Quantum Plexcitonic Sensing

While fundamental to quantum sensing, quantum state control has been traditionally limited to extreme conditions. This restricts the impact of the practical implementation of quantum sensing on a broad range of physical measurements. Plexcitons, however, provide a promising path under ambient conditions toward quantum state control and thus quantum sensing, owing to their origin from strong plasmon-exciton coupling. Herein, we harness plexcitons to demonstrate quantum plexcitonic sensing by strongly coupling excitonic particles to a plasmonic hyperbolic metasurface. As compared to classical sensing in the weak-coupling regime, our model of quantum plexcitonic sensing performs at a level that is ∼40 times more sensitive. Noise-modulated sensitivity studies reinforce the quantum advantage over classical sensing, featuring better sensitivity, smaller sensitivity uncertainty, and higher resilience against optical noise. The successful demonstration of quantum plexcitonic sensing opens the door for a variety of physical, chemical, and biological measurements by leveraging strongly coupled plasmon-exciton systems.

Pyramidal hyperbolic metasurfaces enhance spontaneous emission of nitrogen-vacancy centers in nanodiamond

Nitrogen-vacancy (NV) centers in nanodiamond hold great promise for creating superior biological labels and quantum sensing methods. Yet, inefficient photon generation and extraction from excited NV centers restricts the achievable sensitivity and temporal resolution. Herein, we report an entirely complementary route featuring pyramidal hyperbolic metasurface to modify the spontaneous emission of NV centers. Fabricated using nanosphere lithography, the metasurface consists of alternatively stacked silica-silver thin films configured in a pyramidal fashion, and supports both spectrally broadband Purcell enhancement and spatially extended intense local fields owing to the hyperbolic dispersion and plasmonic coupling. The enhanced photophysical properties are manifested as a simultaneous amplification to the spontaneous decay rate and emission intensity of NV centers. We envision the reported pyramidal metasurface could serve as a versatile platform for creating chip-based ultrafast single-photon sources and spin-enhanced quantum biosensing strategies, as well as aiding in further fundamental understanding of photoexcited species in condensed phases.

Deep Learning Image Analysis of Nanoplasmonic Sensors: Toward Medical Breath Monitoring

Sensing biomarkers in exhaled breath offers a potentially portable, cost-effective, and noninvasive strategy for disease diagnosis screening and monitoring, while high sensitivity, wide sensing range, and target specificity are critical challenges. We demonstrate a deep learning-assisted plasmonic sensing platform that can detect and quantify gas-phase biomarkers in breath-related backgrounds of varying complexity. The sensing interface consisted of Au/SiO₂ nanopillars covered with a 15 nm metal-organic framework. A small camera was utilized to capture the plasmonic sensing responses as images, which were subjected to deep learning signal processing. The approach has been demonstrated at a classification accuracy of 95 to 98% for the diabetic ketosis marker acetone within a concentration range of 0.5-80 μmol/mol. The reported work provides a thorough exploration of single-sensor capabilities and sets the basis for more advanced utilization of artificial intelligence in sensing applications.

Plasmonic Sensing Studies of a Gas-Phase Cystic Fibrosis Marker in Moisture Laden Air

A plasmonic sensing platform was developed as a noninvasive method to monitor gas-phase biomarkers related to cystic fibrosis (CF). The nanohole array (NHA) sensing platform is based on localized surface plasmon resonance (LSPR) and offers a rapid data acquisition capability. Among the numerous gas-phase biomarkers that can be used to assess the lung health of CF patients, acetaldehyde was selected for this investigation. Previous research with diverse types of sensing platforms, with materials ranging from metal oxides to 2-D materials, detected gas-phase acetaldehyde with the lowest detection limit at the µmol/mol (parts-per-million (ppm)) level. In contrast, this work presents a plasmonic sensing platform that can approach the nmol/mol (parts-per-billion (ppb)) level, which covers the required concentration range needed to monitor the status of lung infection and find pulmonary exacerbations. During the experimental measurements made by a spectrometer and by a smartphone, the sensing examination was initially performed in a dry air background and then with high relative humidity (RH) as an interferent, which is relevant to exhaled breath. At a room temperature of 23.1 °C, the lowest detection limit for the investigated plasmonic sensing platform under dry air and 72% RH conditions are 250 nmol/mol (ppb) and 1000 nmol/mol (ppb), respectively.

Conformational Changes of Immobilized Polythymine due to External Stressors Studied with Temperature-Controlled Electrochemical Microdevices

Conformational changes of single-stranded DNA (ssDNA) play an important role in a DNA strand's ability to bind to target ligands. A variety of factors can influence conformation, including temperature, ionic strength, pH, buffer cation valency, strand length, and sequence. To better understand the effects of these factors on immobilized DNA structures, we employ temperature-controlled electrochemical microsensors to study the effects of salt concentration and temperature variation on the conformation and motion of polythymine (polyT) strands of varying lengths (10, 20, 50 nucleotides). PolyT strands were tethered to a gold working electrode at the proximal end through a thiol linker via covalent bonding between the Au electrode and sulfur link, which can tend to decompose between a temperature range of 60 and 90 °C. The strands were also modified with an electrochemically active methylene blue (MB) moiety at the distal end. Electron transfer (eT) was measured by square wave voltammetry (SWV) and used to infer information pertaining to the average distance between the MB and the working electrode. We observe changes in DNA flexibility due to varying ionic strength, while the effects of increased DNA thermal motion are tracked for elevated temperatures. This work elucidates the behavior of ssDNA in the presence of a phosphate-buffered saline at NaCl concentrations ranging from 20 to 1000 mmol/L through a temperature range of 10-50 °C in 1° increments, well below the decomposition temperature range. The results lay the groundwork for studies on more complex DNA strands in conjunction with different chemical and physical conditions.

Composite-Scattering Plasmonic Nanoprobes for Label-Free, Quantitative Biomolecular Sensing

Biosensing based on localized surface plasmon resonance (LSPR) relies on concentrating light to a nanometeric spot and leads to a highly enhanced electromagnetic field near the metal nanostructure. Here, a design of plasmonic nanostructures based on rationally structured metal-dielectric combinations is presented, called composite scattering probes (CSPs), to generate an integrated multimodal biosensing platform featuring LSPR and surface-enhanced Raman spectroscopy (SERS). Specifically, CSP configurations are proposed, which have several prominent resonance peaks enabling higher tunability and sensitivity for self-referenced multiplexed analyte sensing. Using electron-beam evaporation and thermal dewetting, large-area, uniform, and tunable CSPs are fabricated, which are suitable for label-free LSPR and SERS measurements. The CSP prototypes are used to demonstrate refractive index sensing and molecular analysis using albumin as a model analyte. By using partial least squares on recorded absorption profiles, differentiation of subtle changes in refractive index (as low as 0.001) in the CSP milieu is demonstrated. Additionally, CSPs facilitate complementary untargeted plasmon-enhanced Raman measurements from the sample's compositional contributors. With further refinement, it is envisioned that the method may lead to a sensitive, versatile, and tunable platform for quantitative concentration determination and molecular fingerprinting, particularly where limited a priori information of the sample is available.

Miniaturized nanohole array based plasmonic sensor for the detection of acetone and ethanol with insights into the kinetics of adsorptive plasmonic sensing

The present work demonstrates development of a miniaturized plasmonic platform comprised of a Au nanohole array (NHA) on a Si/Si3N4 substrate. Plasmonic responses of the NHA platform, which is coated with Cu-benzenetricarboxylate metal organic framework (MOF), are found to be promising even towards 500 nmol mol-1 (ppb) of acetone or ethanol vapors at room temperature. The sensing characteristics are further investigated by varying the operating temperature (296 K to 318 K) of the sensor and the concentrations of vapors (500 nmol mol-1 to 320 μmol mol-1). The plasmonic responses for the sensors are correlated with the adsorption of vapors on the MOF surface and modeled in accordance to Langmuir-type adsorption. Kinetic parameters are estimated for the adsorption of fixed concentrations of acetone and ethanol vapors within the studied operating temperature range. The linear variation of characteristic response time constants with the operating temperature provides Arrhenius activation energies for the adsorption of acetone and ethanol vapors. The comparatively lower activation energy estimated for the adsorption of ethanol results in faster and more sensitive response of the sensor towards that analyte. The plasmonic sensor for the detection of nmol mol-1 level acetone and ethanol vapors at room temperature along with the kinetic correlation on plasmonic response with the adsorption of the analytes described herein offer new insights to existing reports on surface modification and plasmonic detection.

The I/O transform of a chemical sensor

A number of sensing technologies, using a variety of transduction principles, have been proposed for non-invasive chemical sensing. A fundamental problem common to all these sensing technologies is determining what features of the transducer's signal constitute a chemical fingerprint that allows for precise analyte recognition. Of particular importance is the need to extract features that are robust with respect to the sensor's age or stimulus intensity. Here, using pulsed stimulus delivery, we show that a sensor's operation can be modeled as a linear input-output (I/O) transform. The I/O transform is unique for each analyte and can be used to precisely predict a temperature-programmed chemiresistor's response to the analyte given the recent stimulus history (i.e. state of an analyte delivery valve being open or closed). We show that the analyte specific I/O transforms are to a certain degree stimulus intensity invariant and can remain consistent even when the sensor has undergone considerable aging. Significantly, the I/O transforms for a given analyte are highly conserved across sensors of equal manufacture, thereby allowing training data obtained from one sensor to be used for recognition of the same set of chemical species with another sensor. Hence, this proposed approach facilitates decoupling of the signal processing algorithms from the chemical transducer, a key advance necessary for achieving long-term, non-invasive chemical sensing.

Gas Sensing with Bare and Graphene-covered Optical Nano-Antenna Structures

The motivation behind this work is to study the gas phase chemical sensing characteristics of optical (plasmonic) nano-antennas (ONA) and graphene/graphene oxide-covered versions of these structures. ONA are devices that have their resonating frequency in the visible range. The basic principle governing the detection mechanism for ONA is refractive index sensing. The change in the concentration of the analyte results in a differing amount of adsorbate and correlated shifts in the resonance wavelength of the device. In this work, bare and graphene or graphene oxide covered ONA have been evaluated for gas sensing performance. Four different analytes (ethanol, acetone, nitrogen dioxide and toluene) were used in testing. ONA response behavior to different analytes was modified by adsorption within the graphene and graphene oxide overlayers. This work is a preliminary study to understand resonance wavelength shift caused by different analytes. Results imply that the combination of well-structured ONA functionalized by graphene-based adsorbers can give sensitive and selective sensors but baseline drift effects identified in this work must be addressed for applied measurements.

Demonstration of fast and accurate discrimination and quantification of chemically similar species utilizing a single cross-selective chemiresistor

Performance characteristics of gas-phase microsensors will determine the ultimate utility of these devices for a wide range of chemical monitoring applications. Commonly employed chemiresistor elements are quite sensitive to selected analytes, and relatively new methods have increased the selectivity to specific compounds, even in the presence of interfering species. Here, we have focused on determining whether purposefully driven temperature modulation can produce faster sensor-response characteristics, which could enable measurements for a broader range of applications involving dynamic compositional analysis. We investigated the response speed of a single chemiresitive In2O3 microhotplate sensor to four analytes (methanol, ethanol, acetone, 2-butanone) by systematically varying the oscillating frequency (semicycle periods of 20-120 ms) of a bilevel temperature cycle applied to the sensing element. It was determined that the fastest response (≈ 9 s), as indicated by a 98% signal-change metric, occurred for a period of 30 ms and that responses under such modulation were dramatically faster than for isothermal operation of the same device (>300 s). Rapid modulation between 150 and 450 °C exerts kinetic control over transient processes, including adsorption, desorption, diffusion, and reaction phenomena, which are important for charge transfer occurring in transduction processes and the observed response times. We also demonstrate that the fastest operation is accompanied by excellent discrimination within a challenging 16-category recognition problem (consisting of the four analytes at four separate concentrations). This critical finding demonstrates that both speed and high discriminatory capabilities can be realized through temperature modulation.

Effect of interdome spacing on the resonance properties of plasmonic nanodome arrays for label-free optical sensing

In this paper, we report on experimental and theoretical studies that investigate how the structural properties of plasmonic nanodome array devices determine their optical properties and sensing performance. We examined the effect of the interdome gap spacing within the plasmonic array structures on the performance for detection of change in local refractive index environment for label-free capture affinity biosensing applications. Optical sensing properties were characterized for nanodome array devices with interdome spacings of 14 nm, 40 nm, and 79 nm, as well as for a device where adjacent domes are in contact. For each interdome spacing, the extinction spectrum was measured using a broadband reflection instrumentation, and finite-difference-time-domain (FDTD) simulation was used to model the local electric field distribution associated with the resonances. Based on these studies, we predict that nanodome array devices with gap between 14 nm to 20 nm provide optimal label-free capture affinity biosensing performances, where the dipole resonance mode exhibits the highest overall surface sensitivity, as well as the lowest limit of detection.

Multi-resonant plasmonic nanodome arrays for label-free biosensing applications

The characteristics and utility of plasmonic nanodome arrays capable of supporting multiple resonance modes are described. A low-cost, large-area replica molding process is used to produce, on flexible plastic substrates, two-dimensional periodic arrays of cylinders that are subsequently coated with SiO2 and Ag thin films to form dome-shaped structures, with 14 nm spacing between the features, in a precise and reproducible fashion. Three distinct optical resonance modes, a grating diffraction mode and two localized surface plasmon resonance (LSPR) modes, are observed experimentally and confirmed by finite-difference-time-domain (FDTD) modeling which is used to calculate the electromagnetic field distribution of each resonance around the nanodome array structure. Each optical mode is characterized by measuring sensitivity to bulk refractive index changes and to surface effects, which are examined using stacked polyelectrolyte layers. The utility of the plasmonic nanodome array as a functional interface for biosensing applications is demonstrated by performing a bioassay to measure the binding affinity constant between protein A and human immunoglobulin G (IgG) as a model system. The nanoreplica molding process presented in this work allows for simple, inexpensive, high-throughput fabrication of nanoscale plasmonic structures over a large surface area (120 × 120 mm(2)) without the requirement for high resolution lithography or additional processes such as etching or liftoff. The availability of multiple resonant modes, each with different optical properties, allows the nanodome array surface to address a wide range of biosensing problems with various target analytes of different sizes and configurations.

Machine learning applied to chemical analysis: sensing multiple biomarkers in simulated breath using a temperature-pulsed electronic-nose

Monitoring of chemical species in breath offers an approach for the detection of disease and other conditions that cause homeostatic imbalance. Here, we demonstrate the use of microsensor-based devices for detecting select biomarkers in simulated exhaled breath as a step toward enabling fast and inexpensive breath-screening technology. Microhotplate elements functionalized with three chemiresistive metal-oxide films (SnO(2), In(2)O(3), and CuO) were used to acquire data in simulated breath containing single targets [(5 to 20) μmol/mol ammonia, methanol, and acetone], as well as mixtures of those species. All devices were operated with programmed thermal cycles featuring rapid temperature excursions, during which film resistances were measured. Material-specific temperature programs were optimized to achieve temperature-dependent metal-oxide sensing film conductance levels and target selectivity. A supervised hierarchical machine-learning algorithm using linear discriminant analysis for dimensional reduction of sensing data and discrimination was developed. This algorithm was employed in the classification and quantification of biomarkers. This approach to microsensor data collection and processing was successful in classifying and quantifying the model biomarkers in validation-set mixtures.

Signal-on electrochemical Y or junction probe detection of nucleic acid

A methylene-blue (MB)-labeled molecular beacon junction probe allows for a signal-on electrochemical detection of nucleic acids via target recycling using endonucleases. Electron transfer is reduced when the MB is intercalated in the stem of the molecular beacon, but then electron transfer from MB to a gold electrode is enhanced upon cleavage of the junction probe due to increased probability of MB approaching the electrode when attached to the more flexible ssDNA.

Mimicking biological design and computing principles in artificial olfaction

Biology has inspired solutions to many engineering problems, including chemical sensing. Modern approaches to chemical sensing have been based on the biological principle of combining cross-selective chemical sensors with a pattern recognition engine to identify odors. Here, we review some recent advances made in mimicking biological design and computing principles to develop an electronic nose. The resulting technology will have important applications in fundamental biological research, as well as in industrial, security, and medical domains.

MOCVD OF SnO2 on Silicon Microhotplate Arrays for use un Gas Sensing Applications

The quantitative detection of gas concentrations in mixed atmospheres is becoming increasingly important in manufacturing processing, environmental monitoring, and medical diagnostics. Several conductive oxides, such as SnO2, ZnO, and TiO2, are well known to exhibit changes in resistivity when exposed to various gases at temperatures ranging from 200–500°C. Current discrete devices based on resistive changes such as the Taguchi sensor, however, suffer from certain performance problems, including poor gas detection specificity. Integrated arrays of sensors, fabricated using planar technology, offer a promising solution to these problems, as well as other benefits such as low power consumption and low cost.

In this paper, we report the results of using Metalorganic Chemical Vapor Deposition (MOCVD) to fabricate thin films of SnO2 on microhotplate arrays. The studied arrays contain 4 micromachined, suspended elements, each having an integrated resistive heater that produces a rapid thermal rise time ∼3 msec. By separately heating individual elements, we can take advantage of the thermally selective nature of the MOCVD process to limit deposition to these areas, resulting in a maskless deposition process. In addition, these array elements have surface electrical contacts that permit the measurement of the resistance of the thin films during deposition, as well as when they are operated in a gas sensing mode. In situ growth measurements will be reported.

Micromachined Array Studies of Tin Oxide Films: Nucleation, Structure and Gas Sensing Characteristics

The ability to fabricate sensitive and stable gas sensors which can detect low concentrations of gaseous species is necessary for many critical applications such as environmental safety monitoring. Although highly sensitive gas sensors have been produced by dispersion of catalytic metals on oxide sensing films, fouling of catalysts can cause instability in sensor performance. We have examined an approach which involves fine tuning the microstructure of tin oxide sensing films by vapor depositing an ultra-thin film of seed layer metals prior to tin oxide deposition. Metals including Fe, Sn and Pt have been investigated for their influence on tin oxide growth. Systematic studies of the growth mechanism and microstructure of CVD tin oxide using four-element arrays of “microhotplates” have revealed a number of different film morphologies which result from seeding. Enhancements in sensitivity for seeded growth relative to unseeded growth suggest a method of producing sensitive gas sensors which may not require the addition of surface catalytic layers. In this study we also demonstrate the use of microhotplates not only as sensing devices, but as excellent platforms for materials research.

Detecting chemical hazards with temperature-programmed microsensors: overcoming complex analytical problems with multidimensional databases

Complex analytical problems, such as detecting trace quantities of hazardous chemicals in challenging environments, require solutions that most effectively extract relevant information about a sample's composition. This review presents a chemiresistive microarray-based approach to identifying targets that combines temperature-programmed elements capable of rapidly generating analytically rich data sets with statistical pattern recognition algorithms for extracting multivariate chemical fingerprints. We describe the chemical-microsensor platform and discuss its ability to generate orthogonal data through materials selection and temperature programming. Visual inspection of data sets reveals device selectivity, but statistical analyses are required to perform more complex identification tasks. Finally, we discuss recent advances in both devices and algorithms necessary to deal with practical issues involved in long-term deployment. These issues include identification and correction of signal drift, challenges surrounding real-time unsupervised operation, repeatable device manufacturability, and hierarchical classification schemes designed to deduce the chemical composition of untrained analyte species.

Bioinspired methodology for artificial olfaction

Artificial olfaction is a potential tool for noninvasive chemical monitoring. Application of "electronic noses" typically involves recognition of "pretrained" chemicals, while long-term operation and generalization of training to allow chemical classification of "unknown" analytes remain challenges. The latter analytical capability is critically important, as it is unfeasible to pre-expose the sensor to every analyte it might encounter. Here, we demonstrate a biologically inspired approach where the recognition and generalization problems are decoupled and resolved in a hierarchical fashion. Analyte composition is refined in a progression from general (e.g., target is a hydrocarbon) to precise (e.g., target is ethane), using highly optimized response features for each step. We validate this approach using a MEMS-based chemiresistive microsensor array. We show that this approach, a unique departure from existing methodologies in artificial olfaction, allows the recognition module to better mitigate sensor-aging effects and to better classify unknowns, enhancing the utility of chemical sensors for real-world applications.

Porous tin oxide nanostructured microspheres for sensor applications

We have sought to enhance the sensitivity of conductometric gas microsensors through the design and fabrication of porous, three-dimensional tin oxide nanoparticle structures. Electrostatically controlled layer-by-layer processing in aqueous solutions was used to decorate sacrificial latex microspheres with Sb:SnO2 nanoparticles. To evaluate their sensing performance, these structures were then deposited as films, via micropipetting, on MEMS micro-hot-plate platforms with interdigitated electrodes. Prior to gas testing, rapid heating of the micro-hot-plates was used to remove the sacrificial latex templates, thereby revealing a 3-D structure composed of interconnected spherical tin oxide nanoparticle shells with porous ultrathin walls. Changes in film conductance, caused by exposure to test gases (methanol, carbon monoxide, benzene, water) in a dry air background, were measured at different temperatures. Hollow nanoparticle microsphere films exhibited partial selectivity for these different gases, good dynamic range at different temperatures and gas concentrations, and good repeatability and stability over long runs. These films also yielded approximately 3-fold and 5-fold increases in sensitivity to methanol when compared to SnO2 polycrystalline chemical vapor deposition films and Sb:SnO2 microporous nanoparticle films, respectively. Gains in sensitivity are attributed to the multiscale porous architecture of the hollow microsphere films. This architecture promotes gas diffusion and increases the active surface area.

Controlled Electrophoretic Patterning of Polyaniline from a Colloidal Suspension

We present a method for controlled deposition of polyaniline from colloidal suspensions. Stable suspensions of polyaniline colloids (approximately 115 nm in diameter) were formed by dispersing polyaniline/formic acid solution into acetonitrile. It was demonstrated that the positively charged polyaniline colloids can be electrophoretically deposited onto various substrate materials such as platinum and ITO, forming continuous ultrathin films. We examined the film morphology, as well as the effects of process parameters, such as deposition time, colloid concentration, and applied voltage, on the deposition efficiency. Furthermore, the efficacy of the technique was illustrated by electrophoretically patterning polyaniline thin films onto selected individual micrometer-scale sensing elements within a microfabricated sensor array, and by further demonstrating its sensitivity to gaseous analytes including water and methanol.

Thermolithographic Patterning of Sol−Gel Metal Oxides on Micro Hot Plate Sensing Arrays Using Organosilanes

Sol-gel-derived SnO2 and Fe2O3 were selectively deposited on elements of micro hot plate (microHP) arrays. The silicon micromachined microHP arrays contain heating elements (100 microm x 100 microm) that are electronically addressable and thermally isolated from each other. Thin films of (tridecafluoro-1,1,2,2-tetrahydrooctyl)trichlorosilane (TFS) or hexyltrichlorosilane (HFS) assembled on surfaces of the arrays served as thermally sensitive resists whereby heating of specific microHPs resulted in removal of organosilane films only in heated areas. TFS-masked surfaces were characterized with condensation figures and secondary ion mass spectrometry (SIMS) imaging. TFS was removed from regions heated above 400 degrees C to expose hydrophilic surfaces, while TFS films in unheated areas were unaffected and remained hydrophobic. Sol-gel tin oxide spin-coated on the thermally patterned arrays adhered only to the hydrophilic regions and was repelled from the hydrophobic areas masked by the TFS films. By using HFS films, it was possible to selectively deposit two sol-gel materials, SnO2 and Fe2O3, on different microHPs in the same array as confirmed by SIMS imaging. Both materials showed varying degrees of electrical response to hydrogen and methanol in gas-sensing measurements.