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Progress in understanding hematite electrochemistry through computational modeling AITranslate

Technion - Israel Institute of Technology; Technion - Israel Institute of Technology; Technion - Israel Institute of Technology
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Publisher: Elsevier
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Abstract AITranslate

Hematite ( α -Fe2O3) is one of the most widely studied materials for the application of water oxidation in the field of renewable energy. In order to push hematite toward maximal efficiency, a better understanding of the intrinsic limitations is essential. In this review, we cover our latest results on identifying and finding ways to overcome bottlenecks by modelling the electrochemical processes in hematite at three regimes: 1. at the bulk, the calculated hole effective mass is unfavorably high and conductivity can be improved through doping and alloying, 2. at the surface, catalysis is slow and involves long-lived surface states, but the catalytic overpotential can be reduced by adding a doping gradient or overlayers without strain, and 3. at the back contact the losses can be improved by selecting a proper metal contact. We provide unique analysis approaches that reveal fundamental understanding of electrochemistry with hematite. These models have made an impact on understanding experimental observations and have influenced subsequent theoretical investigations. Graphical abstract Download : Download high-res image (180KB) Download : Download full-size image

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DOI:https://doi.org/10.1016/j.commatsci.2019.01.001

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Citation Information:

Hematite ( α -Fe2O3) is one of the most widely studied materials for the application of water oxidation in the field of renewable energy. In order to push hematite toward maximal efficiency, a better understanding of the intrinsic limitations is essential. In this review, we cover our latest results on identifying and finding ways to overcome bottlenecks by modelling the electrochemical processes in hematite at three regimes: 1. at the bulk, the calculated hole effective mass is unfavorably high and conductivity can be improved through doping and alloying, 2. at the surface, catalysis is slow and involves long-lived surface states, but the catalytic overpotential can be reduced by adding a doping gradient or overlayers without strain, and 3. at the back contact the losses can be improved by selecting a proper metal contact. We provide unique analysis approaches that reveal fundamental understanding of electrochemistry with hematite. These models have made an impact on understanding experimental observations and have influenced subsequent theoretical investigations. Graphical abstract Download : Download high-res image (180KB) Download : Download full-size image

quote

GB/T 7714-2015 [1] Nadav Snir, Natav Yatom, Maytal Caspary Toroker. Computational Materials Science, 2019(160). DOI:10.1016/j.commatsci.2019.01.001.
MLA [1] Nadav Snir, et al., Computational Materials Science, no. 160, 2019, https://doi.org/10.1016/j.commatsci.2019.01.001.
APA [1] Nadav Snir, Natav Yatom, & Maytal Caspary Toroker. (2019). Computational Materials Science(160). https://doi.org/10.1016/j.commatsci.2019.01.001
IEEE [1] Nadav Snir, Natav Yatom, and Maytal Caspary Toroker, Computational Materials Science, no. 160, 2019, doi: 10.1016/j.commatsci.2019.01.001.