Gemini 3 Deep Think: Optimizing 2D semiconductor fabrication

AI 总结

• 研究场景：杜克大学Wang Lab在材料科学中优化晶体生长与制备方法
• 方法特点：Deep Think将专家级科学知识应用到研究级数据进行工艺设计
• 关键结果：给出精确“配方”，实现>100 μm薄膜尺寸目标
• 意义：解决此前工艺难以达到的规模目标，为2D半导体制造提供更可控的路线

内容摘录

At Duke University, the Wang Lab utilized Gemini 3 Deep Think to solve a complex challenge in materials science: optimizing fabrication methods for crystal growth.

By applying expert-level scientific knowledge to research-level data, Deep Think successfully designed a precise recipe for growing thin films larger than 100 μm—hitting a specific target that previous methods had struggled to reach. 

Learn more at https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-3-deep-think