Next-Generation Quantum Dot Engineering for Photoelectrochemical Hydrogen Production: Insights From Artificial Intelligence-Assisted Approaches

Abstract

The transition to sustainable energy requires efficient technologies for solar-driven hydrogen production. Quantum dots (QDs), with size-tunable bandgaps and favorable interfacial properties, significantly enhance photoelectrochemical (PEC) water splitting by enabling broad-spectrum light harvesting, optimized band alignment, and improved charge separation. However, QD design strategies for PEC systems remain less developed compared to those for light-emitting diodes and solar cells, constrained by incomplete understanding of interfacial photophysics, limited exploration of low-dimensional nanocrystals (1D/2D), and the absence of AI-assisted optimization. This review provides a comprehensive overview of material design strategies for QDs in PEC hydrogen production, encompassing fundamental principles, established approaches, and recent advances in both heavy-metal-based and nontoxic systems. Particular attention is given to emerging paradigms such as dimensional control and AI-driven optimization, which enable predictive modeling, accelerated synthesis, and performance tuning beyond conventional trial-and-error methods. Finally, we address critical challenges—including stability, toxicity, and scalability—and outline future directions for achieving efficient, sustainable QD-based PEC systems suitable for practical and economically viable commercialization.