Nanomechanical membrane-type surface stress sensor

Lung cancer detection in perioperative patients' exhaled breath with nanomechanical sensor array

INTRODUCTION

Breath analysis using a chemical sensor array combined with machine learning algorithms may be applicable for detecting and screening lung cancer. In this study, we examined whether perioperative breath analysis can predict the presence of lung cancer using a Membrane-type Surface stress Sensor (MSS) array and machine learning.

METHODS

Patients who underwent lung cancer surgery at an academic medical center, Japan, between November 2018 and November 2019 were included. Exhaled breaths were collected just before surgery and about one month after surgery, and analyzed using an MSS array. The array had 12 channels with various receptor materials and provided 12 waveforms from a single exhaled breath sample. Boxplots of the perioperative changes in the expiratory waveforms of each channel were generated and Mann-Whitney U test were performed. An optimal lung cancer prediction model was created and validated using machine learning.

RESULTS

Sixty-six patients were enrolled of whom 57 were included in the analysis. Through the comprehensive analysis of the entire dataset, a prototype model for predicting lung cancer was created from the combination of array five channels. The optimal accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were 0.809, 0.830, 0.807, 0.806, and 0.812, respectively.

CONCLUSION

Breath analysis with MSS and machine learning with careful control of both samples and measurement conditions provided a lung cancer prediction model, demonstrating its capacity for non-invasive screening of lung cancer.

Sorption Kinetic Parameters from Nanomechanical Sensing for Discrimination of 2-Nonenal from Saturated Aldehydes

Nanomechanical sensors have gained significant attention as promising platforms for artificial olfaction. Since sorption kinetic parameters that can be estimated from the sensing signals of nanomechanical sensors reflect the chemical and physicochemical interactions between the odorant and receptor material, the parameters can be utilized for the direct discrimination of each odorant. In this study, we demonstrated the discrimination of 20 vapors, including hydrocarbons, alcohols, organic acids, ketones, and aldehydes, which are reported as human body odor components, using the parameters extracted in the analytical solution of nanomechanical sensors based on sorption kinetics with viscoelastic behaviors. By using one of the specific nanomechanical sensors─membrane-type surface stress sensor─as a sensing unit, we successfully discriminated trans-2-nonenal known as an aging marker from other saturated aldehydes along with quantifying their concentrations.

Polymer Ring-Flexure-Membrane Suspended Gate FET Gas Sensor: Design, Modelling and Simulation

This work reports the design, modelling, and simulation of a novel polymer MEMS gas sensor platform called a ring-flexure-membrane (RFM) suspended gate field effect transistor (SGFET). The sensor consists of a suspended polymer (SU-8) MEMS based RFM structure holding the gate of the SGFET with the gas sensing layer on top of the outer ring. During gas adsorption, the polymer ring-flexure-membrane architecture ensures a constant gate capacitance change throughout the gate area of the SGFET. This leads to efficient transduction of the gas adsorption-induced nanomechanical motion input to the change in the output current of the SGFET, thus improving the sensitivity. The sensor performance has been evaluated for sensing hydrogen gas using the finite element method (FEM) and TCAD simulation tools. The MEMS design and simulation of the RFM structure is carried out using CoventorWare 10.3, and the design, modelling, and simulation of the SGFET array is carried out using the Synopsis Sentaurus TCAD. A differential amplifier circuit using RFM-SGFET is designed and simulated in Cadence Virtuoso using the lookup table (LUT) of the RFM-SGFET. The differential amplifier exhibits a sensitivity of 2.8 mV/MPa for a gate bias of 3 V and a maximum detection range of up to 1% hydrogen gas concentration. This work also presents a detailed fabrication process integration plan to realize the RFM-SGFET sensor using a tailored self-aligned CMOS process adopting the surface micromachining process.

Repetitive Direct Comparison Method for Odor Sensing

Olfactory sensors are one of the most anticipated applications of gas sensors. To distinguish odors-complex mixtures of gas species, it is necessary to extract sensor responses originating from the target odors. However, the responses of gas sensors tend to be affected by interfering gases with much higher concentrations than target odor molecules. To realize practical applications of olfactory sensors, extracting minute sensor responses of odors from major interfering gases is required. In this study, we propose a repetitive direct comparison (rDC) method, which can highlight the difference in odors by alternately injecting the two target odors into a gas sensor. We verified the feasibility of the rDC method on chocolates with two different flavors by using a sensor system based on membrane-type surface stress sensors (MSS). The odors of the chocolates were measured by the rDC method, and the signal-to-noise ratios (S/N) of the measurements were evaluated. The results showed that the rDC method achieved improved S/N compared to a typical measurement. The result also indicates that sensing signals could be enhanced for a specific combination of receptor materials of MSS and target odors.

Measurement of Volatile Fatty Acids in Silage through Odors with Nanomechanical Sensors

The measurement of volatile fatty acids (VFAs) is of great importance in the fields of food and agriculture. There are various methods to measure VFAs, but most methods require specific equipment, making on-site measurements difficult. In this work, we demonstrate the measurements of VFAs in a model sample, silage, through its vapor using an array of nanomechanical sensors-Membrane-type Surface stress Sensors (MSS). Focusing on relatively slow desorption behaviors of VFAs predicted with the sorption kinetics of nanomechanical sensing and the dissociation nature of VFAs, the VFAs can be efficiently measured by using features extracted from the decay curves of the sensing response, resulting in sufficient discrimination of the silage samples. Since the present sensing system does not require expensive, bulky setup and pre-treatment of samples, it has a great potential for practical applications including on-site measurements.

Detection of Trace Amounts of Water in Organic Solvents by DNA-Based Nanomechanical Sensors

The detection of trace amounts of water in organic solvents is of great importance in the field of chemistry and in the industry. Karl Fischer titration is known as a classic method and is widely used for detecting trace amounts of water; however, it has some limitations in terms of rapid and direct detection because of its time-consuming sample preparation and specific equipment requirements. Here, we found that a DNA-based nanomechanical sensor exhibits high sensitivity and selectivity to water vapor, leading to the detection and quantification of trace amounts of water in organic solvents as low as 12 ppm in THF, with a ppb level of LoD through their vapors. Since the present method is simple and rapid, it can be an alternative technique to the conventional Karl Fischer titration.

Recent Advances in Nanomechanical Membrane-Type Surface Stress Sensors towards Artificial Olfaction

Nanomechanical sensors have gained significant attention as powerful tools for detecting, distinguishing, and identifying target analytes, especially odors that are composed of a complex mixture of gaseous molecules. Nanomechanical sensors and their arrays are a promising platform for artificial olfaction in combination with data processing technologies, including machine learning techniques. This paper reviews the background of nanomechanical sensors, especially conventional cantilever-type sensors. Then, we focus on one of the optimized structures for static mode operation, a nanomechanical Membrane-type Surface stress Sensor (MSS), and discuss recent advances in MSS and their applications towards artificial olfaction.

Mechano-Nanoarchitectonics: Design and Function

Mechanical stimuli have rather ambiguous and less-specific features among various physical stimuli, but most materials exhibit a certain level of responses upon mechanical inputs. Unexplored sciences remain in mechanical responding systems as one of the frontiers of materials science. Nanoarchitectonics approaches for mechanically responding materials are discussed as mechano-nanoarchitectonics in this review article. Recent approaches on molecular and materials systems with mechanical response capabilities are first exemplified with two viewpoints: i) mechanical control of supramolecular assemblies and materials and ii) mechanical control and evaluation of atom/molecular level structures. In the following sections, special attentions on interfacial environments for mechano-nanoarchitectonics are emphasized. The section entitled iii) Mechanical Control of Molecular System at Dynamic Interface describes coupling of macroscopic mechanical forces and molecular-level phenomena. Delicate mechanical forces can be applied to functional molecules embedded at the air-water interface where operation of molecular machines and tuning of molecular receptors upon macroscopic mechanical actions are discussed. Finally, the important role of the interfacial media are further extended to the control of living cells as described in the section entitled iv) Mechanical Control of Biosystems. Pioneering approaches on cell fate regulations at liquid-liquid interfaces are discussed in addition to well-known mechanobiology.

2-step reaction kinetics for hydrogen absorption into bulk material via dissociative adsorption on the surface

We have demonstrated that the process of hydrogen absorption into a solid experimentally follows a Langmuir-type (hyperbolic) function instead of Sieverts law. This can be explained by independent two theories. One is the well-known solubility theory which is the basis of Sieverts law. It explains that the amount of hydrogen absorption can be expressed as a Langmuir-type (hyperbolic) function of the square root of the hydrogen pressure. We have succeeded in drawing the same conclusion from the other theory. It is a 2-step reaction kinetics (2sRK) model that expresses absorption into the bulk via adsorption on the surface. The 2sRK model has an advantage to the solubility theory: Since it can describe the dynamic process, it can be used to discuss both the amount of hydrogen absorption and the absorption rate. Some phenomena with absorption via adsorption can be understood in a unified manner by the 2sRK model.

Odor-Based Nanomechanical Discrimination of Fuel Oils Using a Single Type of Designed Nanoparticles with Nonlinear Viscoelasticity

Odors are one of the most diverse and complicated gaseous mixtures so that their discrimination is challenging yet attractive because of the rich information about their origin. The more similar the properties of odors are, the more difficult the discrimination becomes. The practical applications, however, often demand such discrimination, especially with a compact sensing platform. In this paper, we show that a nanomaterial designed for a specific type of odors can clearly discriminate them even with a single nanomechanical sensing channel. Fuel oils and their mixture are used as a model target that has similar chemical properties but different compositions mainly consisting of paraffinic, olefinic, naphthenic, and aromatic hydrocarbons. We demonstrate using octadecyl functionalized silica-titania nanoparticles that the difference in the compositions is successfully picked up based on their high affinity for the aliphatic hydrocarbons and alkyl chain length dependent nonlinear viscoelastic behavior. Such a properly designed material is proved to derive sufficient information from a series of analytes to discriminate them even with a single sensing element. This approach provides a guideline to prepare various sensors whose response properties are distinct and optimized depending on applications.

Principles of odor coding in vertebrates and artificial chemosensory systems

The biological olfactory system is the sensory system responsible for the detection of the chemical composition of the environment. Several attempts to mimic biological olfactory systems have led to various artificial olfactory systems using different technical approaches. Here we provide a parallel description of biological olfactory systems and their technical counterparts. We start with a presentation of the input to the systems, the stimuli, and treat the interface between the external world and the environment where receptor neurons or artificial chemosensors reside. We then delineate the functions of receptor neurons and chemosensors as well as their overall I-O relationships. Up to this point, our account of the systems goes along similar lines. The next processing steps differ considerably: while in biology the processing step following the receptor neurons is the "integration" and "processing" of receptor neuron outputs in the olfactory bulb, this step has various realizations in electronic noses. For a long period of time, the signal processing stages beyond the olfactory bulb, i.e., the higher olfactory centers were little studied. Only recently there has been a marked growth of studies tackling the information processing in these centers. In electronic noses, a third stage of processing has virtually never been considered. In this review, we provide an up-to-date overview of the current knowledge of both fields and, for the first time, attempt to tie them together. We hope it will be a breeding ground for better information, communication, and data exchange between very related but so far little connected fields.

Statistical Evaluation of Total Expiratory Breath Samples Collected throughout a Year: Reproducibility and Applicability toward Olfactory Sensor-Based Breath Diagnostics

The endogenous volatile organic compounds (VOCs) in exhaled breath can be promising biomarkers for various diseases including cancers. An olfactory sensor has a possibility for extracting a specific feature from collective variations of the related VOCs with a certain health condition. For this approach, it is important to establish a feasible protocol for sampling exhaled breath in practical conditions to provide reproducible signal features. Here we report a robust protocol for the breath analysis, focusing on total expiratory breath measured by a Membrane-type Surface stress Sensor (MSS), which possesses practical characteristics for artificial olfactory systems. To assess its reproducibility, 83 exhaled breath samples were collected from one subject throughout more than a year. It has been confirmed that the reduction of humidity effects on the sensing signals either by controlling the humidity of purging room air or by normalizing the signal intensities leads to reasonable reproducibility verified by statistical analyses. We have also demonstrated the applicability of the protocol for detecting a target material by discriminating exhaled breaths collected from different subjects with pre- and post-alcohol ingestion on different occasions. This simple yet reproducible protocol based on the total expiratory breath measured by the MSS olfactory sensors will contribute to exploring the possibilities of clinical applications of breath diagnostics.

Determination of quasi-primary odors by endpoint detection

It is known that there are no primary odors that can represent any other odors with their combination. Here, we propose an alternative approach: "quasi" primary odors. This approach comprises the following condition and method: (1) within a collected dataset and (2) by the machine learning-based endpoint detection. The quasi-primary odors are selected from the odors included in a collected odor dataset according to the endpoint score. While it is limited within the given dataset, the combination of such quasi-primary odors with certain ratios can reproduce any other odor in the dataset. To visually demonstrate this approach, the three quasi-primary odors having top three high endpoint scores are assigned to the vertices of a chromaticity triangle with red, green, and blue. Then, the other odors in the dataset are projected onto the chromaticity triangle to have their unique colors. The number of quasi-primary odors is not limited to three but can be set to an arbitrary number. With this approach, one can first find "extreme" odors (i.e., quasi-primary odors) in a given odor dataset, and then, reproduce any other odor in the dataset or even synthesize a new arbitrary odor by combining such quasi-primary odors with certain ratios.

Multimodal real-time frequency tracking of cantilever arrays in liquid environment for biodetection: Comprehensive setup and performance analysis

We present a nanomechanical platform for real-time quantitative label-free detection of target biomolecules in a liquid environment with mass sensitivity down to few pg. Newly fabricated arrays of up to 18 cantilevers are integrated in a micromachined fluidic chamber, connected to software-controlled fluidic pumps for automated sample injections. We discuss two functionalization approaches to independently sensitize the interface of different cantilevers. A custom piezo-stack actuator and optical readout system enable the measurement of resonance frequencies up to 2 MHz. We implement a new measurement strategy based on a phase-locked loop (PLL), built via in-house developed software. The PLL allows us to track, within the same experiment, the evolution of resonance frequency over time of up to four modes for all the cantilevers in the array. With respect to the previous measurement technique, based on standard frequency sweep, the PLL enhances the estimated detection limit of the device by a factor of 7 (down to 2 pg in 5 min integration time) and the time resolution by more than threefold (below 15 s), being on par with commercial gold-standard techniques. The detection limit and noise of the new setup are investigated via Allan deviation and standard deviation analysis, considering different resonance modes and interface chemistries. As a proof-of-concept, we show the immobilization and label-free in situ detection of live bacterial cells (E. coli), demonstrating qualitative and quantitative agreement in the mechanical response of three different resonance modes.

Development of a Mobile Device for Odor Identification and Optimization of Its Measurement Protocol Based on the Free-Hand Measurement

Practical applications of machine olfaction have been eagerly awaited. A free-hand measurement, in which a measurement device is manually exposed to sample odors, is expected to be a key technology to realize practical machine olfaction. To implement odor identification systems based on the free-hand measurement, the comprehensive development of a measurement system including hardware, measurement protocols, and data analysis is necessary. In this study, we developed palm-size wireless odor measurement devices equipped with Membrane-type Surface stress Sensors (MSS) and investigated the effect of measurement protocols and feature selection on odor identification. By using the device, we measured vapors of liquids as odor samples through the free-hand measurement in different protocols. From the measurement data obtained with these protocols, datasets of transfer function ratios (TFRs) were created and analyzed by clustering and machine learning classification. It has been revealed that TFRs in the low-frequency range below 1 Hz notably contributed to vapor identification because the frequency components in that range reflect the dynamics of the detection mechanism of MSS. We also showed the optimal measurement protocol for accurate classification. This study has shown a guideline of the free-hand measurement and will contribute to the practical implementation of machine olfaction in society.

Residual Compressive Stress Enabled 2D-to-3D Junction Transformation in Amorphous Carbon Films for Stretchable Strain Sensors

Usually, two-dimensional (2D) flexible strain sensors based on cracks have very high sensitivities but small measuring ranges, while the three-dimensional (3D) ones behave in the opposite way. Here, by utilizing the large residual compressive stress of an amorphous carbon (a-C) film and the flexibility of polydimethylsiloxane (PDMS), we developed a facile and economic strategy to fabricate a high-sensitive a-C/PDMS stretchable strain sensor. Results showed that for the first time, the a-C film ranging from 25 nm to 1 μm changed the shape and orientation of conductive scales, as well as made a one-step 2D-to-3D electrical junction transformation in integrated sensors. In particular, the sensor with a 1 μm thick a-C film exhibited the best comprehensive performance, displaying a maximum gauge factor of 746.7 and strain range up to 0.5. However, the linearity decreased slightly as the strain range went beyond 0.43. Additionally, the sensor showed a satisfactory repeatability for 5000 cycles, together with excellent time and temperature drift performances at zero position of 75 ppm full scale (FS) and 25 ppm FS·°C^-1 in the range of -20 to 155 °C, respectively. The sensor has large potentials for wearable devices used in the monitoring of various human motions and physiological signals.

Graphene Oxide as a Sensing Material for Gas Detection Based on Nanomechanical Sensors in the Static Mode

Graphene is a key material for gas sensing applications owing to its high specific surface area and vast chemical modification potential. To fully utilize the potential of graphene, a sensing platform independent of conductive properties is required. In this study, we employed membrane-type surface stress sensors (MSS)—A kind of nanomechanical sensor operated in the static mode—As a sensing platform and utilized graphene oxide (GO) as a gas sensing material. MSS detect surface stress caused by gas sorption; therefore, chemically modified graphene with low conductivity can be utilized as a gas sensing material. We evaluated the sensing performance of a GO-coated MSS by measuring its responses to five gases. We demonstrated with the GO-coated MSS the feasibility of GO as a gas sensing material for static mode nanomechanical sensors and revealed its high selectivity to water vapor. Moreover, we investigated the sensing mechanism of the GO-coated MSS by comparing it with the sensing performance of MSS coated with reduced graphene oxide and graphite powder and deduced key factors for sensitivity and selectivity. Considering the high sensitivity of the GO-coated MSS and the compact measurement system that MSS can realize, the present study provides a new perspective on the sensing applications of graphene.

A suspended graphene-based optical interferometric surface stress sensor for selective biomolecular detection

Graphene-based sensors are of great interest in research due to their high specific surface area and high electron mobility that make them suitable for numerous advanced applications. In this paper, selective molecular detection using an antigen-antibody reaction on suspended graphene with a cavity-sealing structure was demonstrated. The suspended graphene sealed nanocavities in a pre-patterned Si substrate, which increased robustness and allowed the use of wet chemical processes for surface functionalization of the suspended graphene to achieve selective molecular binding. The selectivity was evaluated by nanomechanical deflection induced by molecular adsorption on the suspended graphene, resulting in spectral shifts in the optical interference between the suspended graphene and Si substrate. The chemically functionalized suspended graphene enables the analysis of intermolecular interactions and molecular kinetics by colorimetry using optical interference.

Finite Element Analysis of Interface Dependence on Nanomechanical Sensing

Nanomechanical sensors and their arrays have been attracting significant attention for detecting, discriminating and identifying target analytes. The sensing responses can be partially explained by the physical properties of the receptor layers coated on the sensing elements. Analytical solutions of nanomechanical sensing are available for a simple cantilever model including the physical parameters of both a cantilever and a receptor layer. These analytical solutions generally rely on the simple structures, such that the sensing element and the receptor layer are fully attached at their boundary. However, an actual interface in a real system is not always fully attached because of inhomogeneous coatings with low affinity to the sensor surface or partial detachments caused by the exposure to some analytes, especially with high concentration. Here, we study the effects of such macroscopic interfacial structures, including partial attachments/detachments, for static nanomechanical sensing, focusing on a Membrane-type Surface stress Sensor (MSS), through finite element analysis (FEA). We simulate various macroscopic interfacial structures by changing the sizes, numbers and positions of the attachments as well as the elastic properties of receptor layers (e.g., Young’s modulus and Poisson’s ratio) and evaluate the effects on the sensitivity. It is found that specific interfacial structures lead to efficient sensing responses, providing a guideline for designing the coating films as well as optimizing the interfacial structures for higher sensitivity including surface modification of the substrate.

Surface stress-induced membrane biosensor based on double-layer stable gold nanostructures for E. coli detection

The surface stress-based biosensor has been applied in fast and sensitive identification of Escherichia coli (E. coli)with significance for public health, food, and water safety. However, the stable sensitive element of flexible biosensor based on surface stress is still crucial and challengeable. Here, the authors reported surface stress-induced biosensors based on double-layer stable gold nanostructures (D-AuNS-SSMB) for E. coli O157:H7 detection. Bacterial detection demonstrates the high stability of the biosensor. The resistance change of biosensor is linear to the logarithmic value of the E. coli O157:H7 concentrations ranging from 10³ to 10⁷ CFU/mL with a limit of detection (LOD) of 43 CFU/mL. The captured signals of D-AuNS-SSMB comes from surface stress generated by antigen-antibody binding. In addition, the biosensor exhibits good stability, reproducibility and specificity in detection of E. coli O157:H7 as well. This study provides a new preparation method of stable sensitive element for the E. coli detection.

Free-hand gas identification based on transfer function ratios without gas flow control

Gas identification is one of the most important functions of a gas sensor system. To identify gas species from sensing signals without gas flow control such as pumps or mass flow controllers, it is necessary to extract decisive dynamic features from complex sensing signals due to uncontrolled airflow. For that purpose, various analysis methods using system identification techniques have been proposed, whereas a method that is not affected by a gas input pattern has been demanded to enhance the robustness of gas identification. Here we develop a novel gas identification protocol based on a transfer function ratio (TFR) that is intrinsically independent of a gas input pattern. By combining the protocol with MEMS-based sensors-Membrane-type Surface stress Sensors (MSS), we have realized gas identification with a free-hand measurement, in which one can simply hold a small sensor chip near samples. From sensing signals obtained through the free-hand measurement, we have developed highly accurate machine learning models that can identify odors of spices and herbs as well as solvent vapors. Since no bulky gas flow control units are required, this protocol will expand the applicability of gas sensors to portable electronics, leading to practical artificial olfaction.

Nanoarchitectonic-Based Material Platforms for Environmental and Bioprocessing Applications

The challenges of pollution, environmental science, and energy consumption have become global issues of broad societal importance. In order to address these challenges, novel functional systems and advanced materials are needed to achieve high efficiency, low emission, and environmentally friendly performance. A promising approach involves nanostructure-level controls of functional material design through a novel concept, nanoarchitectonics. In this account article, we summarize nanoarchitectonic approaches to create nanoscale platform structures that are potentially useful for environmentally green and bioprocessing applications. The introduced platforms are roughly classified into (i) membrane platforms and (ii) nanostructured platforms. The examples are discussed together with the relevant chemical processes, environmental sensing, bio-related interaction analyses, materials for environmental remediation, non-precious metal catalysts, and facile separation for biomedical uses.

Functional Nanoparticles-Coated Nanomechanical Sensor Arrays for Machine Learning-Based Quantitative Odor Analysis

A sensing signal obtained by measuring an odor usually contains varied information that reflects an origin of the odor itself, while an effective approach is required to reasonably analyze informative data to derive the desired information. Herein, we demonstrate that quantitative odor analysis was achieved through systematic material design-based nanomechanical sensing combined with machine learning. A ternary mixture consisting of water, ethanol, and methanol was selected as a model system where a target molecule coexists with structurally similar species in a humidified condition. To predict the concentration of each species in the system via the data-driven approach, six types of nanoparticles functionalized with hydroxyl, aminopropyl, phenyl, and/or octadecyl groups were synthesized as a receptor coating of a nanomechanical sensor. Then, a machine learning model based on Gaussian process regression was trained with sensing data sets obtained from the samples with diverse concentrations. As a result, the octadecyl-modified nanoparticles enhanced prediction accuracy for water while the use of both octadecyl and aminopropyl groups was indicated to be a key for a better prediction accuracy for ethanol and methanol. As the prediction accuracy for ethanol and methanol was improved by introducing two additional nanoparticles with finely controlled octadecyl and aminopropyl amount, the feedback obtained by the present machine learning was effectively utilized to optimize material design for better performance. We demonstrate through this study that various information which was extracted from plenty of experimental data sets was successfully combined with our knowledge to produce wisdom for addressing a critical issue in gas phase sensing.

Materials Nanoarchitectonics for Mechanical Tools in Chemical and Biological Sensing

In this Focus Review, nanoarchitectonic approaches for mechanical-action-based chemical and biological sensors are briefly discussed. In particular, recent examples of piezoelectric devices, such as quartz crystal microbalances (QCM and QCM-D) and a membrane-type surface stress sensor (MSS), are introduced. Sensors need well-designed nanostructured sensing materials for the sensitive and selective detection of specific targets. Nanoarchitectonic approaches for sensing materials, such as mesoporous materials, 2D materials, fullerene assemblies, supported lipid bilayers, and layer-by-layer assemblies, are highlighted. Based on these sensing approaches, examples of bioanalytical applications are presented for toxic gas detection, cell membrane interactions, label-free biomolecular assays, anticancer drug evaluation, complement activation-related multiprotein membrane attack complexes, and daily biodiagnosis, which are partially supported by data analysis, such as machine learning and principal component analysis.

Effects of Center Metals in Porphines on Nanomechanical Gas Sensing

Porphyrin is one of the most promising materials for realizing a practical artificial olfactory sensor system. In this study, we focus on non-substituted porphyrins—porphines—as receptor materials of nanomechanical membrane-type surface stress sensors (MSS) to investigate the effect of center metals on gas sensing. By omitting the substituents on the tetrapyrrole macrocycle of porphyrin, the peripheral interference by substituents can be avoided. Zinc, nickel, and iron were chosen for the center metals as these metalloporphines show different properties compared to free-base porphine. The present study revealed that iron insertion enhanced sensitivity to various gases, while zinc and nickel insertion led to equivalent or less sensitivity than free-base porphine. Based on the experimental results, we discuss the role of center metals for gas uptake from the view point of molecular interaction. We also report the high robustness of the iron porphine to humidity, showing the high feasibility of porphine-based nanomechanical sensor devices for practical applications in ambient conditions.

Note: Force- and torque-detection of high frequency electron spin resonance using a membrane-type surface-stress sensor

We developed a practical useful method for force- and torque-detected electron spin resonance (FDESR/TDESR) spectroscopy in the millimeter wave frequency region. This method uses a commercially available membrane-type surface-stress (MSS) sensor. The MSS is composed of a silicon membrane supported by four beams in which piezoresistive paths are integrated for detecting the deformation of the membrane. Although this device has a lower spin sensitivity than a microcantilever, it offers several distinct advantages, including mechanical strength, ease of use, and versatility. These advantages make this device suitable for practical applications that require FDESR/TDESR.

Optical-Interferometry-Based CMOS-MEMS Sensor Transduced by Stress-Induced Nanomechanical Deflection

We developed a Fabry-Perot interferometer sensor with a metal-oxide-semiconductor field-effect transistor (MOSFET) circuit for chemical sensing. The novel signal transducing technique was performed in three steps: mechanical deflection, transmittance change, and photocurrent change. A small readout photocurrent was processed by an integrated source follower circuit. The movable film of the sensor was a 350-nm-thick polychloro-para-xylylene membrane with a diameter of 100 µm and an air gap of 300 nm. The linearity of the integrated source follower circuit was obtained. We demonstrated a gas response using 80-ppm ethanol detected by small membrane deformation of 50 nm, which resulted in an output-voltage change with the proposed high-efficiency transduction.

Deposition of a titania layer on spherical porous silica particles and their nanostructure-induced vapor sensing properties

A titania-stearic acid hybrid layer was deposited onto well-defined silica-hexadecyltrimethylammonium hybrid spherical particles with 854 nm size to obtain nanoporous particles with a useful hierarchical core-shell structure. The deposition of a 35 nm-thick titania layer was confirmed by transmission electron microscopy. The core-shell particles were washed with acidic ethanol (solvent extraction) and calcined at 550 °C for 5 h to remove the template, resulting in the formation of nanoporous titania coated nanoporous silica spherical particles, which have a bimodal pore size distribution attributed to the hierarchical porous core and porous shell structure. The nanoporous titania coated particles exhibited an unusual crystal phase transition; only anatase was present even after the calcination at 1000 °C for 1 h. This would be due to the interfacial bonding between the core silica and the shell titania, preventing the crystal phase transition from anatase to rutile. On the other hand, the direct calcination of the titania-stearic acid coated particles without solvent extraction led to a shell composed of both anatase and rutile. The transformation to rutile could be caused by the strong exothermic reaction during the oxidative decomposition of the occluded stearic acid. Furthermore, the intense exothermic reaction induced the formation of a yolk-shell structure, which played a role in the sensitive/selective sensing properties for acetic acid when the yolk-shell particles were coated onto a nanomechanical Membrane-type Surface stress Sensor (MSS).

A Micro-Force Sensor with Beam-Membrane Structure for Measurement of Friction Torque in Rotating MEMS Machines

In this paper, a beam-membrane (BM) sensor for measuring friction torque in micro-electro-mechanical system (MEMS) gas bearings is presented. The proposed sensor measures the force-arm-transformed force using a detecting probe and the piezoresistive effect. This solution incorporates a membrane into a conventional four-beam structure to meet the range requirements for the measurement of both the maximum static friction torque and the kinetic friction torque in rotating MEMS machines, as well as eliminate the problem of low sensitivity with neat membrane structure. A glass wafer is bonded onto the bottom of the sensor chip with a certain gap to protect the sensor when overloaded. The comparisons between the performances of beam-based sensor, membrane-based sensor and BM sensor are conducted by finite element method (FEM), and the final sensor dimensions are also determined. Calibration of the fabricated and packaged device is experimentally performed. The practical verification is also reported in the paper for estimating the friction torque in micro gas bearings by assembling the proposed sensor into a rotary table-based measurement system. The results demonstrate that the proposed force sensor has a potential application in measuring micro friction or force in MEMS machines.

Data-driven nanomechanical sensing: specific information extraction from a complex system

Smells are known to be composed of thousands of chemicals with various concentrations, and thus, the extraction of specific information from such a complex system is still challenging. Herein, we report for the first time that the nanomechanical sensing combined with machine learning realizes the specific information extraction, e.g. alcohol content quantification as a proof-of-concept, from the smells of liquors. A newly developed nanomechanical sensor platform, a Membrane-type Surface stress Sensor (MSS), was utilized. Each MSS channel was coated with functional nanoparticles, covering diverse analytes. The smells of 35 liquid samples including water, teas, liquors, and water/EtOH mixtures were measured using the functionalized MSS array. We selected characteristic features from the measured responses and kernel ridge regression was used to predict the alcohol content of the samples, resulting in successful alcohol content quantification. Moreover, the present approach provided a guideline to improve the quantification accuracy; hydrophobic coating materials worked more effectively than hydrophilic ones. On the basis of the guideline, we experimentally demonstrated that additional materials, such as hydrophobic polymers, led to much better prediction accuracy. The applicability of this data-driven nanomechanical sensing is not limited to the alcohol content quantification but to various fields including food, security, environment, and medicine.

Highly Networked Capsular Silica-Porphyrin Hybrid Nanostructures as Efficient Materials for Acetone Vapor Sensing

The development of novel functional nanomaterials is critically important for the further evolution of advanced chemical sensor technology. For this purpose, metalloporphyrins offer unique binding properties as host molecules that can be tailored at the synthetic level and potentially improved by incorporation into inorganic materials. In this work, we present a novel hybrid nanosystem based on a highly networked silica nanoarchitecture conjugated through covalent bonding to an organic functional molecule, a tetraphenylporphyrin derivative, and its metal complexes. The sensing properties of the new hybrid materials were studied using a nanomechanical membrane-type surface stress sensor (MSS) with acetone and nitric oxide as model analytes. This hybrid inorganic-organic MSS-based system exhibited excellent performance for acetone sensing at low operating temperatures (37 °C), making it available for diagnostic monitoring. The hybridization of an inorganic substrate of large surface area with organic molecules of various functionalities results in sub-ppm detection of acetone vapors. Acetone is an important metabolite in lipid metabolism and can also be present in industrial environments at deleterious levels. Therefore, we believe that the analysis system presented by our work represents an excellent opportunity for the development of a portable, easy-to-use device for monitoring local acetone levels.

Solid surface vs. liquid surface: nanoarchitectonics, molecular machines, and DNA origami

Comparisons of science and technology between these solid and liquid surfaces would be a good navigation for current-to-future developments.

Finite Element Analysis on Nanomechanical Sensing of Cellular Forces

Detection of cellular forces plays an important role in investigating the mechanical basis of cells. As nanomechanical sensors can directly detect surface stress, they can be utilized to detect cellular forces. In the present study, we perform quantitative simulations of nanomechanical sensors for the detection of cellular forces using finite element analyses (FEA). We focus on two types of nanomechanical sensors: a cantilever-type sensor and a membrane-type surface stress sensor (MSS). It is found that sensing signals can be obtained when cells on the nanomechanical sensors synchronize their motions. To effectively detect cellular forces on the nanomechanical sensors, we discuss the optimization scheme for a coating layer on the surface of the sensors.

Piezoresistive Membrane Surface Stress Sensors for Characterization of Breath Samples of Head and Neck Cancer Patients

For many diseases, where a particular organ is affected, chemical by-products can be found in the patient’s exhaled breath. Breath analysis is often done using gas chromatography and mass spectrometry, but interpretation of results is difficult and time-consuming. We performed characterization of patients’ exhaled breath samples by an electronic nose technique based on an array of nanomechanical membrane sensors. Each membrane is coated with a different thin polymer layer. By pumping the exhaled breath into a measurement chamber, volatile organic compounds present in patients’ breath diffuse into the polymer layers and deform the membranes by changes in surface stress. The bending of the membranes is measured piezoresistively and the signals are converted into voltages. The sensor deflection pattern allows one to characterize the condition of the patient. In a clinical pilot study, we investigated breath samples from head and neck cancer patients and healthy control persons. Evaluation using principal component analysis (PCA) allowed a clear distinction between the two groups. As head and neck cancer can be completely removed by surgery, the breath of cured patients was investigated after surgery again and the results were similar to those of the healthy control group, indicating that surgery was successful.

Aero-Thermo-Dynamic Mass Analysis

Each gas molecule has its own molecular weight, while such a microscopic characteristic is generally inaccessible, and thus, it is measured indirectly through e.g. ionization in conventional mass analysis. Here, we present a novel approach to the direct measurement of molecular weight through a nanoarchitectonic combination of aerodynamics, thermodynamics, and mechanics, transducing microscopic events into macroscopic phenomena. It is confirmed that this approach can provide molecular weight of virtually any gas or vaporizable liquid sample in real-time without ionization. Demonstrations through analytical calculations, numerical simulations, and experiments verify the validity and versatility of the novel mass analysis realized by a simple setup with a flexible object (e.g. with a bare cantilever and even with a business card) placed in a laminar jet. Owing to its unique and simple working principle, this aero-thermo-dynamic mass analysis (AMA) can be integrated into various analytical devices, production lines, and consumer mobile platforms, opening new chapters in aerodynamics, thermodynamics, mechanics, and mass analysis.

Finite Element Analysis on Nanomechanical Detection of Small Particles: Toward Virus Detection

Detection of small particles, including viruses and particulate matter (PM), has been attracting much attention in light of increasing need for environmental monitoring. Owing to their high versatility, a nanomechanical sensor is one of the most promising sensors which can be adapted to various monitoring systems. In this study, we present an optimization strategy to efficiently detect small particles with nanomechanical sensors. Adsorption of particles on the receptor layer of nanomechanical sensors and the resultant signal are analyzed using finite element analysis (FEA). We investigate the effect of structural parameters (e.g., adsorption position and embedded depth of a particle and thickness of the receptor layer) and elastic properties of the receptor layer (e.g., Young's modulus and Poisson's ratio) on the sensitivity. It is found that a membrane-type surface stress sensors (MSS) has the potential for robust detection of small particles.

Nanomechanical Sensors

This chapter introduces nanomechanical sensors and their applications. All molecules have “volume” and “mass.” Direct measurement of these fundamental parameters can realize label-free and real-time measurements. Nanomechanical sensors have been emerging as a key device for such label-free and real-time measurements with their multiple operation modes; static and dynamic modes for detecting volume- and mass-related features, respectively. A cantilever array sensor is a representative example among various geometries, while structural optimization can enhance the scope of nanomechanical sensors in both academic and industrial applications. One of the most advanced sensing platforms is a membrane-type surface stress sensor (MSS), which realizes both high sensitivity and compact system at the same time. The MSS is also expected to contribute to addressing nanomechanical behavior of living cells and their network.

Hybrid integrated label-free chemical and biological sensors

Label-free sensors based on electrical, mechanical and optical transduction methods have potential applications in numerous areas of society, ranging from healthcare to environmental monitoring. Initial research in the field focused on the development and optimization of various sensor platforms fabricated from a single material system, such as fiber-based optical sensors and silicon nanowire-based electrical sensors. However, more recent research efforts have explored designing sensors fabricated from multiple materials. For example, synthetic materials and/or biomaterials can also be added to the sensor to improve its response toward analytes of interest. By leveraging the properties of the different material systems, these hybrid sensing devices can have significantly improved performance over their single-material counterparts (better sensitivity, specificity, signal to noise, and/or detection limits). This review will briefly discuss some of the methods for creating these multi-material sensor platforms and the advances enabled by this design approach.

Biosensors based on nanomechanical systems

The advances in micro- and nanofabrication technologies enable the preparation of increasingly smaller mechanical transducers capable of detecting the forces, motion, mechanical properties and masses that emerge in biomolecular interactions and fundamental biological processes. Thus, biosensors based on nanomechanical systems have gained considerable relevance in the last decade. This review provides insight into the mechanical phenomena that occur in suspended mechanical structures when either biological adsorption or interactions take place on their surface. This review guides the reader through the parameters that change as a consequence of biomolecular adsorption: mass, surface stress, effective Young's modulus and viscoelasticity. The mathematical background needed to correctly interpret the output signals from nanomechanical biosensors is also outlined here. Other practical issues reviewed are the immobilization of biomolecular receptors on the surface of nanomechanical systems and methods to attain that in large arrays of sensors. We then describe some relevant realizations of biosensor devices based on nanomechanical systems that harness some of the mechanical effects cited above. We finally discuss the intrinsic detection limits of the devices and the limitation that arises from non-specific adsorption.

Double-side-coated nanomechanical membrane-type surface stress sensor (MSS) for one-chip-one-channel setup

With their capability for real-time and label-free detection of targets ranging from gases to biological molecules, nanomechanical sensors are expected to contribute to various fields, such as medicine, security, and environmental science. For practical applications, one of the major issues of nanomechanical sensors is the difficulty of coating receptor layers on their surfaces to which target molecules adsorb or react. To have measurable deflection, a single-side coating is commonly applied to cantilever-type geometry, and it requires specific methods or protocols, such as inkjet spotting or gold-thiol chemistry. If we can apply a double-side coating to nanomechanical sensors, it allows almost any kind of coating technique including dip coating methods, making nanomechanical sensors more useful with better user experiences. Here we address the feasibility of the double-side coating on nanomechanical sensors demonstrated by a membrane-type surface stress sensor (MSS) and verify its working principle by both finite element analysis (FEA) and experiments. In addition, simple hand-operated dip coating is demonstrated as a proof of concept, achieving practical receptor layers without any complex instrumentation. Because the double-side coating is compatible with batch protocols such as dip coating, double-side-coated MSS represents a new paradigm of one-chip-one-channel (channels on a chip are all coated with the same receptor layers) shifting from the conventional one-chip-multiple-channel (channels on a chip are coated with different receptor layers) paradigm.

Sensitive thermal transitions of nanoscale polymer samples using the bimetallic effect: application to ultra-thin polythiophene

A sensitive nanocalorimetric technology based on microcantilever sensors is presented. The technology, which combines very short response times with very small sample consumption, uses the bimetallic effect to detect thermal transitions. Specifically, abrupt variations in the Young's modulus and the thermal expansion coefficient produced by temperature changes have been employed to detect thermodynamic transitions. The technology has been used to determine the glass transition of poly(3-thiophene methyl acetate), a soluble semiconducting polymer with different nanotechnological applications. The glass transition temperature determined using microcantilevers coated with ultra-thin films of mass = 10(-13) g is 5.2 °C higher than that obtained using a conventional differential scanning calorimeter for bulk powder samples of mass = 5 × 10(-3) g. Atomistic molecular dynamics simulations on models that represent the bulk powder and the ultra-thin films have been carried out to provide understanding and rationalization of this feature. Simulations indicate that the film-air interface plays a crucial role in films with very small thickness, affecting both the organization of the molecular chains and the response of the molecules against the temperature.

A micro-cantilever sensor chip based on contact angle analysis for a label-free troponin I immunoassay

Cantilever sensors have been extensively explored as a promising technique for real-time and label-free analyses in biological systems. A major sensing principle utilized by state-of-the-art cantilever sensors is based on analyte-induced surface stress changes, which result in static bending of a cantilever. The sensor performance, however, suffers from the intrinsically small change in surface stress induced by analytes, especially for molecular recognition such as antigen-antibody binding. Through the contact angle change on a tailored solid surface, it is possible to convert a tiny surface stress into a capillary force-a much larger physical quantity needed for a practical sensor application. In this work, a micro-cantilever sensor based on contact angle analysis (CAMCS) was proposed to effectively enhance the sensitivity of a sensor in proportion to the square of the length to thickness ratio of the cantilever structure. CAMCS chips were fabricated using a standard complementary-metal-oxide-semiconductor (CMOS) process to demonstrate a 1250-fold enhancement in the sensitivity of surface stress to bioanalyte adsorption using a piezoresistive sensing method. A real-time and label-free troponin I (cTnI) immunoassay, which is now widely used in clinics and considered a gold standard for the early diagnosis and prognosis of cardiovascular disease, was performed to demonstrate cTnI detection levels as low as 1 pg mL(-1). The short detection time of this assay was within several minutes, which matches the detection time of commercially available instruments that are based on fluorescence-labeling techniques.

Two dimensional array of piezoresistive nanomechanical Membrane-type Surface Stress Sensor (MSS) with improved sensitivity

We present a new generation of piezoresistive nanomechanical Membrane-type Surface stress Sensor (MSS) chips, which consist of a two dimensional array of MSS on a single chip. The implementation of several optimization techniques in the design and microfabrication improved the piezoresistive sensitivity by 3~4 times compared to the first generation MSS chip, resulting in a sensitivity about ~100 times better than a standard cantilever-type sensor and a few times better than optical read-out methods in terms of experimental signal-to-noise ratio. Since the integrated piezoresistive read-out of the MSS can meet practical requirements, such as compactness and not requiring bulky and expensive peripheral devices, the MSS is a promising transducer for nanomechanical sensing in the rapidly growing application fields in medicine, biology, security, and the environment. Specifically, its system compactness due to the integrated piezoresistive sensing makes the MSS concept attractive for the instruments used in mobile applications. In addition, the MSS can operate in opaque liquids, such as blood, where optical read-out techniques cannot be applied.

A novel integrated multifunction micro-sensor for three-dimensional micro-force measurements

An integrated multifunction micro-sensor for three-dimensional micro-force precision measurement under different pressure and temperature conditions is introduced in this paper. The integrated sensor consists of three kinds of sensors: a three-dimensional micro-force sensor, an absolute pressure sensor and a temperature sensor. The integrated multifunction micro-sensor is fabricated on silicon wafers by micromachining technology. Different doping doses of boron ion, placement and structure of resistors are tested for the force sensor, pressure sensor and temperature sensor to minimize the cross interference and optimize the properties. A glass optical fiber, with a ladder structure and sharp tip etched by buffer oxide etch solution, is glued on the micro-force sensor chip as the tactile probe. Experimental results show that the minimum force that can be detected by the force sensor is 300 nN; the lateral sensitivity of the force sensor is 0.4582 mV/μN; the probe length is linearly proportional to sensitivity of the micro-force sensor in lateral; the sensitivity of the pressure sensor is 0.11 mv/KPa; the sensitivity of the temperature sensor is 5.836 × 10(-3) KΩ/°C. Thus it is a cost-effective method to fabricate integrated multifunction micro-sensors with different measurement ranges that could be used in many fields.