Computational materials science tests physical ideas on a computer before laboratory experiments, or explains experimental results after they are measured. These areas span familiar technologies from clean energy and semiconductors to cutting-edge topological quantum materials.
In this topic, we look at how electrons move through a material. That helps us estimate whether it could work well in chips, LEDs, transistors, or simple electronic sensors before spending time and money building it in a lab.
Here we ask how well a material absorbs sunlight and what happens to that energy afterward. By comparing these results, we can find better candidates for solar cells and other light-based energy devices.
We study how easily ions move in and out of a material during charging and discharging. This helps us find battery materials that can store more energy, last longer, and stay stable over many cycles.
Photocatalysis uses light to speed up chemical reactions. We test whether a material's surface can use sunlight to drive useful reactions, such as splitting water or helping break down pollutants.
In electrocatalysis, electricity helps reactions happen faster on a material surface. We compare different materials to see which ones are more effective for reactions related to hydrogen, oxygen, carbon dioxide, and fuel cells.
This topic focuses on materials with useful magnetic behavior. We explore whether they could store information or support future electronics that use spin, a magnetic property of electrons.
We look at how materials respond when they are stretched, squeezed, or contain defects. This helps us understand which materials are strong, which are fragile, and how they might fail in real use.
Quantum materials can behave in unusual ways that normal materials do not. We use simulations to spot these special behaviors and understand whether they might be useful for future quantum technologies.
For gas sensors, surface interactions are very important. We test how strongly different gases (like CO2, NO2, and H2) stick to a material, so we can estimate how sensitive and selective a sensor might be.