Comparison of fast field-cycling magnetic resonance imaging methods and future perspectives

ABSTRACT

Fast field-cycling (FFC) nuclear magnetic resonance relaxometry is a well-established method to determine the relaxation rates as a function of magnetic field strength. This so-called nuclear magnetic relaxation dispersion gives insight into the underlying molecular dynamics of a wide range of complex systems and has gained interest especially in the characterisation of biological tissues and diseases. The combination of FFC techniques with magnetic resonance imaging (MRI) offers a high potential for new types of image contrast more specific to pathological molecular dynamics. This article reviews the progress in FFC-MRI over the last decade and gives an overview of the hardware systems currently in operation. We discuss limitations and error correction strategies specific to FFC-MRI such as field stability and homogeneity, signal-to-noise ratio, eddy currents and acquisition time. We also report potential applications with impact in biology and medicine. Finally, we discuss the challenges and future applications in transferring the underlying molecular dynamics into novel types of image contrast by exploiting the dispersive properties of biological tissue or MRI contrast agents.     

Applications of coupled LC-GC: A review

Although coupled liquid chromatographygas chromatography (LC-GC) was first demonstrated ten years ago, only in the last few years has there been a sudden surge of interest in the technique. Approximately 70% of the total number of LC-GC applications have been published in the last two years (1987–88) alone. This review categorizes LC-GC publications into four main application areas: fossil fuels, foods, environmental samples, biologiical/pharmaceutical samples, and miscellaneous samples. Multidimensional separations carried out using other coupled-column chromatographic techniques (such as supercritical fluid chromatography (SFC) with GC, and on-line trace enrichment-GC) have also been included in this review.     

Nanotechnology in the Chemical Industry – Opportunities and Challenges

The traditional chemical industry has become a largely mature industry with many commodity products based on established technologies. Therefore, new product and market opportunities will more likely come from speciality chemicals, and from new functionalities obtained from new processing technologies as well as new microstructure control methodologies. It is a well-known fact that in addition to its molecular structure, the microstructure of a material is key to determining its properties. Controlling structures at the micro- and nano-levels is therefore essential to new discoveries. For this article, we define nanotechnology as the controlled manipulation of nanomaterials with at least one dimension less than 100nm. Nanotechnology is emerging as one of the principal areas of investigation that is integrating chemistry and materials science, and in some cases integrating these with biology to create new and yet undiscovered properties that can be exploited to gain new market opportunities. In this article market opportunities for nanotechnology will be presented from an industrial perspective covering electronic, biomedical, performance materials, and consumer products. Manufacturing technology challenges will be identified, including operations ranging from particle formation, coating, dispersion, to characterization, modeling, and simulation. Finally, a nanotechnology innovation roadmap is proposed wherein the interplay between the development of nanoscale building blocks, product design, process design, and value chain integration is identified. A suggestion is made for an R&D model combining market pull and technology push as a way to quickly exploit the advantages in nanotechnology and translate these into customer benefits.     

Cotangent cohomology of Stanley-Reisner rings

Simplicial complexes X provide commutative rings A(X) via the Stanley- Reisner construction. We calculated the cotangent cohomology, i.e., T¹ and T² of A(X) in terms of X. These modules provide information about the deformation theory of the algebro geometric objects assigned to X.