Energy loss analysis in photoelectrochemical water splitting: a case study of hematite photoanodes

Literature Information

Publication Date 2018-08-16
DOI 10.1039/C8CP04021D
Impact Factor 3.676
Authors

Zhiliang Wang, Miaoqiang Lyu, Peng Chen, Songcan Wang, Lianzhou Wang


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Abstract

Insightful understanding of the energy loss mechanism during photoelectrochemical (PEC) processes is of vital importance for efficient solar fuel production. Potential–current features under light illumination are typically used to evaluate the effectiveness of the PEC processes. However, energy loss that leads to various shapes of measured photocurrent–potential (j–E) curves is still not well understood. Herein, based on hematite photoanodes, we systematically studied the photocurrent–potential–light intensity (j–E–I) relationships to acquire quantitative understanding of the loss mechanism during the PEC process by decoupling it into a photovoltaic (PV) and an electrocatalytic (EC) process. Both numerical simulation and experimental results have confirmed the reasonability of this analysis method. It provides comprehensive understanding of the energy loss at the semiconductor–electrolyte junction and the surface electrocatalysis process for further optimizing the PEC solar energy conversion process.

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Source Journal

Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
Self-citation Rate: 10.3%
Articles per Year: 3036

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.

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