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.
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 trends and challenges in modeling complex molecular systems using hierarchical multi-scale approaches, covering length-time scales, atomistic simulations, and force matching techniques.
Explores the transition from spintronics to Majorana states in proximitized materials, focusing on magnetic proximity and topological superconductivity detection.
