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SandboxAQ is leveraging large quantitative models to accelerate the discovery of PFAS-free chemistries for critical semiconductor processes like photolithography, directly addressing a bottleneck in chip manufacturing. This initiative represents a significant convergence where artificial intelligence drives material science innovation to solve environmental compliance challenges within the hardware supply chain. The project highlights how AI is being applied not just for software optimization, but for fundamental breakthroughs in industrial chemistry and sustainability.
SandboxAQ seeks PFAS replacements for chipmaking’s toxic chemicals

SandboxAQ is developing computational methods to find PFAS-free alternatives for semiconductor manufacturing, a process where the “forever chemicals” are used in steps like photolithography.
Since their discovery in 1934, perfluoroalkyl and polyfluoroalkyl substances, or PFAS, have seen expanding use, now becoming critical in surging semiconductor manufacturing despite growing environmental concerns, SandboxAQ says. Semiconductor component maker Brewer Science notes PFAS are used in crucial processes like photolithography, etching, and cleaning, prompting exemptions from recent state bans due to a lack of readily available alternatives. SandboxAQ aims to change that, receiving $500 million through the CHIPS and Science Act to deploy artificial intelligence in researching new chemistries. “SandboxAQ has a goal to find alternative candidates in two to four years using advanced computational methods,” said Stefan Leichenauer, VP of engineering. The Silicon Valley startup will also explore alternatives for rare-earth-free magnets, catalysts, and batteries. The semiconductor industry’s…
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