Computational Design of Chemical Nanosensors: Metal Doped Carbon Nanotubes J. M. Garc´ıa-Lastra$^{1,2}$, ∗ D. J. Mowbray$^{1,2}$, K. S. Thygesen$^{2}$, A. Rubio$^{1,3}$, and K. W. Jacobsen 2 $^{1}$Nano-Bio Spectroscopy group and ETSF Scientific Development Centre, Dpto. F´ısica de Materiales, Universidad del Pa´ıs Vasco, Centro de F´ısica de Materiales CSIC-UPV/EHU- MPC and DIPC, Av. Tolosa 72, E-20018 San Sebasti´an, Spain $^{2}$Center for Atomic-scale Materials Design, Department of Physics, Technical University of Denmark, DK-2800 Kgs. Lyngby, Denmark $^{3}$Fritz-Haber-Institut der Max-Planck-Gesellschaft, Berlin, Germany We use computational screening to systematically investigate the use of transition metal doped carbon nan- otubes for chemical gas sensing. For a set of relevant target molecules (CO, NH$_{3}$, H$_{2}$S) and the main components of air (N$_{2}$, O$_{2}$, H$_{2}$O), we calculate the binding energy and change in conductance upon adsorption on a metal atom occupying a vacancy of a (6,6) carbon nanotube. Based on these descriptors, we identify the most promis- ing dopant candidates for detection of a given target molecule. From the fractional coverage of the metal sites in thermal equilibrium with air, we estimate the change in the nanotube resistance per doping site as a function of the target molecule concentration assuming charge transport in the diffusive regime. Our analysis points to Ni-doped nanotubes as candidates for CO sensors working under typical atmospheric conditions. PACS numbers: 73.63.–b, 68.43.–h, 73.50.Lw The ability to detect small concentrations of specific chem- ical species is fundamental for a variety of industrial and sci- entific processes as well as for medical applications and en- vironmental monitoring [1]. In general, nanostructured mate- rials should be well suited for sensor applications because of their large surface to volume ratio which makes them sensi- tive to molecular adsorption. Specifically, carbon nanotubes (CNT) [2] have been shown to work remarkably well as de- tectors of small gas molecules. This has been demonstrated both for individual CNTs [3–8] as well as for CNT networks [9, 10]. change in CNT resistivity may then be obtained from the cal- culated coverages and single impurity conductances. We find that oxidation of the active metal site passivates the sensor in the case of doping by Ti, V, Cr, and Mn un- der standard conditions (room temperature and 1 bar of pres- sure). Among the remaining metals, we identify Ni as is the most promising candidate for CO detection. For this system the change in resistance per active site is generally significant ( > 1 Ω ) for small changes in CO concentration in the relevant range of around 0.1–10 ppm. Our approach is quite general and is directly applicable to other nanostructures than CNTs, other functionalizations than metal doping, and other back- grounds than atmospheric air. Pristine CNTs are known to be chemically inert – a prop- erty closely related to their high stability. As a consequence, only radicals bind strong enough to the CNT to notably affect its electrical properties [2, 5, 11–13]. To make CNTs attrac- tive for sensor applications thus requires some kind of func- tionalization, e.g. through doping or decoration of the CNT sidewall [13–21]. Ideally, this type of functionalization could be used to control not only the reactivity of the CNT but also the selectivity towards specific chemical species. In this work we consider the possibility of using CNTs doped by 3d transition metal atoms for chemical gas sens- ing. We use computational screening to systematically iden- tify the most promising dopant candidates for detection of three different target molecules (CO, NH$_{3}$, H$_{2}$S) under typi- cal atmospheric conditions. The screening procedure is based on the calculation of two microscopic descriptors: the bind- ing energy and scattering resistance of the molecules when adsorbed on a doped CNT. These two quantities give a good indication of the gas coverage and impact on the resistance. For the most promising candidates we then employ a simple thermodynamic model of the CNT sensor. In this model, the binding energies are used to obtain the fractional coverage of the metallic sites as a function of the target molecule concen- tration under ambient conditions. Under the assumption of transport in the diffusive rather than localization regime, the where E [M@VC] is the total energy of a transition metal atom occupying a vacancy in the nanotube, n is the number of carbon atoms removed to form the vacancy, E [C] is the en- ergy per carbon atom in a pristine nanotube, and E [M@NT] Metallic doping of a (6,6) CNT has been modeled in a su- percell containing six repeated minimal unit cells along the CNT axis (dimensions: 15 ˚ A × 15 ˚ A × 14.622 ˚ A). For this size of supercell a Γ -point sampling of the Brillouin zone was found to be sufficient. The formation energy for creating a vacancy (VC) occupied by a transition metal atom (M) was calculated using the relation All total energy calculations and structure optimizations have been performed with the real-space density functional theory (DFT) code GPAW [22] which is based on the projector augmented wave method. We use a grid spacing of 0.2 ˚ A for representing the density and wave functions and the PBE ex- change correlation functional [23]. Transport calculations for the optimized structures have been performed using the non- equilibrium Green’s function method [24] with an electronic Hamiltonian obtained from the SIESTA code [25] in a dou- ble zeta polarized (DZP) basis set. Spin polarization has been taken into account in all calculations. arXiv:1001.2538v1 [cond-mat.mes-hall] 14 Jan 2010 E$_{form}$ [ M @ VC ] = E [ M @ VC ] + nE [ C ] − E [ M@NT ] (1)