“…In recent years, the predictive power of such methodologies has been demonstrated in a large variety of realistic models of disordered graphene and two-dimensional materials (Ferreira and Mucciolo, 2015;Gargiulo et al, 2014;Trambly de Laissardière and Mayou, 2013;Lherbier et al, 2008b;Radchenko et al, 2013;Wehling et al, 2010;Yuan et al, 2010b;Zhao et al, 2015), multilayer graphene (Missaoui et al, 2018;Yuan et al, 2010a), organic semiconductors (Fratini et al, 2017;Ishii et al, 2018Ishii et al, , 2015Ishii et al, , 2017 and conducting polymers (Adjizian et al, 2016;Ihnatsenka et al, 2015;Tonnelé et al, 2019), quasicrystals and aperiodic systems (Trambly de Laissardière and Mayou, 2014;, silicon nanowires (Markussen et al, 2006;Persson et al, 2008), carbon nanotubes (Ishii et al, 2010b;Latil et al, 2004) and three-dimensional models of topological insulators (Cresti et al, 2016;Soriano et al, 2012;Wehling et al, 2014). Charge, spin and Hall transport coefficients have been numerically computed in different transport regimes, including the quasi-ballistic, diffusive, weak localization, weak antilocalization, and strong (Anderson) localization regimes, providing in-depth quantitative analysis directly comparable with experimental data.…”