A spectral density function approach for design of organic photovoltaic cells

Umar Farooq Ghumman, Joydeep Munshi, Akshay Iyer, Te Yu Chien, Rabindra Dulal, Ganesh Balasubramanian, Aaron Wang, Wei Chen*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Organic Photovoltaic Cells (OPVCs), having received significant attention over the last decade, are yet to be established as viable alternatives to conventional solar cells due to their low power conversion efficiency (PCE). Complex interactions of several phenomena coupled with the lack of understanding regarding the influence of fabrication conditions and nanostructure morphology have been major barriers to realizing higher PCE. To this end, we propose a computational microstructural design framework addressing the Processing–Structure–Performance (PSP) linkages for designing the active layer of P3HT:PCBM based OPVCs conforming to bulk heterojunction architecture. The framework pivots around the Spectral Density Function (SDF), a frequency space microstructure characterization and reconstruction methodology, for microstructure design representation. Nanostructure images obtained by novel Scanning Tunneling Microscopy are used to validate the applicability of SDF for representing active layer morphology in OPVCs. SDF enables a low dimensional microstructure representation that is crucial in formulating a parametrized microstructure optimization scheme. A level-cut Gaussian Random Field (governed by SDF) technique is used to generate reconstructions that serve as Representative Volume Elements (RVEs) for structure-performance simulations. A novel structure-performance simulation approach is developed using physics-based performance metric, Incident Photon to Converted Electron (IPCE) ratio, to account for the impact of microstructural features on OPVC performance. Finally, an SDF based computational IPCE optimization study using metamodels created using design of computer experiments over three design variables results in 36.75% increase in IPCE, underlining the efficacy of proposed design framework.

Original languageEnglish (US)
Title of host publication44th Design Automation Conference
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Electronic)9780791851760
DOIs
StatePublished - Jan 1 2018
EventASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2018 - Quebec City, Canada
Duration: Aug 26 2018Aug 29 2018

Publication series

NameProceedings of the ASME Design Engineering Technical Conference
Volume2B-2018

Other

OtherASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2018
CountryCanada
CityQuebec City
Period8/26/188/29/18

Fingerprint

Organic Photovoltaics
Spectral Density Function
Photovoltaic cells
Spectral density
Probability density function
Microstructure
Cell
Photon
Photons
Electron
Nanostructures
Conversion efficiency
Electrons
Bulk Heterojunction
Gaussian Random Field
Optimization
Computer Experiments
Pivot
Scanning tunneling microscopy
Solar Cells

ASJC Scopus subject areas

  • Mechanical Engineering
  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Modeling and Simulation

Cite this

Ghumman, U. F., Munshi, J., Iyer, A., Chien, T. Y., Dulal, R., Balasubramanian, G., ... Chen, W. (2018). A spectral density function approach for design of organic photovoltaic cells. In 44th Design Automation Conference (Proceedings of the ASME Design Engineering Technical Conference; Vol. 2B-2018). American Society of Mechanical Engineers (ASME). https://doi.org/10.1115/DETC201886154
Ghumman, Umar Farooq ; Munshi, Joydeep ; Iyer, Akshay ; Chien, Te Yu ; Dulal, Rabindra ; Balasubramanian, Ganesh ; Wang, Aaron ; Chen, Wei. / A spectral density function approach for design of organic photovoltaic cells. 44th Design Automation Conference. American Society of Mechanical Engineers (ASME), 2018. (Proceedings of the ASME Design Engineering Technical Conference).
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title = "A spectral density function approach for design of organic photovoltaic cells",
abstract = "Organic Photovoltaic Cells (OPVCs), having received significant attention over the last decade, are yet to be established as viable alternatives to conventional solar cells due to their low power conversion efficiency (PCE). Complex interactions of several phenomena coupled with the lack of understanding regarding the influence of fabrication conditions and nanostructure morphology have been major barriers to realizing higher PCE. To this end, we propose a computational microstructural design framework addressing the Processing–Structure–Performance (PSP) linkages for designing the active layer of P3HT:PCBM based OPVCs conforming to bulk heterojunction architecture. The framework pivots around the Spectral Density Function (SDF), a frequency space microstructure characterization and reconstruction methodology, for microstructure design representation. Nanostructure images obtained by novel Scanning Tunneling Microscopy are used to validate the applicability of SDF for representing active layer morphology in OPVCs. SDF enables a low dimensional microstructure representation that is crucial in formulating a parametrized microstructure optimization scheme. A level-cut Gaussian Random Field (governed by SDF) technique is used to generate reconstructions that serve as Representative Volume Elements (RVEs) for structure-performance simulations. A novel structure-performance simulation approach is developed using physics-based performance metric, Incident Photon to Converted Electron (IPCE) ratio, to account for the impact of microstructural features on OPVC performance. Finally, an SDF based computational IPCE optimization study using metamodels created using design of computer experiments over three design variables results in 36.75{\%} increase in IPCE, underlining the efficacy of proposed design framework.",
author = "Ghumman, {Umar Farooq} and Joydeep Munshi and Akshay Iyer and Chien, {Te Yu} and Rabindra Dulal and Ganesh Balasubramanian and Aaron Wang and Wei Chen",
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Ghumman, UF, Munshi, J, Iyer, A, Chien, TY, Dulal, R, Balasubramanian, G, Wang, A & Chen, W 2018, A spectral density function approach for design of organic photovoltaic cells. in 44th Design Automation Conference. Proceedings of the ASME Design Engineering Technical Conference, vol. 2B-2018, American Society of Mechanical Engineers (ASME), ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2018, Quebec City, Canada, 8/26/18. https://doi.org/10.1115/DETC201886154

A spectral density function approach for design of organic photovoltaic cells. / Ghumman, Umar Farooq; Munshi, Joydeep; Iyer, Akshay; Chien, Te Yu; Dulal, Rabindra; Balasubramanian, Ganesh; Wang, Aaron; Chen, Wei.

44th Design Automation Conference. American Society of Mechanical Engineers (ASME), 2018. (Proceedings of the ASME Design Engineering Technical Conference; Vol. 2B-2018).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - A spectral density function approach for design of organic photovoltaic cells

AU - Ghumman, Umar Farooq

AU - Munshi, Joydeep

AU - Iyer, Akshay

AU - Chien, Te Yu

AU - Dulal, Rabindra

AU - Balasubramanian, Ganesh

AU - Wang, Aaron

AU - Chen, Wei

PY - 2018/1/1

Y1 - 2018/1/1

N2 - Organic Photovoltaic Cells (OPVCs), having received significant attention over the last decade, are yet to be established as viable alternatives to conventional solar cells due to their low power conversion efficiency (PCE). Complex interactions of several phenomena coupled with the lack of understanding regarding the influence of fabrication conditions and nanostructure morphology have been major barriers to realizing higher PCE. To this end, we propose a computational microstructural design framework addressing the Processing–Structure–Performance (PSP) linkages for designing the active layer of P3HT:PCBM based OPVCs conforming to bulk heterojunction architecture. The framework pivots around the Spectral Density Function (SDF), a frequency space microstructure characterization and reconstruction methodology, for microstructure design representation. Nanostructure images obtained by novel Scanning Tunneling Microscopy are used to validate the applicability of SDF for representing active layer morphology in OPVCs. SDF enables a low dimensional microstructure representation that is crucial in formulating a parametrized microstructure optimization scheme. A level-cut Gaussian Random Field (governed by SDF) technique is used to generate reconstructions that serve as Representative Volume Elements (RVEs) for structure-performance simulations. A novel structure-performance simulation approach is developed using physics-based performance metric, Incident Photon to Converted Electron (IPCE) ratio, to account for the impact of microstructural features on OPVC performance. Finally, an SDF based computational IPCE optimization study using metamodels created using design of computer experiments over three design variables results in 36.75% increase in IPCE, underlining the efficacy of proposed design framework.

AB - Organic Photovoltaic Cells (OPVCs), having received significant attention over the last decade, are yet to be established as viable alternatives to conventional solar cells due to their low power conversion efficiency (PCE). Complex interactions of several phenomena coupled with the lack of understanding regarding the influence of fabrication conditions and nanostructure morphology have been major barriers to realizing higher PCE. To this end, we propose a computational microstructural design framework addressing the Processing–Structure–Performance (PSP) linkages for designing the active layer of P3HT:PCBM based OPVCs conforming to bulk heterojunction architecture. The framework pivots around the Spectral Density Function (SDF), a frequency space microstructure characterization and reconstruction methodology, for microstructure design representation. Nanostructure images obtained by novel Scanning Tunneling Microscopy are used to validate the applicability of SDF for representing active layer morphology in OPVCs. SDF enables a low dimensional microstructure representation that is crucial in formulating a parametrized microstructure optimization scheme. A level-cut Gaussian Random Field (governed by SDF) technique is used to generate reconstructions that serve as Representative Volume Elements (RVEs) for structure-performance simulations. A novel structure-performance simulation approach is developed using physics-based performance metric, Incident Photon to Converted Electron (IPCE) ratio, to account for the impact of microstructural features on OPVC performance. Finally, an SDF based computational IPCE optimization study using metamodels created using design of computer experiments over three design variables results in 36.75% increase in IPCE, underlining the efficacy of proposed design framework.

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Ghumman UF, Munshi J, Iyer A, Chien TY, Dulal R, Balasubramanian G et al. A spectral density function approach for design of organic photovoltaic cells. In 44th Design Automation Conference. American Society of Mechanical Engineers (ASME). 2018. (Proceedings of the ASME Design Engineering Technical Conference). https://doi.org/10.1115/DETC201886154