Germanium (II) precursors for use in the synthesis of luminescent germanium nanocrystals
Abstract not provided.
Abstract not provided.
Proposed for prublication in Acta Cryst. E.
Abstract not provided.
Proposed for publication in the Journal of Chemistry and Materials.
In this work, we investigated the controlled growth of nanocrystalline CdE (E = S, Se, and Te) via the pyrolysis of CdO and Cd(O2CCH3)2 precursors, at the specific Cd to E mole ratio of 0.67 to 1. The experimental results reveal that while the growth of CdS produces only a spherical morphology, CdSe and CdTe exhibit rod-like and tetrapod-like morphologies of temporally controllable aspect ratios. Over a 7200 s time period, CdS spheres grew from 4 nm (15 s aliquot) to 5 nm, CdSe nanorods grew from dimensions of 10.8 x 3.6 nm (15 s aliquot) to 25.7 x 11.2 nm, and CdTe tetrapods with arms 15 x 3.5 nm (15 s aliquot) grew into a polydisperse mixture of spheres, rods, and tetrapods on the order of 20 to 80 nm. Interestingly, long tracks of self-assembled CdSe nanorods (3.5 x 24 nm) of over one micron in length were observed. The temporal growth for each nanocrystalline material was monitored by UV-VIS spectroscopy, transmission electron spectroscopy, and further characterized by powder X-ray diffraction. This study has elucidated the vastly different morphologies available for CdS, CdSe, and CdTe during the first 7200 s after injection of the desired chalcogenide.
Developers of computer codes, analysts who use the codes, and decision makers who rely on the results of the analyses face a critical question: How should confidence in modeling and simulation be critically assessed? Verification and validation (V&V) of computational simulations are the primary methods for building and quantifying this confidence. Briefly, verification is the assessment of the accuracy of the solution to a computational model. Validation is the assessment of the accuracy of a computational simulation by comparison with experimental data. In verification, the relationship of the simulation to the real world is not an issue. In validation, the relationship between computation and the real world, i.e., experimental data, is the issue.