A Big Bet on Nanotechnology Has Paid Off

Sat, 09 Oct 2021 05:00:00 GMT
Scientific American - Technology

The National Nanotechnology Initiative promised a lot. It has delivered more

We're now more than two decades out from the initial announcement of the National Nanotechnology Initiative, a federal program from President Bill Clinton founded in 2000 to support nanotechnology research and development in universities, government agencies and industry laboratories across the United States.

In the wake of the NNI, my university, Northwestern University, made the strategic decision to establish the International Institute for Nanotechnology, which now represents more than $1 billion in pure nanotechnology research, educational programs and supporting infrastructure.

There is a beautifully simple principle at the heart of modern nanotechnology research.

The miniaturization of electronics would have continued without the NNI. What the NNI did was move nanotechnology into places it had not significantly ventured before, like the medical, chemical, optical and transportation industries.

Early nanotechnology research was at the foundation of rapid tests that made it possible for schools and society to reopen during the COVID-19 pandemic.

Many of the powerful nucleic acid and antigen tests that definitively diagnose disease are based upon nanotechnology platforms.

As a new route to inter- or transdisciplinary research, which was at the core of the NNI, nanotechnology has driven a new narrative in STEM: collaboration.

Nanotechnology has captured the imagination of a generation of materials scientists, chemists, physicists and biologists to synthesize and understand new materials; as well as inspiring engineers who are trained to develop tools for making and manipulating such structures; and doctors who can use them in the clinic.

Collaborative nanotechnology research at our institute unites faculty members from 32 departments across four schools at Northwestern.

It's important to note that they are a source of high-quality big data, powering new discoveries in machine learning and artificial intelligence geared towards materials discovery.

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