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

Abstract

Photothermal efficiency in MXenes arises from the complex interplay between electronic structure and lattice dynamics, yet the precise contribution of electron-phonon coupling (EPC) remains poorly understood. By integrating ab initio nonadiabatic carrier-dynamics simulations with state-resolved electron-phonon-coupling analysis, the intrinsic mechanisms governing photothermal conversion in MXene materials are elucidated. Results reveal that MXene photothermal performance is dictated by an intrinsic hierarchy of EPC channels and hot-phonon accumulation, whereas defect-mediated non-radiative recombination serves as a secondary channel and ultimately compromises long-term photothermal stability. Building on this mechanistic insight, a physics-inspired and AI-assisted molecular-screening framework is developed to identify surface passivation chemistries capable of extending hot carrier lifetimes and mitigating phonon bottlenecks. Guided by this paradigm, a composite film endowed with a concave-spherical light-trapping array was fabricated, leading to substantial improvements in photothermal conversion efficiency and operational stability. This quantum-to-device co-design paradigm transcends MXenes, providing a data-driven, systematic design pathway that integrates fundamental theory with surface passivation to accelerate the advancement of durable photothermal devices tailored for sustainable energy applications.