Non-copper-based Catalysts for CO2 Electroreduction to Multi-carbon Compounds.

Renewable energy has made significant strides, with the cost of clean electricity plummeting, making the use of renewable electricity for electrocatalytic CO2 reduction to synthesize high-value chemicals and fuels more economically attractive. Notably, certain non-copper-based electrocatalysts have shown remarkable selectivity for C2+ products at low overpotentials, even enabling the production of multi-carbon molecules that are undetectable on copper-based electrodes. This breakthrough opens up new avenues for research into non-copper catalysts.

Enhanced /-photoisomerization and luminescence of stilbene derivative co-coordinated in di-β-diketonate lanthanide complexes.

A new tetradentate chelating ligand appending a stilbene derivative, E-N',N'-bis(pyridin-2-ylmethyl)-4-styrylbenzohydrazide (HL) was synthesized, together with two β-diketonates (4,4,4-trifluoro-1-phenylbutane-1,3-dionate, tfd), with or without the trifluoroacetate anion present as a ligand for coordination with lanthanide(iii) ions to form [Ln(tfd)2(HL)(CF3CO2)] (LnC49H36F9N4O7, Ln = La (1), Nd (2), Eu (3), Gd (4)) and [Yb(tfd)2(L)] (YbC47H35F6N4O5 (5), L = deprotonated HL). All five complexes were structurally characterized, and five crystals were obtained and analyzed by single-crystal X-ray diffraction. The quantum yield of trans-to-cis photoisomerization of the stilbene group in gadolinium complex 4 was enhanced about five-fold compared with that of HL itself.

Multiresolution medical image segmentation based on wavelet transform.

The wavelet transform always is used to analyze image. The watershed transformation is a useful morphological segmentation tool for a variety of grey-scale image. In this paper, an efficient segmentation method for medical image analysis is presented, which combines pyramidal image segmentation with hierarchical watershed segmentation algorithm.