Mass fluctuation kinetics: Capturing stochastic effects in systems of chemical reactions through coupled meanvariance computationsAccurate hybrid stochastic simulation of a system of coupled chemical or biochemical reactionsThe kinetic master equation for the title processes can be formulated as a traditional deterministic set of coupled differential reaction-rate equations, or, alternatively, as a stochastic process in which each reaction is a random-walk transition in energy-species space. This stochastic description is the basis for three methods we describe here to numerically solve the kinetic master equation for chemically activated unimolecular reactions. The first method allows the calculation of the complete time evolution within a given mechanism, and is based on Gillespie's exact stochastic method ͑ESM͒. It is essentially a Monte Carlo simulation of the stochastic reaction processes. The second method allows for the direct calculation of the steady-state product distribution ͑DCPD͒. It describes the random walk within the framework of a discrete time Markov chain, and reduces the calculation of the steady-state product distribution to a fairly simple matrix algebra problem. The third method calculates the steady-state population of the intermediates ͑CSSPI͒, reformulating the solution of the master equation as an eigenvector problem generated by the description as a continuous time Markov chain. To our knowledge, the DCPD method has not been described before. Also, this is the first time that a CSSPI model is used explicitly in this type of calculation. The three methods are illustrated using the simple HϩHNCO reaction, important in the RAPRENO x mechanism for NO x removal from flue gases.
Nanoscaled interdigitated electrode arrays were made with Deep U.V. lithography. Electrode widths and spacings from 500 nm down to 250 nm were achieved on large active areas (OS mm x 1 mm). These electrodes allow for the detection of affinity binding of biomolecular structures (e.g. antigens, DNA) by impedimetric measurements. Such sensor is developed, theoretically analyzed, experimentally characterized, and will be demonstrated as an affinity biosensor.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.