First-Order Individual Gas Sensors as Next Generation Reliable Analytical Instruments

It is conventionally expected that the performance of existing gas sensors may degrade in the field compared to laboratory conditions because (i) a sensor may lose its accuracy in the presence of chemical interferences and (ii) variations of ambient conditions over time may induce sensor-response fluctuations (i.e., drift). Breaking this status quo in poor sensor performance requires understanding the origins of design principles of existing sensors and bringing new principles to sensor designs. Existing gas sensors are single-output (e.g., resistance, electrical current, light intensity, etc.) sensors, also known as zero-order sensors (Karl Booksh and Bruce R. Kowalski, Analytical Chemistry, DOI: 10.1021/ac00087a718). Any zero-order sensor is undesirably affected by variable chemical background and sensor drift that cannot be distinguished from the response to an analyte. To address these limitations, we are developing multivariable gas sensors with independent responses, which are first-order analytical instruments. Here, we demonstrate self-correction against drift in two types of first-order gas sensors that operate in different portions of the electromagnetic spectrum. Our radiofrequency sensors utilize dielectric excitation of semiconducting metal oxide materials on the shoulder of their dielectric relaxation peak and achieve self-correction of the baseline drift by operation at several frequencies. Our photonic sensors utilize nanostructured sensing materials inspired by Morpho butterflies and achieve self-correction of the baseline drift by operation at several wavelengths. These principles of self-correction for drift effects in first-order sensors open opportunities for diverse emerging monitoring applications that cannot afford frequent periodic maintenance that is typical of traditional analytical instruments.

New trends in methyl salicylate sensing and their implications in agriculture

Methyl salicylate (MeSal) is an organic compound present in plants during stress events and is therefore a key marker for early plant disease detection. It has usually been detected by conventional methods that require bulky and costly equipment, such as gas chromatography or mass spectrometry. Currently, however, chemical sensors provide an alternative for MeSal monitoring, showing good performance for its determination in the vapour or liquid phase. The most promising concepts used in MeSal determination include sensors based on electrochemical and conductometric principles, although other technologies based on mass-sensitive, microwave, or spectrophotometric principles also show promise. The receptor elements or sensitive materials are shown to be part of the key elements in these sensing technologies. A literature survey identified a significant contribution of bioreceptors, including enzymes, odourant-binding proteins or peptides, as well as receptors based on polymers or inorganic materials in MeSal determination. This work reviews these concepts and materials and discusses their future prospects and limitations for application in plant health monitoring.

Controlling Mineralization with Protein-Functionalized Peptoid Nanotubes

Sequence-defined foldamers that self-assemble into well-defined architectures are promising scaffolds to template inorganic mineralization. However, it has been challenging to achieve robust control of nucleation and growth without sequence redesign or extensive experimentation. Here, peptoid nanotubes functionalized with a panel of solid-binding proteins are used to mineralize homogeneously distributed and monodisperse anatase nanocrystals from the water-soluble TiBALDH precursor. Crystallite size is systematically tuned between 1.4 and 4.4 nm by changing protein coverage and the identity and valency of the genetically engineered solid-binding segments. The approach is extended to the synthesis of gold nanoparticles and, using a protein encoding both material-binding specificities, to the fabrication of titania/gold nanocomposites capable of photocatalysis under visible-light illumination. Beyond uncovering critical roles for hierarchical organization and denticity on solid-binding protein mineralization outcomes, the strategy described herein should prove valuable for the fabrication of hierarchical hybrid materials incorporating a broad range of inorganic components.

Bio-inspired gas sensing: boosting performance with sensor optimization guided by "machine learning"

The performance of existing gas sensors often degrades in field conditions because of the loss of measurement accuracy in the presence of interferences. Thus, new sensing approaches are required with improved sensor selectivity. We are developing a new generation of gas sensors, known as multivariable sensors, that have several independent responses for multi-gas detection with a single sensor. In this study, we analyze the capabilities of natural and fabricated photonic three-dimensional (3-D) nanostructures as sensors for the detection of different gaseous species, such as vapors and non-condensable gases. We employed bare Morpho butterfly wing scales to control their gas selectivity with different illumination angles. Next, we chemically functionalized Morpho butterfly wing scales with a fluorinated silane to boost the response of these nanostructures to the vapors of interest and to suppress the response to ambient humidity. Further, we followed our previously developed design rules for sensing nanostructures and fabricated bioinspired inorganic 3-D nanostructures to achieve functionality beyond natural Morpho scales. These fabricated nanostructures have embedded catalytically active gold nanoparticles to operate at high temperatures of ≈300 °C for the detection of gases for solid oxide fuel cell (SOFC) applications. Our performance advances in the detection of multiple gaseous species with specific nanostructure designs were achieved by coupling the spectral responses of these nanostructures with machine learning (a.k.a. multivariate analysis, chemometrics) tools. Our newly acquired knowledge from studies of these natural and fabricated inorganic nanostructures coupled with machine learning data analytics allowed us to advance our design rules for sensing nanostructures toward the required gas selectivity for numerous gas monitoring scenarios at room and high temperatures for industrial, environmental, and other applications.

Protein- and Peptide-Based Biosensors in Artificial Olfaction

Animals' olfactory systems rely on proteins, olfactory receptors (ORs) and odorant-binding proteins (OBPs), as their native sensing units to detect odours. Recent advances demonstrate that these proteins can also be employed as molecular recognition units in gas-phase biosensors. In addition, the interactions between odorant molecules and ORs or OBPs are a source of inspiration for designing peptides with tunable odorant selectivity. We review recent progress in gas biosensors employing biological units (ORs, OBPs, and peptides) in light of future developments in artificial olfaction, emphasizing examples where biological components have been employed to detect gas-phase analytes.

Universal sensor array for highly selective system identification using two-dimensional nanoparticles

A typical lock-and-key sensing strategy, relying only on the most dominant interactions between the probe and target, could be too limiting. In reality, the information received upon sensing is much richer. Non-specific events due to various intermolecular forces contribute to the overall received information with different degrees, and when analyzed, could provide a much more powerful detection opportunity. Here, we have assembled a highly selective universal sensor array using water-soluble two-dimensional nanoparticles (nGO, MoS2 and WS2) and fluorescent DNA molecules. The array is composed of 12 fluorescently silent non-specific nanoreceptors (2D-nps) and used for the identification of three radically different systems; five proteins, three types of live breast cancer cells and a structure-switching event of a macromolecule. The data matrices for each system were processed using Partial Least Squares (PLS) discriminant analysis. In all of the systems, the sensor array was able to identify each object or event as separate clusters with 95% confidence and without any overlap. Out of 15 unknown entities with unknown protein concentrations tested, 14 of them were predicted successfully with correct concentration. 8 breast cancer cell samples out of 9 unknown entities from three cell types were predicted correctly. During the assembly of each nanoprobe, the intrinsic non-covalent interactions between unmodified 2D nanoparticles and ssDNAs were exploited. The unmodified 2D materials offer remarkable simplicity in the layout and the use of ssDNAs as probes provides limitless possibilities because the natural interaction of a ssDNA and 2D surface can be fine-tuned with the nucleobase composition, oligonucleotide length and type of 2D nanomaterial. Therefore, the approach described here can be advanced and fine-tuned indefinitely for meeting a particular sensing criterion. Though we have only studied three distinct elements, this approach is universal enough to be applied to a wide-range of systems.

Toward high value sensing: monolayer-protected metal nanoparticles in multivariable gas and vapor sensors

This review provides analysis of advances in multivariable sensors based on monolayer-protected nanoparticles and several principles of signal transduction that result in building non-resonant and resonant electrical sensors as well as material- and structure-based photonic sensors.

Synthesis, Characterization, and Functionalization of Hybrid Au/CdS and Au/ZnS Core/Shell Nanoparticles

Plasmonic nanoparticles are an attractive material for light harvesting applications due to their easily modified surface, high surface area and large extinction coefficients which can be tuned across the visible spectrum. Research into the plasmonic enhancement of optical transitions has become popular, due to the possibility of altering and in some cases improving photo-absorption or emission properties of nearby chromophores such as molecular dyes or quantum dots. The electric field of the plasmon can couple with the excitation dipole of a chromophore, perturbing the electronic states involved in the transition and leading to increased absorption and emission rates. These enhancements can also be negated at close distances by energy transfer mechanism, making the spatial arrangement of the two species critical. Ultimately, enhancement of light harvesting efficiency in plasmonic solar cells could lead to thinner and, therefore, lower cost devices. The development of hybrid core/shell particles could offer a solution to this issue. The addition of a dielectric spacer between a gold nanoparticles and a chromophore is the proposed method to control the exciton plasmon coupling strength and thereby balance losses with the plasmonic gains. A detailed procedure for the coating of gold nanoparticles with CdS and ZnS semiconductor shells is presented. The nanoparticles show high uniformity with size control in both the core gold particles and shell species allowing for a more accurate investigation into the plasmonic enhancement of external chromophores.