Difference between revisions of "Cohan Mechanism"
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The Cohan mechanism, also known as the Cohan theory of capillary condensation, describes the condensation of liquid in a cylindrical pore. The Cohan mechanism states that on adsorption, pores do not fill vertically, but instead fill radially. This it thought to explain the hysteretic behavior seen in the adsorption-desorption process for porous materials. | The Cohan mechanism, also known as the Cohan theory of capillary condensation, describes the condensation of liquid in a cylindrical pore. The Cohan mechanism states that on adsorption, pores do not fill vertically, but instead fill radially. This it thought to explain the hysteretic behavior seen in the adsorption-desorption process for porous materials. | ||
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+ | Figure 1 shows a typical adsorption-desorption isotherm is shown for a porous solid. A hysteresis is evident, indicating that some adsorbate is retained during desorption and released at p/p0 value less than that required to cause adsorption. | ||
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+ | <math>p/p0 = exp (-2\sigma * v_m / rRT) </math> | ||
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+ | [[Image:Porous.jpg|thumb|300px| Isotherm for a porous solid of uniform pore radius.]] | ||
Revision as of 19:05, 5 October 2009
The Cohan mechanism, also known as the Cohan theory of capillary condensation, describes the condensation of liquid in a cylindrical pore. The Cohan mechanism states that on adsorption, pores do not fill vertically, but instead fill radially. This it thought to explain the hysteretic behavior seen in the adsorption-desorption process for porous materials.
Figure 1 shows a typical adsorption-desorption isotherm is shown for a porous solid. A hysteresis is evident, indicating that some adsorbate is retained during desorption and released at p/p0 value less than that required to cause adsorption.
<math>p/p0 = exp (-2\sigma * v_m / rRT) </math>
For a given pore radius r, adsorption with radial capillary condensation occurs at
<math>p_{adsorption} = p_0 exp (-\sigma * v_m / rRT) </math>
whilst for desportion,
<math>p_{desorption} = p_0 exp (-2\sigma * v_m / rRT) </math>