Correction: Highly-sensitive wafer-scale transfer-free graphene MEMS condenser microphones.

[This corrects the article DOI: 10.1038/s41378-024-00656-x.].

Peptide-Based Flavivirus Biosensors: From Cell Structure to Virological and Serological Detection Methods.

In tropical and developing countries, mosquito-borne diseases by flaviviruses pose a serious threat to public health. Early detection is critical for preventing their spread, but conventional methods are time-consuming and require skilled technicians. Biosensors have been developed to address this issue, but cross-reactivity with other flaviviruses remains a challenge. Peptides are essentially biomaterials used in diagnostics that allow virological and serological techniques to identify flavivirus selectively. This biomaterial originated as a small protein consisting of two to 50 amino acid chains. They offer flexibility in chemical modification and can be easily synthesized and applied to living cells in the engineering process. Peptides could potentially be developed as robust, low-cost, sensitive, and selective receptors for detecting flaviviruses. However, modification and selection of the receptor agents are crucial to determine the effectiveness of binding between the targets and the receptors. This paper addresses two potential peptide nucleic acids (PNAs) and affinity peptides that can detect flavivirus from another target-based biosensor as well as the potential peptide behaviors of flaviviruses. The PNAs detect flaviviruses based on the nucleotide base sequence of the target's virological profile via Watson-Crick base pairing, while the affinity peptides sense the epitope or immunological profile of the targets. Recent developments in the functionalization of peptides for flavivirus biosensors are explored in this Review by division into electrochemical, optical, and other detection methods.

Unlocking High-Current Performance in Silicon Anode: Synergistic Phosphorus Doping and Nitrogen-Doped Carbon Encapsulation to Enhance Lithium Diffusivity.

The silicon (Si) offers enormous theoretical capacity as a lithium-ion battery (LIB) anode. However, the low charge mobility in Si particles hinders its application for high current loading. In this study, ball-milled phosphorus-doped Si nanoparticles encapsulated with nitrogen-doped carbon (P-Si@N-C) are employed as an anode for LIBs. P-doped Si nanoparticles are first obtained via ball-milling and calcination of Si with phosphoric acid. N-doped carbon encapsulation is then introduced via carbonization of the surfactant-assisted polymerization of pyrrole monomer on P-doped Si. While P dopant is required to support the stability at high current density, the encapsulation of Si particles with N-doped carbon is influential in enhancing the overall Li+ diffusivity of the Si anode. The combined approaches improve the anode's Li+ diffusivity up to tenfold compared to the untreated anode. It leads to exceptional anode stability at a high current, retaining 87 % of its initial capacity under a large current rate of 4000 mA g-1. The full-cell comprising P-Si@N-C anode and LiFePO4 cathode demonstrates 94 % capacity retention of its initial capacity after 100 cycles at 1 C. This study explores the effective strategies to improve Li+ diffusivity for high-rate Si-based anode.

Highly-sensitive wafer-scale transfer-free graphene MEMS condenser microphones.

Since the performance of micro-electro-mechanical system (MEMS)-based microphones is approaching fundamental physical, design, and material limits, it has become challenging to improve them. Several works have demonstrated graphene's suitability as a microphone diaphragm. The potential for achieving smaller, more sensitive, and scalable on-chip MEMS microphones is yet to be determined. To address large graphene sizes, graphene-polymer heterostructures have been proposed, but they compromise performance due to added polymer mass and stiffness. This work demonstrates the first wafer-scale integrated MEMS condenser microphones with diameters of 2R = 220-320 µm, thickness of 7 nm multi-layer graphene, that is suspended over a back-plate with a residual gap of 5 µm. The microphones are manufactured with MEMS compatible wafer-scale technologies without any transfer steps or polymer layers that are more prone to contaminate and wrinkle the graphene. Different designs, all electrically integrated are fabricated and characterized allowing us to study the effects of the introduction of a back-plate for capacitive read-out. The devices show high mechanical compliances Cm = 0.081-1.07 µmPa-1 (10-100 × higher than the silicon reported in the state-of-the-art diaphragms) and pull-in voltages in the range of 2-9.5 V. In addition, to validate the proof of concept, we have electrically characterized the graphene microphone when subjected to sound actuation. An estimated sensitivity of S1kHz = 24.3-321 mV Pa-1 for a Vbias = 1.5 V was determined, which is 1.9-25.5 × higher than of state-of-the-art microphone devices while having a ~9 × smaller area.

Advanced biopolymer-based edible coating technologies for food preservation and packaging.

Along with the growth of the world's population that reduces the accessibility of arable land and water, demand for food, as the fundamental element of human beings, has been continuously increasing each day. This situation not only becomes a challenge for the modern food chain systems but also affects food availability throughout the world. Edible coating is expected to play a significant role in food preservation and packaging, where this technique can reduce the number of food loss and subsequently ensure more sustainable food and agriculture production through various mechanisms. This review provides comprehensive information related to the currently available advanced technologies of coating applications, which include advanced methods (i.e., nanoscale and multilayer coating methods) and advanced properties (i.e., active, self-healing, and super hydrophobic coating properties). Furthermore, the benefits and drawbacks of those technologies during their applications on foods are also discussed. For further research, opportunities are foreseen to develop robust edible coating methods by combining multiple advanced technologies for large-scale and more sustainable industrial production.

Surface plasmon resonance biosensor chips integrated with MoS2-MoO3 hybrid microflowers for rapid CFP-10 tuberculosis detection.

This study reports on the modification of surface plasmon resonance (SPR) chips with molybdenum disulfide-molybdenum trioxide (MoS2-MoO3) microflowers to detect the tuberculosis (TB) markers of CFP-10. The MoS2-MoO3 microflowers were prepared by hydrothermal methods with variations in the pH and amount of trisodium citrate (Na3Ct), which were projected to influence the shape and size of microflower particles. The analysis shows that optimum MoS2-MoO3 hybrid microflowers were obtained at neutral pH using 0.5 g Na3Ct. The modified SPR biosensor exhibits a ten times higher response than the bare Au. Moreover, increasing MoS2-MoO3 thickness results in a higher detection response, sensitivity, and a smaller limit of detection (LOD). Using the optimized material composition, the Au/MoS2-MoO3-integrated SPR sensor can demonstrate sensitivity and LOD of 1.005 and 3.45 ng mL-1, respectively. This biosensor also has good selectivity, stability, and reproducibility based on cross-sensitivity characterization with other analytes and repeated measurements on several chips with different storing times and fabrication batch. Therefore, this proposed SPR biosensor possesses high potential to be further developed and applied as a detection technology for CFP-10 in monitoring and diagnosing TB.

Dual-Backplate CMUTs With Wide Bandwidth and Low Driving Voltage for Airborne Applications.

In this work, novel airborne capacitive micromachined ultrasonic transducers (CMUTs) based on a dual-backplate (DBP) technology are presented. In contrast to conventional CMUTs, these transducers use a three-electrode-based capacitive system, where the membrane is placed between two highly-perforated counter electrodes, enabling enlarged displacement amplitudes in electrostatic actuation and wide and tunable bandwidth (BW) due to a ventilated air cavity. Fabricated DBP-CMUT prototypes therefore show exceptionally high receive and transmit sensitivities of -34.5 dB(V/Pa) and 259 nm/V, respectively, in their 84-kHz resonance. The viscous dissipation introduced by ventilating the cavity results in a wide factional BW (FBW) of 29%. Applicability of the developed CMUT for airborne ranging is demonstrated in pulse-echo-based ranging measurements, where the distance of a sound-reflecting metal plate can be clearly detected by a single CMUT operated in a transceiver mode.

Rapid analysis of meat floss origin using a supervised machine learning-based electronic nose towards food authentication.

Authentication of meat floss origin has been highly critical for its consumers due to existing potential risks of having allergic diseases or religion perspective related to pork-containing foods. Herein, we developed and assessed a compact portable electronic nose (e-nose) comprising gas sensor array and supervised machine learning with a window time slicing method to sniff and to classify different meat floss products. We evaluated four different supervised learning methods for data classification (i.e., linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), k-nearest neighbors (k-NN), and random forest (RF)). Among them, an LDA model equipped with five-window-extracted feature yielded the highest accuracy values of >99% for both validation and testing data in discriminating beef, chicken, and pork flosses. The obtained e-nose results were correlated and confirmed with the spectral data from Fourier-transform infrared (FTIR) spectroscopy and gas chromatography-mass spectrometry (GC-MS) measurements. We found that beef and chicken had similar compound groups (i.e., hydrocarbons and alcohol). Meanwhile, aldehyde compounds (e.g., dodecanal and 9-octadecanal) were found to be dominant in pork products. Based on its performance evaluation, the developed e-nose system shows promising results in food authenticity testing, which paves the way for ubiquitously detecting deception and food fraud attempts.

Influence of dopant concentration on the ammonia sensing performance of citric acid-doped polyvinyl acetate nanofibers.

The chemical modification of polymer nanofiber-based ammonia sensors by introducing dopants into the active layers has been proven as one of the low-cost routes to enhance their sensing performance. Herein, we investigate the influence of different citric acid (CA) concentrations on electrospun polyvinyl acetate (PVAc) nanofibers coated on quartz crystal microbalance (QCM) transducers as gravimetric ammonia sensors. The developed CA-doped PVAc nanofiber sensors are tested against various concentrations of ammonia vapors, in which their key sensing performance parameters (i.e., sensitivity, limit of detection (LOD), limit of quantification (LOQ), and repeatability) are studied in detail. The sensitivity and LOD values of 1.34 Hz ppm-1 and 1 ppm, respectively, can be obtained during ammonia exposure assessment. Adding CA dopants with a higher concentration not only increases the sensor sensitivity linearly, but also prolongs both response and recovery times. This finding allows us to better understand the dopant concentration effect, which subsequently can result in an appropriate strategy for manufacturing high-performance portable nanofiber-based sensing devices.

Fast and noninvasive electronic nose for sniffing out COVID-19 based on exhaled breath-print recognition.

The reverse transcription-quantitative polymerase chain reaction (RT-qPCR) approach has been widely used to detect the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, instead of using it alone, clinicians often prefer to diagnose the coronavirus disease 2019 (COVID-19) by utilizing a combination of clinical signs and symptoms, laboratory test, imaging measurement (e.g., chest computed tomography scan), and multivariable clinical prediction models, including the electronic nose. Here, we report on the development and use of a low cost, noninvasive method to rapidly sniff out COVID-19 based on a portable electronic nose (GeNose C19) integrating an array of metal oxide semiconductor gas sensors, optimized feature extraction, and machine learning models. This approach was evaluated in profiling tests involving a total of 615 breath samples composed of 333 positive and 282 negative samples. The samples were obtained from 43 positive and 40 negative COVID-19 patients, respectively, and confirmed with RT-qPCR at two hospitals located in the Special Region of Yogyakarta, Indonesia. Four different machine learning algorithms (i.e., linear discriminant analysis, support vector machine, stacked multilayer perceptron, and deep neural network) were utilized to identify the top-performing pattern recognition methods and to obtain a high system detection accuracy (88-95%), sensitivity (86-94%), and specificity (88-95%) levels from the testing datasets. Our results suggest that GeNose C19 can be considered a highly potential breathalyzer for fast COVID-19 screening.

Hybrid learning method based on feature clustering and scoring for enhanced COVID-19 breath analysis by an electronic nose.

Breath pattern analysis based on an electronic nose (e-nose), which is a noninvasive, fast, and low-cost method, has been continuously used for detecting human diseases, including the coronavirus disease 2019 (COVID-19). Nevertheless, having big data with several available features is not always beneficial because only a few of them will be relevant and useful to distinguish different breath samples (i.e., positive and negative COVID-19 samples). In this study, we develop a hybrid machine learning-based algorithm combining hierarchical agglomerative clustering analysis and permutation feature importance method to improve the data analysis of a portable e-nose for COVID-19 detection (GeNose C19). Utilizing this learning approach, we can obtain an effective and optimum feature combination, enabling the reduction by half of the number of employed sensors without downgrading the classification model performance. Based on the cross-validation test results on the training data, the hybrid algorithm can result in accuracy, sensitivity, and specificity values of (86 ± 3)%, (88 ± 6)%, and (84 ± 6)%, respectively. Meanwhile, for the testing data, a value of 87% is obtained for all the three metrics. These results exhibit the feasibility of using this hybrid filter-wrapper feature-selection method to pave the way for optimizing the GeNose C19 performance.

Intracellular gold nanoparticles influence light scattering and facilitate amplified spontaneous emission generation.

Generation of amplified stimulated emission inside mammalian cells has paved the way for a novel bioimaging and cell sensing approach. Single cells carrying gain media (e.g., fluorescent molecules) are placed inside an optical cavity, allowing the production of intracellular laser emission upon sufficient optical pumping. Here, we investigate the possibility to trigger another amplified emission phenomenon (i.e., amplified spontaneous emission or ASE) inside two different cell types, namely macrophage and epithelial cells from different species and tissues, in the presence of a poorly reflecting cavity. Furthermore, the resulting ASE properties can be enhanced by introducing plasmonic nanoparticles. The presence of gold nanoparticles (AuNPs) in rhodamine 6G-labeled A549 epithelial cells results in higher intensity and lowered ASE threshold in comparison to cells without nanoparticles, due to the effect of plasmonic field enhancement. An increase in intracellular concentration of AuNPs in rhodamine 6G-labeled macrophages is, however, responsible for the twofold increase in the ASE threshold and a reduction in the ASE intensity, dominantly due to a suppressed in and out-coupling of light at high nanoparticle concentrations.

Cellular lasers for cell imaging and biosensing.

The possibility to produce laser action involving biomaterials, in particular (single) biological cells, has fostered the development of cellular lasers as a novel approach in biophotonics. In this respect, cells that are engineered to carry gain medium (e.g., fluorescent dyes or proteins) are placed inside an optical cavity (i.e., typically a sandwich of highly reflective mirrors), allowing the generation of stimulated emission upon sufficient optical pumping. In another scenario, micron-sized optical resonators supporting whispering-gallery mode (WGM) or semiconductor-based laser probes can be internalized by the cells and support light amplification. This review summarizes the recent advances in the fields of biolasers and cellular lasers, and most importantly, highlights their potential applications in the fields of in vitro and in vivo cell imaging and analysis. They include biosensing (e.g., in vitro detection of sodium chloride (NaCl) concentration), cancer cell imaging, laser-emission-based microscope, cell tracking, cell distinction study, and tissue contraction monitoring in zebrafish. Lastly, several fundamental issues in developing cellular lasers including laser probe fabrication, biocompatibility of the system, and alteration of local refractive index of optical cavities due to protein absorption or probe aggregation are described. Cellular lasers are foreseen as a promising tool to study numerous biological and biophysical phenomena. STATEMENT OF SIGNIFICANCE: Biolasers are generation of laser involving biological materials. Biomaterials, including single cells, can be engineered to incorporate laser probes or fluorescent proteins or fluorophores, and the resulting light emission can be coupled to optical resonator, allowing generation of cellular laser emission upon optical pumping. Unlike fluorescence, this stimulated emission is very sensitive and is capable of detecting small alterations in the optical property of the cells and their environment. In this review, recent development and applications of cellular lasers in the fields of in vitro and in vivo cell imaging, cell tracking, biosensing, and cell/tissue analysis are highlighted. Several challenges in developing cellular lasers including probe fabrication and biocompatibility as well as alteration of cellular environment are explained.

Vertically Aligned n-Type Silicon Nanowire Array as a Free-Standing Anode for Lithium-Ion Batteries.

Due to its high theoretical specific capacity, a silicon anode is one of the candidates for realizing high energy density lithium-ion batteries (LIBs). However, problems related to bulk silicon (e.g., low intrinsic conductivity and massive volume expansion) limit the performance of silicon anodes. In this work, to improve the performance of silicon anodes, a vertically aligned n-type silicon nanowire array (n-SiNW) was fabricated using a well-controlled, top-down nano-machining technique by combining photolithography and inductively coupled plasma reactive ion etching (ICP-RIE) at a cryogenic temperature. The array of nanowires ~1 µm in diameter and with the aspect ratio of ~10 was successfully prepared from commercial n-type silicon wafer. The half-cell LIB with free-standing n-SiNW electrode exhibited an initial Coulombic efficiency of 91.1%, which was higher than the battery with a blank n-silicon wafer electrode (i.e., 67.5%). Upon 100 cycles of stability testing at 0.06 mA cm-2, the battery with the n-SiNW electrode retained 85.9% of its 0.50 mAh cm-2 capacity after the pre-lithiation step, whereas its counterpart, the blank n-silicon wafer electrode, only maintained 61.4% of 0.21 mAh cm-2 capacity. Furthermore, 76.7% capacity retention can be obtained at a current density of 0.2 mA cm-2, showing the potential of n-SiNW anodes for high current density applications. This work presents an alternative method for facile, high precision, and high throughput patterning on a wafer-scale to obtain a high aspect ratio n-SiNW, and its application in LIBs.

Versatilely tuned vertical silicon nanowire arrays by cryogenic reactive ion etching as a lithium-ion battery anode.

Production of high-aspect-ratio silicon (Si) nanowire-based anode for lithium ion batteries is challenging particularly in terms of controlling wire property and geometry to improve the battery performance. This report demonstrates tunable optimization of inductively coupled plasma reactive ion etching (ICP-RIE) at cryogenic temperature to fabricate vertically-aligned silicon nanowire array anodes with high verticality, controllable morphology, and good homogeneity. Three different materials [i.e., photoresist, chromium (Cr), and silicon dioxide (SiO2)] were employed as masks during the subsequent photolithography and cryogenic ICP-RIE processes to investigate their effects on the resulting nanowire structures. Silicon nanowire arrays with a high aspect ratio of up to 22 can be achieved by tuning several etching parameters [i.e., temperature, oxygen/sulfur hexafluoride (O2/SF6) gas mixture ratio, chamber pressure, plasma density, and ion energy]. Higher compressive stress was revealed for longer Si wires by means of Raman spectroscopy. Moreover, an anisotropy of lattice stress was found at the top and sidewall of Si nanowire, indicating compressive and tensile stresses, respectively. From electrochemical characterization, half-cell battery integrating ICP-RIE-based silicon nanowire anode exhibits a capacity of 0.25 mAh cm-2 with 16.67% capacity fading until 20 cycles, which has to be improved for application in future energy storage devices.

Wafer-scale transfer route for top-down III-nitride nanowire LED arrays based on the femtosecond laser lift-off technique.

The integration of gallium nitride (GaN) nanowire light-emitting diodes (nanoLEDs) on flexible substrates offers opportunities for applications beyond rigid solid-state lighting (e.g., for wearable optoelectronics and bendable inorganic displays). Here, we report on a fast physical transfer route based on femtosecond laser lift-off (fs-LLO) to realize wafer-scale top-down GaN nanoLED arrays on unconventional platforms. Combined with photolithography and hybrid etching processes, we successfully transferred GaN blue nanoLEDs from a full two-inch sapphire substrate onto a flexible copper (Cu) foil with a high nanowire density (~107 wires/cm2), transfer yield (~99.5%), and reproducibility. Various nanoanalytical measurements were conducted to evaluate the performance and limitations of the fs-LLO technique as well as to gain insights into physical material properties such as strain relaxation and assess the maturity of the transfer process. This work could enable the easy recycling of native growth substrates and inspire the development of large-scale hybrid GaN nanowire optoelectronic devices by solely employing standard epitaxial LED wafers (i.e., customized LED wafers with additional embedded sacrificial materials and a complicated growth process are not required).

Performance of an Electrothermal MEMS Cantilever Resonator with Fano-Resonance Annoyance under Cigarette Smoke Exposure.

An electrothermal piezoresistive cantilever (EPC) sensor is a low-cost MEMS resonance sensor that provides self-actuating and self-sensing capabilities. In the platform, which is of MEMS-cantilever shape, the EPC sensor offers several advantages in terms of physical, chemical, and biological sensing, e.g., high sensitivity, low cost, simple procedure, and quick response. However, a crosstalk effect is generated by the coupling of parasitic elements from the actuation part to the sensing part. This study presents a parasitic feedthrough subtraction (PFS) method to mitigate a crosstalk effect in an electrothermal piezoresistive cantilever (EPC) resonance sensor. The PFS method is employed to identify a resonance phase that is, furthermore, deployed to a phase-locked loop (PLL)-based system to track and lock the resonance frequency of the EPC sensor under cigarette smoke exposure. The performance of the EPC sensor is further evaluated and compared to an AFM-microcantilever sensor and a commercial particle counter (DC1100-PRO). The particle mass-concentration measurement result generated from cigarette-smoke puffs shows a good agreement between these three detectors.

Nonmechanical parfocal and autofocus features based on wave propagation distribution in lensfree holographic microscopy.

Performing long-term cell observations is a non-trivial task for conventional optical microscopy, since it is usually not compatible with environments of an incubator and its temperature and humidity requirements. Lensless holographic microscopy, being entirely based on semiconductor chips without lenses and without any moving parts, has proven to be a very interesting alternative to conventional microscopy. Here, we report on the integration of a computational parfocal feature, which operates based on wave propagation distribution analysis, to perform a fast autofocusing process. This unique non-mechanical focusing approach was implemented to keep the imaged object staying in-focus during continuous long-term and real-time recordings. A light-emitting diode (LED) combined with pinhole setup was used to realize a point light source, leading to a resolution down to 2.76 µm. Our approach delivers not only in-focus sharp images of dynamic cells, but also three-dimensional (3D) information on their (x, y, z)-positions. System reliability tests were conducted inside a sealed incubator to monitor cultures of three different biological living cells (i.e., MIN6, neuroblastoma (SH-SY5Y), and Prorocentrum minimum). Altogether, this autofocusing framework enables new opportunities for highly integrated microscopic imaging and dynamic tracking of moving objects in harsh environments with large sample areas.

Intelligent Mobile Electronic Nose System Comprising a Hybrid Polymer-Functionalized Quartz Crystal Microbalance Sensor Array.

We devised a low-cost mobile electronic nose (e-nose) system using a quartz crystal microbalance (QCM) sensor array functionalized with various polymer-based thin active films (i.e., polyacrylonitrile, poly(vinylidene fluoride), poly(vinyl pyrrolidone), and poly(vinyl acetate)). It works based on the gravimetric detection principle, where the additional mass of the adsorbed molecules on the polymer surface can induce QCM resonance frequency shifts. To collect and process the obtained sensing data sets, a multichannel data acquisition (DAQ) circuitry was developed and calibrated using a function generator resulting in a device frequency resolution of 0.5 Hz. Four prepared QCM sensors demonstrated various sensitivity levels with high reproducibility and consistency under exposure to seven different volatile organic compounds (VOCs). Moreover, two types of machine learning algorithms (i.e., linear discriminant analysis and support vector machine models) were employed to differentiate and classify those tested analytes, in which classification accuracies of up to 98 and 99% could be obtained, respectively. This high-performance e-nose system is expected to be used as a versatile sensing platform for performing reliable qualitative and quantitative analyses in complex gaseous mixtures containing numerous VOCs for early disease diagnosis and environmental quality monitoring.

Visible Light-Driven p-Type Semiconductor Gas Sensors Based on CaFe2O4 Nanoparticles.

In this work, we present conductometric gas sensors based on p-type calcium iron oxide (CaFe2O4) nanoparticles. CaFe2O4 is a metal oxide (MOx) with a bandgap around 1.9 eV making it a suitable candidate for visible light-activated gas sensors. Our gas sensors were tested under a reducing gas (i.e., ethanol) by illuminating them with different light-emitting diode (LED) wavelengths (i.e., 465-640 nm). Regardless of their inferior response compared to the thermally activated counterparts, the developed sensors have shown their ability to detect ethanol down to 100 ppm in a reversible way and solely with the energy provided by an LED. The highest response was reached using a blue LED (465 nm) activation. Despite some responses found even in dark conditions, it was demonstrated that upon illumination the recovery after the ethanol exposure was improved, showing that the energy provided by the LEDs is sufficient to activate the desorption process between the ethanol and the CaFe2O4 surface.