TY - JOUR
T1 - MDLab
T2 - AI frameworks for carbon capture and battery materials
AU - Elmegreen, Bruce
AU - Hamann, Hendrik F.
AU - Wunsch, Benjamin
AU - Van Kessel, Theodore
AU - Luan, Binquan
AU - Elengikal, Tonia
AU - Steiner, Mathias
AU - Neumann Barros Ferreira, Rodrigo
AU - Ohta, Ricardo Luis
AU - Oliveira, Felipe Lopes
AU - McDonagh, James L.
AU - O’Conchuir, Breanndan
AU - Zavitsanou, Stamatia
AU - Harrison, Alexander
AU - Cipcigan, Flaviu
AU - de Mel, Geeth
AU - La, Young Hye
AU - Sharma, Vidushi
AU - Zubarev, Dmitry Yu
N1 - Publisher Copyright:
Copyright © 2023 Elmegreen, Hamann, Wunsch, Van Kessel, Luan, Elengikal, Steiner, Neumann Barros Ferreira, Ohta, Oliveira, McDonagh, O’Conchuir, Zavitsanou, Harrison, Cipcigan, de Mel, La, Sharma and Zubarev.
PY - 2023
Y1 - 2023
N2 - There is a growing urgency to discover better materials that capture CO2 from air and improve battery performance. An important step is to search large databases of materials properties to find examples that resemble known carbon capture agents or electrolytes and then test them for effectiveness. This paper describes novel computational tools for accelerated discovery of solvents, nano-porous materials, and electrolytes. These tools have produced interesting results so far, such as the identification of a relatively isolated location in amine configuration space for the solvents with known carbon capture use, and the demonstration of an end-to-end simulation and process model for carbon capture in MOFs.
AB - There is a growing urgency to discover better materials that capture CO2 from air and improve battery performance. An important step is to search large databases of materials properties to find examples that resemble known carbon capture agents or electrolytes and then test them for effectiveness. This paper describes novel computational tools for accelerated discovery of solvents, nano-porous materials, and electrolytes. These tools have produced interesting results so far, such as the identification of a relatively isolated location in amine configuration space for the solvents with known carbon capture use, and the demonstration of an end-to-end simulation and process model for carbon capture in MOFs.
KW - amines
KW - carbon capture
KW - chemical informatics
KW - computational chemistry
KW - electrolytes
KW - nanoporous materials
UR - https://www.scopus.com/pages/publications/85170530049
U2 - 10.3389/fenvs.2023.1204690
DO - 10.3389/fenvs.2023.1204690
M3 - Article
AN - SCOPUS:85170530049
SN - 2296-665X
VL - 11
JO - Frontiers in Environmental Science
JF - Frontiers in Environmental Science
M1 - 1204690
ER -