π Seeking Collaboration in Perovskite Solar Cells Research π
I am excited to announce that I am actively seeking collaboration opportunities in the field of next-generation solar cells including perovskite solar cells (PSCs), DSSCs. QDSSCs, OSCs, etc. With the rapid advancements in this domain, I believe that interdisciplinary collaboration and knowledge-sharing are key to unlocking the full potential of this transformative technology.
I am particularly interested in contributing to and collaborating on projects related to:
π¬ Material Discovery & Design: Leveraging machine learning (ML) for high-throughput screening and predictive modeling of novel perovskite compositions.
βοΈ Device Fabrication Optimization: Using ML to optimize fabrication processes and defect engineering for enhanced performance.
π Performance Prediction & Analysis: Building models to predict efficiency, stability, and lifetime of PSCs.
π Characterization & Degradation Analysis: Applying ML for advanced image and spectroscopic data analysis to understand material properties and degradation mechanisms.
π€ Integration with Experimental Workflows: Combining ML with automated experimentation and real-time monitoring for accelerated research.
I bring expertise in machine learning, data analysis, emerging solar cell technologies, organic electronics, photonics, and materials science, and I am passionate about applying these skills to tackle the challenges in research in next-generation solar cells. Whether you are an experimentalist, theorist, or data scientist, I would love to connect and explore how we can work together to push the boundaries of this field.
If you are working on next-generation solar cells or related areas and are interested in collaboration, feel free to reach out! Letβs connect and drive innovation in renewable energy together.