Understanding Adsorption and Reactions at Aqueous Oxide Interfaces with Neural Network Potential Molecular Dynamics

Area of Science:

• Surface Chemistry
• Computational Materials Science
• Computational Chemistry

Background:

• Chemical processes at metal oxide-water interfaces are crucial for geochemistry, biology, and energy technologies.
• Computational modeling is essential for understanding these complex interfaces due to experimental limitations.
• Machine learning (ML) models, trained on ab initio calculations, offer a balance of accuracy and efficiency for simulating potential energy surfaces (PES).

Purpose of the Study:

• To review recent efforts in understanding adsorption and reactions at aqueous oxide interfaces using deep potential molecular dynamics (DPMD).
• To highlight the application of DPMD in elucidating fundamental chemical characteristics and catalytic properties of oxide-water systems.
• To demonstrate the predictive power of ML-based simulations for complex interfacial phenomena.

Main Methods:

• Deep Potential Molecular Dynamics (DPMD) simulations employing deep neural networks (DNNs).
• Ab initio calculations to generate training data for ML models.
• Analysis of interfacial properties including acid-base chemistry, adsorption, and wettability.

Main Results:

• DPMD accurately reproduces ab initio PESs for aqueous oxide interfaces.
• The rutile IrO2-water interface exhibits significant water dissociation and strong Brønsted acidity, consistent with experimental data.
• Formic and acetic acids influence TiO2 wettability primarily through interfacial acid-base chemistry, not chemisorption.
• Simulations provide mechanistic insights into methanol's role in enhancing photocatalytic hydrogen evolution on TiO2.

Conclusions:

• DPMD is a powerful tool for simulating complex chemical processes at aqueous oxide interfaces.
• Understanding interfacial acid-base chemistry is key to controlling surface charge and wettability.
• ML-based simulations can guide the design of improved catalysts and photocatalytic materials for energy applications.