Trenched microwave resonator integrated with porous PDMS for detection and classification of VOCs with enhanced performance.

Microwave resonators combined with polymer absorption layers are widely used in volatile organic compound (VOC) detection based on their variable resonant frequencies. However, the response time is limited due to the polymer's slow volumetric absorption of VOC molecules. By constructing a porous structure in Polydimethylsiloxane (PDMS), resulting in reduced the response time to as short as 71.1%. To mitigate the sensitivity decline caused by the porous PDMS, a trenched-substrate complementary split-ring resonator (CSRR) is proposed for enhancing the interaction between the electromagnetic fields (EMFs) and the porous PDMS with VOCs. The removal of the substrate beneath CSRR's sensing region enhances the effective EMF, increasing frequency and amplitude sensitivities up to 175.5% and 137.8%, respectively. Responses to four common VOCs by the sensor show a maximum sensitivity of 217 Hz/ppm and a minimum limit of detection of 295 ppm. Additionally, resonant parameters and extracted lumped parameters are utilized to establish two decision-tree-based VOC classification models, achieving high accuracies of 98.71% and 99.59%, respectively. And the latter one fully utilizing responses throughout the swept band, proves superior in identifying similar substances. This sensor technology helps promote the sensitive detection and accurate classification of diverse VOCs.

Hydrophobic MOF/PDMS-Based QCM Sensors for VOCs Identification and Quantitative Detection in High-Humidity Environments.

Metal-organic frameworks (MOFs) have great potential in quartz crystal microbalance (QCM) platforms for volatile organic compound (VOCs) detection and recognition due to their unique properties. However, the MOFs' hydrophilicity degrades performance in high-humidity environments, limiting reliable VOC sensing in complex environments. Herein, we propose a novel VOC virtual sensor array (VSA) using a single QCM sensor with an adsorption layer composed of MIL-101(Cr) MOF and polydimethylsiloxane (PDMS), realizing stable sensing and accurate identification for different VOCs under various relative humidity (RH) conditions. The hydrophobic PDMS layer improves the moisture resistance of the sensor to 4 and 14 times in terms of shifts in resonant frequency and scattering parameters, respectively. In addition, performance is maintained over 2 days of water treatment, demonstrating superior water resistance. The highest sensitivity of 2.68 mdB ppm-1 is achieved for isopropanol detection, with the lowest limit of detection of 20.06 ppm for acetone. Combining resonant signals and lumped parameters, the proposed VSA technique effectively discriminates four VOCs (ethanol, 2-propanol, acetone, and acetonitrile) with a high accuracy of 95.3% under both 60% and 90% RH backgrounds. The studies provide a promising solution for reliable low-concentration VOC detection using QCM sensors in high-humidity environments such as underground spaces.

Ferroelectret nanogenerators for the development of bioengineering systems.

Bioengineering devices and systems will become a practical and versatile technology in society when sustainability issues, primarily pertaining to their efficiency, sustainability, and human-machine interaction, are fully addressed. It has become evident that technological paths should not rely on a single operation mechanism but instead on holistic methodologies that integrate different phenomena and approaches with complementary advantages. As an intriguing invention, the ferroelectret nanogenerator (FENG) has emerged with promising potential in various fields of bioengineering. Utilizing the changes in the engineered macro-scale electric dipoles to create displacement current (and vice versa), FENGs have been demonstrated to be a compelling strategy for bidirectional conversion of energy between the electrical and mechanical domains. Here we provide a comprehensive overview of the latest advancements in integrating FENGs in bioengineering systems, focusing on the applications with the most potential and the underlying current constraints.

Synthesis of biofuel precursors from benzaldehyde and cyclopentanone via aldehyde-ketone condensation in a deep eutectic solvent system.

Production of biofuel precursors from biomass-derived platform compounds (BDPC) has a profound influence on biofuel industries. Herein, an efficient catalytic system composed of the deep eutectic solvent (DES, i.e., ChCl/Fa) and SnCl4 (ChCl/Fa-SnCl4) was developed to produce biofuel precursors (C12 and C19) through aldehyde-ketone (A-K) condensation of benzaldehyde (BD) and cyclopentanone (CPO). ChCl/Fa-SnCl4 exhibited the prospective catalytic performance and given the high selectivity (SC12 = 49.20%, SC19 = 15.20%) and total yield (YC12+C19 = 64.37%) of C12 and C19, as well as 99.96% BD conversion under the optimized conditions (BD : CPO molar ratio of 1 : 6, ChCl : Fa molar ratio of 1 : 12, 4 mmol SnCl4, 80 °C for 120 min). Subsequently, the C12 and C19 precursors were successfully applied to generate cyclic alkanes (C12H14 and C19H18) by hydrodeoxygenation with selectivity of 37.61% and 24.10%, respectively. Finally, the potential catalytic mechanism was explored by density functional theory (DFT) calculations. The results unveiled that the formation of a stable structure for the ChCl/Fa-SnCl4 system was ascribed to the viable interactions among ChCl, Fa and SnCl4 by coordination bonds, electrostatic interactions and H-bonds, which decreased reaction energy barriers and drove the condensation of BD and CPO. In this case, the catalytic reactions between BD and CPO were enhanced to promote the synthesis of C12 and C19. This work provides a novel strategy for the applicability of different BDPC to synthesize fuel precursors for the development of liquid biofuels.

Measuring vibrations on a biofidelic brain using ferroelectret nanogenerator.

Our knowledge of traumatic brain injury has been fast growing with the emergence of new markers pointing to various neurological changes that the brain undergoes during an impact or any other form of concussive event. In this work, we study the modality of deformations on a biofidelic brain system when subject to blunt impacts, highlighting the importance of the time-dependent behavior of the resulting waves propagating through the brain. This study is carried out using two different approaches involving optical (Particle Image Velocimetry) and mechanical (flexible sensors) in the biofidelic brain. Results show that the system has a natural mechanical frequency of [Formula: see text] 25 oscillations per second, which was confirmed by both methods, showing a positive correlation with one another. The consistency of these results with previously reported brain pathology validates the use of either technique, and establishes a new, simpler mechanism to study brain vibrations by using flexible piezoelectric patches. The visco-elastic nature of the biofidelic brain is validated by observing the the relationship between both methods at two different time intervals, by using the information of the strain and stress inside the brain from the Particle Image Velocimetry and flexible sensor, respectively. A non-linear stress-strain relationship was observed and justified to support the same.

Sensitivity Enhancement of Soft Capacitive Pressure Sensors Using a Solvent Evaporation-Based Porosity Control Technique.

Soft pressure sensors play a significant role in developing "man-machine" tactile sensation in soft robotics and haptic interfaces. Specifically, capacitive sensors with micro-structured polymer matrices have been explored with considerable effort because of their high sensitivity, wide linearity range, and fast response time. However, the improvement of the sensing performance often relies on the structural design of the dielectric layer, which requires sophisticated microfabrication facilities. This article reports a simple and low-cost method to fabricate porous capacitive pressure sensors with improved sensitivity using the solvent evaporation-based method to tune the porosity. The sensor consists of a porous polydimethylsiloxane (PDMS) dielectric layer bonded with top and bottom electrodes made of elastic conductive polymer composites (ECPCs). The electrodes were prepared by scrape-coating carbon nanotubes (CNTs)-doped PDMS conductive slurry into mold-patterned PDMS films. To optimize the porosity of the dielectric layer for enhanced sensing performance, the PDMS solution was diluted with toluene of different mass fractions instead of filtering or grinding the sugar pore-forming agent (PFA) into different sizes. The evaporation of the toluene solvent allowed the fast fabrication of a porous dielectric layer with controllable porosities. It was confirmed that the sensitivity could be enhanced more two-fold when the toluene to PDMS ratio was increased from 1:8 to 1:1. The research proposed in this work enables a low-cost method of fabricating fully integrated bionic soft robotic grippers with soft sensory mechanoreceptors of tunable sensor parameters.

MEMS piezoelectric resonant microphone array for lung sound classification.

This paper reports a highly sensitive piezoelectric microelectromechanical systems (MEMS) resonant microphone array (RMA) for detection and classification of wheezing in lung sounds. The RMA is composed of eight width-stepped cantilever resonant microphones with Mel-distributed resonance frequencies from 230 to 630 Hz, the main frequency range of wheezing. At the resonance frequencies, the unamplified sensitivities of the microphones in the RMA are between 86 and 265 mV Pa-1, while the signal-to-noise ratios (SNRs) for 1 Pa sound pressure are between 86.6 and 98.0 dBA. Over 200-650 Hz, the unamplified sensitivities are between 35 and 265 mV Pa-1, while the SNRs are between 79 and 98 dBA. Wheezing feature in lung sounds recorded by the RMA is more distinguishable than that recorded by a reference microphone with traditional flat sensitivity, and thus, the automatic classification accuracy of wheezing is higher with the lung sounds recorded by the RMA than with those by the reference microphone, when tested with deep learning algorithms on computer or with simple machine learning algorithms on low-power wireless chip set for wearable applications.

Thin Film Piezoelectric Nanogenerator Based on (100)-Oriented Nanocrystalline AlN Grown by Pulsed Laser Deposition at Room Temperature.

In wearable or implantable biomedical devices that typically rely on battery power for diagnostics or operation, the development of flexible piezoelectric nanogenerators (NGs) that enable mechanical-to-electrical energy harvesting is finding promising applications. Here, we present the construction of a flexible piezoelectric nanogenerator using a thin film of room temperature deposited nanocrystalline aluminium nitride (AlN). On a thin layer of aluminium (Al), the AlN thin film was grown using pulsed laser deposition (PLD). The room temperature grown AlN film was composed of crystalline columnar grains oriented in the (100)-direction, as revealed in images from transmission electron microscopy (TEM) and X-ray diffraction (XRD). Fundamental characterization of the AlN thin film by piezoresponse force microscopy (PFM) indicated that its electro-mechanical energy conversion metrics were comparable to those of c-axis oriented AlN and zinc oxide (ZnO) thin films. Additionally, the AlN-based flexible piezoelectric NG was encapsulated in polyimide to further strengthen its mechanical robustness and protect it from some corrosive chemicals.

Multimodal Artificial Neurological Sensory-Memory System Based on Flexible Carbon Nanotube Synaptic Transistor.

As the initial stage in the formation of human intelligence, the sensory-memory system plays a critical role for human being to perceive, interact, and evolve with the environment. Electronic implementation of such biological sensory-memory system empowers the development of environment-interactive artificial intelligence (AI) that can learn and evolve with diversified external information, which could potentially broaden the application of the AI technology in the field of human-computer interaction. Here, we report a multimodal artificial sensory-memory system consisting of sensors for generating biomimetic visual, auditory, tactile inputs, and flexible carbon nanotube synaptic transistor that possesses synapse-like signal processing and memorizing behaviors. The transduction of physical signals into information-containing, presynaptic action potentials and the synaptic plasticity of the transistor in response to single and long-term action potential excitations have been systematically characterized. The bioreceptor-like sensing and synapse-like memorizing behaviors have also been demonstrated. On the basis of the memory and learning characteristics of the sensory-memory system, the well-known psychological model describing human memory, the "multistore memory" model, and the classical conditioning experiment that demonstrates the associative learning of brain, "Pavlov's dog's experiment", have both been implemented electronically using actual physical input signals as the sources of the stimuli. The biomimetic intelligence demonstrated in this neurological sensory-memory system shows its potential in promoting the advancement in multimodal, user-environment interactive AI.

Measurement of suction pressure dynamics of sea lampreys, Petromyzon marinus.

Species-specific monitoring activities represent fundamental tools for natural resource management and conservation but require techniques that target species-specific traits or markers. Sea lamprey, a destructive invasive species in the Laurentian Great Lakes and conservation target in North America and Europe, is among very few fishes that possess and use oral suction, yet suction has not been exploited for sea lamprey control or conservation. Knowledge of specific characteristics of sea lamprey suction (e.g., amplitude, duration, and pattern of suction events; hereafter 'suction dynamics') may be useful to develop devices that detect, record, and respond to the presence of sea lamprey at a given place and time. Previous observations were limited to adult sea lampreys in static water. In this study, pressure sensing panels were constructed and used to measure oral suction pressures and describe suction dynamics of juvenile and adult sea lampreys at multiple locations within the mouth and in static and flowing water. Suction dynamics were largely consistent with previous descriptions, but more variation was observed. For adult sea lampreys, suction pressures ranged from -0.6 kPa to -26 kPa with 20 s to 200 s between pumps at rest, and increased to -8 kPa to -70 kPa when lampreys were manually disengaged. An array of sensors indicated that suction pressure distribution was largely uniform across the mouths of both juvenile and adult lampreys; but some apparent variation was attributed to obstruction of sensing portal holes by teeth. Suction pressure did not differ between static and flowing water when water velocity was lower than 0.45 m/s. Such information may inform design of new systems to monitor behavior, distribution and abundance of lampreys.

Quick self-assembly of bio-inspired multi-dimensional well-ordered structures induced by ultrasonic wave energy.

Bottom-up self-assembly of components, inspired by hierarchically self-regulating aggregation of small subunits observed in nature, provides a strategy for constructing two- or three-dimensional intriguing biomimetic materials via the spontaneous combination of discrete building blocks. Herein, we report the methods of ultrasonic wave energy-assisted, fast, two- and three-dimensional mesoscale well-ordered self-assembly of microfabricated building blocks (100 µm in size). Mechanical vibration energy-driven self-assembly of microplatelets at the water-air interface of inverted water droplets is demonstrated, and the real-time formation process of the patterned structure is dynamically explored. 40 kHz ultrasonic wave is transferred into microplatelets suspended in a water environment to drive the self-assembly of predesigned well-ordered structures. Two-dimensional self-assembly of microplatelets inside the water phase with a large patterned area is achieved. Stable three-dimensional multi-layered self-assembled structures are quickly formed at the air-water interface. These demonstrations aim to open distinctive and effective ways for new two-dimensional surface coating technology with autonomous organization strategy, and three-dimensional complex hierarchical architectures built by the bottom-up method and commonly found in nature (such as nacre, bone or enamel, etc.).

Flexible Carbon Nanotube Synaptic Transistor for Neurological Electronic Skin Applications.

There is an increasing interest in the development of memristive or artificial synaptic devices that emulate the neuronal activities for neuromorphic computing applications. While there have already been many reports on artificial synaptic transistors implemented on rigid substrates, the use of flexible devices could potentially enable an even broader range of applications. In this paper, we report artificial synaptic thin-film transistors built on an ultrathin flexible substrate using high carrier mobility semiconducting single-wall carbon nanotubes. The synaptic characteristics of the flexible synaptic transistor including long-term/short-term plasticity, spike-amplitude-dependent plasticity, spike-width-dependent plasticity, paired-pulse facilitation, and spike-time-dependent plasticity have all been systematically characterized. Furthermore, we have demonstrated a flexible neurological electronic skin and its peripheral nerve with a flexible ferroelectret nanogenerator (FENG) serving as the sensory mechanoreceptor that generates action potentials to be processed and transmitted by the artificial synapse. In such neurological electronic skin, the flexible FENG sensor converts the tactile input (magnitude and frequency of force) into presynaptic action potential pulses, which are then passed to the gate of the synaptic transistor to induce change in its postsynaptic current, mimicking the modulation of synaptic weight in a biological synapse. Our neurological electronic skin closely imitates the behavior of actual human skin, and it allows for instantaneous detection of force stimuli and offers biological synapse-like behavior to relay the stimulus signals to the next stage. The flexible sensory skin could potentially be used to interface with skeletal muscle fibers for applications in neuroprosthetic devices.

Electrode Effects on Flexible and Robust Polypropylene Ferroelectret Devices for Fully Integrated Energy Harvesters.

This work presents a characterization study of the electrode interface in polypropylene ferroelectret nanogenerators. An emphasis is made on the comparison of carbon nanotube fiber electrodes with traditional metallic thin film electrodes. Multiple experiments were performed on samples with the same electrode dimensions for a range of applied pressures. Results showed higher open-circuit voltage peak values for the thin film metal electrodes, regardless of the applied pressure. Interestingly, the difference in short-circuit current values between metal and carbon nanotube-based fiber electrodes was not as significant. The carbon nanotube fiber electrode was further investigated by post-treating the fiber with acetone and comparing the results with untreated carbon nanotube film electrodes and thin film metal electrodes. In an effort to enable a monolithic integration of ferroelectret energy harvesters with flexible energy storage elements, this work also presents studies on generation and leakage of induced free charge in the electrodes of flexible ferroelectret energy harvesters. It was found the current leakage through parasitic elements is a faster process than dipole relaxation in the polypropylene film. Finally, an electrode reliability study shows no significant difference in the electrical output of the devices with metallic thin film electrodes after single folding but shows a significant deterioration after crumpling; meanwhile, these processes had no effect on the performance of similar devices with carbon nanotube fiber-based electrodes.

Ferroelectret Nanogenerators for Loudspeaker Applications: A Comprehensive Study.

A ferroelectret nanogenerator (FENG) was recently developed as a flexible energy harvesting device with bi-directional capability between electrical and mechanical energy domains, and its use as a loudspeaker/microphone was demonstrated. Dependencies of Sound Pressure Levels (SPLs) generated by FENG due to an AC voltage stimulus, surface area, geometric shape, and addition of layers are presented here. Also, the relation between the sound output to the electrical input is studied and shown to be linear, which demonstrates that these flexible loudspeakers have low distortion within the human audible range of 20 Hz to 20 kHz. A study for ultrasonic frequencies up to 40 kHz is also presented. A theoretical model relating the electrical and acoustical domain of the FENG is developed based on the experimental observations made and using Boundary Element Methods (BEM) to accurately mimic the testing environment for simulation purposes. The comparison between this model and the actual behavior is presented under several cases and observed to be closely correlated.

Flexible Ferroelectret Polymer for Self-Powering Devices and Energy Storage Systems.

Applying flexible materials for energy scavenging from ambient mechanical vibrations is a clean energy solution that can help alleviate electrical power demands in portable devices and wearable electronics. This work presents fundamental studies on a flexible ferroelectret polymer with a strong piezoelectric effect and its interface with self-powered and energy storage systems. A single-layered device with a thickness of 80 µm was used for characterizing the device's output voltage, current, transferred charge, and energy conversion efficiency. The potential capability of harvesting mechanical energy and delivering to system load is demonstrated by integrating the device into a fully integrated power management system. The theory for determining the harvested energy that is ultimately delivered to external electronic loads (or stored in a battery) is discussed. The maximum power delivery is found to be for a 600 MΩ load, which results in a device power density of 14.0 W/m3 for input mechanical forces with a frequency around 2 Hz.