Sixteen isolated iron magnetic particles [FIG. A]—arranged in some of the smallest, ordered magnetic arrays ever made—are shown in this image captured by a scanning electron microscope. Each dot is in reality a tiny bar magnet, standing on end. These so-called "nano-pillars" stand about 150 nanometers (150 billionths of a meter) tall and are about nine nanometers in diameter, equivalent to the width of about 30 iron atoms. These particles are so small that roughly six million of them can fit inside the period at the end of this sentence. MARTECH physicists designed and built the particles in research aimed at testing the limits of just how small magnetic particles can be made without losing their magnetic characteristics. Such research is fundamental to computer technology that relentlessly pursues smaller, yet more powerful memory storage devices.

[FIG. B]—This image shows the densest configuration of magnetic particles yet achieved by MARTECH researchers, an array of roughly 100 billion particles per square inch. This ultra-dense aggregation is equivalent to about 100 billion bits (100 gigabits) of computer memory storage.

SMALLER THAN A VIRUS [FIG. C]—Nearly two dozen of the MARTECH particles placed side by side could fit across the diameter of an average-sized, common flu virus particle (shown).

[FIG. D]—How MARTECH's "nano-pillars" switch their magnetic polarization is simulated by a group of scientists within FSU's School for Computational Science and Information Technology. Led by researcher Per Arne Rikvold and Mark Novotny, the group specializes in developing computational methods to study magnetization switching in nano-sized magnetic particles, a phenomenon still not clearly understood. This simulation shows how a complete magnetic field reversal (i.e. from "up" to "down" or "0" to "1" in digital language) in a single nano-pillar might occur in a real lab test. Interestingly, Rikvold and Novotny have found that the characteristics of such switching can be significantly manipulated by changing the shape of the nanoparticles themselves. Sharper, more tapered pillars, for example, computationally result in more stabilized switching.