A chemical polymerization of aniline is quenched at specific reaction time intervals and the amounts of unreacted aniline and formed p‐aminodiphenylamine is observed. Oxidation of aniline to generate p‐aminodiphenylamine is observed. Oxidation of aniline to generate p‐aminodiphenylamine is the slow step in the plymerization. Furthermore, the tetramer of aniline is used as starting material for polymerization under the same conditions as polymerization of aniline. Direct coupling of two tetramers leading to polymer is not observed. A mechanism of polymerization of aniline is proposed

Explosive growth in geospatial and temporal data as well as the emergence of new technologies emphasize the need for automated discovery of spatiotemporal knowledge. Spatiotemporal data mining studies the process of discovering interesting and previously unknown, but potentially useful patterns from large spatiotemporal databases. It has broad application domains including ecology and environmental management, public safety, transportation, earth science, epidemiology, and climatology. The complexity of spatiotemporal data and intrinsic relationships limits the usefulness of conventional data science techniques for extracting spatiotemporal patterns. In this survey, we review recent computational techniques and tools in spatiotemporal data mining, focusing on several major pattern families: spatiotemporal outlier, spatiotemporal coupling and tele-coupling, spatiotemporal prediction, spatiotemporal partitioning and summarization, spatiotemporal hotspots, and change detection. Compared with other surveys in the literature, this paper emphasizes the statistical foundations of spatiotemporal data mining and provides comprehensive coverage of computational approaches for various pattern families.ISPRS Int. J. Geo-Inf. 2015, 4 2307We also list popular software tools for spatiotemporal data analysis. The survey concludes with a look at future research needs.

A convenient method is presented for determining the rate of polyaniline formation in the electrochemical polymerization of aniline in aqueous HC1 solution utilizing cyclic potential sweep techniques. In this method, the mass of polyaniline deposited on a platinum electrode is correlated with the polymer anodic peak current that is recorded during the polymerization. The rates of polymer deposition were therefore monitored by the increases in the anodic peak current at various concentrations of aniline. A kinetic expression obtained for the polymerization accounts well for the autoacceleration process in the electrochemical polymerization of aniline and supports the mechanism of polymerization in which monomeric aniline is incorporated in the growing polymer. IntroductionAmong all of the electrically conductive polymers, polyaniline is a particularly attractive material because it has a moderately high conductivity upon doping with simple Bronsted acids,'J is easily synthesized by chemical or electrochemical oxidation of aniline,24 has well-behaved electrochemistry$vs and has good environmental stability.2 In comparison with extensive studies on the chemical structure, conduction mechanism, polymerization mechanism, and other properties of polyaniline, few systematic investigations on the kinetics of the electrochemical polymerization of aniline have been reported, although such investigations could lead to a better understanding of the mechanism of polymerization reactions.The overall electrochemical polymerization of aniline has been as a bimolecular reaction involving a radical cation intermediate and a two-electron-transfer process for each step of polymerization. Recently, polyaniline deposition and doping charges8-l0 were used as probes to monitor the electrochemical polymerization of aniline by cyclic potential sweep techniques.

Perfectly ordered states are targets in diverse molecular to microscale systems involving, for example, atomic clusters, protein folding, protein crystallization, nanoparticle superlattices, and colloidal crystals. However, there is no obvious approach to control the assembly of perfectly ordered global free energy minimum structures; near-equilibrium assembly is impractically slow, and faster out-of-equilibrium processes generally terminate in defective states. Here, we demonstrate the rapid and robust assembly of perfect crystals by navigating kinetic bottlenecks using closed-loop control of electric field mediated crystallization of colloidal particles. An optimal policy is computed with dynamic programming using a reaction coordinate based dynamic model. By tracking real-time stochastic particle configurations and adjusting applied fields via feedback, the evolution of unassembled particles is guided through polycrystalline states into single domain crystals. This approach to controlling the assembly of a target structure is based on general principles that make it applicable to a broad range of processes from nano- to microscales (where tuning a global thermodynamic variable yields temporal control over thermal sampling of different states via their relative free energies).

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