Atomically thin MoS2 is of great interest for electronic and optoelectronic applications because of its unique two-dimensional (2D) quantum confinement; however, the scaling of optoelectronic properties of MoS2 and its junctions with metals as a function of layer number as well the spatial variation of these properties remain unaddressed. In this work, we use photocurrent spectral atomic force microscopy (PCS-AFM) to image the current (in the dark) and photocurrent (under illumination) generated between a biased PtIr tip and MoS2 nanosheets with thickness ranging between n = 1 to 20 layers. Dark current measurements in both forward and reverse bias reveal characteristic diode behavior well-described by Fowler-Nordheim tunneling with a monolayer barrier energy of 0.61 eV and an effective barrier scaling linearly with layer number. Under illumination at 600 nm, the photocurrent response shows a marked decrease for layers up to n = 4 but increasing thereafter, which we describe using a model that accounts for the linear barrier increase at low n, but increased light absorption at larger n creating a minimum at n = 4. Comparative 2D Fourier analysis of physical height and photocurrent images shows high spatial frequency spatial variations in substrate/MoS2 contact that exceed the frequencies imposed by the underlying substrates. These results should aid in the design and understanding of optoelectronic devices based on quantum confined atomically thin MoS2.

Protein A is often used for the purification and detection of antibodies such as immunoglobulin G (IgG) because of its quadrivalent domains that bind to the Fc region of these macromolecules. However, the kinetics and thermodynamics of the binding to many sensor surfaces have eluded mechanistic description due to complexities associated with multivalent interactions. In this work, we use a near-infrared (nIR) fluorescent single-walled carbon nanotube sensor array to obtain the kinetics of IgG binding to protein A, immobilized using a chelated Cu 2+ /His-tag chemistry to hydrogel dispersed sensors. A bivalent binding mechanism is able to describe the concentration dependence of the effective dissociation constant, K D,eff , which varies from 100 pM to 1 μM for IgG concentrations from 1 ng mL −1 to 100 μg mL −1 , respectively. The mechanism is shown to describe the unusual concentration-dependent scaling demonstrated by other sensor platforms in the literature as well, and a comparison is made between resulting parameters. For comparison, we contrast IgG binding with that of human growth hormone (hGH) to its receptor (hGH−R) which displays an invariant dissociation constant at K D = 9 μM. These results should aid in the use of protein A and other recognition elements in a variety of sensor types.

The emergence of label-free lectin microarrays promises rapid and efficient glycoprofiling of complex analyte mixtures. Lectins have limited selectivity for different carbohydrate motifs necessitating relatively large array sizes to discriminate between glycoforms. Microarray technologies able to transduce the dynamics, instead of only the extent of binding, can introduce additional orthogonality in the array and therefore reduce its size. In this work, we develop a mathematical model of glycan binding dynamics to a label-free lectin sensor array, linking the matrix of observed dissociation constants, kinetics of binding, and occupancy to distinct glycoforms for identification. We introduce a matrix algebra approach that formulates the observed array dynamics in terms of a glycosylation matrix containing identifiers for each glycan chain on each protein isoform in the mixture. This formulation allows for straightforward calculation of the minimum array size necessary to distinguish a given set of glycans. As examples, we evaluate the binding of human IgG to two lectins, peanut agglutinin (PNA) and Erythrina cristagalli lectin (ECL), attached to near-infrared fluorescent single-walled carbon nanotube sensor array elements, both of which have affinities for terminal galactose residues. We demonstrate the application of both the steady state and transient model solutions to the glycan-lectin binding data, and we validate that linking microarray dynamics to glycan structure promises to significantly reduce requisite array size and complexity for rapid and efficient glycoprofiling.