- Application of machine learning in predicting workability for alkali-activated materials. In: Case Studies in Construction Materials, v. 18 (July 2023). (2023):
- Fresh properties and characteristic testing methods for alkali-activated materials: A review. In: Journal of Building Engineering, v. 75 (September 2023). (2023):
- Physically explicable mathematical model for strength prediction of UHPFRC. In: Engineering Structures, v. 275 (January 2023). (2023):
- Prediction of the drying shrinkage of alkali-activated materials using artificial neural networks. In: Case Studies in Construction Materials, v. 17 (December 2022). (2022):
- Modeling the Drying Shrinkage of Cement Paste Prepared with Wastewater. In: Journal of Materials in Civil Engineering (ASCE), v. 34, n. 6 (June 2022). (2022):
- Mathematical model for strength of alkali-activated materials. In: Journal of Building Engineering, v. 44 (December 2021). (2021):