The Role of <i>Pτ</i>in the Photothermoelectric Effect and in Photoredox Catalysis Reactions

• 作者: Giovanna Scarel
• 来源期刊: 凝固态物理国际期刊(英文)
• 学科: 医学
• 关键词: Light-Matter Interaction Photothermoelectric Effect PHOTOREDOX REACTIONS
• 年，卷（期）: 2019,（4）
• 页码范围: 91-101
• 页数: 11页
• 分类号: R56

摘要

Context and Background: Recent research has shown that the amount of energy conserved in light-matter interaction is given by the product of light’s power P times its period τ, i.e. Pτ. To date, evidences of the validity of such finding are restricted to the interaction of light with capacitors, infrared spectroscopy, and vision in vertebrates. Motivation: In this article, we want to explore the validity of the role of Pτin a broader range of phenomena. Hypothesis: We assume that the photothermoelectric (PTE) effect and photoredox catalysis reactions (PCRs) are manifestations of light-matter interaction and therefore have Pτconserved in the process. Method: We take the data published in two articles, one on the PTE effect and the other on PCRs and revisit the data analysis of the authors of the original articles considering Pτas the energy conserved. Results: In the case of the PTE effect, we unveil that the size of the light’s beam cross-sectional area impinging on the photodetectors plays a major role in defining the performance of the photodetectors. With our analysis, the photodetector responsivities actually turn out to be higher than those reported in the original article. In the case of the PCRs, we find that the magnitude of Pτinvolved in successful PCRs is independent of the type of light used, whether near-infrared or blue. In addition, the involvement of Pτin the description of PCRs helps to clarify the role of the law of conservation of energy, which was neglected by the authors of the original article. Conclusions: From this study, we infer that the hypothesis that Pτthat the hypothesis that represents the amount of energy conserved in light-matter interaction is valid and general, useful to measure device performance, and predict alternative processes to achieve desired outcomes.