The Detection of Trace Metal Contaminants in Organic Products Using Ion Current Rectifying Quartz Nanopipettes

While ion current rectification (ICR) in aprotic solvent has been fundamentally studied, its application in sensing devices lacks exploration. The development of sensors operable in these solvents is highly beneficial to the chemical industry, where polar aprotic solvents, such as acetonitrile, are widely used. Currently, this industry relies on the use of inductively coupled plasma mass spectrometry (ICP-MS) and optical emission spectroscopy (OES) for the detection of metal contamination in organic products. Herein, we present the detection of trace amounts of Pd2+ and Co2+ using ion current rectification, in cyclam-functionalized quartz nanopipettes, with tetraethylammonium tetrafluoroborate (TEATFB) in MeCN as supporting electrolyte. This methodology is employed to determine the concentration of Pd in organic products, before and after purification by Celite filtration and column chromatography, obtaining comparable results to ICP-MS within minutes and without complex sample preparation. Finite element simulations are used to support our experimental findings, which reveal that the formation of double-junction diodes in the nanopore enables trace detection of these metals, with a significant response from baseline even at picomolar concentrations.


Finite Element Simulations:
Capillary Filling Model Background and Equations: The interface-tension σij and the contact angle θ are two parameters governing the shape of a meniscus via the law of capillary action;  13 −  23 =  12 cos θ ( S1 ) where the indices i, j ∈ {1, 2, 3} denote the gas, liquid, and solid phase, respectively.
The height of the meniscus h is then given by Jurin's law.

h = 2σ cos θ 𝜌gr ( S2 )
which is derived by equating the capillary force FC = 2πrσ and the gravitational force of the liquid G = ρπr 2 hg and substituting the surface tension σ with the contact angle.
The Cahn-Hilliard equations were solved to track the diffuse interface with the phase field help variable, Ψ.
where u is the fluid velocity in m s −1 , γ is the mobility in m 3 s kg −1 , λ is the mixing energy density in N and ε is the interface thickness parameter in m.
For the surface tension coefficient σ follows: and the volume fractions of the two phases are given by: The physical properties of the fluids such as the density in kg m −3 and the viscosity µ in Pa s are then interpolated between the two phases using: To account for mass and momentum transport the Navier-Stokes equations are included in the model-physics with the surface tension force acting at the interface Fst: where ρ is the density in kg m −3 , µ is the dynamic viscosity in Ns m −2 , u is the velocity in m s −1 , p is the pressure in Pa and g is the gravity vector in m s −2 .
Using the chemical potential G in J m 3 : the surface tension can be calculated only with Ψ and the gradient of the phase field variable,    S2.
Figure S3.The procedure employed for selecting diode boundaries from the half peak height of ion enrichment and depletion bands.The boundaries are summarised in Table S2.
Table S2.Summarized state (accumulation or depletion) and boundaries (obtained as per procedure in Figure S3) of double junction diodes as a function of increasing surface charge density in the cyclam functionalized region of a 50 nm quartz nanopipette.

Surface Charge Density in
S8 ) avoiding the usage of the surface normal and the surface curvature.The model-physics are adapted from a model example published by COMSOL® in their model library (application ID 1878).

Figure S1 .
Figure S1.The 2D axisymmetric geometry and corresponding mesh of a 50 nm quartz nanopipette used in finite element simulations, with boundaries corresponding to the boundary conditions in TableS1highlighted.

Figure S4 .
Figure S4.Nanopipette radius determination using a) conductivity measurements indicating a mean radius of 48.5 nm.b,c) Representative SEM and STEM images indicating an internal radius of ~ 60 nm.