Optoelectronic insights into the photovoltaic losses from photocurrent, voltage, and energy perspectives

Shang, Aixue; An, Yidan; Ma, Dong; Li, Xiao Feng

doi:10.1063/1.4990288

Cited by 15 publications

(11 citation statements)

References 28 publications

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“…Moreover, to have a complete information on the photocurrent and various current loss mechanisms, the photogenerated current density ( J ph ) (under perfect internal quantum process), short‐circuit current density ( J sc ) (under realistic optoelectronic calculation), current loss due to bulk recombination ( J bulk ), and current loss due to surface recombination ( J surf ) are all examined for both n‐ and p‐perovskite PSCs, as shown in Figure a,b, respectively. In fact, J ph sets the upper limit of the photocurrent since all carrier losses during the transportation have been neglected; therefore, there has the following conservation:

J_{p h} = J_{s c} + J_{b u l k} + J_{s u r f}

which has indeed been verified by our simulation.…”

Section: Resultssupporting

confidence: 76%

Perovskite Solar Cells: Optoelectronic Simulation and Optimization

Shang

Cao

et al. 2018

Solar RRL

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To realize reliably high efficiency of perovskite solar cells (PSCs), material synthesis, interface manipulation, and device realization have been widely studied. Nevertheless, deeply understanding the fundamental optics and physics which regulate the multi-domain optoelectronic responses is crucial. Here, the authors present an optoelectronic study of PSCs under various configurations. It combines electromagnetic response and carrier electrodynamics inside PSCs so that the microscopic response in frequency/spatial domains and the device output can be obtained. The effects of perovskite doping type/concentration/thickness and doping concentrations of electron (hole) transport layer (i.e., ETL [HTL]) on the optoelectronic response of the complete, free-HTL, and free-ETL PSCs are studied. The energy diagrams addressing the band bending, the built-in electrical field addressing the carrier separation, and the surface/bulk recombination addressing the current losses are analyzed. It is found that the doping type of perovskite greatly affects the cell performance, for example, for ETL-side illumination, pperovskite enables higher efficiency than n-doping due to a much reduced bulk recombination. Achieving good agreements with existing experiments, the model is used for the design of PSCs. It shows that the photoconversion efficiencies of complete, free-HTL, and free-ETL PSCs can be enhanced from 16.6%, 10.7%, and 13.3% to 19.0%, 15.9%, and 18.5%, respectively.

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J_{p h} = J_{s c} + J_{b u l k} + J_{s u r f}

which has indeed been verified by our simulation.…”

Section: Resultssupporting

confidence: 76%

Perovskite Solar Cells: Optoelectronic Simulation and Optimization

Shang

Cao

et al. 2018

Solar RRL

Self Cite

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“…7a, the J-V characteristics have been calculated for the initial temperature (T=293 K) and the coupled temperature (ranged between 315-320 K). The current-density is not affected as it is not directly temperature-dependent [19] but the V oc has significantly reduced for about 0.05 V as it is a temperature-dependent parameter (as expected from Eq. ( 13)).…”

Section: Temperature Impact On J-v Characteristicssupporting

confidence: 61%

“…[20] where a raise in temperature from 293K (T in our initial study) to over 320K (T in our coupled study) deterred the cell efficiency from 21.52% to 19.72%. It is also noted that although the short-circuit current density of the cell did not decrease by the heat generation in this cell, the experimental data shows that for temperatures over 320 K, J sc will also experience a slight decrease due to increased J o and from bandgap's dependency on temperature [23]. Note, in our study, the optical reflection loss and parasitic loss from the resistance of the thin layers in this solar cell structure was not calculated as was pointed in Fig.…”

Section: Temperature Impact On J-v Characteristicsmentioning

confidence: 72%

Simulation of Heat Loss in CZTSSe Thin Film Solar Cells: A Coupled Optical-Electrical-Thermal Modeling

Zandi

Seresht

Gorji

2021

Preprint

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A coupled optical-electrical-thermal modeling has been developed to investigate the heat generation in CZTSSe solar cells via Thermalization, Joule heat, Peltier heat, Surface Recombination heat, and non-radiative recombination heat and also the heat dissipation via convective and radiative cooling. These were calculated and displayed in 2D and 3D maps either at zero bias or open-circuit voltage (V oc) conditions. At V=0, the heat is generated mainly at the junction of CZTSSe/CdS where the thermalization and Joule heats are dominantly higher compared to non-radiative (SRH and Auger) recombination heat. However, at V=V oc , the nan-radiative recombination heat becomes comparatively higher than the Joule heating whereas the thermalization remains highest as before. Apart from the bulk heating factors, we also studied the surface recombination and Peltier heat generation. The surface recombination heat is higher at V=V oc compared to at V=0 while the Peltier heat is zero at V=V oc which can be explained by looking at the energy band diagrams at these voltages. The total heat generation does not change much across the cell thickness (<5×10 9 W/m 3) as the cell is quite thin. Nevertheless, the individual impact of every heat generation factor on power-density and current-voltage characteristics of the cell reveals that the thermalization, Joule, and non-radiative recombination heats reduce the open-circuit voltage of the cell from 0.54 V to 0.49 V (∆V = 0.047 V) while the Peltier and surface recombination heat is less effective. The temperature of the cell shows a small distribution across the cell (0.01 K). However, the temperature of the initial study at 293 K increases to 315-320 K for the coupled study. At this increased temperature, the short current-density doesn’t change but the fill factor decreases from 73.8% to 71.8% and, therefore, the energy conversion efficiency of the cell falls by 11.11% (from initial 12.78% to 11.36%). All the total heat dissipation, convective, and radiation cooling follow a similar trend to the total heat generation but convective cooling is the dominant component of dissipation.

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“…12(a), exhibits maximum heating at the CdS and perovskite surfaces due to the highest SRH recombination rate [28]. Additionally, excess energy above the bandgap (ℎ𝜈 − 𝐸 𝑔 ) generates heat through the thermalization process, which is spatially dependent on the generation rate profile [35]. The non-radiative heat distribution for the grated CdS structure is shown in Fig.…”

Section: Effect Of Plasmonic Np Shapementioning

confidence: 99%

Readiness Assessment of Public University in Bangladesh for Education 4.0: A Case Study of Shahjalal University of Science and Technology – Sylhet, Bangladesh

Islam

2022

Khulna Univ. Stud.

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In order to get the benefits of Industry 4.0 (4ir) we need the graduates who are able to face the challenges of 4ir. As the universities are the main sources of producing graduates, they should produce adaptable graduates of 4ir. The 4ir demands such a system of higher education where each and every stakeholders especially educators and learners should be connected in a globalized automated environment, networked, virtualized and flexible. In the paradigm of 4ir learners should learn to learn the sources of learning how to build knowledge and skills within the process of teaching –learning. The study aims to identify the dimensions of E4.0 corresponding to 4ir and to assess the readiness of Shahjalal University of Science and Technology (SUST) is one of 50 public universities of Bangladesh. At present there are 28 disciplines in six schools of studies in SUST and among them 20 departments have been selected for the study based on minimum 10 years of establishment. The assessment has been focused on four aspects mainly curriculum, teacher (faculty), intuitional qualification and logistic supports in terms of E4.0. In conducting the study data from collected 120 teachers and graduate students with a structured questionnaire. The questionnaire was five point scales. The collected data was analyzed with SPSS and mainly frequency in each dimension was found and finally factor analysis was done to find the factors affecting E4.0. The frequency distribution showed that Robotic Process Automation aspects ranked first following cloud computing, data analytics, IoT, AI, and BCT. The factor analysis showed that seventeen aspects have been considered as important and the top most five aspects are fees and rewards, data as a service, software as a service, AI extraction and user device.

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Optoelectronic insights into the photovoltaic losses from photocurrent, voltage, and energy perspectives

Cited by 15 publications

References 28 publications

Perovskite Solar Cells: Optoelectronic Simulation and Optimization

Perovskite Solar Cells: Optoelectronic Simulation and Optimization

Simulation of Heat Loss in CZTSSe Thin Film Solar Cells: A Coupled Optical-Electrical-Thermal Modeling

Readiness Assessment of Public University in Bangladesh for Education 4.0: A Case Study of Shahjalal University of Science and Technology – Sylhet, Bangladesh

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