Quantum to Device AI-Guided Passivation Paradigm for All-Weather Ultrastable MXene Based Photothermal Converter

Area of Science:

• Materials Science
• Condensed Matter Physics
• Physical Chemistry

Background:

• Photothermal efficiency in MXenes is crucial for sustainable energy applications.
• The exact role of electron-phonon coupling (EPC) in MXene photothermal conversion is not fully understood.
• Understanding these mechanisms is vital for designing stable and efficient photothermal devices.

Purpose of the Study:

• To elucidate the intrinsic mechanisms governing photothermal conversion in MXene materials.
• To identify key factors influencing photothermal efficiency and stability.
• To develop a framework for designing improved photothermal devices.

Main Methods:

• Integrated ab initio nonadiabatic carrier-dynamics simulations.
• State-resolved electron-phonon-coupling analysis.
• AI-assisted molecular screening for surface passivation.

Main Results:

• Photothermal performance is governed by EPC channels and hot-phonon accumulation.
• Defect-mediated recombination compromises long-term stability.
• A novel composite film with a light-trapping array significantly improved efficiency and stability.

Conclusions:

• A quantum-to-device co-design paradigm was established for MXene photothermal materials.
• The study provides a data-driven pathway integrating theory and surface passivation.
• This approach accelerates the development of durable photothermal devices for sustainable energy.