Abstract
Hydrogen, the smallest and most abundant element in nature, can be efficiently incorporated within a solid and drastically modify its electronic and structural state. In most semiconductors interstitial hydrogen binds to defects and is known to be amphoteric, namely it can act either as a donor (H+) or an acceptor (H−) of charge, nearly always counteracting the prevailing conductivity type. Here we demonstrate that hydrogenation resolves an outstanding challenge in chalcogenide classes of three-dimensional (3D) topological insulators and magnets — the control of intrinsic bulk conduction that denies access to quantum surface transport, imposing severe thickness limits on the bulk. With electrons donated by a reversible binding of H+ ions to Te(Se) chalcogens, carrier densities are reduced by over 1020cm−3, allowing tuning the Fermi level into the bulk bandgap to enter surface/edge current channels without altering carrier mobility or the bandstructure. The hydrogen-tuned topological nanostructures are stable at room temperature and tunable disregarding bulk size, opening a breadth of device platforms for harnessing emergent topological states.
| Original language | English |
|---|---|
| Article number | 2308 |
| Journal | Nature Communications |
| Volume | 13 |
| Issue number | 1 |
| DOIs | |
| State | Published - Dec 2022 |
Funding
We wish to thank Tai-De Li for the technical assistance with the surface analytical tools at the Surface Science Facility of CUNY Advanced Science Research Center (ASRC). Jim Hone?s comments are much appreciated. This work was supported by the NSF grants DMR-2011738 and HRD-2112550. Computational support was provided by Virginia Tech ARC and San Diego Supercomputer Center (SDSC) under DMR-060009N. We wish to thank Tai-De Li for the technical assistance with the surface analytical tools at the Surface Science Facility of CUNY Advanced Science Research Center (ASRC). Jim Hone’s comments are much appreciated. This work was supported by the NSF grants DMR-2011738 and HRD-2112550. Computational support was provided by Virginia Tech ARC and San Diego Supercomputer Center (SDSC) under DMR-060009N.