Theory & Computation

Theory & Computation

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22-09-15 15:27
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Disruptive 1st-Principles TCAD

Based on MS-DFT and related computational methods, we are actively developing science and technology that will enable hitherto unachievable ​technology computer-aided design (TCAD) of next-generation semiconductor devices​. We recently demonstrated for the first time ab initio device simulations of graphene-based van der Waals 2D heterojunction transistors. A key focus of our present effort is extending the length and time scales of first-principles electronic structure and TCAD calculations by incorporating artificial intelligence (AI) and multi-scale computing techniques. A notable recent development is the DeepSCF model, which provides a foundational principle for AI-based acceleration of materials simulations across scales.  

 

Selected Publications

 ​"Convolutional network learning of self-consistent electron density via grid-projected atomic fingerprints"

Ryong-Gyu Lee and Yong-Hoon Kim

npj Computational Materials, Vol. 10, Art. 248 (2024)

Media Coverage: KAIST ​News (in Korean)KAIST ​Newsand International Media 


 ​"Gate-versus defect-induced voltage drop and negative differential resistance in vertical graphene heterostructures"

Tae Hyung Kim, Juho Lee, Ryong-Gyu Lee, and Yong-Hoon Kim

npj Computational Materials, Vol. 8, Art. 50 (2022)

Media Coverage: KAIST ​Breakthroughs (Spring 2023), KAIST News (in Korean), and KAIST Times (in Korean)