Maze Solving Using Fatty Acid Chemistry

This study demonstrates that the Marangoni flow in a channel network can solve maze problems such as exploring and visualizing the shortest path and finding all possible solutions in a parallel fashion. The Marangoni flow is generated by the pH gradient in a maze filled with an alkaline solution of a fatty acid by introducing a hydrogel block soaked with an acid at the exit. The pH gradient changes the protonation rate of fatty acid molecules, which translates into the surface tension gradient at the liquid–air interface through the maze. Fluid flow maintained by the surface tension gradient (Marangoni flow) can drag water-soluble dye particles toward low pH (exit) at the liquid–air interface. Dye particles placed at the entrance of the maze dissolve during this motion, thus exhibiting and finding the shortest path and all possible paths in a maze

Swarming Behavior of Gradient-Responsive Colloids with Chemical Signaling

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Thermally induced inactivation and aggregation of urease : experiments and population balance modelling

We present a population balance model for enzyme deactivation and aggregation kinetics with a limited number of physically relevant parameters and use this model to analyse the experimental data for thermal inactivation of jack bean urease. The time dependence of the relative enzymatic activity was found to follow the second order kinetics, which was consistent with pre-equilibrated folding/unfolding of the native enzyme, followed by irreversible cluster–cluster aggregation of the non-native enzyme resulting in gradual and permanent loss of enzymatic activity. Monomer–cluster aggregation scenario was considered but was not consistent with the observed kinetic order of monomer disappearance at longer times. We analysed time evolution of the average hydrodynamic radius obtained from dynamic light scattering measurements and by fitting these data with our model, we were able to estimate the value of the unfolding equilibrium constant with a reasonable accuracy (Kc around 0.05 at 80 degrees C). We were also able to make order of magnitude estimates of the maximum number of enzyme molecules in the aggregated clusters (hundreds)as well as the aggregation rate constant of the non-native enzyme

q-GRID: A New Method To Calculate Lattice and Interaction Energies for Molecular Crystals from Electron Densities

We present a new method to calculate lattice and intermolecular interaction energies for molecular crystals from electron densities obtained within the crystalline environment: <i>q</i>-GRID. The electron density is partitioned over a grid, and each grid point is assigned to a specific molecule. Intermolecular interaction energies are calculated as a sum of Coulomb interactions between grid points and nuclei of pairs of molecules and analytical dispersion and repulsion contributions. An advantage of this method is that the interactions within a molecule are automatically excluded. After a description of the new method and the computational setup, three test cases representing different classes of molecular crystals are presented: anthracene, isonicotinamide, and dl-methionine. For the polymorphic compounds, <i>q</i>-GRID is able to obtain the correct ranking of the polymorphic stability. Calculated lattice energies, as a sum of intermolecular interactions, are in good agreement with sublimation enthalpies. The code of <i>q</i>-GRID is made publicly available