Christopher M. Childs

Cheminformatics for accelerated design of chemical admixtures

Barnabás Póczos, Christopher M. Childs, Oğulcan Canbek, 2020 .

Machine learning approaches to admixture design for clay-based cements

Barnabás Póczos, Christopher M. Childs, Kimberly E. Kurtis, 2018 .

Molecular Engineering of Superplasticizers for Metakaolin‐Portland Cement Blends with Hierarchical Machine Learning

Christopher M. Childs, B. Póczos, K. Kurtis, 2018, Advanced Theory and Simulations.

Embedding domain knowledge for machine learning of complex material systems

Christopher M. Childs, N. Washburn, 2019, MRS Communications.

Elucidating the Physicochemical Basis of the Glass Transition Temperature in Linear Polyurethane Elastomers with Machine Learning.

Christopher M. Childs, N. Washburn, Joseph A. Pugar, 2020, The journal of physical chemistry. B.

Advancing cement-based materials design through data science approaches

Christopher M. Childs, Scott H. Smith, K. Kurtis, 2021, RILEM Technical Letters.

Interplay of Anionic Functionality in Polymer-Grafted Lignin Superplasticizers for Portland Cement

Christopher M. Childs, A. Menon, K. Perkins, 2019, Industrial & Engineering Chemistry Research.

Hierarchical Machine Learning for High-Fidelity 3D Printed Biopolymers.

Barnabás Póczos, Christopher M. Childs, Philip R LeDuc, 2020, ACS biomaterials science & engineering.

Hierarchical Machine Learning for High-Fidelity 3D Printed Biopolymers.

Christopher M. Childs, B. Póczos, A. Feinberg, 2020, ACS biomaterials science & engineering.