Enhanced photocatalytic hydrogen production through tuning charge transfer in TiO2/CdS Se1–-DETA nanocomposites with S-scheme heterojunction structure
Source abstract
Abstract
In addressing the severe energy crisis, adopting efficient and reliable strategies is crucial. Photocatalysis technology, utilizing solar energy to convert it into hydrogen, offers an effective pathway to alleviate energy issues. In this study, we have successfully developed the TiO2/CdSxSe1–x-Diethylenetriamine (abbreviated as DETA) nanocomposites with an S-scheme heterojunction structure. By precisely adjusting the value of x (x = 0, 0.25, 0.50, 0.75 or 1.00), we optimized the charge transfer process, achieving efficient photocatalytic hydrogen evolution reaction. Specifically, the sample containing 20% (in mass) TiO2, denoted as 20-TO, exhibited the best photocatalytic activity. In particular, the activity of 20% (in mass) TiO2/CdS0.25Se0.75-DETA (abbreviated as 20-TO/CS0.25E0.75) reached 32.7 mmol·g–1·h–1, maintaining high hydrogen evolution performance over ten consecutive cycles (totaling 40 h). We used electron paramagnetic resonance (EPR), ultraviolet-visible diffuse reflectance spectroscopy (UV-Vis DRS), femtosecond transient absorption spectroscopy (fs-TAS) and theoretical calculations to comprehensively confirm that the heterojunctions in all nanocomposites conform to the S-scheme mechanism. This mechanism provides an optimal path for charge transfer. Comparative analysis through theoretical calculations revealed that the charge transfer efficiency between TO and CS0.25E0.75 was the highest, which correlates well with the experimental results of photocatalytic hydrogen evolution. This innovative nanocomposites enhances new energy technologies with its efficient charge transfer.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Advanced Photocatalysis Techniques · Perovskite Materials and Applications · Quantum Dots Synthesis And Properties
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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