Photolithography includes manipulating gentle to exactly etch options onto a floor, and is often used to manufacture pc chips and optical units like lenses. However tiny deviations throughout the manufacturing course of usually trigger these units 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 well 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 machine in downstream duties, similar to producing photos with computational cameras. These related simulators allow a consumer to supply an optical machine that higher matches its design and reaches one of the best activity efficiency.
This method may assist scientists and engineers create extra correct and environment friendly optical units for functions 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 methods.
“This concept sounds easy, however the causes folks haven’t tried this earlier than are that actual knowledge may be costly and there aren’t any precedents for the right way to successfully coordinate the software program and {hardware} to construct a high-fidelity dataset,” says Cheng Zheng, a mechanical engineering graduate scholar who’s co-lead writer of an open-access paper describing the work. “Now we have taken dangers and completed intensive exploration, for instance, creating and attempting characterization instruments and data-exploration methods, to find out a working scheme. The result’s surprisingly good, exhibiting that actual knowledge work far more effectively and exactly than knowledge generated by simulators composed of analytical equations. Although it may be costly and one can really feel clueless originally, it’s value doing.”
Zheng wrote the paper with co-lead writer Guangyuan Zhao, a graduate scholar 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 shall be introduced on the SIGGRAPH Asia Convention.
Printing with gentle
Photolithography includes projecting a sample of sunshine onto a floor, which causes a chemical response that etches options into the substrate. Nonetheless, the fabricated machine 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 advanced and onerous to mannequin, many current design approaches depend on equations derived from physics. These normal equations give some sense of the fabrication course of however can’t seize all deviations particular to a photolithography system. This may trigger units to underperform in the true 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 kind of machine-learning mannequin loosely based mostly on the human mind, learns to compensate for most of the system’s particular deviations.
The researchers collect knowledge for his or her technique by producing many designs that cowl a variety of function configurations and dimensions, which they fabricate utilizing the photolithography system. They measure the ultimate constructions 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 relies on the info 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 machine, and a resist mannequin that exhibits how the photochemical response happens to supply options on the floor.
In a downstream activity, they join this discovered photolithography simulator to a physics-based simulator that predicts how the fabricated machine will carry out on this activity, similar to how a diffractive lens will diffract the sunshine that strikes it.
The consumer specifies the outcomes they need a tool to realize. Then these two simulators work collectively inside a bigger framework that exhibits the consumer the right way 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 activity, just like the computational cameras, a promising expertise to make future cameras miniaturized and extra highly effective. We present that, even in the event you use post-calibration to attempt to get a greater consequence, it should nonetheless not be pretty much as good as having our photolithography mannequin within the loop,” Zhao provides.
They examined this system by fabricating a holographic aspect that generates a butterfly picture when gentle shines on it. When in comparison with units designed utilizing different methods, their holographic aspect produced a near-perfect butterfly that extra carefully matched the design. Additionally they produced a multilevel diffraction lens, which had higher picture high quality than different units.
Sooner or later, the researchers wish to improve their algorithms to mannequin extra difficult units, and likewise check the system utilizing shopper cameras. As well as, they wish to increase their strategy so it may be used with several types of photolithography methods, similar to methods 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.