Numerical and Experimental Investigation of Spray Processes for the Production of Perovskite Silicon solar Cells

Perovskite solar cells promise maximum efficiency. However, large-scale industrial production has so far failed due to the complexity of the spraying process. A reproducible, scalable process is intended to remedy this situation for the industry. In the “INTERVENTION” project, we investigated the optimization of spray coating by means of digital simulation of the process and experimental characterization of the materials. A research team developed data-driven solutions for systematic parameter optimization. The aim of the project was to achieve more efficient production on large wafer formats and faster optimization without time-consuming test series – a decisive step towards economically viable high-performance solar cells.

Initial Situation

The perovskite-silicon tandem solar cell is a key technology for increasing the efficiency of photovoltaic modules. We are pursuing the hybrid route for its manufacture, in which the inorganic portion of the absorber is vapor-deposited and the organic portion is then deposited from a solution. Spray coating is suitable for this deposition, but it is highly complex and has a large number of critical control parameters. Sprayed-on layers are often inhomogeneous, which impairs quality and efficiency. Experimental optimization is time-consuming and costly, and therefore often impossible.

A purely empirical approach is not practical. The project therefore used a hybrid approach: simulations combined with experimental investigations enable a deeper understanding of the process and thus contribute to process optimization. Experimental results validate the simulation models that predict process behavior. In this way, the optimal parameters for the spraying process were systematically determined. They are a prerequisite for the efficient and scalable production of a new generation of high-performance solar cells.

Objective

A characterization of the spray mist and coating quality formed the basis for optimizations. Building on this, we developed validated simulation models that reliably map the process and can be used as prediction tools. Using data-driven analysis methods, we identified the optimal process parameters that ensure consistent layer quality. With these parameters, we will achieve reproducible results on large wafer formats, which are a prerequisite for industrial application. In the long term, this research approach enables scalability to industrial manufacturing processes and thus the economic viability of perovskite solar cells.

Approach

The following methods were used in the “Intervention” project to achieve the research objectives:

Characterization Processes

• Spray mist visualization: Laser-assisted visualization enables qualitative characterization of the spray mist.
• Stripe pattern quantification: Fourier transformation quantifies the stripe patterns of the sprayed layers and provides an objective method for evaluating layer quality.
• Color calibration validation method: Fluorescently colored layers are detected via photoluminescence. The previously created calibration curve enables a spatially resolved evaluation of the sprayed quantity.

Experimental Validation and Simulation

• High-resolution photoluminescence images of the experiments validate the simulation model and enable statistical evaluation to identify main effects and interactions of the process parameters.
• A robust simulation model and a comprehensive parameter study enable rapid prediction of optimal parameters—without time-consuming experimental trials.
• Faster and more cost-effective through experiment-simulation integration

Result

As part of the INTERVENTION research project, we were able to systematically optimize the previously almost uncontrollable process of spray coating in order to make the complex spraying process controllable. Specifically, we can report the following research successes:

• Reliable spray mist visualization: The process can now be characterized visually.
• Quantification of stripe patterns: Fourier transformation enables objective layer quality assessment.
• Spatially resolved measurement method: Color calibration with fluorescent dye and imaging photoluminescence enables spatially high-resolution validation of simulations and optimization of spray parameters.
• Validated simulation model: Successfully developed for parameter studies on droplet size, velocity, substrate temperature, and solvent.
• Optimized process parameters: Design of experiments together with a parameter study provides concrete recommendations for critical parameters.

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