A method for controlling film formation of an organic optoelectronic device

Abstract

The application discloses a film forming process regulation method of an organic optoelectronic device, which comprises the following steps: S1, preparing a precursor solution containing at least one donor material and at least one acceptor material; S2, depositing the precursor solution on a substrate surface to form a film, and collecting process signals in real time through an in-situ characterization device during the film forming process; S3, pre-processing the process signals, and extracting characteristic information corresponding to the donor and acceptor components; S4, constructing a process descriptor according to the obtained characteristic information; S5, establishing a corresponding relationship among the process descriptor, film forming quality, film structure characteristics and / or device performance; S6, screening or optimizing the processing conditions according to the corresponding relationship; and S7, preparing the organic optoelectronic device under the screened or optimized processing conditions. The application collects in-situ characterization signals in real time, constructs a process descriptor, and guides the screening, regulation and optimization of film forming process conditions, and belongs to the technical field of organic optoelectronic device preparation.

Description

Technical Field

[0001] This invention relates to the field of organic optoelectronic device fabrication technology, and more specifically to a method for controlling the film formation process of organic optoelectronic devices. Background Technology

[0002] Organic optoelectronic devices, especially organic solar cells, organic light-emitting diodes, and organic photodetectors, have attracted widespread attention in recent years due to their advantages such as light weight, flexibility, large-area fabrication, and suitability for solution processing. For these devices, the microstructure, phase region size, component distribution, crystallinity, orientation, and interface state of the active or functional layer film typically have a decisive influence on charge generation, transport, recombination, radiative transitions, and device stability. Therefore, effectively controlling the film formation process during fabrication is crucial for improving device performance and fabrication reproducibility. In existing technologies, the optimization of organic optoelectronic device processes usually relies on the following approaches: First, conducting numerous parallel experiments by changing process parameters such as solvents, additives, solution concentrations, material ratios, spin-coating speeds, and annealing conditions, followed by screening for optimal conditions through device performance testing; second, analyzing the final film morphology and structure using post-film characterization techniques such as atomic force microscopy, transmission electron microscopy, grazing incidence wide-angle X-ray scattering, grazing incidence small-angle X-ray scattering, ultraviolet-visible absorption spectroscopy, and fluorescence spectroscopy, and then deducing the film formation process from this analysis. Although the above methods are widely used in research, they generally have the following problems.

[0003] First, existing process optimization methods are highly dependent on experience. For multi-component organic semiconductor systems, especially donor / acceptor blends, the film formation process is influenced by multiple factors, including solvent evaporation, component interactions, aggregation-induced behavior, substrate wettability, and external field conditions. Due to the significant differences between different material systems, it is difficult to quickly determine the optimal combination of process parameters based solely on experience. This often requires extensive trial-and-error experiments, resulting in long development cycles, high sample consumption, and low efficiency.

[0004] Second, existing post-characterization methods cannot accurately reflect the dynamic process of film formation. While the final morphology after film formation can provide some information, it is essentially the final result of the entire film formation process and cannot reveal the structural evolution laws of the early, middle, and late stages of film formation. For example, during spin coating or spray coating, the donor and acceptor may undergo multiple stages such as dissolved state, pre-aggregated state, phase separation development state, and dry film stabilization state, and the final state characterization cannot distinguish which stage's key transformation leads to a certain performance improvement.

[0005] Third, although some studies have attempted to use in-situ absorption spectroscopy, in-situ emission spectroscopy, or other online monitoring signals to study the film formation process, most of these works remain at the level of phenomenon description or qualitative analysis. Existing in-situ characterization data usually appear as continuously changing spectral curves, which contain a large amount of information and have strong time resolution. However, without a unified method for quantitative extraction and summarization, they are difficult to use directly for horizontal comparisons between different process conditions, let alone further transform into a basis for process optimization.

[0006] Fourth, in multi-component organic semiconductor systems, the contributions of different components to the spectral response are usually superimposed, and complex phenomena such as peak position shift, peak intensity change, bandwidth change, and shoulder formation occur over time. Current technologies lack a universal and operable parameterization method to extract these in-situ variation characteristics into a "process descriptor" that reflects relative aggregation, phase separation, crystallization evolution, or component enrichment trends. Without this parameterization transformation, in-situ signals cannot truly serve process design.

[0007] Fifth, current process development usually uses the final device performance as the sole selection criterion. However, device performance itself is affected by a variety of factors such as electrodes, interface layers, device area, and testing errors. Without intermediate characterization parameters at the process level as a bridge, it is difficult to establish a clear chain between "process conditions - film formation process - thin film structure - device performance", which is not conducive to forming a transferable and scalable process optimization strategy.

[0008] Therefore, there is an urgent need to provide a new method for optimizing the film deposition process of organic optoelectronic devices, which can acquire process signals in real time during the film deposition process and transform the key dynamic information in the in-situ signals into quantifiable, comparable, and decision-making process descriptors. This would enable rapid screening and optimization of solvent systems, additive systems, and film deposition parameters, improve process development efficiency, and enhance the applicability of the method to different material systems and different solution processing methods. Summary of the Invention

[0009] To address the technical problems existing in the prior art, the purpose of this invention is to provide a method for controlling the film formation process of organic optoelectronic devices. This method involves real-time acquisition of in-situ characterization signals during the film formation process of organic optoelectronic functional layers, extraction of dynamic feature information corresponding to different components, and construction of a process descriptor reflecting the evolutionary behavior of the multi-component system architecture. Furthermore, it establishes a correspondence between the process descriptor and film formation quality, thin film structural characteristics, or device performance, thereby guiding the selection, control, and optimization of film formation process conditions. The aim is to provide a process development approach that transforms in-situ characterization from an "observation tool" into a "decision-making tool," enabling process optimization to move beyond relying solely on final-state characterization and trial-and-error, and instead to make quantitative judgments based on the dynamic laws of the film formation process itself.

[0010] To achieve the above objectives, the present invention adopts the following technical solution: a method for controlling the film formation process of organic optoelectronic devices, comprising the following steps,

[0011] S1, prepare a precursor solution containing at least one donor material and at least one acceptor material;

[0012] S2, the precursor solution is deposited on the substrate surface to form a film, and process signals are collected in real time by an in-situ characterization device during the film formation process;

[0013] S3, preprocess the process signal and extract the feature information corresponding to the donor and acceptor components;

[0014] S4, Construct a process descriptor based on the obtained feature information;

[0015] S5, Establish the correspondence between process descriptors and film quality, thin film structural characteristics and / or device performance;

[0016] S6, Based on the corresponding relationship, the processing conditions are screened or optimized;

[0017] S7, organic optoelectronic devices are prepared under screened or optimized processing conditions.

[0018] In step S1, donor and acceptor materials for forming the organic optoelectronic functional layer are selected and dissolved separately or together in one or more solvents to form a precursor mixed solution. Depending on the specific material system, one or more additives may be added to the precursor mixed solution to adjust the solution aggregation state, evaporation rate, compatibility, or structural evolution behavior during film formation.

[0019] The donor material can be a polymer donor, a small molecule donor, or a combination of both. The acceptor material can be a fullerene acceptor, a non-fullerene acceptor, a small molecule acceptor, a polymer acceptor, or a combination thereof.

[0020] The total concentration of the precursor solution can be 5–50 mg / mL, preferably 10–30 mg / mL; the mass ratio of donor to acceptor can be 3:1–1:3; and the additive content can be 0.1%–10% of the main solvent volume. It should be noted that the above ranges are preferred process windows for the implementation of this invention, and the specific values ​​can be adjusted according to the solubility, viscosity, film thickness requirements, and processing methods of the material system.

[0021] Preferably, the process signal is an in-situ optical signal, including absorption spectrum, transmission spectrum, reflection spectrum, emission spectrum, fluorescence spectrum, or a combination of the above signals. The substrate can be a glass substrate, a quartz substrate, ITO conductive glass, a flexible polymer substrate, or other suitable substrates.

[0022] As a preferred method, the process signal acquisition method employs vertical incidence acquisition, transmission acquisition, reflection acquisition, oblique incidence acquisition, or online acquisition in conjunction with solution processing equipment. Existing equipment is used for the in-situ characterization device. The acquisition optical path can be a vertical optical path, transmission optical path, reflection optical path, or oblique incidence optical path. The in-situ acquisition frequency can be set to 1–100 Hz, preferably 2–20 Hz, depending on the duration of the film formation process, to ensure both the rapid drying process is reflected and the signal-to-noise ratio is considered.

[0023] As a preferred option, in step S2, the film formation method adopts one or more of the following: spin coating, spray coating, blade coating, slot coating, screen printing, gravure printing, and inkjet printing. In-situ spectral acquisition can be performed from before and after droplet ...

[0024] As a preferred embodiment, step S3 involves preprocessing the process signal using at least one of the following methods: dark signal subtraction, blank substrate reference correction, baseline correction, smoothing and denoising, normalization, time axis alignment, feature band truncation, peak separation fitting, and drift correction. This eliminates instrument noise, baseline drift, and systematic errors between different test batches. After preprocessing, a time-resolved signal matrix is ​​obtained that can be used for further feature extraction.

[0025] As a preferred option, process descriptors are used to characterize the relative aggregation behavior, phase separation behavior, crystallization evolution behavior, drying rate change behavior, component enrichment behavior, or interface formation behavior of the material system during film formation.

[0026] As a preferred embodiment, in step S4, the process descriptor includes one or more of the following: the ratio of donor characteristic peak intensity to receptor characteristic peak intensity, the ratio of donor and receptor characteristic peak areas, characteristic peak position offset, characteristic peak half-width variation, first derivative or derivative feature of the characteristic signal, time parameter corresponding to the characteristic signal reaching a threshold, duration of the characteristic signal plateau region, and integral value of the characteristic signal within a predetermined time window. Feature information related to the donor component, receptor component, or their interaction, as described above, is extracted from the preprocessed in-situ signal. The signal intensity at the donor characteristic wavelength and the signal intensity at the receptor characteristic wavelength are selected, and a bivariate feature sequence evolving over time is constructed based on time.

[0027] One or more process descriptors are constructed based on the extracted feature information. The process descriptor can be a single-parameter descriptor or a multi-parameter combination descriptor.

[0028] Single-parameter descriptors include, for example: (1) the instantaneous ratio of donor characteristic signal intensity to receptor characteristic signal intensity, where the donor characteristic signal intensity is denoted as I. D (t), the intensity of the receptor characteristic signal is denoted as I. A (t), where t is the time during the film formation process; (2) donor characteristic signal intensity I D (t) or receptor characteristic signal intensity I A (t) Values ​​at predetermined time points t1, t2, and t3, where t1, t2, and t3 represent different sampling times during the film formation process; (3) The ratio of donor characteristic signal intensity to receptor characteristic signal intensity I D (t) / I A (t) The time corresponding to the maximum or minimum value; (4) The peak position shift of the donor characteristic peak or the acceptor characteristic peak during the film formation process, wherein the peak position shift represents the change in the position of the characteristic peak relative to the initial time or reference state; (5) The time corresponding to the donor characteristic signal or the acceptor characteristic signal reaching the stable plateau, wherein the stable plateau represents the relatively stable stage after the signal change amplitude is lower than the preset threshold; (6) The integral value of the donor characteristic signal, the acceptor characteristic signal, or the ratio of the two within a predetermined time interval, used to characterize the signal cumulative change characteristics during the film formation process.

[0029] Multi-parameter combination descriptors include: combinations of donor / receptor feature intensity ratio and peak offset; ternary descriptors composed of initial rate of change, extreme position, and plateau value; and comprehensive descriptors formed by weighted summation of descriptors from different stages.

[0030] The process descriptor is used to characterize the relative aggregation sequence, relative aggregation intensity, phase separation degree, crystallization development rate, drying transition time, component enrichment process, and film shaping behavior of donors and acceptors during film formation.

[0031] As a preferred option, in step S5, the correspondence is established through empirical rules, threshold determination, correlation analysis, regression model, classification model, cluster analysis model or Bayesian optimization model.

[0032] The obtained process descriptors are correlated with film deposition quality, final-state thin film structural characteristics, and / or device performance. Film deposition quality includes film thickness uniformity, continuity, pinhole defects, and surface roughness. The final-state thin film structural characteristics include crystallization peak intensity, orientation, grain size, phase region size, and compositional distribution uniformity. Device performance includes open-circuit voltage, short-circuit current density, fill factor, photoelectric conversion efficiency, external quantum efficiency, and stability indicators of organic solar cells; turn-on voltage, luminance, current efficiency, power efficiency, external quantum efficiency, and lifetime of organic light-emitting diodes; and responsivity, specific detectivity, dark current, and response time of photodetectors.

[0033] Correspondence can be established through empirical rules, such as limiting a process descriptor to a target interval; or it can be established through statistical or machine learning methods, such as correlation analysis, principal component analysis, partial least squares regression, random forest, support vector machine, Gaussian process regression, Bayesian optimization, or neural network models.

[0034] As a preferred approach, process descriptors are used as input variables and device performance indicators are used as output variables to establish a predictive model, thereby quickly screening high-potential process conditions.

[0035] As a preferred option, in step S6, the optimization method is to select process conditions within a preset process window that cause the target process descriptor to fall into the target range.

[0036] As a preferred option, the target range is determined based on at least one of the following: device efficiency, open-circuit voltage, short-circuit current density, fill factor, external quantum efficiency, luminous efficiency, responsivity, detectivity, thin film roughness, crystal orientation, or stability.

[0037] As a preferred option, the processing conditions include at least one of the following: solvent type, mixed solvent ratio, additive type, additive content, donor-acceptor ratio, solution concentration, solution temperature, substrate temperature, spin coating speed, spin coating acceleration, spray flow rate, nozzle moving speed, nozzle-substrate distance, scraping speed, annealing temperature, annealing time, and ambient atmosphere.

[0038] As a preferred option, organic optoelectronic devices are organic solar cells, organic light-emitting diodes, or organic photodetectors. Organic optoelectronic devices can also be other optoelectronic devices based on organic semiconductor thin films.

[0039] As a preferred method, the film formation process signal is prepared and acquired, preprocessed and a process descriptor is constructed. When the process descriptor (e.g., ID(0) / IA(0)) deviates from the preset target range at the initial time, at least one processing condition is fed back and controlled. The processing conditions fed back and controlled include, but are not limited to, substrate temperature, annealing temperature, annealing time and ambient atmosphere.

[0040] In summary, the present invention has the following advantages:

[0041] (1) The present invention converts in-situ process signals into quantifiable process descriptors, so that the in-situ characterization results can directly serve process optimization, rather than just being used for qualitative observation.

[0042] (2) The present invention can reveal the dynamic evolution behavior of different components during the film formation process and establish an intermediate bridge between process conditions and film formation process.

[0043] (3) The present invention can significantly reduce the trial and error cost in process screening, reduce the number of invalid device preparations, and improve development efficiency.

[0044] (4) This invention can be used for offline process screening, or it can be extended to an online feedback control method.

[0045] (5) The present invention has good universality and can be applied to different material systems, different in-situ characterization methods and different solution processing techniques.

[0046] (6) This invention is beneficial to improving the consistency of device performance and the repeatability of fabrication, and provides quantitative basis for scale-up fabrication at the process level. Attached Figure Description

[0047] Figure 1 This is a comparison of the evolution of in-situ absorption spectra over time under toluene conditions and under conditions with the addition of α-pinene additive in the embodiments of the present invention;

[0048] Figure 2 This is a comparison of the characteristic signal intensity of donor material D18 and acceptor material L8BO over time under toluene conditions and under conditions with the addition of α-pinene additive in the embodiments of the present invention.

[0049] Figure 3 This is a comparison chart of the current density-voltage characteristics of organic solar cells prepared under toluene conditions and under conditions with the addition of α-pinene additive in the embodiments of the present invention. Detailed Implementation

[0050] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0051] Example 1

[0052] A method for controlling the film formation process of an organic optoelectronic device includes the following steps:

[0053] S1, prepare a precursor solution containing at least one donor material and at least one acceptor material;

[0054] S2, the precursor solution is deposited on the substrate surface to form a film, and process signals are collected in real time by an in-situ characterization device during the film formation process;

[0055] S3, preprocess the process signal and extract the feature information corresponding to the donor and acceptor components;

[0056] S4, Construct a process descriptor based on the obtained feature information;

[0057] S5, Establish the correspondence between process descriptors and film quality, thin film structural characteristics and / or device performance;

[0058] S6, Based on the corresponding relationship, the processing conditions are screened or optimized;

[0059] S7, organic optoelectronic devices are prepared under screened or optimized processing conditions.

[0060] The specific implementation process is as follows.

[0061] Polymer donor D18 and non-fullerene acceptor L8BO were selected as the active layer blend system. The donor and acceptor materials were dissolved in toluene, the main solvent, at a mass ratio of 1:1.2 to prepare a precursor mixture solution with a total concentration of 10 mg / mL. The solution was magnetically stirred at room temperature to 80 °C until completely dissolved.

[0062] To investigate the effect of the solvent system on the film formation process, toluene and toluene + 0.5% vol α-pinene were used as solvent systems for comparison. The donor-acceptor ratio and total solids content were kept constant in all solvent systems, and other conditions remained unchanged.

[0063] A pre-cleaned quartz substrate was selected as the substrate. The substrate was then ultrasonically cleaned sequentially with detergent, deionized water, and isopropanol for 10–20 min each, dried, and then subjected to UV-ozone plasma treatment for 5 min.

[0064] The precursor solution was dropped onto the substrate surface and a film was formed by spin coating at a speed of 3000 rpm for 20–30 s. An in-situ absorption spectroscopy acquisition system was simultaneously activated during the spin coating process, recording the spectrum from the moment of droplet application until 20–50 s after the spin coating was completed.

[0065] The in-situ absorption spectroscopy system includes a light source, optical fiber, collimation assembly, sample stage, and spectrometer. The optical path employs transmission, with a wavelength range of 200–990 nm and an acquisition time interval of 0.06 s. To ensure comparability between different experiments, all groups of experiments used the same integration time, sampling frequency, and optical path position. Dark signal subtraction and baseline correction were performed on the acquired in-situ absorption spectra, and the time series was normalized.

[0066] In this embodiment, the ratio of the donor characteristic signal intensity to the receptor characteristic signal intensity at the initial moment is used as the process descriptor, namely: process descriptor ID(0) / IA(0), where ID(0) represents the signal intensity at the donor characteristic wavelength at the initial moment of film formation, and IA(0) represents the signal intensity at the receptor characteristic wavelength at the initial moment of film formation. The process descriptor is used to characterize the relative spectral response relationship between the donor and receptor in the initial stage of film formation and serves as the basis for screening different processing conditions.

[0067] The total concentration of the solution was fixed at 10 mg / mL. -1The substrate and solution were both at room temperature (25 °C), and the spin coating speed was 2500 r / min. The in-situ absorption changes under toluene and α-pinene additive conditions were compared. The results showed that the initial ID(0) / IA(0) ratio was 0.92 under toluene conditions, which increased to 0.96 after adding α-pinene additive. This indicates that the relative signal-to-donor relationship between the donor and acceptor changed in the initial stage of film formation under additive conditions, and can be used as an effective criterion for process screening.

[0068] Combination Figure 1 and Figure 2 It can be seen that under toluene conditions, the main absorption bands gradually strengthen and stabilize over time during film formation. However, after adding α-pinene additives, the absorption changes in the corresponding wavelength regions are more pronounced, and the evolution of the position and intensity of the characteristic absorption bands differs from that under toluene conditions, indicating that the additives affect the component evolution process in the initial stage of film formation. Especially near the characteristic absorption bands of the donor and acceptor, the spectral change trends are different under the two conditions, indicating that α-pinene additives can regulate the structure formation behavior in the early stage of film formation. Therefore, by comparing the initial descriptors ID(0) / IA(0) under different conditions, solvent systems or additive conditions can be quickly screened, providing a basis for process optimization in subsequent device fabrication.

[0069] Organic optoelectronic devices were fabricated under the aforementioned preferred ink processing conditions. The device structure was: ITO / PEDOT:PSS / active layer / PFN-Br / Ag. Thermal annealing was performed at 100 °C for 5 min. Subsequently, a PFN-Br electron transport layer of approximately 5 nm thickness was spin-coated onto the active layer film at a spin speed of 2000 r / min; the PFN-Br solution concentration was 0.5 mg mL⁻¹, and the solvent was methanol. Finally, the device was annealed under a vacuum of 1 × 10⁻¹. 7 In a thermal evaporation chamber with a thermal density of mbar, a 100 nm thick silver electrode was deposited on top of the PFN-Br layer. The effective area of ​​the ITO substrate was 0.0516 cm², further limited to 0.04 cm² by a non-reflective mask. The resulting device was subjected to performance testing, including open-circuit voltage (V). OC ), short-circuit current density (J SC ), fill factor (FF) and photoelectric conversion efficiency (PCE).

[0070] like Figure 3 As shown, the results indicate that the device V prepared using toluene conditions... OC It is 0.88 V, J SC 26.70 mA / cm 2 The FF was 74.45% and the PCE was 17.72%; after adding α-pinene additive, the device VOC Still 0.88 V, J SC Increased to 26.98 mA / cm 2 FF increased to 77.56%, and PCE increased to 18.62%.

[0071] Meanwhile, the process descriptor ID(0) / IA(0) at the initial film formation time increased from 0.92 to 0.96. These results indicate that the addition of α-pinene additives improves device performance, with the most significant improvement in the fill factor. This demonstrates the feasibility of using the process descriptor ID(0) / IA(0) to screen processing conditions, and that the descriptor can provide a valid basis for optimizing the film formation process of organic optoelectronic devices.

[0072] The above embodiments are preferred embodiments of the invention, but the embodiments of the present invention are not limited to the above embodiments. Any changes, modifications, substitutions, combinations, or simplifications made without departing from the spirit and principle of the present invention shall be considered equivalent substitutions and shall be included within the protection scope of the present invention.

Claims

1. A method for controlling the film formation process of an organic optoelectronic device, characterized in that: Includes the following steps, S1, prepare a precursor solution containing at least one donor material and at least one acceptor material; S2, the precursor solution is deposited on the substrate surface to form a film, and process signals are collected in real time by an in-situ characterization device during the film formation process; S3, preprocess the process signal and extract the feature information corresponding to the donor and acceptor components; S4, Construct a process descriptor based on the obtained feature information; S5, Establish the correspondence between process descriptors and film quality, thin film structural characteristics and / or device performance; S6, Based on the corresponding relationship, the processing conditions are screened or optimized; S7, organic optoelectronic devices are prepared under screened or optimized processing conditions.

2. The method for controlling the film formation process of an organic optoelectronic device according to claim 1, characterized in that: The process signal is an absorption spectrum, transmission spectrum, reflection spectrum, emission spectrum, fluorescence spectrum, or a combination of the above signals.

3. The method for controlling the film formation process of an organic optoelectronic device according to claim 1, characterized in that: The process signals are acquired using methods such as vertical incidence acquisition, transmission acquisition, reflection acquisition, oblique incidence acquisition, or online acquisition methods combined with solution processing equipment.

4. The method for controlling the film formation process of an organic optoelectronic device according to claim 1, characterized in that: In step S2, the film-forming method adopts one or more of the following: spin coating, spray coating, scraping coating, slot coating, screen printing, gravure printing, and inkjet printing.

5. The method for controlling the film formation process of an organic optoelectronic device according to claim 1, characterized in that: In step S3, the preprocessing methods for the process signal include at least one of the following: dark signal subtraction, blank substrate reference correction, baseline correction, smoothing and denoising, normalization, time axis alignment, feature band truncation, peak separation fitting, and drift correction.

6. The method for controlling the film formation process of an organic optoelectronic device according to claim 1, characterized in that: In step S4, the process descriptor includes one or more of the following: the ratio of donor characteristic peak intensity to acceptor characteristic peak intensity, the ratio of donor and acceptor characteristic peak area, characteristic peak position offset, characteristic peak half-width variation, first derivative or derivative feature of the characteristic signal, time parameter corresponding to when the characteristic signal reaches a threshold, characteristic signal plateau duration, and integral value of the characteristic signal within a predetermined time window.

7. The method for controlling the film formation process of an organic optoelectronic device according to claim 1, characterized in that: In step S5, the correspondence is established through empirical rules, threshold determination, correlation analysis, regression model, classification model, cluster analysis model or Bayesian optimization model.

8. The method for controlling the film formation process of an organic optoelectronic device according to claim 1, characterized in that: In step S6, the optimization method is to select the process conditions within the preset process window that make the target process descriptor fall into the target range.

9. The method for controlling the film formation process of an organic optoelectronic device according to claim 1, characterized in that: Processing conditions include at least one of the following: solvent type, mixed solvent ratio, additive type, additive content, donor-acceptor ratio, solution concentration, solution temperature, substrate temperature, spin coating speed, spin coating acceleration, spray flow rate, nozzle moving speed, nozzle-substrate distance, scraping speed, annealing temperature, annealing time, and ambient atmosphere.

10. The method for controlling the film formation process of an organic optoelectronic device according to claim 1, characterized in that: Organic optoelectronic devices include organic solar cells, organic light-emitting diodes, or organic photodetectors.

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