High throughput microfluidics-based synthesis of PEGylated liposomes for precise size control and efficient drug encapsulation.

The low scalability and reproducibility of existing synthesis methods have hindered the translation of liposome nanoparticles as carriers for targeted drug delivery from conventional laboratory techniques to mass production. To this end, in this study, we present a high-throughput microfluidics-based approach for the synthesis of PEGylated liposomes with a primary focus on achieving precise size control and efficient encapsulation of hydrophobic drug molecules. In this platform, liposomes were self-assembled through a controllable mixing of lipids (EYPC, cholesterol, and DSPE-PEG 2000) dissolved in ethanol and an aqueous solution. The key parameters, including the chip design, total flow rate, flow rate ratio, lipid concentrations, as well as variations in buffer (HEPES and NaCl) and solvent composition (commercial and reagent-grade ethanol) were explored in detail. Through comprehensive parametric studies, we gained valuable insights into the influence of these variables on the size distribution of liposomes and succeeded in producing highly reproducible liposomes ranging from approximately 60 nm (corresponding to small unilamellar vesicles) to 150 nm (representing large unilamellar vesicles), all while maintaining a polydispersity index (PDI) of less than 0.2. To assess the encapsulation efficiency of hydrophobic drug molecules, Nile red (NR) was employed as a surrogate. We meticulously examined the impact of NR concentration on the drug encapsulation process, resulting in up to 74% drug encapsulation efficiency within the PEGylated liposomes. This research offers crucial advances in liposome synthesis and drug delivery, providing a high-throughput, controllable method for PEGylated liposomes with potential in pharmaceutical and biomedical fields.

Self-powered triboelectric nanogenerator sensor for detecting humidity level and monitoring ethanol variation in a simulated exhalation environment.

Respiration stands as a vital process reflecting physiological and pathological human health status. Exhaled breath analysis offers a facile, non-invasive, swift, and cost-effective approach for diagnosing and monitoring diseases by detecting concentration changes of specific biomarkers. In this study, we employed Polyethylene oxide/copper (I) oxide composite nanofibers (PCNFs), synthesized via the electrospinning method as the sensing material to measure ethanol levels (1-200 ppm) in an exhaled breath simulator environment. The integrated contact-separation triboelectric nanogenerator was utilized to power the self-powered PCNFs exhaled breath sensor. The PCNFs-based gas sensor demonstrates promising results with values of 0.9 and 3.2 for detecting 5 ppm and 200 ppm ethanol, respectively, in the presence of interfering gas at 90% relative humidity (RH). Notably, the sensor displayed remarkable ethanol selectivity, with ratios of 10:1 to methanol and 25:1 to acetone. Response and recovery times for 200 ppm ethanol at 90 RH% were rapid, at 2.7 s and 5.8 s, respectively. The PCNFs-based exhaled breath sensor demonstrated consistent and stable performance in practical conditions, showcasing its potential for integration into wearable devices. This self-powered breath sensor enabling continuous monitoring of lung cancer symptoms and facilitating compliance checks with legal alcohol consumption limits.

Highly selective molecularly imprinted polymer nanoparticles (MIP NPs)-based microfluidic gas sensor for tetrahydrocannabinol (THC) detection.

A highly selective microfluidic integrated metal oxide gas sensor for THC detection is reported based on MIP nanoparticles (MIP NPs). We synthesized MIP NPs with THC recognition sites and coated them on a 3D-printed microfluidic channel surface. The sensitivity and selectivity of coated microfluidic integrated gas sensors were evaluated by exposure to THC, cannabidiol (CBD), methanol, and ethanol analytes in 300-700 ppm at 300 °C. For comparison, reference signals were obtained from a microfluidic channel coated with nonimprinted polymers (NIP NPs). The MIP and NIP NPs were characterized using scanning electron microscopy (SEM) and Raman spectroscopy. MIP and NIP NPs channels response data were combined and classified with 96.3% accuracy using the Fine KNN classification model in MATLAB R2021b Classification Learner App. Compared to the MIP NPs coated channel, the NIP NPs channel had poor selectivity towards THC, demonstrating that the THC recognition sites in the MIP structure enabled selective detection of THC. The findings demonstrated that the recognition sites of MIP NPs properly captured THC molecules, enabling the selective detection of THC compared to CBD, methanol, and ethanol.

Microplastic in situ detection based on a portable triboelectric microfluidic sensor.

Microplastics (MPs) are a size-based category of plastic pollutants between 1 µm to 5 mm in particle size that are ubiquitous in land and water resources due to anthropogenic activity. Current methodologies for MPs identification and characterization require laboratory instruments and specialized training. In the present study, a miniaturized microfluidic triboelectric sensor (M-TES) is proposed for the rapid detection of MPs from water samples. The viability and versatility of this device is illustrated for in situ measurement of the size and concentration of polystyrene (PS) micro-particles in water. The M-TES sensor relies on inducing and measuring electrical charges generated by microplastic flow within water droplets passing through a microfluidic channel. The experimental samples encompass pure polystyrene (PS) microparticles ranging from 500 nm to 10 µm, as well as actual samples collected from a coffee machine. The results reveal that the sensor's response exhibits a linear correlation with the increase in both microplastic size and concentration. The proposed sensing system could distinguish between microplastics of different sizes and concentrations. The results demonstrate the applicability of the M-TES in the field of sensors for environmental monitoring.

Microfluidic integrated gas sensors for smart analyte detection: a comprehensive review.

The utilization of gas sensors has the potential to enhance worker safety, mitigate environmental issues, and enable early diagnosis of chronic diseases. However, traditional sensors designed for such applications are often bulky, expensive, difficult to operate, and require large sample volumes. By employing microfluidic technology to miniaturize gas sensors, we can address these challenges and usher in a new era of gas sensors suitable for point-of-care and point-of-use applications. In this review paper, we systematically categorize microfluidic gas sensors according to their applications in safety, biomedical, and environmental contexts. Furthermore, we delve into the integration of various types of gas sensors, such as optical, chemical, and physical sensors, within microfluidic platforms, highlighting the resultant enhancements in performance within these domains.

Exhaled Breath Analysis for Diabetes Diagnosis and Monitoring: Relevance, Challenges and Possibilities.

With the global population prevalence of diabetes surpassing 463 million cases in 2019 and diabetes leading to millions of deaths each year, there is a critical need for feasible, rapid, and non-invasive methodologies for continuous blood glucose monitoring in contrast to the current procedures that are either invasive, complicated, or expensive. Breath analysis is a viable methodology for non-invasive diabetes management owing to its potential for multiple disease diagnoses, the nominal requirement of sample processing, and immense sample accessibility; however, the development of functional commercial sensors is challenging due to the low concentration of volatile organic compounds (VOCs) present in exhaled breath and the confounding factors influencing the exhaled breath profile. Given the complexity of the topic and the skyrocketing spread of diabetes, a multifarious review of exhaled breath analysis for diabetes monitoring is essential to track the technological progress in the field and comprehend the obstacles in developing a breath analysis-based diabetes management system. In this review, we consolidate the relevance of exhaled breath analysis through a critical assessment of current technologies and recent advancements in sensing methods to address the shortcomings associated with blood glucose monitoring. We provide a detailed assessment of the intricacies involved in the development of non-invasive diabetes monitoring devices. In addition, we spotlight the need to consider breath biomarker clusters as opposed to standalone biomarkers for the clinical applicability of exhaled breath monitoring. We present potential VOC clusters suitable for diabetes management and highlight the recent buildout of breath sensing methodologies, focusing on novel sensing materials and transduction mechanisms. Finally, we portray a multifaceted comparison of exhaled breath analysis for diabetes monitoring and highlight remaining challenges on the path to realizing breath analysis as a non-invasive healthcare approach.

Enhancement of self-powered humidity sensing of graphene oxide-based triboelectric nanogenerators by addition of graphene oxide nanoribbons.

A triboelectric nanogenerator (TENG) electrode sensitive to the adsorption of water molecules has been introduced to create a self-powered humidity sensor. Graphene oxide (GO) nanosheets and graphene oxide nanoribbon (GONR) possessing oxygenated functional groups, as well as high dielectric constants, have been proposed as appropriate candidates for this purpose. GO papers have been fabricated in three forms, i.e. pure  GO paper, uniform composites of GONR and GO, and double-layer structures of GONR on top of  GO. Results showed that all of the prepared paper-based TENGs revealed excellent performances by maximum output voltage above 300 V. As active humidity sensors, the maximum voltage response values of 57%, 124%, and 78% were obtained for GO, GONR+GO, and GONR/GO TENGs, respectively. Besides high sensitivity and precision of all variants, GO+GONR TENG demonstrated a rapid response/recovery behavior (0.3/0.5 s). This phenomenon can be attributed to the higher oxygenated groups and defects on the edges of GONR, which leads to facilitating the bulk diffusion of water molecules. Our results open new avenues of GONR application as an additive to enhance the performance of self-powered humidity sensors, as well as conventional hygrometers.

Graphene Oxide Papers in Nanogenerators for Self-Powered Humidity Sensing by Finger Tapping.

Triboelectric nanogenerators (TENGs) offer an emerging market of self-sufficient power sources, converting the mechanical energy of the environment to electricity. Recently reported high power densities for the TENGs provide new applications opportunities, such as self-powered sensors. Here in this research, a flexible graphene oxide (GO) paper was fabricated through a straightforward method and utilized as the electrode of TENGs. Outstanding power density as high as 1.3 W.m-2, an open-circuit voltage up to 870 V, and a current density of 1.4 µA.cm-2 has been extracted in vertical contact-separation mode. The all-flexible TENG has been employed as a self-powered humidity sensor to investigate the effect of raising humidity on the output voltage and current by applying mechanical agitation in two forms of using a tapping device and finger tapping. Due to the presence of superficial functional groups on the GO paper, water molecules are inclined to be adsorbed, resulting in a considerable reduction in both generated voltage (from 144 V to 14 V) and current (from 23 µA to 3.7 µA) within the range of relative humidity of 20% to 99%. These results provide a promising applicability of the first suggested sensitive self-powered GO TENG humidity sensor in portable/wearable electronics.

A Novel Approach in Sorting Chirality Species of Single-Wall Carbon Nanotubes Based on an Aqueous Two-Phase System of Polymer-Salt.

Sorting of distinct (n, m) chirality species of single-wall carbon nanotubes (SWCNTs) is essential for progress in technical applications in the field of electronic and optic devices. The purpose of this study is to investigate the isolation of single-wall carbon nanotubes based on diameters/chirality in a polymer-salt (polyethylene glycol and sodium citrate) aqueous two-phase system (ATPS) a substitute for common polymer-polymer (polyethylene glycol and dextran) system. The ATPS based on polymer-salt used instead of the common polymer-polymer system due to low viscosity, reduced surface tension, and lower cost of sodium citrate compared to the dextran. For this purpose, the ratio of concentrations of polyethylene glycol to sodium citrate as well as the effect of temperature on the isolation are both investigated and the selectivity and the recovery estimated approximately. The absorbance spectra from both top and bottom phases at different polymer and salt contents and at different temperatures show that by using this system in optimal conditions of polymer to salt ratio of 2:1 at temperature of 20 °C, a suitable separation of nanotubes with 85% yield of the chiral groups of 9 and 10 can be obtained.

A graphene/TiS3 heterojunction for resistive sensing of polar vapors at room temperature.

The room temperature polar vapor sensing behavior of a graphene-TiS3 heterojunction material and TiS3 nanoribbons is described. The nanoribbons were synthesized via chemical vapor transport (CVT) and their structure was investigated by scanning electron microscopy, high resolution transmission electron microscopy, energy dispersive X-ray spectroscopy, X-ray diffraction, Raman and Fourier transform infrared spectroscopies. The gas sensing performance was assessed by following the changes in their resistivities. Sensing devices were fabricated with gold contacts and with lithographically patterned graphene (Gr) electrodes in a heterojunction Gr-TiS3-Gr. The gold contacted TiS3 device has a rather linear I-V behavior while the Gr-TiS3-Gr heterojunction forms a contact with a higher Schottky barrier (250 meV). The I-V responses of the sensors were recorded at room temperature at a relative humidity of 55% and for different ethanol vapor concentrations (varying from 2 to 20 ppm). The plots indicate an increase in the resistance of Gr-TiS3-Gr due to adsorption of water and ethanol with a relatively high sensing response (~495% at 2 ppm). The results reveal that stable responses to 2 ppm concentrations of ethanol are achieved at room temperature. The response and recovery times are around 8 s and 72 s, respectively. Weaker responses are obtained for methanol and acetone. Graphical abstract Schematic representation of resistance sensor for detection of low concentration of ethanol vapor. The graphene and TiS3 nanoribbons were synthesized using chemical vapor deposition and chemical vapor transport technique respectively. The 2D graphene/TiS3 heterojunction device was fabricated to make a high response sensor due to their synergy effect.

Optimization of Porous Silicon Conditions for DNA-based Biosensing via Reflectometric Interference Spectroscopy.

OBJECTIVE: Substantial effort has been put into designing DNA-based biosensors, which are commonly used to detect presence of known sequences including the quantification of gene expression. Porous silicon (PSi), as a nanostructured base, has been commonly used in the fabrication of optimally transducing biosensors. Given that the function of any PSi-based biosensor is highly dependent on its nanomorphology, we systematically optimized a PSi biosensor based on reflectometric interference spectroscopy (RIS) detecting the high penetrance breast cancer susceptibility gene, BRCA1. MATERIALS AND METHODS: In this experimental study, PSi pore sizes on the PSi surface were controlled for optimum filling with DNA oligonucleotides and surface roughness was optimized for obtaining higher resolution RIS patterns. In addition, the influence of two different organic electrolyte mixtures on the formation and morphology of the pores, based on various current densities and etching times on doped p-type silicon, were examined. Moreover, we introduce two cleaning processes which can efficiently remove the undesirable outer parasitic layer created during PSi formation. Results of all the optimization steps were observed by field emission scanning electron microscopy (FE-SEM). RESULTS: DNA sensing reached its optimum when PSi was formed in a two-step process in the ethanol electrolyte accompanied by removal of the parasitic layer in NaOH solution. These optimal conditions, which result in pore sizes of approximately 20 nm as well as a low surface roughness, provide a considerable RIS shift upon complementary sequence hybridization, suggesting efficient detectability. CONCLUSION: We demonstrate that the optimal conditions identified here makes PSi an attractive solid-phase DNA-based biosensing method and may be used to not only detect full complementary DNA sequences, but it may also be used for detecting point mutations such as single nucleotide substitutions and indels.

Computational investigation of gas detection and selectivity on TiS3 nanoflakes supported by experimental evidence.

Titanium trisulfide (TiS3), a transition metal chalcogenide, bears the potential to replace silicon, when taking the form of nanoflakes, due to its favorable band gap and optical response. In this paper, we investigate the response of TiS3 nanoflakes to gas detection through a careful quantum computational approach and a few succinct measurements. The computations are benchmarked and compared with a relevant experiment at each step, where their results/conclusions are discussed. The most stable surface of TiS3 particles is determined as (001), in agreement with the literature. The adsorption of 5 gas molecules is characterized through formulating and estimating their adsorption intensity values, rather than using singled-out values of binding energies. This formulation, which is rooted in a statistical view of the gas adsorption process, distinguishes H2 and CH4 molecules from H2O and O2 explicitly and unambiguously through comparing their adsorption profiles. The difference in the adsorption intensities thus predicts and elucidates the difference in the sensing behaviour of TiS3 particles. This work suggests that the computationally obtained profile for the adsorption spectrum of gas molecules serves as a tool/criterion to predict the selectivity of their detection by TiS3.

Hydrogen sensing properties of nanocomposite graphene oxide/Co-based metal organic frameworks (Co-MOFs@GO).

This paper reports on hydrogen sensing based graphene oxide hybrid with Co-based metal organic frameworks (Co-MOFs@GO) prepared by the hydrothermal process. The texture and morphology of the hybrid were characterized by powder x-ray diffraction, scanning electron microscopy and Brunauer-Emmett-Teller analysis. Porous flower like structures assembled from Co-MOFs and GO flakes with sufficient specific surface area are obtained, which are ideal for gas molecules diffusion and interactions. Sensing performance of Co-MOFs@GO were tested and also improved by sputtering platinum (Pt) as a catalyst. The Pt-sputtered Co-MOFs@GO show outstanding hydrogen resistive-sensing with response and recovery times below 12 s at 15 °C. Also, they show stable, repeatable and selective responses to the target gas which make it suitable for the development of a high performance hydrogen sensor.