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Liu et al. J Mater Inf 2024;4:33 https://dx.doi.org/10.20517/jmi.2024.48 Page 3 of 33

performance photocatalysts for real-world applications. The integration of machine learning with
computational methodologies establishes a dynamic and iterative framework, allowing continuous
refinement and optimization of photocatalytic systems. This integrated approach of computational
modeling and deep learning accelerates the design process and significantly elevates photocatalyst
performance, addressing the fundamental limitations of traditional methodologies.

Here, this review presents a transformative approach to photocatalyst design by integrating computational
science with deep learning technologies. Fundamental principles of photocatalysis are explored, offering a
comprehensive foundation for understanding the key factors that drive efficiency in photocatalytic systems.
A detailed examination of computational methodologies follows, focusing on first-principles calculations
and HTS, which play a critical role in optimizing photocatalytic performance and accelerating the discovery
of efficient photocatalysts. The workflow for deep-learning-assisted photocatalyst design is outlined,
emphasizing how data collection, feature engineering, model training, and validation are integrated with
machine learning models to guide experimental validation and enhance predictive capabilities. Deep
learning approaches are thoroughly investigated, with attention to the discovery of novel photocatalysts,
microstructural design, property optimization, innovative design frameworks, application exploration, and
mechanistic insights into photocatalysis. The synergy between multidimensional computations and deep
learning is examined, demonstrating how this integrated framework addresses the inherent challenges of
traditional design and fosters breakthroughs in photocatalyst development. This review offers
transformative insights that not only advance the design of high-performance photocatalysts but also
expand their practical applications across various fields, contributing to the broader goals of environmental
sustainability and energy efficiency.

DESIGN OF PHOTOCATALYSTS
General principle of photocatalysis
Photocatalysis has emerged as a crucial technology with applications spanning environmental remediation,
[28]
energy conversion, and sustainable chemical production . Its significance lies in its ability to harness solar
energy to drive chemical reactions, contributing to pollution reduction, carbon neutrality, and green energy
generation. One of the primary advantages of photocatalysis is its ability to operate in-situ without the need
[29]
for external energy inputs, relying solely on solar energy . For example, in environmental remediation,
photocatalysis has been extensively demonstrated under natural sunlight conditions . Furthermore, it
[30]
[31]
supports simultaneous pollution reduction and carbon mitigation . This is evidenced by the photocatalytic
reduction of CO into useful fuels or chemicals, promoting both environmental sustainability and carbon
2
neutrality .
[32]
The fundamental mechanism [33-35] of photocatalysis involves the excitation of electrons within a
semiconductor upon absorption of photons with energy equal to or greater than its band gap. This
excitation promotes electrons from the valence to the conduction band, leaving corresponding holes in the
valence band. The photogenerated charge carriers (electrons and holes) then migrate to the surface, where
they participate in redox reactions. Electrons predominantly participate in reduction reactions, where they
are transferred to oxygen molecules (O ) adsorbed on the photocatalyst surface, leading to the formation of
2
superoxide radicals (•O ). These superoxide radicals can subsequently react with protons to produce
-
2
hydrogen peroxide (H O ) or other reactive oxygen species (ROS), which are highly effective in degrading
2
2
organic pollutants and reducing heavy metals. Conversely, the holes (h ) facilitate oxidation reactions by
+
oxidizing water (H O) molecules adsorbed on the photocatalyst surface, generating hydroxyl radicals (•OH),
2
which are highly reactive species capable of decomposing complex organic pollutants, splitting water or
producing hydrogen peroxide, thus contributing to sustainable production. The overall efficiency of