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Electrochemical CO₂ reduction predictor

Year: 2025

Type: article

Abstract: Electrochemical CO₂ reduction predictor provides a unified environment for data-centric exploration and machine-learning-based design of CO₂ electroreduction catalysts.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.17434469

Authors: Seyedalikhani, Seyed Aryan, Ghafarian Nia, Seyyed Alireza, Aghbashlo, Mortaza

Institution: University of Tehran

Language: English

Topic: CO2 Reduction Techniques and Catalysts

Subfield: Renewable Energy, Sustainability and the Environment

Field: Energy

Domain: Physical Sciences

SDG: Climate action

Open Access status: green

OpenAlex ID: W7094959830

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