Towards net zero by data-driven discovery of sustainable cement alternatives
The construction industry faces mounting pressure to reduce its carbon footprint, with cement production alone contributing over 6% of global greenhouse gas emissions. In recent work, machine learning models screened over 14,000 materials from scientific literature and 1 million rock samples, identifying a diverse set of secondary and natural materials that could partially replace global cement production.
Authors
- Jack D. Evans (ORCID: https://orcid.org/0000-0001-9521-2601)
Institutions
- The University of Adelaide (AU)
Publication Details
- Journal
- Communications Chemistry
- Published
- 2025-07-24
- DOI
- https://doi.org/10.1038/s42004-025-01608-w
- Citations
- 1
- Primary Topic
- Reservoir Engineering and Simulation Methods
- Type
- article
- Field-Weighted Citation Impact
- 1.15