The winners were announced at a reception held by the university's Office of Technology Commercialization, which sponsors the annual event. Winning inventions are selected each year by an independent panel based on creativity, novelty and potential overall benefit to society. Among the 33 past winning inventions, 25 have been licensed or optioned and five are base technologies for University of Maryland start-up companies.
Physical Science Invention of the Year
The 2001 Physical Science Invention of the Year is a process to create polymer-based nanocomposites that could save chip manufacturers time and money while greatly increasing the memory capacity of computer chips, CDs and other high-density information storage devices. On computer hard disks, data is recorded and stored as tiny areas of magnetized iron or chromium oxide. University of Maryland associate professor of chemical engineering Peter Kofinas and research graduate assistants Steven Bullock and Sufi Ahmed have developed a method that produces polymer-templated nanoparticles based on cobalt iron oxide. These nanoparticles have superparamagnetic properties and can act as a data storage material. The nanoparticles, which are smaller than the wavelength of light, self-assemble at room temperature when created using the method of Kofinas, Bullock and Ahmed. Each individual nanoparticle of the oxide developed by their process can hold one bit of informationCa zero and a one. Each square centimeter of this nanocomposite oxide can store 110 gigabytes of data per square centimeter, which is a 1,000-times improvement over the information storage capabilities of today's computer chips.
The patent-pending polymer and its manufacturing process could be developed into new plastic magnetic random-access memories to replace the standard types of random-access memories currently used in computer chips. This new memory would be cheaper, faster, denser and non-volatile. It also would use significantly less power. These oxides could be used for many other applications as well, including ferrofluids for biomedical applications and magnetic sensor technologies, such as DVD and CD-ROM discs.
Other finalists in the physical science category were "Biomimetic Wing or Blade Drive Mechanism for Pitching, Flapping, Translational and Rotational Motion" developed by Darryll Pines and Felipe Bohorquez; and "InP-Integrated Optical Micro-Resonator Technology," developed by Rohit Grover, John Hryniewicz, Oliver King, Vien Van, Philippe Absil, Lynn Calhoun and Ping-Tong Ho.
Information Science Invention of the Year
It has become increasingly hard to manage and analyze the network traffic dynamics of large-scale networked IT environments. And the traditionally used network visualization tools, which operate in two-dimensional space, are becoming inadequate and aged. To address these problems, Ravindra Kulkarni, a faculty research assistant in the Office of Information Technology, has developed a three-dimensional/four-dimensional network traffic visualization technique that is both integrated with a network forensics database and deliverable over the Web.
The prototype developed by Kulkarni clearly identifies both normal patterns of network traffic and deviations from the norm and creates multiple views that provide rapid visualization of the network traffic. It also maps the Internet protocol, or IP, session parameters (such as the port and network address) to three-dimensional spatial axes, color and time, which enables accelerated visual data mining and event reconstructionCimportant keys to network forensics and warding off hackers and cyber thieves.
In addition to network security and forensics, this technology could also be used for remote visualization in telemedicine, visualization of large multiparameter databases, interactive shared data collaboration, metadata visualization, and to enable public access to government and corporate data archives.
Other finalists in the information science category were "Billing and Accounts Receivables System 2000," developed by Ann Holmes and Muddu Salem; and "Automated Inclusion and Quantification of Common Cause Failures in System Fault Trees of the Quantitative Risk Assessment System (QRAS)," developed by Ali Mosleh, Carol Smidts, Franciscus Groen, and Swaminathan Sankaran.
