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Cited by 971

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Water splitting–biosynthetic system with CO 2 reduction efficiencies exceeding photosynthesis

Open access
Liu, Chong, Colón, Brendan C., Ziesack, Marika, Silver, Pamela A., Nocera, Daniel G.·2016·Science

Abstract

Artificial photosynthesis steps up: Photosynthesis fixes CO 2 from the air by using sunlight. Industrial mimics of photosynthesis seek to convert CO 2 directly into biomass, fuels, or other useful products. Improving on a previous artificial photosynthesis design, Liu et al. combined the hydrogen-oxidizing bacterium Raistonia eutropha with a cobalt-phosphorus water-splitting catalyst. This biocompatible self-healing electrode circumvented the toxicity challenges of previous designs and allowed it to operate aerobically. When combined with solar photovoltaic cells, solar-to-chemical conversion rates should become nearly an order of magnitude more efficient than natural photosynthesis. Science , this issue p. 1210

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Crossref · 10.1126/science.aaf5039

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Metadata

Authors
Liu, C., Colón, B. C., Ziesack, M., Silver, P. A., & Nocera, D. G.
Venue
Science
Published
2016-06-03
Volume
352
Issue
6290
Pages
1210-1213
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W2412520413
Cited by
971
References
3
FWCI
62.58
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Water splitting–biosynthetic system with CO 2 reduction efficiencies exceeding photosynthesis. https://app.cochat.ai/papers/10.1126/science.aaf5039
The paper
Liu, C., Colón, B. C., Ziesack, M., Silver, P. A., & Nocera, D. G. (2016). Water splitting–biosynthetic system with CO 2 reduction efficiencies exceeding photosynthesis. Science. https://doi.org/10.1126/science.aaf5039

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.