February 12, 2010
Discover magazinehas named a research finding by New York University physicists one of the top 100 stories of 2009. In the study, which first appeared in the journal Nature, NYU scientists determined how to count different-sized spheres packed in a container.
“The county-fair challenge of guessing how many gum balls are in a jar is far more than just a game for kids; understanding how objects pack into a particular volume is a fundamental problem of physics and engineering,” wrote the magazine, which ranked the NYU discovery No. 15 in its list of 100 top stories in 2009. “A team of physicists at New York University recently loosened the problem a bit, producing a simple model that predicts the arrangement of randomly packed spherical particles, even when the objects are of different sizes.”
The NYU team, led by Jasna Brujic, an assistant professor in NYU’s Department of Physics, developed an innovative way to tabulate the number of spheres-they created a method for determining how spheres pack from inside the jar, making it easier to more accurately count them.
To answer the question of how particles pack in general, the NYU researchers made a transparent, fluorescent packing of oil droplets in water, which allowed it to record three-dimensional images and examine the local geometry of each member of the pack. In other words, what does a packing look like from the point of view of a grain within-i.e., a “granocentric” view?
Their findings show that packing strongly depends on the size distribution-larger particles pack with more neighbors than do smaller ones. Nevertheless, the average number of contacts per particle always stays the same to preserve mechanical stability.
These experimental clues led the researchers to develop a model that successfully captures the geometry, connectivity, and density of the observed sphere packings. This means that starting from a set of particles of known sizes, the density of packing can be determined, making it possible to guess the number of sweets in the jar. Indeed, the model was able to also predict experimentally observed trends in density for mixtures of particles of two different sizes with varying ratios.
Packing problems are important in technological settings as well, ranging from oil extraction through porous rocks to grain storage in silos to the compaction of pharmaceutical powders into tablets. The ability to predict the packing of polydisperse particles-a range of sizes in a single system-has significant impact on these and related technologies.
The study’s other co-authors were post-doctoral researchers Maxime Clusel and Eric Corwin and junior research scientist Alexander Siemens.
The Brujic Laboratory is part of NYU’s Center for Soft Matter Research. For more on the Brujic Laboratory; for more on the center, click here.
Type: Press Release