Computer chips are filled with billions of microscopic transistors that enable powerful computing, but also generate a lot of heat. Heat buildup can slow down a computer’s processor, making it less efficient and less reliable. Engineers use heat sinks to cool chips, sometimes with fans or liquid cooling systems; however, these methods often require a lot of energy to operate.
The MIT researchers took a different approach. They developed an algorithm and software system capable of automatically designing a nanoscale material capable of conducting heat in a specific way, such as channeling heat in a single direction.
Since these materials are measured in nanometers (a human hair is about 80,000 nanometers wide), they could be used in computer chips that can dissipate heat on their own due to the geometry of the material.
The researchers developed their system by taking computational techniques traditionally used to develop large structures and adapting them to create nanoscale materials with defined thermal properties.
They designed a material capable of conducting heat in a preferred direction (an effect known as thermal anisotropy) and a material capable of efficiently converting heat into electricity. They are using this latest design to fabricate a nanostructured silicon device for waste heat harvesting at MIT.nano.
Scientists typically use a combination of guesswork and trial and error to optimize a nanomaterial’s ability to conduct heat. Instead, someone could input the desired thermal properties into their software system and receive a design that can achieve those properties and can be realistically manufactured.
In addition to creating computer chips that can dissipate heat, the technique could be used to develop materials that can efficiently convert heat into electricity, called thermoelectric materials. These materials could capture waste heat from a rocket’s engines, for example, and use it to power the spacecraft, says lead author Giuseppe Romano, a researcher at MIT’s Soldier Nanotechnology Institute and MIT Fellow. -IBM Watson AI Lab.
“The goal here is to design these nanostructured materials that transport heat very differently from any natural materials,” says lead author Steven Johnson, a professor of applied math and physics who leads the Nanostructures and Computation group at from the MIT Electronic Research Laboratory. “But the question is, how do you do that as efficiently as possible, rather than just trying a bunch of different things based on intuition? Giuseppe applied computer design to allow the computer to explore many possible shapes and find the one with the best possible thermal properties.
Their research paper is published today in Structural and multidisciplinary optimization.
Heat in semiconductors moves through vibration. Molecules vibrate faster when they heat up, causing nearby groups of molecules to vibrate, and so on, moving heat through a material like a crowd of fans doing the “wave” at a baseball game. At the atomic scale, these vibration waves are captured in discrete packets of energy, called phonons.
Researchers want to create nanoscale materials that control heat transfer in very specific ways, such as a material that conducts more heat in a horizontal direction and less heat in a vertical direction. To do this, they must control how the phonons move through the material.
The materials they focused on are known as periodic nanostructures, made up of a network of arbitrarily shaped structures. Changing the sizes or arrangement of these structures can dramatically change the thermal properties of the entire system.
In principle, the researchers could have made parts of these structures too narrow for phonons to pass through, controlling how heat can move through the material. But there are virtually endless configurations, so it would have been extremely difficult to figure out how to arrange them for some specific thermal properties using just intuition.
“Instead, we borrowed a calculation technique traditionally developed for structures like bridges. Imagine that we transform a material into an image and then find the best pixel distribution that gives us the prescribed property,” says Romano.
Using this computational technique, an algorithm must determine whether or not to place a hole at each pixel in the image.
“Because there are millions of pixels, if you just try each one, there are just too many possibilities to simulate. continuously deforming the structure to make it better and better,” says Johnson.
But this type of optimization is very difficult to achieve with nanomaterials.
For one thing, the physics of thermal transport behaves differently at the nanoscale, so the usual equations don’t work. Moreover, the modeling of the movement of phonons is particularly complex. You have to know where they are in three-dimensional space as well as how fast they are moving and in what direction.
Taming complex equations
The researchers developed a new technique, known as the method of transmission interpolation, which allows these very complex equations to behave in a way that the algorithm can handle. With this method, the computer can smoothly and continuously distort the material distribution until it achieves the desired thermal properties, rather than trying each pixel one by one.
The team also created a open-source software system and one Web application which allows a user to enter desired thermal properties and receive a fabricable nanoscale material structure. By making the system open source, the researchers hope to inspire other scientists to contribute to this area of research.
With this new tool in hand, researchers are exploring other materials that can be optimized through this system, such as metal alloys, which could open the door to new applications. They are also investigating methods to optimize thermal conductivity in three dimensions, rather than just horizontally and vertically.
“As far as I know, Romano and Johnson’s paper is among the first to achieve optimal material topology design for nanoscale heat transfer with Boltzmann’s phonon transport model. The technical novelty of their method mainly lies in a clever integration of a transmission interpolation method with the Boltzmann transport model so that the gradient of the design objective function with respect to the material structure can be calculated,” explains Kui Ren, professor of applied mathematics at Columbia University, who was not involved in this work.”The idea is quite new and general, and I can imagine that this idea will soon be adopted for topological design purposes with more complicated heat transport models, and in many other regimes of heat transfer applications.”
This research was partially funded by the MIT-IBM Watson AI Laboratory.