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Doped semiconductor nanowires are emerging as next-generation electronic colloidal materials, and the efficient manipulation of such nanostructures is crucial for technological applications. In fluid suspension, pn nanowires (pn NWs), unlike homogeneous nanowires, have a permanent dipole, and thus, experience a torque under an external DC field that orients the nanowire with its n-type end in the direction of the field. Here, we quantitatively measure the permanent dipoles of various Si nanowire pn diodes and investigate their origin. By comparing the dipoles of pn NWs of different lengths and radii, we show that the permanent dipole originates from non-uniform surface-charge distributions, rather than the internal charges at the p–n junction as was previously proposed. This understanding of the mechanism for pn NWs orientation has relevance to the manipulation, assembly, characterization, and separation of nanowire electronics by electric fields. 

Abstract We demonstrate a bottom-up process for programming the deposition of coaxial thin films aligned to the underlying dopant profile of semiconductor nanowires. Our process synergistically combines three distinct methods—vapor–liquid–solid nanowire growth, selective coaxial lithography via etching of surfaces (SCALES), and area-selective atomic layer deposition (AS-ALD)—into a cohesive whole. Here, we study ZrO 2 on Si nanowires as a model system. Si nanowires are first grown with an axially modulated n-Si/i-Si dopant profile. SCALES then yields coaxial poly(methyl methacrylate) (PMMA) masks on the n-Si regions. Subsequent AS-ALD of ZrO 2 occurs on the exposed i-Si regions and not on those masked by PMMA. We show the spatial relationship between nanowire dopant profile, PMMA masks, and ZrO 2 films, confirming the programmability of the process. The nanoscale resolution of our process coupled with the plethora of available AS-ALD chemistries promises a range of future opportunities to generate structurally complex nanoscale materials and electronic devices using entirely bottom-up methods.