Data-Driven Machine Learning Strategy for Designing Metal-Ion-Doped γ-BiMoO Photocatalysts to Enhance Degradation Performance.

Doped semiconductors are often used to improve photocatalytic efficiency and address the challenges of easy recombination of electron-hole pairs and poor photoluminescence. However, the reproducibility and complexity of experimental studies result in time-consuming and less cost-effective studies, and it is difficult to gain insights into the intrinsic properties of doped photocatalysts to control their performance. Introducing a machine learning approach, we constructed a photocatalytic model of transition-metal- and rare earth metal-ion-doped γ-BiMoO.

Using Er/Cd-Codoped BiOBr Microspheres to Enhance Antibiotic Degradation under Visible Illumination: A Combined Experimental and DFT Investigation.

High levels of antibiotic accumulation and the difficulty of degradation can have serious consequences for the environment and, therefore, require urgent attention. To solve this problem, a synergistic Er and Cd ion-codoped BiOBr photocatalyst was proposed. The degradation rate of sulfamethoxazole (SMX) by Er/Cd-BiOBr was eight times higher than that of pure BiOBr, exceeding that of single Er-doped or Cd-doped BiOBr, which was attributed to the ability of Er/Cd-BiOBr to generate a variety of free radicals.