Delft student team develops gene doping detection method and wins prizes in worldwide Synthetic Biology competition
TU Delft students have devised and developed a method for detecting gene doping. This method, called ADOPE (Advanced Detection of Performance Enhancement) has the potential to combat the abuse of gene therapy in sport. Through this project, the students in the iGEM team aim to highlight how important it is that synthetic biology is used safely. They presented their idea at last week’s International Genetically Engineered Machine (iGEM) competition in Boston, winning prizes for their new application and product design.
Student-built Delft exoskeleton wins international Cybathlon
The new MARCH III by TU Delft student team Project MARCH has won the Cybathlon Experience in Düsseldorf, the international obstacle race for exoskeletons. Entrants from several countries competed in the test of robotic harnesses for people with paraplegia, ending on 29 September. Together with ‘pilot’ Sjaan Quirijns, who has had paraplegia since 2000, MARCH III achieved the fastest time and the highest number of points. Thanks to improvements to the suit and intensive training of its wearer, the team successfully completed a four-obstacle course in just under 9.5 minutes. Project MARCH gained particular plaudits for the independent functioning of its device.
Students win world championship with high-tech recumbent bike
Cyclist Lieke de Cock won the world championship for cycling in the Nevada desert in the US with a speed of 120 km/h.
Newspaper articles on TU Delft on-site cycling aerodynamics experiments
Delft simulation model for optimum performance during team time trials
During his Mechanical Engineering degree programme, TU Delft student Mats Overtoom came up with a mathematical model that could provide answers to such questions as ‘What is the optimum changeover schedule for a cyclist in a team time trial?’ and ‘How fast does he need to cycle up a mountain to reach optimum performance?’. The input for the simulation model was data from cyclists from Team Sunweb and specific track information. It gives the Dumoulin team strategic tips for optimum performance, the best order of the cyclists and the length of turns on the front during a team time trial.