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January 14th, 2009, 12:04 GMT · By

New Nanoscale MRI Detection Method from IBM

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IBM has been leading in patent application numbers for the past 15 years
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Working in collaboration with the Stanford University Center for Probing the Nanoscale, experts at IBM Research developed a new way of producing magnetic resonance imaging (MRI), about 100 million times finer than existing similar techniques. According to the team that worked on the project, their accomplishment paves the way for innovation in the fields of molecular biology and nanotechnology, as the intricate processes that take place at a nanoscale can now be observed easily.

"MRI is well known as a powerful tool for medical imaging, but its capability for microscopy has always been very limited. Our hope is that nano MRI will eventually allow us to directly image the internal structure of individual protein molecules and molecular complexes, which is key to understanding biological function," says Dan Rugar, who is the manager of nanoscale studies at IBM Research.

"This technology stands to revolutionize the way we look at viruses, bacteria, proteins, and other biological elements," adds Mark Dean, the vice president of strategy and operations at IBM Research, who is also an IBM Fellow.

The goal of using the new technology is to be able to observe the complex structure of proteins, as well as the interactions between them. This could pave the way for a new understanding of how some of the deadliest threats in the world – such as viruses and bacteria – work. It will allow engineers working on various nanotechnology projects to better observe and determine the nature of the forces that, at this point, stop significant progress in this field.

The new device elaborates on the principles of magnetic resonance force microscopy (MRFM), which is a technique that can observe layers of materials hidden by other molecules, and which does not destroy sensitive biological materials, like electron microscopy does. Basically, it detects ultrasmall magnetic forces, which allows it to identify the object it's watching precisely, through its signature.

 

 





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