Computer simulations offer new insights into enhancing solar cell materials

Computer simulations offer new insights into enhancing solar cell materials

by Robert Schreiber

Berlin, Germany (SPX) Oct 16, 2024

Researchers from Chalmers University of Technology in Sweden have made progress in understanding halide perovskites, a promising class of materials for solar cells. These materials could serve as an efficient and cost-effective alternative to traditional silicon-based cells, but they face challenges with stability. The new insights are expected to aid the development of more reliable and efficient solar cells, key components in the transition to sustainable energy.

Halide perovskites refer to a group of materials recognized for their potential in flexible, lightweight solar cells and various optical applications, such as LEDs. They exhibit high efficiency in light absorption and emission, making them suitable for next-generation solar technologies. However, understanding the causes of rapid degradation remains a hurdle in optimizing these materials.

Advanced computer simulations reveal material behavior

The research team employed advanced computer simulations and machine learning to study 2D perovskite materials, which are typically more stable than their 3D counterparts. The findings, published in *ACS Energy Letters*, provide new insights into the factors that influence the materials’ properties.

“By mapping out the material in computer simulations and subjecting it to different scenarios, we can draw conclusions about how the atoms in the material react when exposed to heat, light, and so on,” explained Professor Paul Erhart from the research team. “We now have a microscopic description of the material that is independent of what experiments have shown, but which we can show to lead to the same behavior as the experiments.”

Simulations allow researchers to analyze material behaviors at a detailed level, offering a unique view that complements experimental data. This approach has made it possible to observe what leads to specific outcomes in experiments, deepening the understanding of 2D perovskites’ functionality.

Machine learning enables broader and deeper analysis

The integration of machine learning techniques allowed the researchers to study larger systems over longer durations than was previously feasible.

“This has given us both a much broader overview than before, but also the ability to study materials in much more detail,” said Associate Professor Julia Wiktor. “We can see that in these very thin layers of material, each layer behaves differently, and that’s something that is very difficult to detect experimentally.”

The composition and interaction of layers in 2D perovskites

2D perovskites consist of inorganic layers separated by organic molecules, which play a crucial role in determining the material’s stability and optical properties. Understanding the atomic movements within these layers and their connection to the organic linkers is essential for designing efficient devices.

“In 2D perovskites, you have perovskite layers linked with organic molecules. What we have discovered is that you can directly control how atoms in the surface layers move through the choice of the organic linkers,” noted Erhart. “This movement is crucial to the optical properties, creating a domino effect that extends deep inside the material.”

Future research directions

The study’s results pave the way for developing more stable and efficient optoelectronic devices by identifying which molecular configurations could enhance performance. The researchers aim to extend their work to more complex systems, focusing on interfaces that are essential for device functionality.

“Our next step is to move to even more complex systems and in particular interfaces that are fundamental for the function of devices,” Wiktor added.

Research Report:Impact of Organic Spacers and Dimensionality on Templating of Halide Perovskites