A novel application of nanoporous gold to humidity sensing: a framework for a general volatile compound sensor

Highly Porous 3D Gold Enhances Sensitivity of Amperometric Biosensors Based on Oxidases and CuCe Nanoparticles

Metallic nanoparticles potentially have wide practical applications in various fields of science and industry. In biosensorics, they usually act as catalysts or nanozymes (NZs) and as mediators of electron transfer. We describe here the development of amperometric biosensors (ABSs) based on purified oxidases, synthesized nanoparticles of CuCe (nCuCe), and micro/nanoporous gold (pAu), which were electro-deposited on a graphite electrode (GE). As an effective peroxidase (PO)-like NZ, nCuCe was used here as a hydrogen-peroxide-sensing platform in ABSs that were based on glucose oxidase, alcohol oxidase, methylamine oxidase, and L-arginine oxidase. At the same time, nCuCe is an electroactive mediator and has been used in laccase-based ABSs. As a result, the ABSs we constructed and characterized were based on glucose, methanol, methyl amine, L-arginine, and catechol, respectively. The developed nCuCe-based ABSs exhibited improved analytical characteristics in comparison with the corresponding PO-based ABSs. Additionally, the presence of pAu, with its extremely advanced chemo-sensing surface layer, was shown to significantly increase the sensitivities of all constructed ABSs. As an example, the bioelectrodes containing laccase/GE, laccase/nCuCe/GE, and laccase/nCuCe/pAu/GE exhibited sensitivities to catechol at 2300, 5055, and 9280 A·M⁻¹·m⁻², respectively. We demonstrate here that pAu is an effective carrier of electroactive nanomaterials coupled with oxidases, which may be promising in biosensors.

Probing the Surface Chemistry of Nanoporous Gold via Electrochemical Characterization and Atom Probe Tomography

Surface chemistry information is crucial in understanding catalytic and sensing mechanisms. However, resolving the outermost monolayer composition of metallic nanoporous materials is challenging due to the high tortuosity of their morphology. In this study, we first elaborate on the capabilities and limitations of atom probe tomography (APT) in resolving interfaces. Subsequently, an electrochemical approach is designed to characterize the surface composition of nanoporous gold (NPG), developed from dealloying an inexpensive precursor (95 at. % Ag, 5 at. % Au), by the means of aqueous electrochemical measurements of the selective electrosorption of sulfide ions, which react strongly with Ag, but to a significantly lesser extent with Au. Accordingly, cyclic voltammetry was performed at various scan rates on NPG in alkaline aqueous solutions (0.2 M NaOH; pH 13) in the presence and absence of 1 mM Na2S. Calibrations via similar voltammetric measurements on pure polycrystalline Ag and Au surfaces allowed for a quantitative estimation for the Ag surface coverage of NPG. The sensitivity threshold for the detection of the adsorbate-Ag interaction was assessed to be approximately 2% Ag surface coverage. As curves measured on NPG only showed featureless capacitive currents, no faradaic charge density associated with sulfide electrosorption could be detected. This study opens a new avenue to gain further insight into the monolayer surface coverage of metallic nanoporous materials and assists in enhancement of the interpretation of APT reconstructions.

Nanoporous Gold as a VOC Sensor, Based on Nanoscale Electrical Phenomena and Convolutional Neural Networks

Volatile organic compounds (VOCs) are prevalent in daily life, from the lab environment to industrial applications, providing tremendous functionality but also posing significant health risk. Moreover, individual VOCs have individual risks associated with them, making classification and sensing of a broad range of VOCs important. This work details the application of electrochemically dealloyed nanoporous gold (NPG) as a VOC sensor through measurements of the complex electrical frequency response of NPG. By leveraging the effects of adsorption and capillary condensation on the electrical properties of NPG itself, classification and regression is possible. Due to the complex nonlinearities, classification and regression are done through the use of a convolutional neural network. This work also establishes key strategies for improving the performance of NPG, both in sensitivity and selectivity. This is achieved by tuning the electrochemical dealloying process through manipulations of the starting alloy and through functionalization with 1-dodecanethiol.