A UT Arlington team of researchers has proven that the effect of mass is important, can be measured and has a significant impact on any calculations and measurements at the sub-micrometer scale.
The findings help to better understand movement of nano-sized objects in fluid environments that can be characterized by a low Reynolds number, which often occurs in biological systems. The unconventional results are consistent with Newton’s Second Law of Motion, a well-established law of physics, and imply that mass should be included in the dynamic model of these nano-systems. The most widely accepted models omit mass at that scale.
Alan Bowling, an assistant professor of mechanical and aerospace engineering, collaborated with Samarendra Mohanty, an assistant professor of physics, and doctoral students Mahdi Haghshenas-Jaryani, Bryan Black and Sarvenaz Ghaffari, as well as graduate student James Drake, to make the discovery.
A key advantage of the new model is that it can be used to build computer simulations of nano-sized objects that have drastically reduced run times as compared to a conventional model based on Newton’s second law. These conventional models have run times of days, weeks, months and years while the new model requires only seconds or minutes to run.
In the past, researchers attempted to address the long run time by omitting the mass terms in the model. This resulted in faster run times but, paradoxically, violated Newton’s second law upon which the conventional model was based. The remedy for this paradox was to argue that mass was unimportant at the nano-scale.
However, the new model retains mass, and predicts unexpected motion of nano-sized objects in a fluid that has been experimentally observed. The new model also runs much faster than both the conventional and massless models. It is expected that this new model will significantly accelerate research involving small-scale phenomena.
Research areas that Bowling, Mohanty and collaborators at UT Arlington are currently investigating include cell migration, protein function, bionic medical devices and nanoparticle suspensions for storing thermal energy. However, the applications for the computer simulation in medicine, biology,