Literature DB >> 26808228

Modelling materials for solar fuel synthesis by artificial photosynthesis; predicting the optical, electronic and redox properties of photocatalysts.

Pierre Guiglion1, Enrico Berardo, Cristina Butchosa, Milena C C Wobbe, Martijn A Zwijnenburg.   

Abstract

In this mini-review, we discuss what insight computational modelling can provide into the working of photocatalysts for solar fuel synthesis and how calculations can be used to screen for new promising materials for photocatalytic water splitting and carbon dioxide reduction. We will extensively discuss the different relevant (material) properties and the computational approaches (DFT, TD-DFT, GW/BSE) available to model them. We illustrate this with examples from the literature, focussing on polymeric and nanoparticle photocatalysts. We finish with a perspective on the outstanding conceptual and computational challenges.

Entities:  

Year:  2016        PMID: 26808228     DOI: 10.1088/0953-8984/28/7/074001

Source DB:  PubMed          Journal:  J Phys Condens Matter        ISSN: 0953-8984            Impact factor:   2.333


  1 in total

1.  Mapping binary copolymer property space with neural networks.

Authors:  Liam Wilbraham; Reiner Sebastian Sprick; Kim E Jelfs; Martijn A Zwijnenburg
Journal:  Chem Sci       Date:  2019-04-01       Impact factor: 9.825

  1 in total

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