Using a Neural Network to Improve the Optical Absorption in Halide Perovskite Layers Containing Core-Shells Silver Nanoparticles
Interdisciplinary Centre for Nanostructured Materials and Interfaces (CIMaINa) and Physics Department “Aldo Pontremoli”, University of Milan, Via Celoria 16, 20133 Milan, Italy
*
Author to whom correspondence should be addressed.
Nanomaterials 2019, 9(3), 437; https://doi.org/10.3390/nano9030437
Received: 3 February 2019
/
Revised: 6 March 2019
/
Accepted: 12 March 2019
/
Published: 15 March 2019
(This article belongs to the Special Issue Nanoparticles for Photovoltaics)
Core-shells metallic nanoparticles have the advantage of possessing two plasmon resonances, one in the visible and one in the infrared part of the spectrum. This special property is used in this work to enhance the efficiency of thin film solar cells by improving the optical absorption at both wavelength ranges simultaneously by using a neural network. Although many thin-film solar cell compositions can benefit from such a design, in this work, different silver core-shell configurations were explored inside a Halide Perovskite (CH3NH3PbI3) thin film. Because the number of potential configurations is infinite, only a limited number of finite difference time domain (FDTD) simulations were performed. A neural network was then trained with the simulation results to find the core-shells configurations with optimal optical absorption across different wavelength ranges. This demonstrates that core-shells nanoparticles can make an important contribution to improving solar cell performance and that neural networks can be used to find optimal results in such nanophotonic systems.
View Full-Text
Keywords:
solar cell; plasmonics; light management; perovskite; core-shells; nanoparticles; silver 7; thin films; neural network; machine learning
▼
Show Figures
Figure 1
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
- Supplementary File 1:
PDF-Document (PDF, 161 KiB)
MDPI and ACS Style
Nelson, M.D.; Di Vece, M. Using a Neural Network to Improve the Optical Absorption in Halide Perovskite Layers Containing Core-Shells Silver Nanoparticles. Nanomaterials 2019, 9, 437. https://doi.org/10.3390/nano9030437
AMA Style
Nelson MD, Di Vece M. Using a Neural Network to Improve the Optical Absorption in Halide Perovskite Layers Containing Core-Shells Silver Nanoparticles. Nanomaterials. 2019; 9(3):437. https://doi.org/10.3390/nano9030437
Chicago/Turabian StyleNelson, Michael D., and Marcel Di Vece. 2019. "Using a Neural Network to Improve the Optical Absorption in Halide Perovskite Layers Containing Core-Shells Silver Nanoparticles" Nanomaterials 9, no. 3: 437. https://doi.org/10.3390/nano9030437
Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.
