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Elvan Sahin

Government of the United States of America - Idaho National Laboratory

Box 1625

Idaho Falls, ID 83415

United States

  • Government of the United States of America - Idaho National Laboratory

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Data-Driven Forecasting of Solid Oxide Electrolysis Cell Degradation Using Deep Transfer Learning​

Number of pages: 45 Posted: 20 Mar 2026
Elvan Sahin, Nicholas Kane, Joseph Barton, Jeremy Lee Hartvigsen, Meng Li, Temitayo Olowu and Micah Casteel
Government of the United States of America - Idaho National Laboratory, Government of the United States of America - Idaho National Laboratory, Government of the United States of America - Idaho National Laboratory, Government of the United States of America - Idaho National Laboratory, Government of the United States of America - Idaho National Laboratory, Government of the United States of America - Idaho National Laboratory and Government of the United States of America - Idaho National Laboratory
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Abstract:

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SOEC degradation, Deep learning, LSTM, transfer learning, attention mechanism