DFT Screening of Lead-Free Perovskites

ISEF Category: Energy: Sustainable Materials and Design

Subcategory: Solar Process, Materials, and Design  ·  Difficulty: Advanced  ·  Setup: University Lab  ·  Time: Full Year

The Hook

Lead in solar materials works well, but it also raises safety and disposal problems. That tradeoff has pushed researchers to hunt for safer replacements. You can test which lead-free perovskite mixes look most promising before anyone grows a crystal. Your project becomes a search for the best absorber on a computer.

What Is It?

Perovskites are a class of crystals that can absorb light very well. Think of them like a sponge for sunlight. In solar cells, that matters because a good absorber can turn more incoming light into usable electrical energy. Your project asks which lead-free versions of these crystals might work best.

DFT, short for density functional theory, is a way to estimate how electrons behave in a material. You are not building the material first. You are using physics to predict its properties from its atomic structure. Quantum ESPRESSO is one software package that can run these calculations. On Google Colab, you can access computing power through a browser, which helps if your school computer is limited.

Why This Is a Good Topic

This is a strong science fair topic because you can compare many materials without making them in a lab first. You can test clear variables, like which metal mix changes the band gap, stability, or predicted absorption most. The project connects to safer solar materials, which matters for real devices and manufacturing. You can also learn how researchers screen candidates before spending time and money on synthesis.

Research Questions

• How does replacing lead with tin, germanium, or bismuth change the predicted band gap of a perovskite absorber?
• What is the effect of different Sn/Ge/Bi mixing ratios on the calculated electronic structure of a lead-free perovskite?
• Does adding a second or third metal improve the predicted stability of a perovskite crystal compared with a single-metal replacement?
• To what extent do lattice changes correlate with band gap shifts in candidate absorber materials?
• Which lead-free perovskite composition gives the best balance of predicted low toxicity and strong light absorption?
• How does the choice of exchange-correlation approximation affect the ranking of candidate perovskites?

Basic Materials

• Laptop or desktop with reliable internet access.
• Google account for Colab access.
• Quantum ESPRESSO installed in a Colab notebook or accessible through a guided notebook.
• Spreadsheet software for tracking compositions and results.
• Graphing software such as Google Sheets or LibreOffice Calc.
• Basic notes template for recording structure names, input settings, and outputs.
• PubMed or Google Scholar access for reading background papers.

Advanced Materials

• Access to a Linux workstation or university cluster.
• Quantum ESPRESSO with pseudopotential libraries.
• Visualization tool such as VESTA or XCrySDen for crystal structures.
• Python environment with NumPy, pandas, matplotlib, and SciPy.
• Materials Project or similar open materials database for structure comparison.
• Phonon or post-processing tools for stability checks if available.
• Band structure and density of states analysis scripts.

Software & Tools

• Quantum ESPRESSO: Runs DFT calculations for crystal structures, electronic properties, and band structures.
• Google Colab: Gives you a browser-based place to run notebooks and share your workflow.
• Python: Helps you organize outputs, compare candidates, and make plots.
• pandas: Sorts composition data, calculation results, and ranking tables.
• matplotlib: Turns raw numbers into graphs that make trends easier to see.

Experiment Steps

1. Define the exact perovskite family you will screen, including the site you will replace and the range of Sn, Ge, and Bi mixtures you will compare.
2. Choose one primary property to rank candidates, such as band gap, predicted stability, or a combined score.
3. Build a small, consistent workflow for generating input structures so every candidate gets tested the same way.
4. Decide the controls that anchor your results, such as a known lead-based reference and a simple lead-free baseline.
5. Plan a scoring method that turns several outputs into one comparison table, so you can rank candidates fairly.
6. Design a validation check that compares your computational trend with published data or with a second calculation setup.

Common Pitfalls

• Changing the structure setup between candidates, which makes your comparisons unfair.
• Ranking materials only by band gap and ignoring stability, which can make a pretty result that has no practical value.
• Mixing incompatible pseudopotentials or calculation settings, which can break the consistency of your DFT workflow.
• Trusting one relaxed structure without checking whether the geometry converged well enough to support the result.
• Comparing your outputs to published values without matching the same crystal phase, which can make a correct calculation look wrong.

What Makes This Competitive

A stronger project does more than list band gaps. It compares several candidate compositions with the same workflow, explains why one score matters more than another, and checks whether the trend survives a second method or sensitivity test. You can also make the work stand out by building a clear screening pipeline that other students could repeat. A clean comparison table, solid controls, and a thoughtful tie to real solar material design make the project feel research-grade.

Project Variations

• Screen double perovskite candidates that replace lead with only two-metal or three-metal mixtures.
• Compare how the same lead-free compositions behave under two different DFT settings, then test whether the ranking stays the same.
• Add a toxicity and abundance filter to your computational ranking, so you score candidates by both performance and material practicality.

Learn More

• MIT OpenCourseWare: Search the materials science and solid-state physics courses for lectures on crystal structures, band theory, and electronic materials.
• NIST Materials Data Repository: Look for open materials data and property definitions that help you compare candidate solids.
• PubMed: Search for review articles on lead-free perovskite solar absorbers and stability trends.
• NASA ADS: Search for physics and materials papers on perovskite electronic structure and computational screening.
• Quantum ESPRESSO documentation: Read the official user guides and tutorials for input files, SCF runs, and band structure workflows.
• Materials Project: Explore crystal structures and computed properties for comparison against your own screening results.