Patterning methods, chemical approaches

Electrochemical polymerization is a fast and simple, widely used method to synthesize different conducting polymers. Electrodeposition enables film formation on surfaces with complicated patterns as well as control of film thickness [5]. Furthermore, the subsequent growth of the polymer film and the charging reactions can be followed in situ [6]. Parameters such as solvent media, electrolyte, electrochemical method used for polymerization and monomer material, all have a profound effect on film morphology, charge transfer and transport properties. Different from the powdery products prepared through chemical approaches, this method enables an easy one-step deposition of the film directly at the surface of the electrode substrate that can be further applied for electrochemical purposes. 

Other methods have been developed that allow the detection of point mutations in non-hybridization based assays. An effective alternative electrochemical method harnesses differences in the kinetics of the reaction of Ru(bpy)3 with gnanine in the context of base mismatches to report base substitutions [47]. In addition, altered patterns of chemical reactivity have been detected in RNA-DNA hybrids containing 2-NH2 modifications in an RNA complement at mispaired positions [48]. Extension of this approach to an immobilized system has not yet been demonstrated, but it may hold pronfise for any applications where alterations in chemical, rather than electrochanical, reactivity are required. 

PCA is a method based on the Karhunen-Loeve transformation (KL transformation) of the data points in the feature space. In KL transformation, the data points in the feature space are rotated such that the new coordinates of the sample points become the linear combination of the original coordinates. And the first principal component is chosen to be the direction with largest variation of the distribution of sample points. After the KL transformation and the neglect of the components with minor variation of coordinates of sample points, we can make dimension reduction without significant loss of the information about the distribution of sample points in the feature space. Up to now PCA is probably the most widespread multivariate statistical technique used in chemometrics. Within the chemical community the first major application of PCA was reported in 1970s, and form the foundation of many modem chemometric methods. Conventional approaches are univariate in which only one independent variable is used per sample, but this misses much information for the multivariate problem of SAR, in which many descriptors are available on a number of candidate compounds. PCA is one of several multivariate methods that allow us to explore patterns in multivariate data, answering questions about similarity and classification of samples on the basis of projection based on principal components. 

Nanomaterials can be manufactured by one of two groups of methods, one physical and one chemical. In top-down approaches, nanoscale materials are carved into shape by the use of physical nanotechnology methods such as lithography (Fig. 15.30). In bottom-up approaches, molecules are encouraged to assemble themselves into desired patterns chemically by making use of specific... 

While principal components models are used mostly in an unsupervised or exploratory mode, models based on canonical variates are often applied in a supervisory way for the prediction of biological activities from chemical, physicochemical or other biological parameters. In this section we discuss briefly the methods of linear discriminant analysis (LDA) and canonical correlation analysis (CCA). Although there has been an early awareness of these methods in QSAR [7,50], they have not been widely accepted. More recently they have been superseded by the successful introduction of partial least squares analysis (PLS) in QSAR. Nevertheless, the early pattern recognition techniques have prepared the minds for the introduction of modem chemometric approaches. 

From the early advances in the quantum-chemical description of molecular electron densities [1-9] to modem approaches to the fundamental connections between experimental electron density analysis, such as crystallography [10-13] and density functional theories of electron densities [14-43], patterns of electron densities based on the theory of catastrophes and related methods [44-52], and to advances in combining theoretical and experimental conditions on electron densities [53-68], local approximations have played an important role. Considering either the formal charges in atomic regions or the representation of local electron densities in the structure refinement process, some degree of approximate transferability of at least some of the local structural features has been assumed. 

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