Explores the properties and applications of carbon nanostructures, including graphene and carbon nanotubes, emphasizing their unique characteristics and diverse uses.
Covers the Fast Fourier Transform (FFT) algorithm and its applications in computational physics, including image processing, experimental techniques, filters, and analysis of microscopy images.
Explores the potential of graphene in developing efficient neural interfaces with the nervous system, addressing current challenges and discussing various graphene-based technologies.
Explores the engineering of intrinsic π-electron magnetism in carbon nanostructures, focusing on inducing magnetism in graphene and nanographenes through sublattice imbalance and topological frustration.
Explores the transition from spintronics to Majorana states in proximitized materials, focusing on magnetic proximity and topological superconductivity detection.
