Simulations

Computational Discovery of Fast Interstitial Oxygen Conductors

Meng, J., Sheikh, M.S., Jacobs, R., Liu, J., Nachlas, W.O., Li, X., and Morgan, D., 2024, Computational Discovery of Fast Interstitial Oxygen Conductors. Nature Materials. https://doi.org/10.1038/s41563-024-01919-8

Falyn Eisiminger2024-07-16T17:34:28+00:00June 13th, 2024|

Monitoring Natural Gas Infrastructure

AI Enhanced Distributed Fiber Optic Sensing

Problem: Sensor data for various pipeline events are scarce for AI based classification

Solution: Develop Hybrid AI model to simulate distributed optical fiber sensor response for various pipeline integrity events

NETL’s pipeline sensors team tested new technologies in mid-February 2023 at the Southwest Research Institute test facility at a pilot-scale and recently signed a CRADA to continue field demonstrations.

Falyn Eisiminger2024-09-18T16:07:27+00:00May 14th, 2024|

URC Resource Assessment Method/Tool

Federated-AI modeling for improving Natural Resource Assessments

NETL’s geologic resource assessment AI Model helped uncover the largest unconventional deposit of magnetic rare earth elements (REE) in the U.S.
The AI model was tested at a coal mine in Wyoming’s Powder River Basin and revealed the largest unconventional deposit of magnetic REEs discovered in the US.
- Featured in the Wall Street Journal – WSJ
- Also featured in energy trade journal, JPT
In the last year, NETL has released five, peer-reviewed, data-driven products that help characterize unconventional critical minerals, all developed in support of SAMI.

Expanded use for Groundwater, Carbon Storage, H2, hydrocarbons, geothermal and more.

Try the database here.