ABSTRACT
To monitor and manage hydrological systems such as brooks, streams, rivers, the use of tracers is a well-established process. Limited number of potential tracers such as salts, isotopes and dyes, make study of hydrological processes a challenge. Traditional tracers find limited use due to lack of multiplexed, multipoint tracing and background noise, among others. In this regard, DNA based tracers possess remarkable advantages including, environmentally friendly, stability, and high sensitivity in addition to showing great potential in the synthesis of ideally unlimited number of unique tracers capable of multipoint tracing. To prevent unintentional losses in the environment during application and easy recovery for analysis, we hereby report DNA encapsulation in silica containing magnetic cores (iron oxide) of two different shapes-spheres and cubes. The iron oxide nanoparticles having size range 10-20 nm, have been synthesized using co-precipitation of iron salts or thermal decomposition of iron oleate precursor in the presence of oleic acid or sodium oleate. Physico-chemical properties such as size, zeta potential, magnetism etc. of the iron oxide nanoparticles have been optimized using different ligands for effective binding of dsDNA, followed by silanization. We report for the first time the effect of surface coating on the magnetic properties of the iron oxide nanoparticles at each stage of functionalization, culminating in silica shells. Efficiency of encapsulation of three different dsDNA molecules has been studied using quantitative polymerase chain reaction (qPCR). Our results show that our DNA based magnetic tracers are excellent candidates for hydrological monitoring with easy recoverability and high signal amplification.
ABSTRACT
Iron oxide (Fe3O4) nanoparticle was synthesized by coprecipitation and was modeled and solved using a hybrid (discrete-continuous) model, based on a kinetic Monte Carlo (kMC) simulation scheme. The latter was combined with the constant number MC method, to improve both speed and accuracy of the simulation. Complete particle size distribution (PSD) from simulation matches very well with PSD of both uncoated and coated (with either polyacrylic acid or dextran) Fe3O4 nanoparticles, obtained from our experiments. The model is general, as the time scales of various processes (nucleation, diffusion-growth and coagulation-growth) are incorporated in rate equations, while, input simulation parameters are experimentally measured quantities. With the help of the validated model, effect of coating agent on coagulation-growth was estimated by a single, fitted, coagulation-efficiency parameter. Our simulation shows that, logarithm of coagulation-efficiency scales linearly with logarithm of inverse of the molecular weight of the coating agent. With this scaling law, our model is able to a priori predict the experimental PSD of Fe3O4 nanoparticles, synthesized with an even higher molecular weight of dextran.
