🌟 A Deep Learning Approach for Quantum Dots Sizing 🌟
🌈 Exciting News Ahead! 📚💡🔍
🧠✨ Our pioneering fusion of Wide-Angle X-ray Total Scattering and AI surpasses 97% accuracy 🎯, leaving calibration curves behind! 🚀
Welcome to our exciting preprint, where we present a successful combination of total scattering data with a deep learning classifier for directly sizing quantum dots in both colloidal and dry states.
Our model 💻, rigorously tested 📊 on data 📈 with physically meaningful augmentation, has tackled extreme conditions: from low QDs concentrations to short angular ranges and bad angular resolutions. The result? Solid performance 🔥, even in untrained experimental conditions, leaving the chemists 🧑🔬 and 🥼 material scientists community with a robust and flexible model.
This offers a compelling alternative to the lengthy process 🕰️ of deriving sizing curves from transmission electron microscopy coupled with spectroscopic measurements.
☀️ Nanoscale revelations await – Stay tuned for the future of quantum dots research! 🔬📚
#QuantumDots #DeepLearning #NanoscienceInnovation #SneakPeek 👀
Download the preprint!
🦆
