Oct 10 2022Reviewed by Alex Smith
Computer chips contain billions of microscopic transistors that allow robust computation, but also produce an enormous amount of heat.
This image shows a nanomaterial that has been digitized so its structure can be optimized using the researchers' computational technique, which designs nanomaterials that conduct heat in specific ways. Image Credit: Courtesy of the researchers, edited by MIT News.
Increased heat can decelerate a computer processor and render it less efficient and dependable. Engineers use heat sinks to cool off the chips, occasionally with liquid cooling systems or fans; however, these approaches mostly necessitate a lot of energy to work.
Scientists at MIT have adopted a diverse method. They created an algorithm and software platform that can automatically develop a nanoscale material that can transmit heat in a specific manner, such as directing heat in only one direction.
As these materials are measured in nanometers (a human hair is around 80,000 nm wide), they could be employed in computer chips that can disperse heat on their own because of the material’s geometry.
The scientists created their system by taking computational methods conventionally used to create large structures and then adapting them to produce nanoscale materials with specific thermal properties.
The scientists engineered a material that can transmit heat along a chosen direction (an effect called thermal anisotropy) and a material that can perfectly turn heat into electricity. They employ the latter design to produce a nanostructured silicon device for waste heat recovery at MIT.nano.
Researchers usually use a mixture of guesswork and trial and error to enhance a nanomaterial’s capacity to transmit heat. Instead, a person could input the preferred thermal properties into their software platform and receive a design that can accomplish those properties and that can credibly be made.
Besides producing computer chips that can disperse heat, the method could be used to create materials that can perfectly turn heat into electricity, referred to as thermoelectric materials.
These materials could trap waste heat from rockets' engines, for instance, and use it to help drive the spacecraft, explains study lead author Giuseppe Romano, a research scientist at MIT’s Institute for Soldier Nanotechnology and a member of the MIT-IBM Watson AI Lab.
The goal here to design these nanostructured materials that transport heat very differently than any natural materials.
Steven Johnson, Senior Study Author and Professor, Applied Mathematics and Physics, Massachusetts Institute of Technology
Steven Johnson also heads the Nanostructures and Computation Group within the MIT Research Laboratory for Electronics.
“But the question is, how do you do this as efficiently as possible, rather than just trying a bunch of different things based on intuition? Giuseppe applied computational design to let the computer explore over many possible shapes and come up the one that has the best possible thermal properties,” Steven Johnson added.
Their research paper has been recently published in Structural and Multidisciplinary Optimization.
Controlling Vibrations
Heat in semiconductors moves due to vibrations. Molecules vibrate faster as the heat increases, causing adjacent groups of molecules to begin vibrating, and so on, pushing the heat through a material like a crowd of sports fans doing “the wave” at a baseball event. At the atomic scale, these waves of vibrations are trapped into discrete packets of energy, called phonons.
Scientists want to develop nanoscale materials capable of controlling heat transfer in pre-determined ways, such as a material that transmits more heat in a vertical direction and less heat in a horizontal direction. To achieve this, they must regulate how phonons travel through the material.
The team concentrated on materials called periodic nanostructures, which are created by a lattice of structures with a random shape. Altering the arrangement or the sizes of these structures may greatly change the thermal properties of the total system.
In theory, the scientists could have made certain parts of these structures extremely narrow for phonons to travel through, regulating how heat can move through the material. However, there are virtually countless configurations, so discovering how to organize them for some particular thermal properties using only instinct would have been very challenging.
Instead, we borrowed a computational technique that was traditionally developed for structures like bridges. Imagine that we transform a material into a picture, and then we find the best pixel distribution that gives us the prescribed property.
Giuseppe Romano, Lead Author and Research Scientist, Institute for Soldier Nanotechnology, Massachusetts Institute of Technology
Using this computational method, an algorithm has to discover whether or not to put 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. The way you have to optimize this is to start with some guess and then evolve it in a way of continuously deforming the structure to make it better and better.
Steven Johnson, Senior Study Author and Professor, Applied Mathematics and Physics, Massachusetts Institute of Technology
However, this kind of enhancement is very hard to realize with nanomaterials.
Firstly, the physics of thermal transport acts inversely at the nanoscale, so the standard equations will not work. Additionally, modeling the flow of phonons is particularly complex. One must know where they are in three-dimensional (3D) space, how quickly they are flowing, and in what direction.
Taming Complex Equations
The scientists formulated a new method, called the transmission interpolation method, that allows these very complex equations to act in a way that the algorithm can adapt. With this technique, the computer can easily and continuously deform the material dispersal until it realizes the anticipated thermal properties instead of trying pixel by pixel at a time.
The MIT team also developed an open-source software system and a web app that allows users to input preferred thermal features and obtain a manufacturable nanoscale material structure. By rendering the system open source, the scientists hope to stimulate other researchers to add to this study area.
Equipped with this new tool, MIT scientists are analyzing other materials that can be improved using this system, namely metal alloys, which could pave the way to new applications. They are also exploring approaches to enhance thermal conductivity in three dimensions, instead of only horizontal and vertical.
Kui Ren states, “As far as I know, the paper by Romano and Johnson is among the first ones in performing topological optimal material design for nanoscale heat transfer with the phonon Boltzmann transport model.”
“The technical novelty of their method is mainly 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 structure of the material can be calculated,” says Kui Ren, a professor of applied mathematics at Columbia University, who was not involved with this work.
The idea is quite novel and general, and I can imagine that this idea will soon be adopted for topological design objectives with more complicated heat transport models, and in many other regimes of heat transfer applications.
Kui Ren, Professor, Applied Mathematics, Columbia University
The MIT-IBM Watson AI Laboratory partially supported this study.
Journal Reference:
Romano, G. & Johnson, S.G. (2022) Inverse design in nanoscale heat transport via interpolating interfacial phonon transmission. Structural and Multidisciplinary Optimization. doi.org/10.1007/s00158-022-03392-w.
Source: https://mit.edu/