Constructing Moisture-Induced Degradation Pathways in Metal-Oxide Resists from Two-Phase Active Learning of Deep...

Area of Science:

• Materials Science
• Computational Chemistry
• Chemical Engineering

Background:

• Tin-based metal-oxide resist (Sn-MOR) is a key material for advanced photolithography.
• Sn-MOR's practical application is limited by its instability in the presence of ambient moisture.
• Understanding the degradation mechanism is crucial for developing more stable photolithography materials.

Purpose of the Study:

• To investigate the molecular-level mechanisms of Sn-MOR degradation induced by ambient moisture.
• To develop and apply a computational framework capable of simulating rare-event degradation dynamics.
• To provide insights for designing Sn-MOR materials with improved moisture stability and photospeed.

Main Methods:

• Introduction of a two-phase active learning (2P-AL) framework.
• Coupling deep potential molecular dynamics with well-tempered metadynamics (WT-MetaD) for rare-event dynamics.
• Utilizing WT-MetaD simulations to construct the free energy landscape of Sn-MOR degradation in aqueous solution.

Main Results:

• Successfully mapped the free energy landscape of moisture-induced degradation for Sn-MOR molecules.
• Uncovered a plausible degradation pathway initiated by ambient moisture.
• Gained molecular-level understanding of the stability challenges faced by Sn-MOR materials.

Conclusions:

• The developed 2P-AL framework efficiently captures solution-phase reactive system dynamics.
• The study provides critical molecular insights into moisture-induced degradation in disordered Sn-MOR materials.
• Findings can guide the design of next-generation photolithography materials with enhanced stability.