In the article “Atomic Neighborhoods in Semiconductors Provide New Avenue for Designing Microelectronics,” the Berkeley Lab reports on a research collaboration with GW Engineering. The study, published in Science, investigates the atomic structure of semiconductor materials and confirms for the first time that they arrange themselves in distinctive local patterns known as short-range order (SRO). Professor of Civil and Environmental Engineering Tianshu Li co-led the GW team, which developed a machine learning model that simulates the material’s atomic structure.
Here is an excerpt from the article: “Shunda Chen, a research scientist in Li’s group who developed the model, said: “With these models, which combine machine learning with first-principles calculations, we can replicate experimental procedures with high fidelity and pinpoint the structural motifs that would otherwise remain hidden.”
Read the full article on the Berkeley Lab website. For more coverage, check out TechXplore and Interesting Engineering.