In this thesis, the effective strategy to achieve high performance of OPVs, a combination of NFAs and ternary systems was introduced; It is noteworthy to mention that NFAs permits to achieve high VOC
arise from easily tunable energy levels compared to FAs and improved photon harvesting from complementary absorption is feasible in the ternary blend system. Therefore, photovoltaic application based NFAs and ternary blend systems were carried out and their properties were intensively investigated.
The second chapter deal with a novel ternary blend composed of PTB7-Th, IEICO-4F and two bithiophene core with rhodanine end-groups based NFAs, T2-ORH and T2-OEHRH and their energy conversion electronics; The addition of T2-ORH or T2-OEHRH to the IEICO-4F binary blends did not exhibit a significant beneficial effect on the photovoltaic properties where all the ternary blends achieved ~10% of PCE. Nevertheless, the monotonously enhanced VOCs with increasing T2-ORH or T2-OEHRH contents were observed, the reason would be the remarkably lower LUMO of IEICO-4F (4.19 eV) than that of T2-ORH (3.59 eV) and T2-OEHRH (3.58 eV). It is evident that the working principle of the ternary OPVs is likely to show alloy-like behavior. Although there were no improvements on the photovoltaic properties, the coloration of the blend film was easily implemented including cyan blue purple reddish purple colors by modulating the ratios of IEICO-4F:T2- ORH or IEICO-4F:T2-OEHRH with PTB7-Th. It is because PTB7-Th and IEICO-4F are narrow band gap and two NFAs are ultra-wide ban gap materials, respectively. Furthermore, the color difference was optically characterized through transmission measurements, originated from transmission of different bands of light in the visible spectrum. The ranges of colors were quantified using the CIE chromaticity system and the CIELAB color space coordinates. The color transition is clearly correlated with the component ratio of IEICO-4F:T2-ORH or :T2-OEHRH. The CIELAB results further revealed more negative b* values in T2-ORH than T2-OEHRH binary systems, i.e., more reddish hues can be demonstrated using T2-OEHRH. It is additionally observed that the color calculation through the RGB model is good agreement with the CIE and the CIELAB results.
It is obvious that such multi-component system shows versatile properties as well as provides opportunity to achieve high performance of OPVs. However, exploring numerous possible material combinations and manufacturing toward labtofab translation are challenging and time-consuming.
The situation demands a novel research method which can rapidly explore the enormous parameter space via industry-relevant methods.
In this perspective, the last chapter introduced a new digital research methodology, the R2R process as a high-throughput in-situ formulation screening tool to combine with ML technology. PM6:Y6:IT-
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4F, one of high-performance NFA-based ternary combination, was selected to utilize the methodology.
UV-vis measurement with assistance of AFM analysis was conducted as an evidence of in-situ formulation fabrication and confirmed qualitative changes were observed depending on the material composition. The consistent 2218 OPV devices using the high-throughput fabrication system were then fabricated to produce training data for ML technology. The deposition parameters, absolute amounts of each component and total solid per unit area (DD and TDD), were introduced and cover thicknesses of device and ratio between components. The compositions and the deposition parameters were thoroughly studied and the performance trends depending on the parameters were clearly observed. The PCE data of the 2218 devices were used as training data with the DDs, as a reusable feature of OPVs. Among a variety of ML algorithms to build model, RF regression algorithm was chosen because it exhibited the remarkable model performance metrics in the hold-out validation process (R2 = 0.996 for training and R2 = 0.967 for testing set). The RF regression-based model was used to predict two formulations, BPF (1:1.215:0.165, w/w) and BEF (1:1.08:0.27, w/w). The experimental validations were also conducted and clearly indicated BPF which is necessary in the industrial printing process exhibited higher tolerance to the thickness variation compared to BEF. Furthermore, BEF showed up to 10.2% PCE at the predicted thickness range whereas BPF showed the inferior photovoltaic performance. It is noted that the efficiency of BEF is the highest PCE among the reported R2R processed OPVs so far and it is achieved without using problematic solvent additives, as a result, the intact stability can be expected.
To the best of our knowledge, this work is the first ML-assisted OPV study based on the consistent experimental datasets and demonstrates the true potential of ML-assisted research for OPVs. We believe such a digital transformation of OPV research would lead to the breakthrough toward commercialization.
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