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Calibri 83ffff̙̙3f3fff3f3f33333f33333.^TU Delft RepositorygD"uuidrepository linktitleauthorcontributorpublication yearabstract
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departmentresearch group programmeprojectcoordinates)uuid:78f026fe-e68f-43db-b230-8943e74369cbDhttp://resolver.tudelft.nl/uuid:78f026fe-e68f-43db-b230-8943e74369cb]Membrane mediated interactions and pattern formation of conical inclusions on a flat membranehVos, Roel (TU Delft Applied Sciences; TU Delft Electrical Engineering, Mathematics and Computer Science)Idema, Timon (mentor); Dubbeldam, Johan (mentor); van der Heul, Duncan (graduation committee); Beaumont, Bertus (mentor); Delft University of Technology (degree granting institution)In this thesis, we investigate interactions between conical inclusions in a lipid bilayer membrane and make predictions about the patterns they form. To find these patterns, we derive an expression for the energy of a membrane as a function of the inclusion locations and search numerically for the pattern<br/>that gives minimum energy.<br/><br/>The energy of a membrane with conical inclusions can be derived using the point particles model with corresponding formalism developed by Dommersnes and Fournier [1]. In this thesis, we apply this formalism to the finite size particles model described by Weikl et al. [2]. We compare the results of both<br/>models for a system of three inclusions, to validate the point particles model s ability to accurately predict equilibrium patterns for conical inclusions. For most non-conical inclusions, however, the point particles model proves inadequate, leaving only the computationally intensive finite size particles model to be used for more complex inclusions.<br/><br/>We develop a new numerical method for finding equilibrium patterns: the gradient descent method. This method is several hundred times faster than the standard Metropolis algorithm, and gives acceptable results. For large systems of inclusions, the method is very sensitive to local minima and has difficulties<br/>merging small groups. The addition of noise in the Brownian motion method proves to be unable to resolve the local minima sensitivity, but we speculate that small bursts of high noise or grouping stable inclusions structures and moving the groups as a whole may be more effective. <br/><br/>Using the point particles model, we found that four-inclusion square-shaped structures and six-inclusion butterfly-shaped structures are favored in all systems with more than six inclusions.<brrLipid membrane; Conical inclusions; Point Particles Model; Finite Size Particles Model; Gradient Descent algorithmenbachelor thesisBSc Applied Mathematics
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