Intermolecular forces which govern self-organization of biological and synthetic nanostructures. Thermodynamic aspects of strong (covalent and coulomb interactions) and weak forces (dipolar, hydrogen bonding). Self-assembling systems: micelles, bilayers, and biological membranes. Computer simulations for ôhands-onö experience with nanostructures.
Interaction forces in interfacial systems; fluid interfaces; colloids; amphiphilic systems; interfaces in polymeric systems & polymer composites; liquid coating processes.
Materials for biomedical applications; synthetic polymers, metals and composite materials as biomaterials; biopolymers, dendrimers, hydrogels, polyelectrolytes, drug delivery systems, implants, tissue grafts, dental materials, ophthalmic materials, surgical materials, imaging materials.
Fundamental physico-chemical concepts of polymeric systems in bulk, in solutions and at surfaces. The interactions of polymers in bulk; thermal and structural properties; thermodynamics of polymer solutions in different concentration regimes; polymer adsorption at surfaces; functional polymer thin films/coatings; self-assembly of block copolymers; experimental methods to characterize physicochemical properties, structure and morphology of polymers. Emphasis on recent research results and applications.
Size related properties of nanoparticles; synthetic strategies, main characterization tools, stabilization, surface functionalization and technological applications.
Bioengineering, engineering materials, medicine, polymers, metals, smart materials, surgical implants, surgical instruments, cell and tissue mechanics, microsurgery, self-expanding stents, physical therapy, phase transformations, shape memory alloys.
Introduction, material properties, crystal growth, epitaxy, ion implantation, cleaning, wet etching, photolithography, non-optical lithography, plasma processing, dry etching, metal deposition, diagnostic techniques.
D-group transiton elements and their properties, complexes and coordination compounds bonding and isomerism (cis-trans) in coordination compounds, crystal field theory, ligand field theory, octahedral and tetrahedral complexes, color and magnetism, UV-VIS spectra, introduction to organometallic compounds, 18 electron rule, enzymes.
Linear algebra: Vector and inner product spaces, linear operators, eigenvalue problems; Vector calculus: Review of differential and integral calculus, divergence and Stokes' theorems. Ordinary differential equations: Linear equations, Sturm-Liouville theory and orthogonal functions, system of linear equations; Methods of mathematics for science and engineering students.
A graduate level introduction to matrix-based computing. Stable and efficient algorithms for linear equations, least squares and eigenvalue problems. Both direct and iterative methods are considered and MATLAB is used as a computing environment.
Development and analysis of numerical methods for ODEs, an introduction to numerical optimization methods, and an introduction to random numbers and Monte Carlo simulations. The course starts with a short survey of numerical methods for ODEs. The related topics include stability, consistency, convergence and the issue of stiffness. Then it moves to computational techniques for optimization problems arising in science and engineering. Finally, it discusses random numbers and Monte Carlo simulations. The course combines the theory and applications (such as programming in MATLAB) with the emphasis on algorithms and their mathematical analysis.
Free electron theory of metals. Crystal lattices. Reciprocal lattice. Classification of Bravais lattices. X-ray diffraction and the determination of crystal structures. Electrons in a periodic potential. Tight binding method. Band structures. Semi-classical theory of conduction in metals. Fermi surface. Surface effects.
Classification of solids. Theory of harmonic crystals. Phonons and phonon dispersion relations. Anharmonic effects in crystals. Phonons in metals. Dielectric properties of insulators. Semiconductors. Diamagnetism and paramagnetism. Electron interactions and magnetic structure. Magnetic ordering. Superconductivity.
Classical thermodynamics: enthalpy, entropy, free energies, equilibria; introduction to statistical thermodynamics to describe the properties of materials; kinetic processes; diffusion of mass, heat, energy; fundamentals of rate processes in materials, kinetics of transformations.
Differences between small molecules and polymers; thermosets; thermoplastics. Relationships between molecular structure and properties. Major types of polymers. Supramolecular architectures, composites, copolymers.
The principles and computational methods to study the biological data generated by genome sequencing, gene expressions, protein profiles, and metabolic fluxes. Application of arithmetic, algebraic, graph, pattern matching, sorting and searching algorithms and statistical tools to genome analysis. Applications of Bioinformatics to metabolic engineering, drug design, and biotechnology.
Fundamentals of diffusion; primary mechanisms for mass transfer; mass transfer coupled with chemical reactions; membrane processes and controlled release phenomena.
Recombinant DNA, enzymes and other biomolecules. Molecular genetics. Commercial use of microorganisms. Cellular reactors; bioseparation techniques. Transgenic systems. Gene therapy. Biotechnology applications in environmental, agricultural and pharmaceutical problems.
Quantum mechanical description of the molecular structure; exact solution of simple systems, approximate solutions to molecular problems; variational solutions, molecular orbital theory, Hückel approximation, self-consistent-field theory, semiempirical and ab-initio methods, and electron correlation. Properties such as interaction potential functions, electrostatic potential maps and population analysis will be analyzed using MOPAC, GAUSSIAN 94 and MOLCAD.
An introduction to interactive Python and Jupyter Notebooks, Python built-in data structures, conditional statements, loops, functions, strings and basic input/output, basics of data manipulation and visualization with relevant Python libraries, different types of plots, vector/matrix representations, linear algebra operations, probability/statistics operations, data analysis applications
Relationship between structure, function and dynamics in biomolecules. Overview of the biomolecular databases and application of computational methods to understand molecular interactions; networks. Principles of computational modeling and molecular dynamics of biological systems.
Theory and practice of 3D computer graphics. Topics covered include graphics systems and models; geometric representations and transformations; graphics programming; input and interaction; viewing and projections; compositing and blending; illumination and color models; shading; texture mapping; animation; rendering and implementation; hierarchical and object-oriented modeling; scene graphs; 3D reconstruction and modeling.