Nanowires are excellent model systems for investigating the effects of low dimensionality in materials. Controlling the diameter of the nanowires, and hence its surface-to-volume ratio, the presence or relevance of surface-related characteristics can be addressed. This is of particular interest in the case of topological insulators owing to electronic surface states (topologically protected) independent from bulk states. Tetradymite chalcogenides Bi2Te3, Bi2Se3, and Sb2Te3 are small band gap semiconductors with wide application in state-of-the-art Peltier cooling devices or thermoelectric power generators. They are also strong 3D-topological insulator, with topologically protected states predicted to appear on any free surface regardless of the crystallographic orientation. This Dataset is referring to the following study, in which the resistance of an ordered 3D-Bi2Te3 nanowire nanonetwork was studied at low temperatures. Below 50 K the increase in resistance was found to be compatible with the Anderson model for localization, considering that conduction takes place in individual parallel channels across the whole sample. Angle-dependent magnetoresistance measurements showed a distinctive weak antilocalization characteristic with a double feature that we could associate with transport along two perpendicular directions, dictated by the spatial arrangement of the nanowires. The coherence length obtained from the Hikami–Larkin–Nagaoka model was about 700 nm across transversal nanowires, which corresponded to approximately 10 nanowire junctions. Along the individual nanowires, the coherence length was greatly reduced to about 100 nm. The observed localization effects could be the reason for the enhancement of the Seebeck coefficient observed in the 3D-Bi2Te3 nanowire nanonetwork compared to individual nanowires.

According to the open access nature and its exceptions in the datasets regulation of the Call ERC-2021-ADG, and having reflected the following statements in the Data Management Plan of such project (ID: 101052603; POWERbyU; ERC-2021-ADG), the authors of the data associated with this publication state the following: The datasets associated with this publication will be available upon request, due to these datasets being subjected to Intellectual Property Restrictions; requests by externals for the use of these datasets will be approved by the project coordinator. Please, contact Prof. Marisol Martín-González: marisol.martin@csic.es This modus operandi will remain in effect, at least until the end of the project.

The authors would like to acknowledge the financial support from the projects ERC Adv. POWERbyU 101052603, PID2020-118430GB-100, and PID2019-106165GB-C21 (MICINN) and project 2D-MESES from CSIC. This work was also cofinanced by the 2014–2020 ERDF Operational Programme and the Department of Economy, Knowledge, Business and University of the Regional Government of Andalusia, project reference no. FEDER-UCA18-107139. The authors would also like to acknowledge the service from the MiNa Laboratory at IMN, and its funding from CM (project SpaceTec, S2013/ICE2822), MINECO (project CSIC13-4E-1794), and EU (FEDER, FSE). F.P. acknowledges the support from ICREA Academia 2022 and 2021SGR00242, Generalitat de Catalunya.

No