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.

Strain Sensor-Inserted Microchannel for Gas Viscosity Measurement.

Quantifying the viscosity of a gas is of great importance in determining its properties and can even be used to identify what the gas is. While many techniques exist for measuring the viscosities of gases, it is still challenging to probe gases with a simple, robust setup that will be useful for practical applications. We introduce a facile approach to estimating gas viscosity using a strain gauge inserted in a straight microchannel with a height smaller than that of the gauge. Using a constrained geometry for the strain gauge, in which part of the gauge deforms the channel to generate initial gauge strain that can be transduced into pressure, the pressure change induced via fluid flow was measured. The change was found to linearly correlate with fluid viscosity, allowing estimation of the viscosities of gases with a simple device.

Visualization of Flow-Induced Strain Using Structural Color in Channel-Free Polydimethylsiloxane Devices.

Measuring flow of gases is of fundamental importance yet is typically done with complex equipment. There is, therefore, a longstanding need for a simple and inexpensive means of flow measurement. Here, gas flow is measured using an extremely simple device that consists of an Ar plasma-treated polydimethylsiloxane (PDMS) slab adhered on a glass substrate with a tight seal. This device does not even have a channel, instead, gas can flow between the PDMS and the glass by deforming the PDMS wall, in other words, by making an interstice as a temporary path for the flow. The formation of the temporary path results in a compressive bending stress at the inner wall of the path, which leads to the formation of well-ordered wrinkles, and hence, the emergence of structural color that changes the optical transmittance of the device. Although it is very simple, this setup works sufficiently well to measure arbitrary gases and analyzes their flow rates, densities, and viscosities based on the change in color. It is also demonstrated that this technique is applicable to the flow-induced display of a pattern such as a logo for advanced applications.

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.

Drug Molecular Immobilization and Photofunctionalization of Calcium Phosphates for Exploring Theranostic Functions.

Theranostics (bifunction of therapeutics and diagnostics) has attracted increasing attention due to its efficiency that can reduce the physical and financial burden on patients. One of the promising materials for theranostics is calcium phosphate (CP) and it is biocompatible and can be functionalized not only with drug molecules but also with rare earth ions to show photoluminescence that is necessary for the diagnostic purpose. Such the CP-based hybrids are formed in vivo by interacting between functional groups of organic molecules and inorganic ions. It is of great importance to elucidate the interaction of CP with the photofunctional species and the drug molecules to clarify the relationship between the existing state and function. Well-designed photofunctional CPs will contribute to biomedical fields as highly-functional ormultifunctional theranostic materials at the nanoscales. In this review, we describe the hybridization between CPs and heterogeneous species, mainly focusing on europium(III) ion and methylene blue molecule as the representative photofunctional species for theranostics applications.

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.

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.

Microchannel measurements of viscosity for both gases and liquids.

Quantifying the viscosity of a fluid is of great importance in determining its properties and can even be used to identify what the fluid is. While many techniques exist for measuring the viscosity of either gases or liquids, it is very challenging to probe both gases and liquids with a single approach because of the significant difference in their nature, and the vast difference in the values of their viscosities. We introduce a facile approach to measuring the viscosity of a Newtonian fluid, either a gas or a liquid, by flowing it through a deformable microchannel where the deformation depends on the pressure required to induce the flow, which, in turn, depends on the fluid viscosity. A strain gauge embedded just above and across the microchannel transduces the flow-induced deformation into strain. The strain is proportional to the square of the flow-induced deformation enabling us to precisely discriminate not only gases but also liquids based on their viscosities with the same device.

Preparation of Monodispersed Nanoporous Eu(III)/Titania Loaded with Ibuprofen: Optimum Loading, Luminescence, and Sustained Release.

Functional nanomaterials are one of the potential carriers for drug delivery, whereas there are many prerequisites for this purpose. The carrier should be monodispersed, be fluorescent, and have a proper nanostructure to keep/release drug molecules to achieve controlled release, although preparing a nanomaterial which fulfills all the demands is still very challenging. In this paper, we show the preparation of monodispersed nanoporous amorphous titania submicron particles with fluorescent property. They adsorb a model drug molecule-ibuprofen-with their surface coverage up to 100%. Such a perfect loading does not decrease the fluorescent intensity because of any quenching effects but even maximize it. We also demonstrate the release behavior of IBU into simulated body fluid. Interestingly, the present carrier releases most of IBU in 6 h, whereas that modified with the polyethylene glycol moiety takes 48 h to finish releasing IBU, indicating its potential for controlled release applications.

Microfluidic Production of Autofluorescent BSA Hydrogel Microspheres and Their Sequential Trapping for Fluorescence-Based On-Chip Permanganate Sensing.

Microfabrication technologies have extensively advanced over the past decades, realizing a variety of well-designed compact devices for material synthesis, separation, analysis, monitoring, sensing, and so on. The performance of such devices has been undoubtedly improved, while it is still challenging to build up a platform by rationally combining multiple processes toward practical demands which become more diverse and complicated. Here, we present a simple and effective microfluidic system to produce and immobilize a well-defined functional material for on-chip permanganate (MnO4-) sensing. A droplet-based microfluidic approach that can continuously produce monodispersed droplets in a water-in-oil system is employed to prepare highly uniform microspheres (average size: 102 µm, coefficient of variation: 3.7%) composed of bovine serum albumin (BSA) hydrogel with autofluorescence properties in the presence of glutaraldehyde (GA). Each BSA hydrogel microsphere is subsequently immobilized in a microchannel with a hydrodynamic trapping structure to serve as an independent fluorescence unit. Various anions such as Cl-, NO3-, PO43-, Br-, BrO3-, ClO4-, SCN-, HCO3-, and MnO4- are individually flowed into the microchannel, resulting in significant fluorescence quenching only in the case of MnO4-. Linear correlation is confirmed at an MnO4- concentration from 20 to 80 µM, and a limit of detection is estimated to be 1.7 µM. Furthermore, we demonstrate the simultaneous immobilization of two kinds of different microspheres in parallel microchannels, pure BSA hydrogel microspheres and BSA hydrogel microspheres containing rhodamine B molecules, making it possible to acquire two fluorescence signals (green and yellow). The present microfluidics-based combined approach will be useful to record a fingerprint of complicated samples for sensing/identification purposes by flexibly designing the size and composition of the BSA hydrogel microspheres, immobilizing them in a desired manner and obtaining a specific pattern.

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.

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.

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.

Precise Synthesis of Well-Defined Inorganic-Organic Hybrid Particles.

Synthesis of hybrid particles toward precisely designed hierarchical nanoarchitectures is summarized. In order to satisfy the demands for a variety of materials' performances, the selection of materials, composition and synthesis is carefully done. Flow reactors are one of the useful synthetic means to prepare hybrid materials, especially those with hierarchically and precisely designed multi-components hybrid particles, owing to the efficient mixing and heat exchange in the reactor as well as its connectable (both parallel and sequential) feature. In this review article, after the summary of the preparation of hybrids based on oxides and organics through conventional batch reactors, the application of flow reactors to the preparation of various hybrid particles is introduced to highlight the present status and future possibility of the flow reactor synthesis.

Preparation of Eu(iii) acetylacetonate-doped well-defined titania particles with efficient photoluminescence properties.

The aggregation/dispersion of luminescent species is a critical factor that determines their luminescence properties. In this study, europium(iii) acetylacetonate (Eu(acac)3) was doped into a titania matrix to form Eu(acac)3-doped titania particles with well-defined size and shape through a microreactor-based sol-gel approach. The morphology and structure of the as-synthesized products were characterized by Fourier transform infrared spectroscopy, scanning electron microscopy, transmission electron microscopy, scanning transmission electron microscopy and X-ray diffraction measurements. The Eu/Ti value of the products varied in the range from 0.125 to 5.0 and the resulting luminescence properties were examined. It should be noted that there was an optimum Eu/Ti value that exhibited the strongest luminescence. A possible reason for this phenomenon can be explained on the basis of a balance between the inter-molecular distance of Eu(acac)3 and its doped amount. The effects of the crystal phase of the titania matrix on luminescence behavior were also investigated. As a result, Eu(acac)3-doped amorphous titania demonstrated more efficient luminescence than that after calcined at 550 °C for 6 h to convert amorphous to anatase probably because of the aggregation of Eu species on the crystallite surface. The stability of the present Eu(acac)3-doped titania was confirmed by preparing thin films on a glass substrate and by applying UV/ozone treatment. As compared to bare Eu(acac)3, degradation in luminescence was suppressed in the case of Eu(acac)3-doped titania. Thus, the present titania-based hybrid with controlled Eu(acac)3 doping is useful as a stable, luminescent material for optical, biological and environmental applications.

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.

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.

Mesoporous silica coated silica-titania spherical particles: from impregnation to core-shell formation.

The coating of solid surfaces with inorganic materials is a promising approach not only to impart various functionalities but also to modify physicochemical properties that are affected by the geometry/structure of the coating. In this study, a silica-hexadecyltrimethylammonium (silica-CTA) hybrid layer was deposited on monodispersed spherical particles composed of titania and octadecylamine (titania-ODA) by a sol-gel reaction of tetraethoxysilane in aqueous CTA/ammonia/methanol solution. The formation of the coating was confirmed by SEM and TEM observations. The coating thickness varied from a few nm to 100 nm depending on the Si/Ti ratio. We found that Si/Ti = 0.68 resulted in the formation of microporous silica-titania particles with the pore size of 0.7 nm as revealed by nitrogen adsorption/desorption measurements. Because the titania-ODA particles can be converted to mesoporous titania particles after removing ODA by acid/base treatment, the silica species can be impregnated into the titania particles and replace ODA under basic conditions. By increasing the Si/Ti molar ratio up to 1.4, silica-titania particles with non-porous structures were obtained. An amorphous to anatase transition occurred at around 800 °C, indicating the complete impregnation of silica inside the titania particles. Further increases of the Si/Ti molar ratio (to 3.4 and 6.8) led to the formation of the silica-CTA shell on the core particles, and the shell was converted to mesoporous silica layers with a pore size of 2 nm after calcination at 550 °C for 5 h. Non-linear control of the pore size/structure is presented for the first time; this will be useful for the precise design of diverse hybrid materials for optical, catalytic and biomedical applications.

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.