What happened to the computation of DNA?

spintronics icon

spintronics

Computer chips are built around strategies to control the flow of electrons, more specifically, their charge. In addition to charge, however, electrons also have angular momentum, or spin, which can be manipulated with magnetic fields. Spintronics emerged in the 1980s, with the idea that spin can be used to represent bits: an address could represent one and the other 0.

In theory, spintronic transistors can be made small, allowing for densely packed chips. But in practice it has been difficult to find the right substances to build them. The researchers say much remains to be done in basic materials science.

However, spintronic technologies have been commercialized in some very specific areas, says Gregory Fuchs, an applied physicist at Cornell University in Ithaca, New York. So far, spintronics’ greatest success has been non-volatile memory, the kind that prevents data loss in the event of a power outage. STT-RAM (for “Spin Transfer Torque Random Access Memory”) has been in production since 2012 and can be found in cloud storage facilities.

memristors

Classical electronics is based on three components: capacitor, resistor and inductor. In 1971, electrical engineer Leon Chua theorized about a fourth component which he called a memristor, for “memory resistor”. In 2008, researchers at Hewlett-Packard developed the first practical memristorusing titanium dioxide.

It was exciting because, in theory, memristors can be used for both memory and logic. The devices “remember” the last applied voltage, so they retain the information even if they are powered off. They also differ from ordinary resistors in that their resistance can change depending on the amount of voltage applied. Such modulation can be used to perform logic operations. If performed within a computer’s memory, these operations can reduce the amount of data that must be transferred between the memory and the processor.

Memristors made their commercial debut as non-volatile storage, called RRAM or ReRAM, for “resistive random access memory”. But the field continues to advance. In 2019, researchers developed a 5832 memristor chip that can be used for artificial intelligence.

carbon nanotubes

Carbon is not an ideal semiconductor. But under the right conditions you can make it form nanotubes which are excellent. The carbon nanotubes were first crafted into transistors in the early 2000s, and studies showed they could be 10 times more energy efficient than silicon.

In fact, of the five alternative transistors discussed here, carbon nanotubes may be the most advanced. In 2013Stanford researchers built the world’s first working computer powered entirely by carbon nanotube transistorsalbeit simple.

But carbon nanotubes tend to roll up into little balls and clump together like spaghetti. Furthermore, most conventional synthesis methods make metallic and semiconducting nanotubes a messy mix. Materials scientists and engineers have been investigating ways to correct and work around these imperfections. In 2019, MIT researchers used improved techniques to build a 16-bit microprocessor with more than 14,000 carbon nanotube transistors. That’s still a long way from a silicon chip with millions or billions of transistors, but it’s progress nonetheless.

DNA computing

In 1994, Leonard Adleman, a computer scientist at the University of Southern California in Los Angeles, made a computer out of DNA soup. He showed that DNA could self-assemble in a test tube to explore all possible paths in the famous “peddler” problem. Experts predicted that the computation of DNA hit silicon-based technology, particularly with massively parallel computing. The researchers later concluded that DNA computation is not fast enough to do that.

But DNA has some advantages. Researchers have shown that it is possible to encode poetry, GIFs and digital movies in the molecules. The potential density is amazing. All the digital data in the world could be stored in a cup of coffee filled with DNA, biological engineers at MIT estimated in an article earlier this year. The problem is cost: A co-author later said that DNA synthesis would have to be six orders of magnitude cheaper to compete with magnetic tape.

Unless researchers can reduce the cost of DNA storage, the stuff of life will remain trapped in cells.

molecular electronics

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It’s a compelling insight: transistors are getting smaller and smaller, so why not go ahead and do from single molecules? Nanometer-scale switches would be a highly cost-effective, densely packed chip. The chips could even assemble themselves thanks to interactions between molecules.

Groups at Hewlett-Packard and elsewhere in the early 2000s scrambled to make chemistry and electronics work together.

But after decades of work, the dream of molecular electronics remains just that. Researchers have discovered that individual molecules can be delicate and function like transistors only under very narrow conditions. “No one has shown how single-molecule devices can be reliably integrated into massively parallel microelectronics,” says Richard McCreery, a chemist at the University of Alberta.

The dream of molecular electronics isn’t entirely dead, but these days it’s largely relegated to chemistry and physics labs, where researchers continue to struggling to make infinitely fickle molecules behave.

What comes next?

Silicon still reigns supreme, but time is running out for everyone’s favorite semiconductor. The last International Roadmap for Devices and Systems (IRDS) it suggests that transistors are expected to stop shrinking after 2028 and that integrated circuits will need to be stacked in three dimensions to continue making faster and more efficient chips possible.

This could be the time when other computing devices find an opportunity, but only in combination with silicon technology. The researchers are exploring hybrid approaches to making chips. In 2017, researchers who had advanced carbon nanotube transistors integrated them with layers of nonvolatile memristors and silicon devices, a prototype of an approach to improve speed and power consumption in computing by moving away from traditional architecture. .

Classic silicon-based chips will continue to progress, says AMD’s Malaya. But, she adds, “I think the future will be heterogeneous, in which all technologies are probably used in a complementary way to traditional computing.”

In other words, the future will remain silicon. But it will also be other things.

Lakshmi Chandrasekaran is a freelance science writer based in Chicago..

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