Turning CO2 into 3D-Printed Concrete via Integrated Machine Learning, Simulations, and Experiments

Project Personnel

Mathieu Bauchy

Principal Investigator

University of California, Los Angeles

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Ximin He

University of California, Los Angeles

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Puneet Gupta

University of California, Los Angeles

Email

Gaurav Sant

University of California, Los Angeles

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Funding Divisions

Civil, Mechanical and Manufacturing Innovation (CMMI)

This objective of this research is to decipher the fundamental knowledge required to accelerate the design of a new 3D-printable portlandite-based cementitious binder that permits CO2 uptake. Toward this end, this research aims: (i) to understand, control, and optimize the rheology of concentrated portlandite suspensions to enable printability, (ii) to refine portlandite carbonation routes at ambient temperature to maximize CO2 uptake to accelerate the carbonation kinetics, and (iii) to discover new multi-material 3D-printed metastructures with high load-bearing capability and optimal strength-to-weight ratio. This research relies on an iterative closed-loop integration of simulation (i.e., from electrons to continua), experimental, and machine learning activities that mutually inform and advance each other. The synergy between experimental and computational approaches will shed new light on interfacial reaction processes of mineral sorbents. This project will also advance the state of the art in our understanding of the rheology of concentrated suspensions, and elucidate the molecular design principles behind the discovery of polymers that permit the printability of concentrated slurries. Finally, by pioneering machine-learning-informed multi-material 3D-printing, this research will develop new methods to optimize the geometry and spatial distribution of metastructures that are light, stiff, and strong. Overall, by marrying the benefits of CO2 mineralization and 3D-printing, this work will result in pioneering intellectual contributions to accelerate the design of transformative construction materials with desirable properties and low carbon impact.

Publications

EBOD: An ensemble-based outlier detection algorithm for noisy datasets
B. Y. Ouyang, Y. Song, Y. H. Li, G. Sant, and M. Bauchy
Nov 2021
Controls on CO2 Mineralization Using Natural and Industrial Alkaline Solids under Ambient Conditions
E. C. La Plante, I. Mehdipour, I. Shortt, K. Yang, D. Simonetti, M. Bauchy, and G. N. Sant
Aug 2021
Topological origin of phase separation in hydrated gels
C. Zhao, W. Zhou, Q. Zhou, Z. Wang, G. Sant, L. J. Guo, and M. Bauchy
May 2021
Predicting the early-stage creep dynamics of gels from their static structure by machine learning
H. Liu, S. Q. Xiao, L. W. Tang, E. Bao, E. Li, C. Yang, Z. J. Zhao, G. Sant, M. M. Smedskjaer, L. J. Guo, and M. Bauchy
May 2021
Machine Learning Enables Rapid Screening of Reactive Fly Ashes Based on Their Network Topology
Y. Song, K. Yang, J. Y. Chen, K. X. Wang, G. Sant, and M. Bauchy
Feb 2021
Artificial intelligence and machine learning in glass science and technology: 21 challenges for the 21st century
V. Venugopal, S. Bishnoi, S. Singh, M. Zaki, H. S. Grover, M. Bauchy, M. Agarwal, and N. M. A. Krishnan
Jan 2021
Saline Water-Based Mineralization Pathway for Gigatonne-Scale CO2 Management
E. C. La Plante, D. A. Simonetti, J. B. Wang, A. Al-Turki, X. Chen, D. Jassby, and G. N. Sant
Jan 2021
The role of gas flow distributions on CO2 mineralization within monolithic cemented composites: coupled CFD-factorial design approach
I. Mehdipour, G. Falzone, D. Prentice, N. Neithalath, D. Simonetti, and G. Sant
Jan 2021
New insights into the mechanisms of carbon dioxide mineralization by portlandite
G. Falzone, I. Mehdipour, N. Neithalath, M. Bauchy, D. Simonetti, and G. Sant
Jan 2021
Atomic Dislocations and Bond Rupture Govern Dissolution Enhancement under Acoustic Stimulation
Longwen Tang, Shiqi Dong, Ross Arnold, Erika Callagon La Plante, Juan Carlos Vega-Vila, Dale Prentice, Kirk Ellison, Aditya Kumar, Narayanan Neithalath, Dante Simonetti, Gaurav Sant, and Mathieu Bauchy
Dec 2020
Predicting Concrete’s Strength by Machine Learning: Balance between Accuracy and Complexity of Algorithms
B. Ouyang, Y. Song, Y. Li, F. Wu, H. Yu, Y. Wang, G. Sant, and M. Bauchy
Nov 2020
Temperature-Induced Aggregation in Portlandite Suspensions
Sharu Bhagavathi Kandy, Iman Mehdipour, Narayanan Neithalath, Mathieu Bauchy, Edward Garboczi, Samanvaya Srivastava, Torben Gaedt, and Gaurav Sant
Aug 2020
Mineral Dissolution under Electric Stimulation
Yi-Hsuan Hsiao, Xin Chen, Erika Callagon La Plante, Aditya Kumar, Mathieu Bauchy, Dante Simonetti, David Jassby, Jacob Israelachvili, and Gaurav Sant
Jul 2020
Precipitation of calcium–alumino–silicate–hydrate gels: The role of the internal stress
C. Zhao, W. Zhou, Q. Zhou, Y. Zhang, H. Liu, G. Sant, X. H. Liu, L. J. Guo, and M. Bauchy
Jul 2020
Role of Internal Stress in the Early-Stage Nucleation of Amorphous Calcium Carbonate Gels
Q. Zhou, T. Du, L. J. Guo, G. Sant, and M. Bauchy
Jun 2020
Dispersing nano- and micro-sized portlandite particulates via electrosteric exclusion at short screening lengths
J. Timmons, I. Mehdipour, S. Gao, H. Atahan, N. Neithalath, M. Bauchy, E. Garboczi, S. Srivastava, and G. Sant
Mar 2020