Courtesy of the researchers and MIT News
MIT CubeSat Sensor
MIT has announced that a team of researchers has created the "first completely digitally manufactured plasma sensors" for orbiting spacecraft. The sensors, also known as retarding potential analyzers (RPAs), are used by satellites to determine the chemical composition and ion energy distribution of the atmosphere.
The 3D printed and laser-cuit hardware performed just as well as the state-of-the-art semiconductor plasma sensors that are manufactured in a cleanroom. The sensors manufactured in the cleanroom are expensive and require weeks of intricate fabrication, whereas the 3D printed sensors can be produced for tens of dollars in a matter of days.
The low cost and quick production of the sensors make them ideal for CubeSats. These are inexpensive, low-power and lightweight satellites that are often used for communication and environmental monitoring in Earth’s upper atmosphere.
A glass-ceramic was used in a fabrication process that was developed for 3D printing with plastics. This meant the researchers were able to create sensors with complex shapes that could withstand the wide temperature swings a spacecraft would encounter in lower Earth orbit.
“Additive manufacturing can make a big difference in the future of space hardware. Some people think that when you 3D print something, you have to concede less performance. But we’ve shown that is not always the case. Sometimes there is nothing to trade off,” said Luis Fernando Velásquez-Garcia, a principal scientist in MIT’s Microsystems Technology Laboratories (MTL) and senior author of the paper presenting the new plasma sensors.
An RPA was first used in a space mission in 1959. The sensors detect energy in ions, or charged particles, that are floating in plasma, which is a superheated mix of molecules present in the Earth’s upper atmosphere.
Courtesy of the researchers
With the sensors aboard an orbiting spacecraft like a CubeSat, the instruments measure energy and conduct chemical analyses that can help scientists predict the weather or monitor climate change.
Key to the success of an RPA is the housing structure that aligns with the series of electrically charged meshes. The structure must be electrically insulating whilst withstanding sudden swings in temperature. A printable, glass-ceramic material that displays these properties, known as Vitrolite, was used.
Vitrolite was pioneered in the early 1900s, and was often used in colourful tiles, and became common in art deco buildings. The material is able to withstand temperatures up to 800 degrees Celsius without breaking down. Polymers used in semiconductor RPAs start to melt at 400 degrees Celsius.
Typically with the 3D printing process for ceramics, the laser will leave the material coarse and weak from the heat. The MIT researchers used vat polymerisation, a process where a 3D structure is built one layer at a time by submerging it repeatedly into a vat of liquid material, in this case Vitrolite.
UV light is used to cure the material after each layer is added, before it is submerged in the vat again. Each layer is only 100 microns thick (roughly the diameter of a human hair), enabling the creation of smooth, pore-free, complex ceramic shapes.
Additive manufacturing technology allows objects to be designed very intricately. The precision allowed the researchers to create laser-cut meshes with unique shapes so the holes line up perfectly when they were set inside the RPA housing.
The high precision could enable 3D printed sensors for applications in fusion energy research or supersonic flight. According to the researchers, the rapid prototyping process could even spur more innovation in satellite and spacecraft design.
Velásquez-Garcia added: “If you want to innovate, you need to be able to fail and afford the risk. Additive manufacturing is a very different way to make space hardware and if it fails, it doesn’t matter because I can make a new version very quickly and inexpensively, and really iterate on the design. It is an ideal sandbox for researchers.”
MIT researchers often involve additive manufacturing in their work. Recently, a team at the institute created a machine-learning system that could adjust the 3D printing process to correct errors in real time.
Courtesy of the researchers
