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

Related publications (12)

Toward Reliable Human Pose Forecasting With Uncertainty

Alexandre Massoud Alahi, Saeed Saadatnejad, Taylor Ferdinand Mordan

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 ...

2024

An oxide-promoted, self-supported Ni4Mo catalyst for high current density anion exchange membrane water electrolysis

Xile Hu, Nanjun Chen, Ariana Serban

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 ...

ROYAL SOC CHEMISTRY2024

Optical biosensors towards the clinic

Hatice Altug

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 ...

Nature Publishing Group2024

Pathways to enhance electrochemical CO2 reduction identified through direct pore-level modeling

Sophia Haussener, Etienne Boutin, Shuo Liu, Evan Fair Johnson

Electrochemical conversion of CO2 to fuels and valuable products is one pathway to reduce CO2 emissions. Electrolyzers using gas diffusion electrodes (GDEs) show much higher current densities than aqueous phase electrolyzers, yet models for multi-physical ...

2023

Electron imaging of gas diffusion electrodes for proton exchange membrane fuel cells

Michele Bozzetti

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 ...

EPFL2023

Lignin, from biomass waste to sustainable materials for food packaging, antiviral coatings and agriculture

Alice Boarino

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 ...

EPFL2023

Highly selective CO2 photoreduction to CO on MOF-derived TiO2

Berend Smit, Christopher Patrick Ireland, Stavroula Kampouri

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 ...

ROYAL SOC CHEMISTRY2023

Euclid: Constraining ensemble photometric redshift distributions with stacked spectroscopy

Georges Meylan

Context. The ESA Euclid mission will produce photometric galaxy samples over 15 000 square degrees of the sky that will be rich for clustering and weak lensing statistics. The accuracy of the cosmological constraints derived from these measurements will de ...

EDP SCIENCES S A2022

Distributed adjustable robust optimal power-gas flow considering wind power uncertainty

Colin Neil Jones, Yuning Jiang

The rapid uptake of natural gas-fired units in energy systems poses significant challenges in coordinating the electricity and gas systems. Besides, the uncertainty caused by integrated renewable energy such as wind power raises more requirements on the ro ...

2022

Probing transfer learning with a model of synthetic correlated datasets

Lenka Zdeborová, Luca Saglietti, Federica Gerace

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 ...

2022

Statistical limits of high-dimensional inference problems

Clément Dominique Luneau

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 ...

EPFL2021

Electrochemical reconstruction of ZnO for selective reduction of CO2 to CO

Andreas Züttel, Wen Luo, Jie Zhang, Kun Zhao, Emanuele Moioli

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 ...

2020