Using the tools of physics and design principles, AMOLF researchers study complex matter, such as light at the nanoscale, living matter, designer matter and nanoscale solar cells. These insights open up opportunities to create new functional materials and to find solutions to societal challenges.
SolarNL is a national research, innovation and industrial investment program to bring back and stimulate photovoltaics manufacturing to the Netherlands/Europe. It has been submitted as a proposal for the National …
Floppy or not: artificial intelligence predicts properties of complex metamaterials
Given a 3D piece of origami, can you flatten it without damaging it? Just by looking at the design, the answer is hard to predict, because each and every fold in the design has to be compatible with the flattening process. This is an example of a combinatorial problem. New research led by the University of Amsterdam and AMOLF has demonstrated that machine learning algorithms can accurately and efficiently answer these kinds of questions. This is expected to give a boost to the artificial intelligence-assisted design of complex and functional (meta)materials.
Daughter cells in the intestine do what their mother tells them
AMOLF researchers have discovered what prevents cells in the intestine from dividing rampantly. One hypothesis was that this happens because, on average, for each cell that divides, another cell stops dividing. However, this model failed to provide a good answer to the question as to why cell growth fluctuates so little. Jeroen van Zon and his colleagues have now discovered how that mechanism works by making time-lapse videos of the cells. They noted that two daughter cells from the mother cell always do the same. Either they both divide, or neither divides. As a result of this, cell growth is constant with less chance of cancer and other diseases.