Simultaneous Multiparametric Readout for Low-Cost NP Sensors

SMARTNANO aims at developing novel sensor strategies to detect engineered nanoparticles (ENPs) in aqueous solutions. ENPs attract increasing interest in industry including manufacturers of consumer products. For instance, TiO2 nanoparticles are widely used in cosmetics, e.g. sunscreens. To date, it is not known which (long-term) effects are caused in humans by such ENP. There are also only few methods to analyze them in aqueous matrices. Most of those methods are rather complex and expensive. SMARTNANO proposes innovations in both parts of a chemical sensor, i.e. the receptor layer that captures the target particle, and the transducer leading to an electrical signal. Artificial receptors will be based on so-called molecularly imprinted polymers (MIP). They are artificial matrices that are synthesized in the presence of the later analyte ENP (which acts as a template) and grow around it. After removing the respective ENP from the polymer surface, it leaves behind cavities that correspond to its surface chemistry and size. Such layers hence can distinguish ENPs with different diameters that contain different stabilizer shells. Transducers will detect three different signals, namely: 1.) frequency shifts caused by mass change on so-called quartz crystal microbalances (QCM). Within SMARTNANO, the consortium will implement QCM comprising three electrodes that can detect two different ENPs and a background signal; 2.) Impedance measurements above each sensor spot of the QCM; and 3.) heat transfer resistance measurements: if a cavity in the MIP is occupied by a ENP, the speed of heat transfer across the polymer layer changes. Using these three different, physically independent, signals leads to two distinct advantages: Firstly, also the core material of the ENP can be assessed, because different materials have different densities leading to different mass signals. The type of core material leads to different impedance/heat resistance properties. Hence combining MIP and multi-parameter transducers will allow to completely characterizing ENPs. The multiparameteric device will hence also be used to find optimal MIP synthesis protocols. Once both the transducer system and optimal MIP are in place, the SMARTNANO consortium will aim at developing low-cost sensors based on heat-transfer and impedance measurements at MIP layers on microwires to design good-value analysis for ENP detection. The project brings together two groups at the University of Vienna and at the Catholic University of Leuven. The former is specialized in developing MIP-based sensor layers among others. The latter is on the forefront of developing innovative sensor devices.

Human activity releases nanoparticles into the environment, be it through incomplete combustion, by adding them to cosmetics, or traffic, to name a few. Their full impact on health is still not understood, but it becomes increasingly clear that society needs efficient tools to detect them. The collaborative project SMARTNANO has brought together two groups aiming at designing a sensor system for that purpose: one is the group of Prof. Peter Lieberzeit at the University of Vienna, which has profound experience in designing artificial receptors to recognize different species from small molecules to entire cells. The other one is led by Prof. Patrick Wagner at KU Leuven, who has in-deep expertise in designing measuring systems to be used in real environments and clinical settings. The Austrian part of this bilateral project focused on developing so-called molecularly imprinted polymers (MIPs) that can selectively bind defined ENP species. Simply put, molecular imprinting in this case generates cavities in a polymer surface that match both the size and the surface chemistry of the respective particles. However, to the best of our knowledge only one group has published in imprinting ENPs, but using a completely different approach, namely electropolymerization. The project followed two synthesis routes: one was "classical" polymerization using different systems including urethanes, styrenes, and acrylates. After spin-coating them onto the surfaces of quartz crystal microbalance (QCM) sensors (i.e. basically very fine scales), they indeed were able to rebind their respective ENP, usually Ag or Au with 75 nm diameter. The resulting sensors revealed concentration-dependent signals and bound other nanoparticles to a lesser extent, i.e.: they turned out selective. The second route aimed at growing the polymer layers directly from the sensor surface in the presence of ENPs. For that purpose, the project relied on so-called controlled radical polymerization, because it allows for tuning layer thicknesses through polymerization time. In this case the nanoparticles analyzed consisted of magnetite (for easier handling, proof of concept) and titania (which, e.g., is used in sunscreens). Also, this route has led to appreciable sensor responses. The polymers again preferably bind their target ENP. It is especially suited for the sensing systems designed by the project partners at KU Leuven. The results have thus laid the foundations for understanding nanoparticle binding and the underlying processes better, though it also has opened several new questions on the relation between nanoparticle properties and sensor responses. Furthermore, it brings the consortium one step closer to developing robust, potentially marketable sensing systems.