Parallel experiments in electrochemical CO<sub>2</sub> reduction enabled by standardized analytics

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Recently, there has been an arms race of pose forecasting methods aimed at solving the spatio-temporal task of predicting a sequence of future 3D poses of a person given a sequence of past observed ones. However, the lack of unified benchmarks and limited ...

Anionic exchange membrane (AEM) water electrolyzers are emerging as a cost-effective technology for green hydrogen production. However, state-of-the-art AEM electrolyzers rely on platinum group metal (PGM) catalysts for the hydrogen evolution reaction (HER ...

Nature Photonics spoke with Hatice Altug, from the & Eacute;cole Polytechnique F & eacute;d & eacute;rale de Lausanne (EPFL), Thomas Krauss, from the University of York, and Malini Olivo from the Agency for Science, Technology and Research (A*STAR) about o ...

The current energy crisis demands the development of new sustainable energy sources and devices with low environmental impact, including in the field of electrochemical cells. Mass transport limitations can reduce the overall performance of the device by l ...

Our planet has been challenged for years by our reckless use of fossil fuels, which has led to the ongoing climate change and energy crisis. The transition to the use of renewable alternative sources has now became urgent and inevitable. The valorization o ...

Metal-Organic Framework (MOF)-derived TiO2, synthesised through the calcination of MIL-125-NH2, is investigated for its potential as a CO2 photoreduction catalyst. The effect of the reaction parameters: irradiance, temperature and partial pressure of water ...

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Transfer learning can signiﬁcantly improve the sample eﬃciency of neural networks, by exploiting the relatedness between a data-scarce target task and a data-abundant source task. Despite years of successful applications, transfer learning practice often r ...

This thesis focuses on two kinds of statistical inference problems in signal processing and data science. The first problem is the estimation of a structured informative tensor from the observation of a noisy tensor in which it is buried. The structure com ...

Electrocatalytic conversion of CO2 to valuable chemicals is a highly promising route to close the carbon cycle. Herein, Zn catalysts derived from electrochemical reconstruction of ZnO materials are presented as efficient CO2-to-CO catalysts. We found that ...

Parallel experiments in electrochemical CO<sub>2</sub> reduction enabled by standardized analytics

Chattez avec Graph Search

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Highly selective CO2 photoreduction to CO on MOF-derived TiO2

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Electrochemical reconstruction of ZnO for selective reduction of CO2 to CO