**Syntax:**

app_style membrane w01 w11 mu

- membrane = style name of this application
- w01 = sovent-protein interaction energy (typically 1.25)
- w11 = sovent-solvent interaction energy (typically 1.0)
- mu = chemical potential to insert a solvent (typically -2.0)

**Examples:**

app_style membrane 1.25 1.0 -3.0

**Description:**

This is an on-lattice application which evolves a membrane model, where each lattice site is in one of 3 states: lipid, water, or protein. Sites flip their state as the model evolves. See the paper of (Sarkisov) for a description of the model and its applications to porous media. Here it is used to model the state of a lipid membrane around embedded proteins, such as one enclosing a biological cell.

In the model, protein sites are defined by the inclusion command and never change. The remaining sites are initially lipid and can flip between solvent and lipid as the model evolves. Typically, water will coat the surface of the proteins and create a pore in between multiple proteins if they are close enough together.

The Hamiltonian represeting the energy of site I is as follows:

H = - mu x_i - Sum_j (w11 a_ij + w01 b_ij)

where Sum_j is a sum over all the neighbor sites of site I, x_i = 1 if site I is solvent and 0 otherwise, a_ij = 1 if both the I,J sites are solvent and 0 otherwise, b_ij = 1 if one of the I,J sites is solvent and the other is protein and 0 otherwise. Mu and w11 and w01 are user inputs. As discussed in the paper, this is essentially a lattice gas grand-canonical Monte Carlo model, which is isomorphic to an Ising model. The mu term is a penalty for inserting solvent which prevents the system from becoming all solvent, which the 2nd term would prefer.

As explained on this page, this application can be evolved by either a kinetic Monte Carlo (KMC) or rejection KMC (rKMC) algorithm. You must thus define a KMC solver or sweeping method to be used with the application via the solve_style or sweep commands.

For solution by a KMC algorithm, a site event is a spin flip from a lipid to fluid state or vice versa. The probability of the event is min[1,exp(-dE/kT)], where dE = Efinal - Einitial using the Hamiltonian defined above for the energy of the site, and T is the temperature of the system defined by the temperature command (which includes the Boltzmann constant k implicitly).

For solution by a Metropolis algorithm, the site is set randomly to fluid or lipid, unless it is a protein site in which case it is skipped altogether. The energy change dE = Efinal - Einitial is calculated, as is a uniform random number R between 0 and 1. The new state is accepted if R < min[1,exp(-dE/kT)], else it is rejected.

The following additional commands are defined by these applications:

inclusion | specify which sites are proteins |

temperature | set Monte Carlo temperature |

**Restrictions:** none

**Related commands:** none

**Default:** none

**(Sarkisov)** Sarkisov and Monson, Phys Rev E, 65, 011202 (2001).