Nature

Industrial-scale prediction of cement clinker phases using machine learning

Cement production exceeds 4.1 billion tonnes annually, emitting 2.4 billion tonnes of CO 2 annually, necessitating improved process control. Traditional models, limited to steady-state conditions, ...
CNBC

Meet the 33-year-old Canadian chemist and the renowned MIT professor who are building the 'electric vehicle of cement making'

Cement is necessary for making concrete, which is foundational in constructing buildings and infrastructure around the globe because it is relatively low-cost, strong and durable. But making cement ...
For Construction Pros

Machine Control in Concrete Applications

Machine control technologies range from 2D and 3D grade control to automation, robotic control, and augmented reality. GPS/3D control – eliminating the need for placing stringline by hand – is ...
Nature

Ensemble machine learning models for predicting strength of concrete with foundry sand and coal bottom ash as fine aggregate replacements

Natural sand scarcity and environmental concerns have encouraged the adoption of industrial waste materials in sustainable concrete. Foundry sand (FS) and coal bottom ash (CBA), both industrial waste ...
Hosted on MSN

New cement process developed by scientists that slashes energy use by 70%

A new cement-making process could sharply reduce pollution from one of the world's most carbon-intensive industries. In a study published May 13 in ACS Energy Letters, researchers described an ...