Photolithography entails manipulating gentle to exactly etch options onto a floor, and is usually used to manufacture laptop chips and optical gadgets like lenses. However tiny deviations in the course of the manufacturing course of typically trigger these gadgets to fall wanting their designers’ intentions.
To assist shut this design-to-manufacturing hole, researchers from MIT and the Chinese language College of Hong Kong used machine studying to construct a digital simulator that mimics a particular photolithography manufacturing course of. Their method makes use of actual knowledge gathered from the photolithography system, so it may extra precisely mannequin how the system would fabricate a design.
The researchers combine this simulator right into a design framework, together with one other digital simulator that emulates the efficiency of the fabricated system in downstream duties, reminiscent of producing photos with computational cameras. These linked simulators allow a consumer to provide an optical system that higher matches its design and reaches the very best job efficiency.
This method may assist scientists and engineers create extra correct and environment friendly optical gadgets for purposes like cellular cameras, augmented actuality, medical imaging, leisure, and telecommunications. And since the pipeline of studying the digital simulator makes use of real-world knowledge, it may be utilized to a variety of photolithography programs.
“This concept sounds easy, however the causes individuals haven’t tried this earlier than are that actual knowledge will be costly and there are not any precedents for learn how to successfully coordinate the software program and {hardware} to construct a high-fidelity dataset,” says Cheng Zheng, a mechanical engineering graduate pupil who’s co-lead writer of an open-access paper describing the work. “Now we have taken dangers and performed intensive exploration, for instance, growing and making an attempt characterization instruments and data-exploration methods, to find out a working scheme. The result’s surprisingly good, displaying that actual knowledge work rather more effectively and exactly than knowledge generated by simulators composed of analytical equations. Though it may be costly and one can really feel clueless originally, it’s price doing.”
Zheng wrote the paper with co-lead writer Guangyuan Zhao, a graduate pupil on the Chinese language College of Hong Kong; and her advisor, Peter T. So, a professor of mechanical engineering and organic engineering at MIT. The analysis will probably be introduced on the SIGGRAPH Asia Convention.
Printing with gentle
Photolithography entails projecting a sample of sunshine onto a floor, which causes a chemical response that etches options into the substrate. Nonetheless, the fabricated system finally ends up with a barely completely different sample due to miniscule deviations within the gentle’s diffraction and tiny variations within the chemical response.
As a result of photolithography is complicated and exhausting to mannequin, many present design approaches depend on equations derived from physics. These basic equations give some sense of the fabrication course of however can’t seize all deviations particular to a photolithography system. This could trigger gadgets to underperform in the actual world.
For his or her method, which they name neural lithography, the MIT researchers construct their photolithography simulator utilizing physics-based equations as a base, after which incorporate a neural community educated on actual, experimental knowledge from a consumer’s photolithography system. This neural community, a sort of machine-learning mannequin loosely based mostly on the human mind, learns to compensate for lots of the system’s particular deviations.
The researchers collect knowledge for his or her technique by producing many designs that cowl a variety of characteristic styles and sizes, which they fabricate utilizing the photolithography system. They measure the ultimate buildings and examine them with design specs, pairing these knowledge and utilizing them to coach a neural community for his or her digital simulator.
“The efficiency of discovered simulators is determined by the information fed in, and knowledge artificially generated from equations can’t cowl real-world deviations, which is why you will need to have real-world knowledge,” Zheng says.
Twin simulators
The digital lithography simulator consists of two separate parts: an optics mannequin that captures how gentle is projected on the floor of the system, and a resist mannequin that exhibits how the photochemical response happens to provide options on the floor.
In a downstream job, they join this discovered photolithography simulator to a physics-based simulator that predicts how the fabricated system will carry out on this job, reminiscent of how a diffractive lens will diffract the sunshine that strikes it.
The consumer specifies the outcomes they need a tool to attain. Then these two simulators work collectively inside a bigger framework that exhibits the consumer learn how to make a design that can attain these efficiency targets.
“With our simulator, the fabricated object can get the absolute best efficiency on a downstream job, just like the computational cameras, a promising expertise to make future cameras miniaturized and extra highly effective. We present that, even if you happen to use post-calibration to attempt to get a greater end result, it should nonetheless not be nearly as good as having our photolithography mannequin within the loop,” Zhao provides.
They examined this system by fabricating a holographic factor that generates a butterfly picture when gentle shines on it. When in comparison with gadgets designed utilizing different methods, their holographic factor produced a near-perfect butterfly that extra intently matched the design. In addition they produced a multilevel diffraction lens, which had higher picture high quality than different gadgets.
Sooner or later, the researchers need to improve their algorithms to mannequin extra sophisticated gadgets, and likewise check the system utilizing shopper cameras. As well as, they need to increase their method so it may be used with several types of photolithography programs, reminiscent of programs that use deep or excessive ultraviolet gentle.
This analysis is supported, partially, by the U.S. Nationwide Institutes of Well being, Fujikura Restricted, and the Hong Kong Innovation and Know-how Fund.
