Supramolecular Organization of Metal Nanoparticles in Solution and of Phenyleneethynylenes on Surfaces

Most of the procedures reported for the synthesis of metal nanoparticles involve the use of strong reducing agents or elevated temperatures. This limits the possibility of developing metal nanoparticle based sensors for the in situ detection of analytes. One of the objectives of the present investigations is to (i) develop newer methodologies for the synthesis of metal nanoparticles in aqueous medium at ambient conditions and (ii) their use in the detection of metal cations by taking advantage of the unique coordination ability. Ideally, biocompatible molecules which possess both the reducing and stabilizing groups are desirable for such applications. Formation of stable supramolecular assembly, by bringing metal nanoparticles close to each other, results in plasmon coupling and this strategy can be effectively utilized for the development of metal nanoparticle based sensors.Another objective of the present study is to understand the supramolecular organization of molecules on surfaces. Various noncovalent interactions between the molecules and with surface play a decisive role in their organizations. An in-depth understanding of these interactions is essential for device fabrications. Recent photophysical studies have revealed that phenyleneethynylene based molecular systems are ideal for device application. The second objective of the thesis focuses on understanding the (i) organization of phenyleneethynylenes on highly oriented pyrolytic graphite (HOPG) surface with atomic level precision and (ii) weak intermolecular interactions which drive their organization.

A Copy detection Method for Malayalam Text Documents using N-grams Model

In this paper a method of copy detection in short Malayalam text passages is proposed. Given two passages one as the source text and another as the copied text it is determined whether the second passage is plagiarized version of the source text. An algorithm for plagiarism detection using the n-gram model for word retrieval is developed and found tri-grams as the best model for comparing the Malayalam text. Based on the probability and the resemblance measures calculated from the n-gram comparison , the text is categorized on a threshold. Texts are compared by variable length n-gram(n={2,3,4}) comparisons. The experiments show that trigram model gives the average acceptable performance with affordable cost in terms of complexity