This is significant progress on molecular computing with molecular switches that is highly parallel and using cellular automata.
* This molecular processor can also heal itself if there is a defect
* The building block of this computer is an organic compound known as 2,3-dichloro-5,6-dicyano-p-benzoquinone, or DDQ for short. This molecule can basically switch between four different electrically conductive states — think of a ring with four spokes.
* molecules of DDQ were deposited onto a surface of gold, which then spontaneously assembled into two layers, each a hexagonal grid of molecules.
* at least 300 molecules in the system interact together like a massively parallel computer, each changing states when data is written into the system. (300 molecular switches operating as cellular automata)
* One important weakness of the system is how it depends on scanning tunneling microscopy, which is a slow process. In the future, it may be possible to use multiple tips to simultaneously scan many molecules at one time, Pati suggested.
* Since these molecules assemble themselves into grids, scaling them up to a larger system will not be a problem. The team’s next target is a computer employing 1,000 molecular switches.
Abstract – Modern computers operate at enormous speeds—capable of executing in excess of 10^13 instructions per second—but their sequential approach to processing, by which logical operations are performed one after another, has remained unchanged since the 1950s. In contrast, although individual neurons of the human brain fire at around just 10^3 times per second, the simultaneous collective action of millions of neurons enables them to complete certain tasks more efficiently than even the fastest supercomputer. Here we demonstrate an assembly of molecular switches that simultaneously interact to perform a variety of computational tasks including conventional digital logic, calculating Voronoi diagrams, and simulating natural phenomena such as heat diffusion and cancer growth. As well as representing a conceptual shift from serial-processing with static architectures, our parallel, dynamically reconfigurable approach could provide a means to solve otherwise intractable computational problems.