scholarly journals Machine learning property prediction for organic photovoltaic devices

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Nastaran Meftahi ◽  
Mykhailo Klymenko ◽  
Andrew J. Christofferson ◽  
Udo Bach ◽  
David A. Winkler ◽  
...  
Keyword(s):  
Machine Learning ◽  
Molecular Orbital ◽  
Short Circuit ◽  
Open Circuit ◽  
Green Energy ◽  
Organic Photovoltaic ◽  
Learning Approaches ◽  
Potential Donor ◽  
Energy Applications ◽  
Donor And Acceptor

Abstract Organic photovoltaic (OPV) materials are promising candidates for cheap, printable solar cells. However, there are a very large number of potential donors and acceptors, making selection of the best materials difficult. Here, we show that machine-learning approaches can leverage computationally expensive DFT calculations to estimate important OPV materials properties quickly and accurately. We generate quantitative relationships between simple and interpretable chemical signature and one-hot descriptors and OPV power conversion efficiency (PCE), open circuit potential (Voc), short circuit density (Jsc), highest occupied molecular orbital (HOMO) energy, lowest unoccupied molecular orbital (LUMO) energy, and the HOMO–LUMO gap. The most robust and predictive models could predict PCE (computed by DFT) with a standard error of ±0.5 for percentage PCE for both the training and test set. This model is useful for pre-screening potential donor and acceptor materials for OPV applications, accelerating design of these devices for green energy applications.

Effective Light Harvesting of Tandem Polymer Solar Cell

2010 ◽  
Vol 132 (2) ◽  
Author(s):  
Yi-Chun Chen ◽  
Chao-Ying Yu ◽  
Chih-Ping Chen ◽  
Shu-Hua Chan ◽  
Ching Ting
Keyword(s):  
Solar Cell ◽  
Molecular Orbital ◽  
Open Circuit Voltage ◽  
Polymer Solar Cell ◽  
Short Circuit ◽  
Active Material ◽  
Weight Ratio ◽  
Acid Methyl Ester ◽  
Open Circuit ◽  
Ito Glass

A novel soluble conjugated polymers, P2, with coplanar thiophene-phenylene-thiophene unit is designed and synthesized as suitable active material used in tandem cells to compensate the poly(3-hexylthiophene) (P3HT)/[6,6]-phenyl-C71 butyric acid methyl ester (PC71BM) bulk-heterojunction cell in this paper. P2 polymer bears advantages in both low optical bandgap (1.7 eV) and high hole mobility properties (3.4×10−3 cm2/V-s from field-effect transistor measurement). Furthermore, the electrochemical studies of P2 indicate desirable highest occupied molecular orbital/lowest unoccupied molecular orbital (HOMO/LUMO) band structure that enables a high open circuit voltage when pairing with PCBM acceptor. The best power conversion efficiency of this polymer solar cell thus far based on P2/PC71BM system with a weight ratio of 1:3 reached 4.4% with a short circuit current density (Jsc) of 10.2 mA/cm2, an open circuit voltage (Voc) of 0.81 V, and a fill factor (FF) of 0.53 under air mass (AM) 1.5 G (100 mW/cm2). The preliminary data of the tandem cell with indium tin oxide (ITO) glass/PEDOT:PSS/P2:PC71BM/TiOx/PEDOT:PSS/P3HT:PC71BM/TiOx/Al configuration has reached Jsc of 6.2 mA/cm2, Voc of 1.33 V, FF of 0.56 and an overall efficiency of 4.6% under AM 1.5 G (100 mW/cm2).

scholarly journals Molecular-level architectural design using benzothiadiazole-based polymers for photovoltaic applications

2017 ◽  
Vol 13 ◽  
pp. 863-873 ◽  
Author(s):  
Vinila N Viswanathan ◽  
Arun D Rao ◽  
Upendra K Pandey ◽  
Arul Varman Kesavan ◽  
Praveen C Ramamurthy
Keyword(s):  
Molecular Orbital ◽  
Architectural Design ◽  
Density Functional ◽  
Short Circuit ◽  
Energy Levels ◽  
Photovoltaic Performance ◽  
Hole Mobility ◽  
Short Circuit Current ◽  
Open Circuit ◽  
Lowest Unoccupied Molecular Orbital

A series of low band gap, planar conjugated polymers, P1 (PFDTBT), P2 (PFDTDFBT) and P3 (PFDTTBT), based on fluorene and benzothiadiazole, was synthesized. The effect of fluorine substitution and fused aromatic spacers on the optoelectronic and photovoltaic performance was studied. The polymer, derived from dithienylated benzothiodiazole and fluorene, P1, exhibited a highest occupied molecular orbital (HOMO) energy level at −5.48 eV. Density functional theory (DFT) studies as well as experimental measurements suggested that upon substitution of the acceptor with fluorine, both the HOMO and lowest unoccupied molecular orbital (LUMO) energy levels of the resulting polymer, P2, were lowered, leading to a higher open circuit voltage and short circuit current with an overall improvement of more than 110% for the photovoltaic devices. Moreover, a decrease in the torsion angle between the units was also observed for the fluorinated polymer P2 due to the enhanced electrostatic interaction between the fluorine substituents and sulfur atoms, leading to a high hole mobility. The use of a fused π-bridge in polymer P3 for the enhancement of the planarity as compared to the P1 backbone was also studied. This enhanced planarity led to the highest observed mobility among the reported three polymers as well as to an improvement in the device efficiency by more than 40% for P3.

Nanostructured Molybdenum Trioxide Layer on the Silver Anode of a Top-Incident Organic Photovoltaic Device

2021 ◽  
Vol 21 (3) ◽  
pp. 1659-1666
Author(s):  
Chia-Hsun Chen ◽  
Jiun Haw Lee ◽  
Chien-Liang Lin ◽  
Tien-Lung Chiu
Keyword(s):  
Buffer Layer ◽  
Deposition Rate ◽  
Fill Factor ◽  
Molybdenum Trioxide ◽  
Short Circuit ◽  
Short Circuit Current ◽  
Short Circuit Current Density ◽  
Open Circuit ◽  
Organic Photovoltaic ◽  
20 Nm

A nanostructured molybdenum trioxide (MoO3) layer was successfully fabricated utilizing various deposition rates, employed as an anodic buffer layer to separate the active layer from a silver anode and modifying the anodic surface to facilitate hole transportation for top-incident organic photovoltaic (TIOPV) devices. The deposition rate and thickness of the MoO3 layer were crucial parameters for determining the surface morphology and work function, and the internal optical field distribution, respectively. These factors affected the performance of the devices in terms of their open-circuit voltage (VOC), short-circuit current density (JSC), and fill factor (FF). The baseline TIOPV device without a buffer layer had a power conversion efficiency (PCE) of only 0.47%. By contrast, with a smooth 20-nm MoO3 buffer layer fabricated using a deposition rate of 1 Å/s (which prevented problems caused by the Ag anode), another fabricated TIOPV device had substantially higher VOC, JSC and FF values, which improved the PCE by a factor of 6.2 to 2.92%. When an additional 5-nm nanostructured MoO3 layer was deposited at a deposition rate of 0.5 Å/s, the most efficient TIOPV device had an even greater PCE, a factor of 7.5 times higher at 3.53%.

Organic Photovoltaic Cells Prepared with Toluene Sulfonic Acid Doped Polypyrrole

2010 ◽  
Vol 428-429 ◽  
pp. 450-453 ◽  
Author(s):  
Fu Fang Zhou ◽  
Chun Xu Pan ◽  
Yuan Ming Huang
Keyword(s):  
Indium Tin Oxide ◽  
Sulfonic Acid ◽  
Light Exposure ◽  
Short Circuit ◽  
Photovoltaic Cells ◽  
Short Circuit Current ◽  
Open Circuit ◽  
Organic Photovoltaic ◽  
Organic Photovoltaic Cells ◽  
Toluene Sulfonic Acid

Organic photovoltaic cells were fabricated by sandwiching p-toluene sulfonic acid doped conducting polymer polypyrrole between indium-tin-oxide cathodes and aluminum anodes. The active polymeric layers could effectively absorb incident photons more than 75 % in the entire spectral region of 250~1100 nm. Upon light exposure, the short-circuit current and the open-circuit voltage were recorded up to 0.6 μA/cm2 and 60 mV, respectively, for the organic photovoltaic cells. The dynamics of the generation and decay of the photocurrent and photovoltage in our organic photovoltaic cells were investigated.

scholarly journals Synthesis of Cyano-Substituted Conjugated Polymers for Photovoltaic Applications

Polymers ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 746 ◽  
Author(s):  
Mun Ho Yang ◽  
Ho Cheol Jin ◽  
Joo Hyun Kim ◽  
Dong Wook Chang
Keyword(s):  
Conjugated Polymers ◽  
Molecular Orbital ◽  
Polymer Solar Cells ◽  
Short Circuit ◽  
Energy Levels ◽  
Coupling Reaction ◽  
Short Circuit Current ◽  
Open Circuit ◽  
Strong Electron ◽  
Photovoltaic Properties

Three conjugated polymers, in which the electron-donating (D) 5-alkylthiophene-2-yl-substitued benzodithiophene was linked to three different electron-accepting (A) moieties, i.e., benzothiadiazole (BT), diphenylquinoxaline (DPQ), and dibenzophenazine (DBP) derivative via thiophene bridge, were synthesized using the Stille coupling reaction. In particular, the strong electron-withdrawing cyano (CN) group was incorporated into the A units BT, DPQ, and DBP to afford three D–A type target polymers PB–BTCN, PB–DPQCN, and PB–DBPCN, respectively. Owing to the significant contribution of the CN-substituent, these polymers exhibit not only low-lying energy levels of both the highest occupied molecular orbital and the lowest unoccupied molecular orbital, but also reduced bandgaps. Furthermore, to investigate the photovoltaic properties of polymers, inverted-type devices with the structure of ITO/ZnO/Polymer:PC71BM/MoO3/Ag were fabricated and analyzed. All the polymer solar cells based on the three cyano-substituted conjugated polymers showed high open-circuit voltages (Voc) greater than 0.89 V, and the highest power conversion efficiency of 4.59% was obtained from the device based on PB-BtCN with a Voc of 0.93 V, short-circuit current of 7.36 mA cm−2, and fill factor of 67.1%.

scholarly journals Machine Learning as an Efficient Diagnostic Tool for Fault Detection and Localization in Solar Photovoltaic Arrays

10.29007/34bz ◽  
2019 ◽  
Author(s):  
Masoud Alajmi ◽  
Sultan Aljahdali ◽  
Sultan Alsaheel ◽  
Mohammed Fattah ◽  
Mohammed Alshehri
Keyword(s):  
Machine Learning ◽  
Renewable Energy ◽  
Fault Detection ◽  
Solar Energy ◽  
Hot Spot ◽  
Low Cost ◽  
Short Circuit ◽  
Renewable Energy Sources ◽  
Open Circuit ◽  
Detection And Localization

Solar energy, one of many types of renewable energy, is considered to be an excellent alternative to non-renewable energy sources. Its popularity is increasing rapidly, especially because fuel energy consumes and depletes finite natural resources, polluting the environment, whereas solar energy is low- cost and clean. To produce a reliable supply of energy, however, solar energy must also be consistent. The energy we derive from a photovoltaic (PV) array is dependent on changeable factors such as sunlight, positioning of the array, covered area, and status of the solar cell. Every change adds potential for the creation of error in the array. Therefore, thorough research and a protocol for fast, efficient location and correction of all kinds of errors must be an urgent priority for researchers.For this project we used machine learning (ML) with voltage and current sensors to detect, localize and classify common faults including open circuit, short circuit, and hot-spot. Using the proposed algorithm, we have improved the accuracy of fault detection, classification and localization to 100%. Further, the proposed method can execute all three tasks (detection, classification, and localization) simultaneously.

scholarly journals Optimization of the Bulk Heterojunction of All-smallmolecule Organic Photovoltaics Using Design of Experiment and Machine Learning Approaches

2020 ◽  
Author(s):  
Aaron Kirkey ◽  
Erik Luber ◽  
Bing Cao ◽  
Brian Olsen ◽  
Jillian Buriak
Keyword(s):  
Machine Learning ◽  
Small Molecule ◽  
High Efficiency ◽  
Bulk Heterojunction ◽  
Core Layer ◽  
Processing Parameters ◽  
Learning Approaches ◽  
Large Parameter ◽  
Donor And Acceptor ◽  
Experimental Processing

All-small-molecule organic photovoltaic (OPV) cells based upon the small molecule donor, DRCN5T, and non-fullerene acceptors, ITIC, IT-M, and IT-4F, were optimized using Design of Experiments (DOE) and machine learning (ML) approaches. This combination enables rational sampling of large parameter spaces in a sparse but mathematically deliberate fashion and promises economies of precious resources and time. The work focused upon the optimization of the core layer of the OPV device, the bulk heterojunction (BHJ). Many experimental processing parameters play critical roles in the overall efficiency of a given device and are often correlated, and thus are difficult to parse individually. DOE was applied to the (i) solution concentration of the donor and acceptor ink used for spin-coating, (ii) the donor fraction, and (iii) the temperature and (iv) duration of the annealing of these films. The ML-based approach was then used to derive maps of the PCE landscape for the first and second rounds of optimization to be used as guides to determine the optimal values of experimental processing parameters with respect to device efficiency. This work shows that with little knowledge of a potential combination of components for a given BHJ, a large parameter space can be effectively screened and investigated to rapidly determine its potential for high efficiency OPVs.

scholarly journals Design, Electrical, and Optical Modelling of Bulk Heterojunction Polymer Solar Cell

2018 ◽  
Vol 2018 ◽  
pp. 1-6
Author(s):  
Muhammad Ali ◽  
Ahmed Shuja ◽  
Ahsan Baig ◽  
Erum Jamil ◽  
Muhammad Amjad
Keyword(s):  
Solar Cells ◽  
Solar Cell ◽  
Polymer Solar Cell ◽  
Bulk Heterojunction ◽  
Short Circuit ◽  
Short Circuit Current ◽  
Clean Energy ◽  
Open Circuit ◽  
Solar Module ◽  
Donor And Acceptor

The energy scenario today is focused on the development and usage of solar cells, especially in the paradigm of clean energy. To readily create electron and hole pairs, solar cells utilize either photoactive or photosensitive components. A bulk heterojunction (BHJ) is a nanolayer consisting of donor and acceptor components with a large interpenetrated acceptor and donor contact area. In this context, a mix of P3HT and PCBM offers novelty for its use as an acceptor as well as a donor. In the work presented here, we address the mechanism of modelling and characterization of a BHJ-based polymer solar cell. Here, a new design of BHJ polymer solar cells have been designed, modelled, using Silvaco TCAD in the Organic Solar module, and matched with an already assembled device having similar features. Using this model, we have been able to estimate key parameters for the modelled devices, such as the short-circuit current density, open-circuit voltage, and fill factor with less than 0.25 error index compared to the fabricated counterpart, paving the way for fabless polymer solar cell design and optimization.

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