Former Research Groups

Future magnetic recording media (storage density &gt; 1 Tbit/in<sup>2</sup>) and high-performance permanent magnets are based on magnetic nanostructures with tailored magnetic properties and specific texture. We develop and characterize extended nanodot arrays and separated nanoparticles, which are produced by advanced lithography methods and annealing at elevated temperatures, respectively.

Former Minerva Research Group Magnetic Nanostructures (Dagmar Goll)

Future magnetic recording media (storage density > 1 Tbit/in2) and high-performance permanent magnets are based on magnetic nanostructures with tailored magnetic properties and specific texture. We develop and characterize extended nanodot arrays and separated nanoparticles, which are produced by advanced lithography methods and annealing at elevated temperatures, respectively. [more]
Proteins are exposed to and tightly regulated by external pertubations, binding partners and mechanical stress, altering their assembly and reactivity. Revealing the molecular driving forces and evolutionary constraints in biomolecular systems is a requirement of designing biological materials aund processes, for applications in materials science and biomedicine, which is the aim of our research.

Former Research Group Protein Mechanics and Evolution (Frauke Gräter)

Proteins are exposed to and tightly regulated by external pertubations, binding partners and mechanical stress, altering their assembly and reactivity. Revealing the molecular driving forces and evolutionary constraints in biomolecular systems is a requirement of designing biological materials aund processes, for applications in materials science and biomedicine, which is the aim of our research. [more]
Our project involves the development of a new generation of coatings for medical products. The concept of all the coatings is based on using a nanolithography technique to create bio-functionalized surfaces that modulate cell behavior.

Former Research Group Applications of cells at tailored interfaces (Raquel Martín)

Our project involves the development of a new generation of coatings for medical products. The concept of all the coatings is based on using a nanolithography technique to create bio-functionalized surfaces that modulate cell behavior. [more]
How do molecular interfacial properties translate into chemical and physical properties? - A large portion of natural matter exists on a micro- and nanoscopic scale. Living cells, organelles, colloidal systems, emulsions, micelles, nanoparticles and many other systems are composed of (sub)micron sized parts. For such systems, the relative interfacial area - and consequently the importance of interface atoms and molecules - increases. Nonlinear light scattering is a promising method to investigate interface properties of micro- and nanoscopic matter.

Former MPG Research Group Nonlinear Spectroscopy of Bio-Interfaces (Sylvie Roke)

How do molecular interfacial properties translate into chemical and physical properties? - A large portion of natural matter exists on a micro- and nanoscopic scale. Living cells, organelles, colloidal systems, emulsions, micelles, nanoparticles and many other systems are composed of (sub)micron sized parts. For such systems, the relative interfacial area - and consequently the importance of interface atoms and molecules - increases. Nonlinear light scattering is a promising method to investigate interface properties of micro- and nanoscopic matter. [more]
What is "Machine Learning"? - In many applications and domains, massive amounts of data are collected and processed every day. To be able to make efficient use of such data, there is an urgent need for tools to extract important pieces of information from the flood of unimportant details. Machine learning is a relatively young discipline that tries to deal with this problem by designing algorithms to analyze large amounts of complex data in a principled way.

Former Research Group Machines Learning Theory (Ulrike von Luxburg)

What is "Machine Learning"? - In many applications and domains, massive amounts of data are collected and processed every day. To be able to make efficient use of such data, there is an urgent need for tools to extract important pieces of information from the flood of unimportant details. Machine learning is a relatively young discipline that tries to deal with this problem by designing algorithms to analyze large amounts of complex data in a principled way. [more]
 
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