Film morphology evolution during solvent vapor annealing of highly efficient small molecule donor/acceptor blends

Improving the Molecular Packing Order and Vertical Phase Separation of the P3HT:O-IDTBR Blend by Extending the Crystallization Period of O-IDTBR

The morphology with strong molecular packing order and gradient vertical composition distribution associated with efficient charge transport and collection is critical to achieve high performance in nonfullerene solar cells. However, the rapid solidification process of the active layer upon the fast removal of solvent usually results in a kinetically trapped state with undesired morphology. Herein, we proposed a strategy to extend the crystal growth time of the acceptor via a high-boiling-point additive that selectively dissolved the acceptor. This was enabled by adding dibenzyl ether (DBE) to the poly(3-hexylthiophene) (P3HT):O-IDTBR blend in chlorobenzene (CB) solution. The combination of the kinetic study by time-resolved ultraviolet-visible (UV-vis) absorption spectra and detailed morphological characterization allows us to correlate the crystallization kinetics with the microstructural transition. The results show that the crystal growth time of O-IDTBR increases from 3 to 60 s upon the addition of 0.75% DBE, leading to further evolution of the molecular order of O-IDTBR during the DBE-dominated drying period. Meanwhile, O-IDTBR has more time to migrate toward the substrate owing to the larger surface energy. In addition, the onset of the crystallization process of P3HT is brought forward from 8 to 6 s due to the reduced solvent quality, which favors P3HT to crystallize into a fibril network. As a result, an optimized morphology that features the enhanced molecular packing order of P3HT and O-IDTBR as well as the vertical compositional gradient of O-IDTBR is obtained. Devices based on the optimized blend show more balanced charge transport and suppressed bimolecular recombination, giving rise to an improved power conversion efficiency (PCE) from 4.29 ± 0.04 to 7.30 ± 0.12%.

Operando Characterization of Organic Mixed Ionic/Electronic Conducting Materials

Operando characterization plays an important role in revealing the structure-property relationships of organic mixed ionic/electronic conductors (OMIECs), enabling the direct observation of dynamic changes during device operation and thus guiding the development of new materials. This review focuses on the application of different operando characterization techniques in the study of OMIECs, highlighting the time-dependent and bias-dependent structure, composition, and morphology information extracted from these techniques. We first illustrate the needs, requirements, and challenges of operando characterization then provide an overview of relevant experimental techniques, including spectroscopy, scattering, microbalance, microprobe, and electron microscopy. We also compare different in silico methods and discuss the interplay of these computational methods with experimental techniques. Finally, we provide an outlook on the future development of operando for OMIEC-based devices and look toward multimodal operando techniques for more comprehensive and accurate description of OMIECs.

Efficient all-small-molecule organic solar cells based on a fluorinated small-molecule donor

A fluorinated donor with a deep HOMO energy level enables efficient all-small-molecule organic solar cells.

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

All-small-molecule organic photovoltaic (OPV) cells based upon the small-molecule donor, DRCN5T, and nonfullerene 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. This 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, (iii) the temperature, and (iv) duration of the annealing of these films. The ML-based approach was then used to derive maps of the power conversion efficiencies (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 PCE. 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.

Effects of Solvent Vapor Annealing on Morphology and Charge Transport of Poly(3-hexylthiophene) (P3HT) Films Incorporated with Preformed P3HT Nanowires

We systematically studied the influence of solvent vapor annealing on the molecular ordering, morphologies, and charge transport properties of poly(3-hexylthiophene) (P3HT) thin films embedded with preformed crystalline P3HT nanowires (NWs). Solvent vapor annealing (SVA) with chloroform (CF) was found to profoundly impact on the structural and morphological changes, and thus on the charge transport characteristics, of the P3HT-NW-embedded P3HT films. With increased annealing time, the density of crystalline P3HT NWs was increased within the resultant films, and also intra- and intermolecular interactions of the corresponding films were significantly improved. As a result, the P3HT-NW-embedded P3HT films annealed with CF vapor for 20 min resulted in a maximized charge carrier mobility of ~0.102 cm² V⁻¹ s⁻¹, which is higher than that of pristine P3HT films by 4.4-fold (μ = ~0.023 cm² V⁻¹ s⁻¹).

Template-Assisted Formation of High-Quality α-Phase HC(NH2)2PbI3 Perovskite Solar Cells

Formamidinium (FA) lead halide (α-FAPbI3) perovskites are promising materials for photovoltaic applications because of their excellent light harvesting capability (absorption edge 840 nm) and long carrier diffusion length. However, it is extremely difficult to prepare a pure α-FAPbI3 phase because of its easy transformation into a nondesirable δ-FAPbI3 phase. In the present study, a "perovskite" template (MAPbI3-FAI-PbI2-DMSO) structure is used to avoid and suppress the formation of δ-FAPbI3 phases. The perovskite structure is formed via postdeposition involving the treatment of colloidal MAI-PbI2-DMSO film with FAI before annealing. In situ X-ray diffraction in vacuum shows no detectable δ-FAPbI3 phase during the whole synthesis process when the sample is annealed from 100 to 180 °C. This method is found to reduce defects at grain boundaries and enhance the film quality as determined by means of photoluminescence mapping and Kelvin probe force microscopy. The perovskite solar cells (PSCs) fabricated by this method demonstrate a much-enhanced short-circuit current density (  J sc) of 24.99 mA cm-2 and a power conversion efficiency (PCE) of 21.24%, which is the highest efficiency reported for pure FAPbI3, with great stability under 800 h of thermal ageing and 500 h of light soaking in nitrogen.

How To Optimize Materials and Devices via Design of Experiments and Machine Learning: Demonstration Using Organic Photovoltaics

Most discoveries in materials science have been made empirically, typically through one-variable-at-a-time (Edisonian) experimentation. The characteristics of materials-based systems are, however, neither simple nor uncorrelated. In a device such as an organic photovoltaic, for example, the level of complexity is high due to the sheer number of components and processing conditions, and thus, changing one variable can have multiple unforeseen effects due to their interconnectivity. Design of Experiments (DoE) is ideally suited for such multivariable analyses: by planning one's experiments as per the principles of DoE, one can test and optimize several variables simultaneously, thus accelerating the process of discovery and optimization while saving time and precious laboratory resources. When combined with machine learning, the consideration of one's data in this manner provides a different perspective for optimization and discovery, akin to climbing out of a narrow valley of serial (one-variable-at-a-time) experimentation, to a mountain ridge with a 360° view in all directions.

Three-Dimensional Observation of a Light-Soaked Photoreactant Layer in BTR:PCBM Solar Cells Treated with/without Solvent Vapor Annealing

A key challenge to the commercialization of solution-processed solar cells is a proper understanding of the morphological variations during long periods, particularly under light-soaking conditions. Many research groups have competitively reported solvent vapor annealing (SVA)-treated small-molecule devices with efficiency rates exceeding 11%; however, their light-soaking effects have been rarely studied. Here, we investigate the morphological changes in the light-soaked devices with/without SVA treatments depending on the illumination time via three-dimensional observations. From the results, we found that the trends of morphological variations differ in the surface and bulk parts of the active film and that the difference is closely related to the device performance capabilities. Therefore, our research will enhance the underlying knowledge of the light-soaking effect on active morphologies over long term.