Accelerating the Design of Double-Absorber Solar Cells: From Surrogate Model-Assisted Reinforcement Learning and Multi-Algorithm Optimization Comparison to Transfer Learning.
- DOI
- 10.3390/ma19143091
- Published
- 2026 Jul 17
- Container
- Materials (Basel, Switzerland)
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3390/ma19143091,
title = {Accelerating the Design of Double-Absorber Solar Cells: From Surrogate Model-Assisted Reinforcement Learning and Multi-Algorithm Optimization Comparison to Transfer Learning.},
author = {Zhang Y and Sun Q and Zhao J},
year = {2026},
journal = {Materials (Basel, Switzerland)},
doi = {10.3390/ma19143091},
url = {https://doi.org/10.3390/ma19143091}
}RIS
TY - JOUR TI - Accelerating the Design of Double-Absorber Solar Cells: From Surrogate Model-Assisted Reinforcement Learning and Multi-Algorithm Optimization Comparison to Transfer Learning. AU - Zhang Y AU - Sun Q AU - Zhao J PY - 2026 JO - Materials (Basel, Switzerland) DO - 10.3390/ma19143091 UR - https://doi.org/10.3390/ma19143091 ER -
APA
Y, Z., Q, S., & J, Z. (2026). Accelerating the Design of Double-Absorber Solar Cells: From Surrogate Model-Assisted Reinforcement Learning and Multi-Algorithm Optimization Comparison to Transfer Learning.. Materials (Basel, Switzerland). https://doi.org/10.3390/ma19143091
Source records
- pubmed · retrieved 2026-09-25T19:43:51.371Z