Work

Innovative Electrochemical Synthesis of Portland Cement Precursor (Ca(OH)2) with Machine Learning-Enabled Predictive Insights

Year: 2026

Type: article

Abstract: For long the manufacturing of calcium hydroxide, a major precursor of cement production, relies heavily on calcining, which not only costs much energy, but also releases a significant amount of carbon dioxide. To electrochemically synthesize calcium hydroxide is a high-potential substitution, as it utilizes pH gradient to decarbonate limestone and generate calcium hydroxide, which can be carried out at room temperature. But creating a pH gradient with electrolysis of water requires a relatively high voltage, which could be energy-draining in manufacturing. So here an innovative three-chamber electrolysis system based on hydrogen evolution reaction (HER) and hydrogen oxidation reaction (HOR) is proposed, which lowers the electrolysis voltage while achieving very high current efficiency (~100%). A regularized linear regression model and a multi-layer perceptron are also developed to analyze the influence of key factors, including current density and electrolyte concentration, on the calcium hydroxide production rate of the system. The possibility of further applying deep learning to optimize experimental parameters, recognize major restrictions from high-dimensional data, and predict test results is also discussed. This work offers a new low-energy, decarbonized path for cement precursor production and references for combining electrochemistry with machine learning.

Source: Hydrogen

DOI: 10.3390/hydrogen7040190

Authors: Yan-He Wang, Guo-Ming Weng

Institution: Shanghai Jiao Tong University

Language: English

Topic: Electrocatalysts for Energy Conversion

Subfield: Renewable Energy, Sustainability and the Environment

Field: Energy

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $1,207