Trends in the electronic and geometric structure of non-fullerene based acceptors for organic solar cells

Kuzmich, Alina; Padula, Daniele; Ma, Haibo; Troisi, Alessandro

doi:10.1039/c6ee03654f

Cited by 103 publications

(91 citation statements)

References 77 publications

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“…Many challenges prevent the prediction of the PCE in OPV materials from its constituents. [46][47][48] Since both donor and acceptor conjugated molecules have high probabilities of exhibiting energetically close HOMO and HOMO−1 (LUMO and LUMO+1), [47] it would be necessary to examine the importance of new parameters in predicting PCE for OPVs, such as the near-degeneracy of frontier molecular orbitals also in donor molecules. Here, it is important to note that we need to choose quantum chemical descriptors instead of simple topological descriptors, generally applied to drug designing, as they do not provide good results when applied to database of conjugated molecules for the solar cell application.…”

Section: Introductionmentioning

confidence: 99%

Toward Predicting Efficiency of Organic Solar Cells via Machine Learning and Improved Descriptors

Sahu

Rao

Troisi

et al. 2018

Advanced Energy Materials

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include the strong electron-electron interactions and strong electron-phonon couplings as well as the complicated donor/ acceptor (D/A) interface morphology, which are fundamentally different from inorganic semiconductors. [23,24] Therefore, the accurate simulating of OPVs requires high-level theoretical methods in quantum chemistry, quantum dynamics and statistical mechanics, and in recent years there have been substantial progress for the theoretical understanding of many microscopic processes such as charge transport, [25] exciton dissociation, [26,27] singlet fission, [28][29][30] etc. These methods are useful for few benchmark systems but cannot be used to explore the chemical space, i.e., screen a large number of candidate materials.The predictive power of a theoretical model by high-throughput virtual screening has been explored in the recent years. [31][32][33][34][35][36][37][38][39][40] For example, in the Harvard Clean Energy Project (CEP), [41] Aspuru-Guzik and co-workers have screened ≈2.3 million compounds by employing the Scharber model [42,43] to find out efficient new donor molecules for OPVs. Here, the computed energies of the highest occupied molecular orbital (HOMO)/the lowest unoccupied molecular orbital (LUMO) of organic molecules are calibrated to experimentally determined values, and then employing an averaging scheme, energies of HOMO/LUMO are estimated to use them as input in the Scharber model. However, the prediction of PCE of an OPV is much more challenging compared to the energies of orbitals. Very recently, the same research team [44] noticed that the Scharber model, widely used in these virtual screening works, is not accurate enough for the prediction of PCE, and calibration of PCE by considering molecular similarity, molecular weight and band gap energy leads to improvement in correlation between experimental (49 OPVs) and calculated PCE (Pearson's coefficient (r) is increased from 0.30 to 0.43). Further, the Scharber model is only optimized for the PC 61 BM acceptor [42] and a more general model is desired to take account of nonfullerene molecules.In an OPV, energy conversion is accomplished by four consecutive steps: i) absorption of photons and exciton formation, ii) exciton diffusion to D/A interface, iii) exciton dissociation, and iv) transport of holes/electrons to the respective electrode. Taking account of all these processes, the efficiency of a device depends on many microscopic properties of the organic material such as optical gap, charge-carrier mobility, ionization To design efficient materials for organic photovoltaics (OPVs), it is essential to identify the largest number of parameters that control their properties and build a model using these parameters (known as descriptors) for the prediction of the power conversion efficiency (PCE). By constructing a dataset for 280 small molecule OPV systems, it is found that for all high-performing devices, frontier molecular orbitals of donor molecules are nearly degenerated and in such cases, orbitals other than just high...

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Section: Introductionmentioning

confidence: 99%

Toward Predicting Efficiency of Organic Solar Cells via Machine Learning and Improved Descriptors

Sahu

Rao

Troisi

et al. 2018

Advanced Energy Materials

Self Cite

206

220

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“…Therefore, excitons will not spontaneously split to free carrier and extra forces like band offset and energetic difference at the interface of the two organic material are required for splitting the exciton into the free carriers. The exciton-splitting mechanism has attracted notable interest and extensive studies have been dedicated to this field specifically [52,53]. Obviously, highly sophisticated and advanced models can capture the separation mechanism more accurately, however, coupling such models to the transport model adds more complexity to the system.…”

Section: Role Of Exciton Statementioning

confidence: 99%

“…The schematic diagram of developed model is shown in Figure 7. to this field specifically [52,53]. Obviously, highly sophisticated and advanced models can capture the separation mechanism more accurately, however, coupling such models to the transport model adds more complexity to the system.…”

Section: Role Of Exciton Statementioning

confidence: 99%

Sensitivity of the Drift-Diffusion Approach in Estimating the Power Conversion Efficiency of Bulk Heterojunction Polymer Solar Cells

2017

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There are numerous theoretical approaches to estimating the power conversion efficiency (PCE) of organic solar cells (OSCs), ranging from the empirical approach to calculations based on general considerations of thermodynamics. Depending on the level of abstraction and model assumptions, the accuracy of PCE estimation and complexity of the calculation can change dramatically. In particular, PCE estimation with a drift-diffusion approach (widely investigated in the literature), strongly depends on the assumptions made for the physical models and optoelectrical properties of semiconducting materials. This has led to a huge deviation as well as complications in the analysis of simulated results aiming to understand the factors limiting the performance of OSCs. In this work, we intend to highlight the complex relation between mobility, exciton dynamics, nanoscale dimension, and loss mechanisms in one framework. Our systematic analysis represents key information on the sensitivity of the drift-diffusion approach, to estimate how physical parameters and physical processes bind the PCE of the device under the influence of structure, contact, and material layer properties. The obtained results ultimately led to recommendations for putting effort into certain properties to get the most out of avoidable losses, presented the impact and importance of modification of material properties, and in particular, recommended to what degree the design of new material could improve OSC performance.

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“…

the continued research has led to power conversion efficiencies (PCEs) over 11% for single-junction devices. [9][10][11][12][13][14][15][16] Noteworthy improvements have been made over the last few years, and state-of-the-art NFA-OSCs have been reported with PCEs over 16 %, thus outperforming their fullerene-based counterparts. [9][10][11][12][13][14][15][16] Noteworthy improvements have been made over the last few years, and state-of-the-art NFA-OSCs have been reported with PCEs over 16 %, thus outperforming their fullerene-based counterparts.

…”

mentioning

confidence: 99%

Quantifying the Nongeminate Recombination Dynamics in Nonfullerene Bulk Heterojunction Organic Solar Cells

Vollbrecht

Брус

et al. 2019

Advanced Energy Materials

140

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the continued research has led to power conversion efficiencies (PCEs) over 11% for single-junction devices. [7,8] Be that as it may, difficulties in tuning the molecular structure and electronic properties, as well as the comparatively high cost of production of fullerene-based acceptors are drawbacks that have triggered the search for nonfullerene acceptors (NFAs) as an alternative. [9][10][11][12][13][14][15][16] Noteworthy improvements have been made over the last few years, and state-of-the-art NFA-OSCs have been reported with PCEs over 16 %, thus outperforming their fullerene-based counterparts. [17,18] In tandem and ternary systems, PCEs reaching even up to 17.3% have been recently achieved. [19,20] Additionally, the reduction in the bandgap of NFAs opens up the possibility to fabricate semitransparent OSCs that could be applied in building-integrated photovoltaics or power generating greenhouses. [21][22][23][24] To further improve the performance of OSCs, loss-processes such as nongeminate recombination, the recombination of electrons and holes which do not originate from the same exciton, have to be curtailed. This includes bimolecular recombination (also known as Langevin recombination), where charge carriers recombine directly from band to band, as well as trap-assisted recombination (also known as Shockley-Read-Hall recombination), where states deep in the bandgap act as efficient recombination centers. A detailed understanding of these mechanisms responsible for the aforementioned recombination losses is required. [25] Whether or not there are considerable differences in recombination dynamics between NFA-OSCs and fullerene-based OSCs, has yet to be understood since most research in regard to recombination dynamics was performed only with OSCs employing fullerene acceptors. [26][27][28] Furthermore, the majority of studies describe recombination dynamics based on a numerical, drift-diffusion model under the assumption of an effective-medium for the BHJ active layer. [29][30][31][32][33][34][35][36][37][38] The concentration of charge carriers is the key differential parameter in the theory of recombination dynamics. However, only integral parameters (electrical conductivity, impedance, open-circuit voltage, V OC ) can be directly measured by experiments. Therefore, the primary challenge of the theoretical background of any method developed to quantify recombination processes in photovoltaic devices is based on finding the appropriate relationship between the measured In this study, a comprehensive analytical model to quantify the total nongeminate recombination losses, originating from bimolecular as well as bulk and surface trap-assisted recombination mechanisms in nonfullerene-based bulk heterojunction organic solar cells is developed. This proposed model is successfully employed to obtain the different contributions to the recombination current of the investigated solar cells under different illumination intensities. Additionally, the model quantitatively describes the experimentally measured ope...

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Trends in the electronic and geometric structure of non-fullerene based acceptors for organic solar cells

Abstract: High power conversion efficiency are displayed by organic solar cells with small energy gap between LUMO+1 and LUMO orbitals.

Cited by 103 publications

References 77 publications

Toward Predicting Efficiency of Organic Solar Cells via Machine Learning and Improved Descriptors

Toward Predicting Efficiency of Organic Solar Cells via Machine Learning and Improved Descriptors

Sensitivity of the Drift-Diffusion Approach in Estimating the Power Conversion Efficiency of Bulk Heterojunction Polymer Solar Cells

Quantifying the Nongeminate Recombination Dynamics in Nonfullerene Bulk Heterojunction Organic Solar Cells

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