Fenton chemistry-based detemplation of an industrially relevant microcrystalline beta zeolite. Optimization and scaling-up studies

A mild template removal of microcrystalline beta zeolite, based on Fenton chemistry, was optimized. Fenton detemplation was studied in terms of applicability conditions window, reaction rate and scale up. TGA and CHN elemental analysis were used to evaluate the detemplation effectiveness, while ICP, XRD, LPHR-Ar physisorption, and 27Al MAS NMR were applied to characterize the structure and texture of the resulting materials. The material properties were compared to calcination. By understanding the interplay of relevant parameters of the Fenton chemistry, the process can be optimized in order to make it industrially attractive for scale-up. The H2O2 utilization can be minimized down to 15 mL H2O2/g (88 °C, 30 ppm Fe), implying a high solid concentration and low consumption of H2O2. When Fe concentration must be minimized, values as low as 5 ppm Fe can be applied (88 °C, 30 mL H2O2/g), to achieve full detemplation. The reaction time to completeness can be reduced to 5 h when combining a Fe-oxalate catalyst with UV radiation. The protocol was scaled up to 100 times larger its original recipe. In terms of the material's properties, the scaled material is structurally comparable to the calcined counterpart (comparable Si/Al and XRD patterns), while it displays benefits in terms of texture and Al-coordination, the latter with full preservation of the tetrahedral Al

Grid-texture mechanisms in human vision:contrast detection of regular sparse micro-patterns requires specialist templates

Previous work has shown that human vision performs spatial integration of luminance contrast energy, where signals are squared and summed (with internal noise) over area at detection threshold. We tested that model here in an experiment using arrays of micro-pattern textures that varied in overall stimulus area and sparseness of their target elements, where the contrast of each element was normalised for sensitivity across the visual field. We found a power-law improvement in performance with stimulus area, and a decrease in sensitivity with sparseness. While the contrast integrator model performed well when target elements constituted 50–100% of the target area (replicating previous results), observers outperformed the model when texture elements were sparser than this. This result required the inclusion of further templates in our model, selective for grids of various regular texture densities. By assuming a MAX operation across these noisy mechanisms the model also accounted for the increase in the slope of the psychometric function that occurred as texture density decreased. Thus, for the first time, mechanisms that are selective for texture density have been revealed at contrast detection threshold. We suggest that these mechanisms have a role to play in the perception of visual textures.

Light self-focusing in the atmosphere:thin window model

Ultra-high power (exceeding the self-focusing threshold by more than three orders of magnitude) light beams from ground-based laser systems may find applications in space-debris cleaning. The propagation of such powerful laser beams through the atmosphere reveals many novel interesting features compared to traditional light self-focusing. It is demonstrated here that for the relevant laser parameters, when the thickness of the atmosphere is much shorter than the focusing length (that is, of the orbit scale), the beam transit through the atmosphere in lowest order produces phase distortion only. This means that by using adaptive optics it may be possible to eliminate the impact of self-focusing in the atmosphere on the laser beam. The area of applicability of the proposed "thin window" model is broader than the specific physical problem considered here. For instance, it might find applications in femtosecond laser material processing.