CX-101228 Optimized Hydrogen Adsorbents via Machine Learning and Crystal Engineering

Award Number: DE-EE0008093CX(s) Applied: A9, B3.6Fuel Cell Technologies OfficeLocation(s): MIOffice(s): Golden Field Office

Office of NEPA Policy and Compliance

October 22, 2018
Estimated Read Time   min

Award Number: DE-EE0008093
CX(s) Applied: A9, B3.6
Fuel Cell Technologies Office
Location(s): MI
Office(s): Golden Field Office

The U.S. Department of Energy (DOE) is proposing to provide federal funding to the Regents of the University of Michigan (UM) to use machine learning techniques to predict and reverse engineer new metal organic frameworks (MOFs) that show promise for high hydrogen storage capacity. Only Budget Period 1 (BP1) was negotiated at the outset of the project. Accordingly, BP1 activities received a conditional NEPA Determination on July 20, 2017. Upon completion of BP1, a Go Decision was reached. Budget Periods 2 and 3 (BP2 and BP3) have now also been negotiated. This NEPA review will apply to all BP2 and BP3 activities.