Multifunctional Magnetic-fluorescent Nanocomposites for Biomedical Applications

Nanotechnology is a fast-growing area, involving the fabrication and use of nano-sized materials and devices. Various nanocomposite materials play a number of important roles in modern science and technology. Magnetic and fluorescent inorganic nanoparticles are of particular importance due to their broad range of potential applications. It is expected that the combination of magnetic and fluorescent properties in one nanocomposite would enable the engineering of unique multifunctional nanoscale devices, which could be manipulated using external magnetic fields. The aim of this review is to present an overview of bimodal “two-in-one” magnetic-fluorescent nanocomposite materials which combine both magnetic and fluorescent properties in one entity, in particular those with potential applications in biotechnology and nanomedicine. There is a great necessity for the development of these multifunctional nanocomposites, but there are some difficulties and challenges to overcome in their fabrication such as quenching of the fluorescent entity by the magnetic core. Fluorescent-magnetic nanocomposites include a variety of materials including silica-based, dye-functionalised magnetic nanoparticles and quantum dots-magnetic nanoparticle composites. The classification and main synthesis strategies, along with approaches for the fabrication of fluorescent-magnetic nanocomposites, are considered. The current and potential biomedical uses, including biological imaging, cell tracking, magnetic bioseparation, nanomedicine and bio- and chemo-sensoring, of magnetic-fluorescent nanocomposites are also discussed

The yield estimation of semiconductor products based on truncated samples

Product yield reflects the potential product quality and reliability, which means that high yield corresponds to good quality and high reliability. Yet consumers usually couldn’t know the actual yield of the products they purchase. Generally, the products that consumers get from suppliers are all eligible. Since the quality characteristic of the eligible products is covered by the specifications, then the observations of quality characteristic follow truncated normal distribution. In the light of maximum likelihood estimation, this paper proposes an algorithm for calculating the parameters of full Gaussian distribution before truncation based on truncated data and estimating product yield. The confidence interval of the yield result is derived, and the effect of sample size on the precision of the calculation result is also analyzed. Finally, the effectiveness of this algorithm is verified by an actual instance

The yield estimation of semiconductor products based on truncated samples

Product yield reflects the potential product quality and reliability, which means that high yield corresponds to good quality and high reliability. Yet consumers usually couldn’t know the actual yield of the products they purchase. Generally, the products that consumers get from suppliers are all eligible. Since the quality characteristic of the eligible products is covered by the specifications, then the observations of quality characteristic follow truncated normal distribution. In the light of maximum likelihood estimation, this paper proposes an algorithm for calculating the parameters of full Gaussian distribution before truncation based on truncated data and estimating product yield. The confidence interval of the yield result is derived, and the effect of sample size on the precision of the calculation result is also analyzed. Finally, the effectiveness of this algorithm is verified by an actual instance

Optical limiting with neutral nickel dithiolene complexes

Materials Research Society Symposium - Proceedings597413-418MRSP

Optical-limiting properties of neutral nickel dithiolenes

Applied Physics B: Lasers and Optics702-6809-812APBO