applications.

$D_{s0}^*(2317)$ Meson and $D$-Meson-Kaon Scattering from Lattice QCD

Abstract: The scalar meson D*(s0)(2317) is found 37(17) MeV below the DK threshold in a lattice simulation of the J(P)=0(+) channel using, for the first time, both DK as well as s¯c interpolating fields. The simulation is done on N(f)=2+1 gauge configurations with m(π) is approximately equal to 156 MeV, and the resulting M(D*(s0))-1/4(M(D(s))+3M(D*(s)))=266(16) MeV is close to the experimental value 241.5(0.8) MeV. The energy level related to the scalar meson is accompanied by additional discrete levels due to DK scattering states. The levels near threshold lead to the negative DK scattering length a(0)=-1.33(20) fm that indicates the presence of a state below threshold.

FEM: feature-enhanced map

Abstract: A method is presented that modifies a 2mFobs − DFmodel σA-weighted map such that the resulting map can strengthen a weak signal, if present, and can reduce model bias and noise. The method consists of first randomizing the starting map and filling in missing reflections using multiple methods. This is followed by restricting the map to regions with convincing density and the application of sharpening. The final map is then created by combining a series of histogram-equalized intermediate maps. In the test cases shown, the maps produced in this way are found to have increased interpretability and decreased model bias compared with the starting 2mFobs − DFmodel σA-weighted map.