Predictive Hierarchical Modeling Of Chemical Separations And Transformations In Functional Nanoporous Materials

Predictive Hierarchical Modeling Of Chemical Separations And Transformations In Functional Nanoporous Materials

View the public abstract at DOE

Associated Software

CP2K
RASPA
Zeo++
Chemical VAE
PySCF
MCCCS-MN
SorbNet
QMMM
memPy
QMOF Database
SorbMetaML
SupramolecularVAE
mrh and pDMET
Predicted Nanoporous Material Structures
QSoME
pySIMM

Associated Highlights

Energy-Based Descriptors to Rapidly Predict Hydrogen Storage in Metal–Organic Frameworks
Deep Neural Network Learning of Complex BinarySorption Equilibria from Molecular Simulation Data

Award Number

SC0008688

Is this a center?

Yes

Center

Nanoporous Materials Genome Center (NMGC)

PI First Name

J. Ilja

PI Last Name

Siepmann

PI Link

The Siepmann Group

Institution

University of Minnesota

Home

Minneapolis, MN

FY Start

2017

FY End

2021

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