Is it possible to program a computer without knowing what’s inside? Jim Tour thinks it is, and thanks to the hard work of some applied mathematics students in his research group, he’s compiling the data to prove it.

At issue is the feasibility of programming molecular computers, something Tour, the Chao Professor of Chemistry, professor of mechanical engineering and materials science and professor of computer science, has been working to develop for more than a decade.

Molecular microchips are an ambitious departure from the norm in computing. At present, chipmakers use precision lithography to etch transistors into silicon wafers.

For the past 20 years, the number of transistors crammed into a fingertip-sized chip has doubled every 18 months, and today’s chips contain more than 10 million transistors apiece.

To program a computer, computer scientists rely on the fact that they know precisely where each transistor is and how much current it will take to switch the transistor from “on” to “off.” All computer logic builds from this simple, binary, on-or-off state.

For example, it takes a group of 50 transistors working in concert to form a two-bit adder, a logic circuit capable of adding two whole numbers that are less than or equal to three.

Molecular computing is altogether different. It is based on research by chemists, like Tour, who have shown that individual molecules can perform the same switching functions as the transistors on silicon chips. Since the molecules are about one million times smaller than their solid-state counterparts, the potential processing power of a molecular computer dwarfs anything available today.

One of the chief benefits of the technology is that molecular chips would “self-assemble,” meaning chemists would simply mix up some chemicals and pour them onto a flat film and the chemical transistors would assemble by themselves. That’s a lot cheaper way to build chips than etching. A state-of-the-art chip plant today costs $3 billion and is expected to cost $6 billion by the middle of this decade.

But critics of molecular computing have also pointed to self-assembly as the Achilles’ heel of the technology. Regardless how cheap or powerful the computer is, it’s useless if it can’t be programmed.

However, today’s programming relies on the notion that the programmer is omnipotent: not only do they know exactly what’s inside the chip and where, they also have the power to change the state of any single transistor.

Tour has never listened to those critics. Based upon his experience, both as a teacher and a father, he knows it’s possible to teach pupils without understanding the precise workings of their minds. Tour believes the key to “mortal programming” — programming a computer without knowing what is inside or having the ability to change the state of individual transistors — is to find the right mathematical techniques to simulate the type of learning people experience every day.

“The first time I brought this up in a speech to the Rice faculty three years ago, several people told me it could never be done,” Tour said. “At that point, I knew I needed to talk to students, because students don’t have any preconceived ideas about what is possible or impossible.”

So Tour invited a pair of students to his office — Summer and Chris Husband — a newly married couple of incoming graduate students in applied mathematics.

“The joke around the office is that we didn’t know that we were signing up for the impossible,” Summer Husband said. “Chris and I just thought it was a really intriguing idea, and as graduate students, we wanted to work on a project that was challenging and unique.”

To find out whether mortal programming was feasible, the Husbands wrote a series of computer simulations that mimic what goes on inside a nanocell — a one micron square of film containing several hundred gold nanoparticles interlaced with thousands of molecular switches.

Using a variety of mathematical techniques, Tour’s research team, which included computer science graduate student William L. Van Zandt and undergraduate Lauren S. Wilson, collaborated with Paul D. Franzon and David P. Nackashi of North Carolina State University.

The team showed that it was possible to train nanocells for a variety of purposes. For example, some nanocells were trained as adders and as related systems called half-adders.

The group also showed that nanocells could be trained as logic gates, the elementary building blocks of digital circuitry. Simple logic gates each have two input wires and one output. In solid state components, gates are hardwired to perform specific tasks. An “AND” gate, for example, might be programmed to send a signal only if input A is “on” and input B is “on.”

In a paper titled “Nanocell Logic Gates for Molecular Computing,” published recently in the IEEE Transactions on Nanotechnology, Tour’s research team describes how it trained nanocells.

The findings are significant because nanocells are up to 50 times smaller than the solid-state-based logic gates. Solid-state systems also consume more power and generate more heat than nanocells, and they don’t self-assemble. The published study simply sought to prove the basic underpinnings of mortal programming — i.e., it is possible to train nanocells as logic gates. By necessity, that preliminary work was done from an omniscient point of view.

Now the group is asking the really hard question: Can they conduct “mortal programming” — programming without knowing or being able to change what’s inside the nanocell.

Tour expects to publish that work this year.

Story by: Jade Boyd

Rice Office of Media Relations