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μ is the growth rate of a considered microorganism, μ max is the maximum growth rate of this microorganism, [S] is the concentration of the limiting substrate S for growth, K s is the "half-velocity constant"—the value of [S] when μ/μ max = 0.5. μ max and K s are empirical (experimental) coefficients to the Monod equation. They will ...
Concentration profile in a diffusion-controlled system for a spherical nucleus with radius , where is the concentration of atoms in the solid nucleus, is the concentration in the liquid right at the surface if the nucleus, is the equilibrium concentration in the liquid phase and + is the distance from the nucleus where the equilibrium ...
This is an energy balance which defines the position of the moving interface. Note that this evolving boundary is an unknown (hyper-)surface; hence, Stefan problems are examples of free boundary problems. Analogous problems occur, for example, in the study of porous media flow, mathematical finance and crystal growth from monomer solutions. [1]
Fick's first law relates the diffusive flux to the gradient of the concentration. It postulates that the flux goes from regions of high concentration to regions of low concentration, with a magnitude that is proportional to the concentration gradient (spatial derivative), or in simplistic terms the concept that a solute will move from a region of high concentration to a region of low ...
The solutions on the left are more dilute, compared to the more concentrated solutions on the right. Often in informal, non-technical language, concentration is described in a qualitative way, through the use of adjectives such as "dilute" for solutions of relatively low concentration and "concentrated" for solutions of relatively high ...
The silver concentration in the test sample is the x-intercept of the plot. The dilution factor is multiplied by this initial concentration to determine the original concentration. Matrix effects occur even with methods such as plasma spectrometry , which have a reputation for being relatively free from interferences.
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Another example of hyperbolic growth can be found in queueing theory: the average waiting time of randomly arriving customers grows hyperbolically as a function of the average load ratio of the server. The singularity in this case occurs when the average amount of work arriving to the server equals the server's processing capacity.