Optimization of the Bulk Heterojunction of All-Small-Molecule Organic Photovoltaics Using Design of Experiment and Machine Learning Approaches

2020 ◽  
Vol 12 (49) ◽  
pp. 54596-54607
Author(s):  
Aaron Kirkey ◽  
Erik J. Luber ◽  
Bing Cao ◽  
Brian C. Olsen ◽  
Jillian M. Buriak
Keyword(s):  
Machine Learning ◽  
Small Molecule ◽  
Organic Photovoltaics ◽  
Design Of Experiment ◽  
Bulk Heterojunction ◽  
Learning Approaches

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 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 Melt-processing of small molecule organic photovoltaics via bulk heterojunction compatibilization

2018 ◽  
Vol 20 (10) ◽  
pp. 2218-2224 ◽  
Author(s):  
Aiman Rahmanudin ◽  
Liang Yao ◽  
Xavier A. Jeanbourquin ◽  
Yongpeng Liu ◽  
Arvindh Sekar ◽  
...  
Keyword(s):  
Small Molecule ◽  
Organic Photovoltaics ◽  
Bulk Heterojunction ◽  
Melt Processing ◽  
Organic Photovoltaic ◽  
Photovoltaic Devices ◽  
Organic Photovoltaic Devices

A specially-designed molecular compatibilizer enables bulk-heterojunction organic photovoltaic devices that tolerate melt processing thus reducing the need for toxic solvents.

Improvement of Interfacial Contacts for New Small-Molecule Bulk-Heterojunction Organic Photovoltaics

2012 ◽  
Vol 24 (39) ◽  
pp. 5368-5373 ◽  
Author(s):  
Andres Garcia ◽  
Gregory C. Welch ◽  
Erin L. Ratcliff ◽  
David S. Ginley ◽  
Guillermo C. Bazan ◽  
...  
Keyword(s):  
Small Molecule ◽  
Organic Photovoltaics ◽  
Bulk Heterojunction

scholarly journals Improving the Photostability of Small-Molecule-Based Organic Photovoltaics by Providing a Charge Percolation Pathway of Crystalline Conjugated Polymer

Polymers ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 2598
Author(s):  
Jihee Kim ◽  
Chang Woo Koh ◽  
Mohammad Afsar Uddin ◽  
Ka Yeon Ryu ◽  
Song-Rim Jang ◽  
...  
Keyword(s):  
Small Molecule ◽  
Organic Photovoltaics ◽  
Conjugated Polymer ◽  
Bulk Heterojunction ◽  
Hole Mobility ◽  
Chemical Structures ◽  
Active Layers ◽  
Similar Chemical ◽  
A Charge ◽  
Soaking Test

Photostability of small-molecule (SM)-based organic photovoltaics (SM-OPVs) is greatly improved by utilizing a ternary photo-active layer incorporating a small amount of a conjugated polymer (CP). Semi-crystalline poly[(2,5-bis(2-hexyldecyloxy)phenylene)-alt-(5,6-difluoro-4,7-di(thiophen-2-yl)benzo[c][1,2,5]thiadiazole)] (PPDT2FBT) and amorphous poly[(2,5-bis(2-decyltetradecyloxy)phenylene)-alt-(5,6-dicyano-4,7-di(thiophen-2-yl)benzo[c][1,2,5]thiadiazole)] (PPDT2CNBT) with similar chemical structures were used for preparing SM:fullerene:CP ternary photo-active layers. The power conversion efficiency (PCE) of the ternary device with PPDT2FBT (Ternary-F) was higher than those of the ternary device with PPDT2CNBT (Ternary-CN) and a binary SM-OPV device (Binary) by 15% and 17%, respectively. The photostability of the SM-OPV was considerably improved by the addition of the crystalline CP, PPDT2FBT. Ternary-F retained 76% of its initial PCE after 1500 h of light soaking, whereas Ternary-CN and Binary retained only 38% and 17% of their initial PCEs, respectively. The electrical and morphological analyses of the SM-OPV devices revealed that the addition of the semi-crystalline CP led to the formation of percolation pathways for charge transport without disturbing the optimized bulk heterojunction morphology. The CP also suppressed trap-assisted recombination and enhanced the hole mobility in Ternary-F. The percolation pathways enabled the hole mobility of Ternary-F to remain constant during the light-soaking test. The photostability of Ternary-CN did not improve because the addition of the amorphous CP inhibited the formation of ordered SM domains.

Insulating polymer additives in small molecule and polymer photovoltaics: how they are tolerated and their use as potential interlayers

2017 ◽  
Vol 5 (13) ◽  
pp. 3315-3322 ◽  
Author(s):  
Joseph G. Manion ◽  
Dong Gao ◽  
Peter M. Brodersen ◽  
Dwight S. Seferos
Keyword(s):  
Small Molecule ◽  
Organic Photovoltaics ◽  
Bulk Heterojunction ◽  
Polymer Additives ◽  
Polymer Photovoltaics ◽  
Efficient Performance

Additives are key to achieving optimal morphologies and efficient performance in bulk heterojunction organic photovoltaics.

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