Various tools and platforms facilitate data-driven research in nanotechnology:
1. Materials Databases: Online repositories such as the Materials Project and NOMAD provide access to extensive datasets on material properties. 2. Machine Learning Libraries: Libraries like TensorFlow, Scikit-learn, and PyTorch are commonly used for developing ML models. 3. Simulation Software: Tools such as LAMMPS and VASP are used for molecular dynamics and quantum simulations. 4. Data Analytics Platforms: Platforms like Hadoop and Spark enable the processing of large datasets.
