Phillip Isabio Pohl

Critical conditions for ferric chloride‐induced flocculation of freshwater algae

The effects of algae concentration, ferric chloride dose, and pH on the flocculation efficiency of the freshwater algae Chlorella zofingiensis can be understood by considering the nature of the electrostatic charges on the algae and precipitate surfaces. Two critical conditions are identified which, when met, result in flocculation efficiencies in excess of 90% for freshwater algae. First, a minimum concentration of ferric chloride is required to overcome the electrostatic stabilization of the algae and promote bridging of algae cells by hydroxide precipitates. At low algae concentrations, the minimum amount of ferric chloride required increases linearly with algae concentration, characteristic of flocculation primarily through electrostatic bridging by hydroxide precipitates. At higher algae concentrations, the minimum required concentration of ferric chloride for flocculation is independent of algae concentration, suggesting a change in the primary flocculation mechanism from bridging to sweep flocculation. Second, the algae must have a negative surface charge. Experiments and surface complexation modeling show that the surface charge of C. zofingiensis is negative above a pH of 4.0 ± 0.3 which agrees well with the minimum pH required for effective flocculation. These critical flocculation criteria can be extended to other freshwater algae to design effective flocculation systems. Biotechnol. Bioeng. 2012; 109:493–501.

Molecular dynamics computer simulation of gas permeation in thin silicalite membranes

In this work we simulate the permeation of Lennard-Jones gases across a zeolite model membrane. Using a newly developed dual control volume grand canonical molecular dynamics technique, we create spatial variation in the chemical potential in a dynamical system and hence an accurate simulation of steady-state pressure-driven diffusion. The molecular sieving nature of microporous zeolites is discussed, and the results from the simulation are compared very favourably with recent experimentalresults of He, H2 and CH4 permeation through ZSM-5 polycrystalline membranes. A massively parallel algorithm is utilized to give a quick and insightful study of this and other microporous materials for use as membranes.

Modeling and risk assessment of a 30‐Year‐old subsurface radioactive‐liquid drain field

The contamination from a 30-year-old radioactive liquid drain field was assessed for movement in the subsurface and potential risks to humans. This assessment included determining field concentrations of cesium 137 (137Cs) and other inorganic contaminants and modeling of the flow and transport of the liquid waste that was sent to the drain field. The field investigation detected no contamination deeper than 15 feet (4.6 m) from the bottom of the drain field. Prediction of the water content of the vadose zone showed no saturated conditions for times greater than 10 years after the known infiltration. Sensitivity analysis of the modeling parameters showed the equilibrium sorption coefficient to be the most important factor in predicting the contaminant plumes. Calibration of modeling results with field data gave a 137Cs sorption coefficient that is within the range of values found in the literature. The risk assessment for the site showed that the contamination poses no significant risk to human health.

Molecular Dynamics Computer Simulations of Diffusion in Porous Silicates

In this work a newly developed dual control volume grand canonical molecular dynamics technique simulates the diffusion of gas in a cylindrical pore. This allows spatial variation of chemical potential and hence an accurate simulation of steady state pressure driven diffusion. The molecular sieving nature of imicroporous imogolite models and the Knudsen effect are discussed and compared with experimental data.

A general framework for modeling growth and division of mammalian cells

BackgroundModeling the cell-division cycle has been practiced for many years. As time has progressed, this work has gone from understanding the basic principles to addressing distinct biological problems, e.g., the nature of the restriction point, how checkpoints operate, the nonlinear dynamics of the cell cycle, the effect of localization, etc. Most models consist of coupled ordinary differential equations developed by the researchers, restricted to deal with the interactions of a limited number of molecules. In the future, cell-cycle modeling--and indeed all modeling of complex biologic processes--will increase in scope and detail.ResultsA framework for modeling complex cell-biologic processes is proposed here. The framework is based on two constructs: one describing the entire lifecycle of a molecule and the second describing the basic cellular machinery. Use of these constructs allows complex models to be built in a straightforward manner that fosters rigor and completeness. To demonstrate the framework, an example model of the mammalian cell cycle is presented that consists of several hundred differential equations of simple mass action kinetics. The model calculates energy usage, amino acid and nucleotide usage, membrane transport, RNA synthesis and destruction, and protein synthesis and destruction for 33 proteins to give an in-depth look at the cell cycle.ConclusionsThe framework presented here addresses how to develop increasingly descriptive models of complex cell-biologic processes. The example model of cellular growth and division constructed with the framework demonstrates that large structured models can be created with the framework, and these models can generate non-trivial descriptions of cellular processes. Predictions from the example model include those at both the molecular level--e.g., Wee1 spontaneously reactivates--and at the system level--e.g., pathways for timing-critical processes must shut down redundant pathways. A future effort is to automatically estimate parameter values that are insensitive to changes.