Quantum to Device AI‐Guided Passivation Paradigm for All‐Weather Ultrastable MXene Based Photothermal Converter
Tianyang Cui, Yapeng Zheng, Wei Cai, Liangyuan Qi, Jingwen Wang, Wei Yang, Weiguo Song, Yuan Hu, Jixin Zhu
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.