Flow Micro Research Articles

A Machine Learning Assisted Non-Enzymatic Electrochemical Biosensor to Detect Urea Based on Multi-Walled Carbon Nanotube Functionalized with Copper Oxide Micro-Flowers.

Detecting urea is crucial for diagnosing related health conditions and ensuring timely medical intervention. The addition of machine learning (ML) technologies has completely changed the field of biochemical sensing, providing enhanced accuracy and reliability. In the present work, an ML-assisted screen-printed, flexible, electrochemical, non-enzymatic biosensor was proposed to quantify urea concentrations. For the detection of urea, the biosensor was modified with a multi-walled carbon nanotube-zinc oxide (MWCNT-ZnO) nanocomposite functionalized with copper oxide (CuO) micro-flowers (MFs). Further, the CuO-MFs were synthesized using a standard sol-gel approach, and the obtained particles were subjected to various characterization techniques, including X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), and Fourier transform infrared (FTIR) spectroscopy. The sensor's performance for urea detection was evaluated by assessing the dependence of peak currents on analyte concentration using cyclic voltammetry (CV) at different scan rates of 50, 75, and 100 mV/s. The designed non-enzymatic biosensor showed an acceptable linear range of operation of 0.5-8 mM, and the limit of detection (LoD) observed was 78.479 nM, which is well aligned with the urea concentration found in human blood and exhibits a good sensitivity of 117.98 mA mM-1 cm-2. Additionally, different regression-based ML models were applied to determine CV parameters to predict urea concentrations experimentally. ML significantly improves the accuracy and reliability of screen-printed biosensors, enabling accurate predictions of urea levels. Finally, the combination of ML and biosensor design emphasizes not only the high sensitivity and accuracy of the sensor but also its potential for complex non-enzymatic urea detection applications. Future advancements in accurate biochemical sensing technologies are made possible by this strong and dependable methodology.

Numerical modeling and experimental validation of fluid flow in micro- and meso-fluidic siphons

Siphons have been used for thousands of years to transfer fluids without the use of pumps or power and are present in our daily lives. Paradoxically, it is only in recent decades that the operation of siphons has been fully clarified, which is now understood to be exclusively linked to gravity and molecular cohesion. Siphons are uniquely able to offer automatic, intermittent flow, yet present the main drawback of requiring a source of energy to induce initial flow. Our research team has recently disclosed a microfluidic siphon able to self-prime and deliver a sequence of bioanalytical reagents, previously demonstrated for high-performance, multi-reagents diagnostic testing. Here we show for the first time 2D and 3D computational fluid dynamics (CFD) modeling and the experimental characterization of fluid flow in a range of miniaturized hydrophilic siphons of varying hydraulic liquid height-to-length ratios, ΔH/LT = 0–0.9, using fluids of varying viscosities. CFD simulations using velocity- and pressure-driven inlet boundary conditions were generally in good agreement with experimental fluid flow rates and pressure-balance predictions for plastic ∼0.2 mm and glass ∼0.6 mm internal diameter microfluidic siphons. CFD predictions of fluid flow in “meso-scale” siphons with 1 and 2 mm internal diameters also fully matched normalized experimental data, suggesting that miniaturized siphons are scalable. Their discharge rate and pressure drop are readily predicted and fine-tunable through the physical properties of the fluid and some design parameters of the siphon. The wide range of experimental and numerical parameters studied here provide an important framework for the design and application of gravity-driven micro- and meso-fluidic siphons in many applications, including but not limited to life sciences, clinical diagnostics, and process intensification.

Efficient continuous synthesis of long-chain alkylbenzenes catalyzed by ionic liquids in microreaction systems

Alkylbenzene (LAB) is an important benzene derivative that can be used as a raw material for high-performance anionic surfactants such as alkylbenzene sulfonates (LAS) to meet the new requirements for surfactants in many fields. LAB can be synthesized through Friedel-Crafts reaction in the presence of acidic catalysts as alkylating agents, which is commonly used in the production of fine chemicals. In this work, a novel and efficient continuous flow micro reaction system was introduced to enhance the production of long-chain alkylbenzene catalyzed by [(CH3)3NH][Al2Cl7] ionic liquid. The optimal conditions were investigated for the synthesis of long-chain alkylbenzenes with the 1-tetradecene and mixing α-alkenes of C14-C16 from Fischer-Tropsch process. The results showed that the yield of benzene alkylation can achieve 99 % under the optimal process conditions which the reaction tube length was 2000 mm, the reaction temperature was 30 ℃, the catalyst dosage was 0.30 mL/min and the molar ratio of aluminum chloride to trimethylamine hydrochloride was 2:1. In addition, α-alkenes with C14-C16 lead to deactivation of the ionic liquids catalyst easier because of transfer of AlCl3 from the ionic liquid to the organic phase compared to the pure 1-tetradecene as an alkylating agent. Continuous synthesis of the long-chain alkylbenzenes catalyzed by ionic liquids can achieve in the microchannel reaction system by controlling the flow patterns.

Photoreceptor-Mimetic Microflowers for Restoring Light Responses in Degenerative Retina through a 2D Nanopetal/Cell Biointerface.

Retinitis pigmentosa is the main cause of inherited human blindness and is associated with dysfunctional photoreceptors (PRs). Compared with traditional methods, optoelectronic stimulation can better preserve the structural integrity and genetic content of the retina. However, enhancing the spatiotemporal accuracy of stimulation is challenging. Quantum dot-doped ZnIn2S4 microflowers (MF) are utilized to construct a biomimetic photoelectric interface with a 0D/3D heterostructure, aiming to restore the light response in PR-degenerative mice. The MF bio interface has dimensions similar to those of natural PRs and can be distributed within the curved spatial region of the retina, mimicking cellular dispersion. The soft 2D nano petals of the MF provide a large specific surface area for photoelectric activation and simulate the flexibility interfacing between cells. This bio interface can selectively restore the light responses of seven types of retina ganglion cells that encode brightness. The distribution of responsive cells forms a pattern similar to that of normal mice, which may reflect the generation of the initial "neural code" in the degenerative retina. Patch-clamp recordings indicate that the bio interface can induce spiking and postsynaptic currents at the single-neuron level. The results will shed light on the development of a potential bionic subretinal prosthetic toolkit for visual function restoration.

Upgrading the Compressor Stage of the CAT250TJ Micro Gas Turbine Engine

AbstractDue to their simplicity and relative ease of manufacture, single-stage centrifugal and mixed flow micro gas turbine (MGT) engines are preferred in thrust-based remotely piloted aerial vehicles. A single-stage mixed-flow compressor upgrade for the 200 N CAT250TJ MGT engine is numerically evaluated and presented. An in-house developed mean line application and commercial CFD software is used for the design and performance evaluation of the proposed upgrade configurations. The CAT250TJ – Gen1 engine features a single-stage centrifugal compressor, annular combustor, and single stage axial turbine. Apart from an upgraded impeller, a new crossover diffuser configuration is introduced to replace the wedge-type, straight outlet diffuser configuration of the Gen1 engine. The new single vane crossover diffuser configuration provides a design point total-to-total efficiency and pressure ratio increase of 8.3% and 12.1%, respectively. A disadvantage of a single-vaned crossover diffuser compared to legacy diffusers is a narrower operating range. To alleviate this issue, various combinations of tandem and splitter vane crossover diffuser configurations are proposed. These provide an enhanced operating range, comparable with the operating range displayed by the Gen1 configuration. A turbine power matching analysis is additionally completed to ensure proper compressor integration. Gas turbine cycle software is used to evaluate the on-engine performance of the upgraded compressor configurations. It is shown that the new baseline, single vane crossover diffuser configuration provides a 10.74% increase in design point static thrust.

CoFeBP Micro Flowers (MFs) for Highly Efficient Hydrogen Evolution Reaction and Oxygen Evolution Reaction Electrocatalysts.

Hydrogen is one of the most promising green energy alternatives due to its high gravimetric energy density, zero-carbon emissions, and other advantages. In this work, a CoFeBP micro-flower (MF) electrocatalyst is fabricated as an advanced water-splitting electrocatalyst by a hydrothermal approach for hydrogen production with the highly efficient hydrogen evolution reaction (HER) and oxygen evolution reaction (OER). The fabrication process of the CoFeBP MF electrocatalyst is systematically optimized by thorough investigations on various hydrothermal synthesis and post-annealing parameters. The best optimized CoFeBP MF electrode demonstrates HER/OER overpotentials of 20 mV and 219 mV at 20 mA/cm2. The CoFeBP MFs also exhibit a low 2-electrode (2-E) cell voltage of 1.60 V at 50 mA/cm2, which is comparable to the benchmark electrodes of Pt/C and RuO2. The CoFeBP MFs demonstrate excellent 2-E stability of over 100 h operation under harsh industrial operational conditions at 60 °C in 6 M KOH at a high current density of 1000 mA/cm2. The flower-like morphology can offer a largely increased electrochemical active surface area (ECSA), and systematic post-annealing can lead to improved crystallinity in CoFeBP MFs.

Multiagent-Based Control for Plug-and-Play Batteries in DC Microgrids with Infrastructure Compensation

The influence of the DC infrastructure on the control of power-storage flow in micro- and smart grids has gained attention recently, particularly in dynamic vehicle-to-grid charging applications. Principal effects include the potential loss of the charge–discharge synchronization and the subsequent impact on the control stabilization, the increased degradation in batteries’ health/life, and resultant power- and energy-efficiency losses. This paper proposes and tests a candidate solution to compensate for the infrastructure effects in a DC microgrid with a varying number of heterogeneous battery storage systems in the context of a multiagent neighbor-to-neighbor control scheme. Specifically, the scheme regulates the balance of the batteries’ load-demand participation, with adaptive compensation for unknown and/or time-varying DC infrastructure influences. Simulation and hardware-in-the-loop studies in realistic conditions demonstrate the improved precision of the charge–discharge synchronization and the enhanced balance of the output voltage under 24 h excessively continuous variations in the load demand. In addition, immediate real-time compensation for the DC infrastructure influence can be attained with no need for initial estimates of key unknown parameters. The results provide both the validation and verification of the proposals under real operational conditions and expectations, including the dynamic switching of the heterogeneous batteries’ connection (plug-and-play) and the variable infrastructure influences of different dynamically switched branches. Key observed metrics include an average reduced convergence time (0.66–13.366%), enhanced output-voltage balance (2.637–3.24%), power-consumption reduction (3.569–4.93%), and power-flow-balance enhancement (2.755–6.468%), which can be achieved for the proposed scheme over a baseline for the experiments in question.

Developed and quasi-developed macro-scale flow in micro- and mini-channels with arrays of offset strip fins

We investigate to what degree the steady laminar flow in typical micro- and mini-channels with offset strip fin arrays can be described as developed on a macro-scale level, in the presence of channel entrance and sidewall effects. Hereto, the extent of the developed and quasi-developed flow regions in such channels is determined through large-scale numerical flow simulations. It is observed that the onset point of developed flow increases linearly with the Reynolds number and channel width but remains small relative to the total channel length. Furthermore, we find that the local macro-scale pressure gradient and closure force for the (double) volume-averaged Navier–Stokes equations are adequately modeled by a developed friction factor correlation, as typical discrepancies are below 15% in both the developed and developing flow region. We show that these findings can be attributed to the eigenvalues and mode amplitudes, which characterize the quasi-developed flow in the entrance region of the channel. Finally, we discuss the influence of the channel side walls on the flow periodicity, the mass flow rate, as well as the macro-scale velocity profile, which we capture by a displacement factor and slip length coefficient. Our findings are supported by extensive numerical data for fin height-to-length ratios up to 1, fin pitch-to-length ratios up to 0.5, and channel aspect ratios between 1/5 and 1/17, covering Reynolds numbers from 28 to 1224.

Bimetallic Ag-Cu Alloy SERS Substrates as Label-Free Biomedical Sensors: Femtomolar Detection of Anticancer Drug Mitoxantrone with Multiplexing.

Surface-enhanced Raman spectroscopy (SERS) has been recognized as a promising label-free technology for clinical monitoring due to its high sensitivity and multiplexing ability, which should accelerate the screening of important drugs in the blood and plasma of cancer patients in a simpler, faster, and less-expensive manner. In this work, bimetallic Ag-Au and Ag-Cu alloy microflowers (MFs) with tunable surface compositions were fabricated on a glass cover slip by simple thermolysis of a metal alkyl ammonium halide precursor and used as SERS substrates for the sensitive detection of anticancer drug mitoxantrone (MTO). Two different laser excitation sources, 532 and 632.8 nm, were used to explore the possibility of surface-enhanced resonance Raman scattering. The Ag-Cu substrate showed superior detection capability over Ag-Au, whereby the sensor recorded a noteworthy "limit of detection" value of 1 fM for MTO. Theoretical electromagnetic field maps were simulated on appropriately chosen plasmonic systems to compare the electromagnetic field enhancements with the experimental SERS efficiencies of the substrates. Further, using a 10% Ag-Cu substrate, efficient multiplexing detection of MTO was demonstrated with another anticancer drug doxorubicin (DOX) in water and mouse blood plasma.

Research on non-Newtonian characteristics of crude oil flow at micro-nano scale

The characteristic scale of flow in micro–nanochannels is generally in the range of 0.01 μm∼1 μm. When crude oil passes through micro-nano channels and tight reservoirs, it shows obvious nonlinear seepage characteristics, which does not conform to the continuity assumption of fluid. Therefore, a non-Newtonian model of crude oil flowing in micro-nano channels and tight reservoirs under the action of shear stress is established, and the relationship between flow rate and apparent viscosity and shear rate is analyzed. The experiment of crude oil flow in micro-nano channels and tight oil reservoir cores shows that the model can be used to describe the nonlinear seepage law of liquid through the nonlinear fitting. The power law index of the oil-phase power-law non-Newtonian fluid is greater than 1 at the micro-nano scale, which conforms to the flow characteristics of the expansive fluid, thus verifying the effectiveness of the non-Newtonian model. In addition, the study of apparent viscosity and shear rate of non-Newtonian fluid shows that the increasing and decreasing trends of flow rate and shear rate and the changing trends of flow rate and pressure gradient are consistent, and shear rate can be used to describe the characteristics of fluid instead of the pressure gradient.

Advanced hybrid supercapacitors assembled with beta-Co(OH)2 microflowers and microclews as high-performance cathode materials

Supercapacitors (SCs) have received increasing attention thanks to their high power density, cyclic stability, and quick charging capability. Herein, a battery-type beta-Co(OH)2 electrode materials including two types of microstructures of nanosheets-assembled microflowers (MFs) and nanowires-based microclews (MCs) have been prepared through a three-step synthetic method, which contains an initial solvothermal reactions, aging the precursor in water, and final hydrothermal treatment. The mixed solvent of glycerol and isopropanol with different volume ratio in the first solvothermal stage has a crucial impact on the formation of different microstructures. Both the MFs and MCs possess huge surface area, and may provide abundant electro-active sites for further Faradic reactions. After they were tested in different electrode systems, it was found that the β-Co(OH)2 MFs presented a specific capacity of 396.5 C g−1 (1 A g−1) along with a rate of 81.2% at 10 A g−1, and the MCs exhibited an inferior capacity of 303.9 C g−1. In order to further assess the potential of practical applications in SCs, a hybrid supercapacitor (HSC) device was designed by choosing activated carbon (AC) as negative electrode. The β-Co(OH)2 MFs//AC device exhibited 158.6 C g−1 and an energy density (Ed) of 43.6 W h kg−1. In contrast, the β-Co(OH)2 MCs//AC HSC showed lower Ed of 34.1 W h kg−1 at 954.7 W kg−1. Both HSCs exhibited brilliant cycling stability over 5000 continuous cycles at 6 A g−1. Such impressive electrochemical response of β-Co(OH)2 MFs & MCs makes them the suitable candidates to assemble advanced HSC devices with high-performance, and may anticipate their promising application prospect in the near future.

Machine learning-based models for frictional pressure drop prediction of condensing and adiabatic flow in micro, mini and macro channels utilizing universal data

This study proposes a universal machine learning-based model to predict the adiabatic and condensing frictional pressure drop. For developing the proposed model, 11,411 data points of adiabatic and condensing flow inside micro, mini and macro channels are collected from 80 sources. The database consists of 24 working fluids, hydraulic diameters from 0.07 to 18 mm, mass velocities from 6.3 to 2000 Kg/m2s, and reduced pressures from 0.001 to 0.95. Using this database, four machine learning regression models, including “artificial neural network”, “support vector regression”, “gradient boosted regression”, and “random forest regression”, are developed and compared with each other. A wide range of dimensionless parameters as features, “two-phase friction factor” and “Chisholm parameter” are each considered separately as targets. Using search methods, the optimal values of important hyperparameters in each model are determined. The results showed that the “gradient boosted regression” model performs better than other models and predicts the frictional pressure drop with a mean absolute relative deviation of 3.24%. Examining the effectiveness of the new model showed that it predicts data with uniform accuracy over a vast range of variations of each flow parameter.

Reinforcement Learning-Based Intelligent Control Strategies for Optimal Power Management in Advanced Power Distribution Systems: A Survey

Intelligent energy management in renewable-based power distribution applications, such as microgrids, smart grids, smart buildings, and EV systems, is becoming increasingly important in the context of the transition toward the decentralization, digitalization, and decarbonization of energy networks. Arguably, many challenges can be overcome, and benefits leveraged, in this transition by the adoption of intelligent autonomous computer-based decision-making through the introduction of smart technologies, specifically artificial intelligence. Unlike other numerical or soft computing optimization methods, the control based on artificial intelligence allows the decentralized power units to collaborate in making the best decision of fulfilling the administrator’s needs, rather than only a primitive decentralization based only on the division of tasks. Among the smart approaches, reinforcement learning stands as the most relevant and successful, particularly in power distribution management applications. The reason is it does not need an accurate model for attaining an optimized solution regarding the interaction with the environment. Accordingly, there is an ongoing need to accomplish a clear, up-to-date, vision of the development level, especially with the lack of recent comprehensive detailed reviews of this vitally important research field. Therefore, this paper fulfills the need and presents a comprehensive review of the state-of-the-art successful and distinguished intelligent control strategies-based RL in optimizing the management of power flow and distribution. Wherein extensive importance is given to the classification of the literature on emerging strategies, the proposals based on RL multiagent, and the multiagent primary secondary control of managing power flow in micro and smart grids, particularly the energy storage. As a result, 126 of the most relevant, recent, and non-incremental have been reviewed and put into relevant categories. Furthermore, salient features have been identified of the major positive and negative, of each selection.

Hemorheological profiles and chronic inflammation markers in transfusion-dependent and non-transfusion- dependent thalassemia.

The rheological properties of blood play an important role in regulating blood flow in micro and macro circulation. In thalassemia syndromes red blood cells exhibit altered hemodynamic properties that facilitate microcirculatory diseases: increased aggregation and reduced deformability, as well as a marked increase in adherence to the vascular endothelial cells. A personalized approach to treating thalassemia patients (transfusions, iron chelation, and splenectomy), has increased patients' life expectancy, however they generally present many complications and several studies have demonstrated the presence of high incidence of thromboembolic events. In this study the hemorheological profiles of thalassemia patients have been characterized to point out new indices of vascular impairment in thalassemia. Plasma viscosity, blood viscosities at low and high shear rates (η1 and η200, respectively), erythrocyte aggregation index (η1/η200), and the erythrocyte viscoelastic profile (elastic modulus G', and viscous modulus G") have been studied in transfusion-dependent and non-transfusion-dependent thalassemia patients. Moreover, the levels of inflammation biomarkers in thalassemia have been evaluated to investigate a relationship between the biomarkers, the disease severity and the rheological parameters. The biomarkers studied are the main components of the immune and endothelial systems or are related to vascular inflammation: cytokines (IL-2, IL-6, IL-10, IL-17A, TNF-alpha), chemokines (IL-8, MIP-1alpha), adipocytokines (leptin and adiponectin), growth factors (VEGF, angiopoietin-1), adhesion molecules (ICAM-1, VCAM-1, E-selectin, L-selectin), and a monocyte/macrophage activation marker (CD163). This study shows that transfusion-dependent thalassemia patients, both major and intermedia, have blood viscosities comparable to those of healthy subjects. Non-transfusion-dependent thalassemia intermedia patients show high blood viscosities at low shear rates (η1), corresponding to the flow conditions of the microcirculation, an increase in erythrocyte aggregation, and high values of the elastic G' and viscous G" modules that reflect a reduced erythrocyte deformability and an increase in blood viscosity. Levels of cytokines, chemokines and adhesion molecules are different in transfusion- and non-transfusion dependent patients and positive correlations between η1 or η1/η200 and the cytokines IL-6 and IL-10 have been observed. The evaluation of the hemorheological profiles in thalassemia can provide new indicators of vascular impairment and disease severity in thalassemia in order to prevent the onset of thromboembolic events.

Thermal and Flow Analysis of Fully Developed Electroosmotic Flow in Parallel-Plate Micro- and Nanochannels with Surface Charge-Dependent Slip.

This study analytically investigates the coupled effects of surface charge and boundary slip on the fully developed electroosmotic flow and thermal transfer in parallel plate micro and nanochannels under the high zeta potential. The electric potential, velocity, temperature, flow rate, and Nusselt number are obtained analytically. The main results are that the velocity of bulk flow is significantly reduced in the presence of the surface charge-dependent slip. Moreover, the maximum velocity at ζ = -125 mV is approximately twice as large as that at ζ = -25 mV. The velocity and dimensionless temperature increase as the zeta potential increases. The dimensionless temperature of the surface charge-dependent slip flow is larger than that of the surface charge-independent slip flow. For the surface charge-dependent slip flow, the maximum temperature at ζ = -125 mV is approximately four times larger than that at ζ = -25 mV. The Nusselt number decreases with Joule heating and increases with a positive heat transfer coefficient. The Nusselt number decreases as the electric field and the magnitude of the zeta potential increase. In the surface charge-dependent slip flows, the Nusselt number is smaller than that in the surface charge-independent slip flows.

Assembly of high-performance hybrid supercapacitors using FeCo2O4 microflowers as battery-type cathode materials

In this work, FeCo2O4 microflowers (MFs) and microparticles (MPs) were respectively prepared at different temperatures via a wet chemical method, along with a post annealing treatment in air. These MFs and MPs exhibited huge specific surface area and a large number of mesopores. Several electrochemical tests were conducted in a three-electrode configuration. The FeCo2O4 MFs delivered a specific capacity of 301.3C g−1, higher than 253.9C g−1 for FeCo2O4 MPs. A hybrid supercapacitor (HSC) device was assembled with FeCo2O4 as cathode and activated carbon (AC) as anode to investigate the practical applications in electrochemical energy storage. The FeCo2O4 MFs//AC HSC delivered a capacity of 107.2C g−1 at 1 A g−1 and an energy density (Ed) of 25.7 W h kg−1 at 862.6 W kg−1, respectively, while the FeCo2O4 MPs//AC HSC showed an Ed of 23.8 W h kg−1 at the power density (Pd) of 878.9 W kg−1. The two HSCs showed little capacity decay after 3000 cycles at 6 A g−1. The capacity of FeCo2O4 MFs and the obtained Ed of HSC were in a high status among those of transition metal oxides (TMOs)-based electrodes reported earlier. The current synthetic strategy can be used as a reference to the synthesis of other similar electrochemical materials for HSC electrodes.

Review on Microscopic Model of Continuous Pedestrian Flow

Continuous pedestrian flow micro model is an important method to study pedestrian flow at present. Compared with macro model and discrete model, continuous pedestrian flow micro model can better simulate pedestrian flow phenomenon. This paper summarizes the research significance and achievements of the continuous pedestrian flow micro model. The research contents and corresponding modeling methods of relevant models are mainly introduced, and the future development of pedestrian flow micro models is prospected.

Durable drag reduction and anti-corrosion for liquid flows inside lubricant-infused aluminum/copper capillaries

Frictional drag reduction and anti-corrosion for the liquid flows in micro- and nanochannels result in considerable economic and environmental benefits. The lubricant infused surface (LIS) has emerged as a promising technology for achieving the two functionalities. This work proposes the fabrication of LISs on the inner walls of metal capillaries for endowing the capillaries with sustainable drag reduction and anti-corrosion properties. Specifically, we demonstrate the fabrication of the LIS aluminum (Al) capillaries with varying viscosity of lubricants and systematically investigate their drag reduction performance by measuring the relationship between the frictional factor/slip length and Reynolds number. We find that the LIS Al capillary exhibits durable drag reduction and anti-corrosion characteristics which can also be achievable in other LIS metal capillaries, such as LIS copper capillaries. A comparison of the LIS Al capillary with the Al capillary with a superhydrophobic surface (SHS) suggests that the former outperforms the latter in terms of durability, e.g., the LIS capillary with the lowest lubricant viscosity considered can withstand a shear force as high as Re≈700, which is more than twice that of the SHS capillary (Re≈300). The LIS capillaries can reduce the frictional factor by up to 30%. Varying the viscosity of infusion lubricants is an effective way to tune the drag reduction performance of the LIS metal capillaries. The present work paves a way for applying LIS metal capillaries in instrumentation, thermal management, microfluidic devices, etc.

Efficient lock-in CuO/WON heterostructures tailored for highly sensitive electrochemical detection of hazardous herbicide diuron in fruit juices and aqua region

A micro-nano lock-in heterostructure has attracted significant attention for electrochemical sensor application due to its high specific surface area, more exposed active sites, and fast ion transport. Despite these advantages, here we prepared lock-in hetero structured tungsten oxynitride (WON) with a flower of CuO architecture by using the impregnation method. The tungsten oxynitride (WON) was prepared from the doping of nitrogen over the lattice of WO3 via a reactive NH3 gas etching process which turns WO3 nanoflakes (NFs) into the WON etched nanoflakes (EFs). The EFs act as cages to hold the hydrothermally prepared CuO micro flowers (MFs) and forms a new type of ‘lock-in’ heterostructure. This structure enables the stable and faster charge transfer between the CuO MFs and WON EFs, resulting in an efficient electrochemical performance towards the detection of diuron herbicide. The prepared CuO/WON were subjected to physiochemical characterizations such as X-ray diffraction (XRD), Raman spectroscopy, and X-ray photoelectron spectroscopy (XPS). The morphological and elemental information was interpreted by field-emission scanning electron microscopy (FESEM) combined with EDX and mapping analysis. Then, CuO/WON/GCE sensor electrode exhibited a wide diuron (DU) detection range of about 0.01–764.4 µM. Moreover, the estimated limit of detection and sensitivity from the slope of DU detection is 5.5 nm and 0.445 µM µA−1 cm−2 respectively. The practical applicability of the sensor electrodes was tested in the DU-added grape juice, orange juice, tap water, and river water samples.

Strategy for Fast Decision on Material System Suitability for Continuous Crystallization Inside a Slug Flow Crystallizer.

There is an increasing focus on two-phase flow in micro- or mini-structured apparatuses for various manufacturing and measurement instrumentation applications, including the field of crystallization as a separation technique. The slug flow pattern offers salient features for producing high-quality products, since narrow residence time distribution of liquid and solid phases, intensified mixing and heat exchange, and an enhanced particle suspension are achieved despite laminar flow conditions. Due to its unique features, the slug flow crystallizer (SFC) represents a promising concept for small-scale continuous crystallization achieving high-quality active pharmaceutical ingredients (API). Therefore, a time-efficient strategy is presented in this study to enable crystallization of a desired solid product in the SFC as quickly as possible and without much experimental effort. This strategy includes pre-selection of the solvent/solvent mixture using heuristics, verifying the slug flow stability in the apparatus by considering the static contact angle and dynamic flow behavior, and modeling the temperature-dependent solubility in the supposed material system using perturbed-chain statistical associating fluid theory (PC-SAFT). This strategy was successfully verified for the amino acids l-alanine and l-arginine and the API paracetamol for binary and ternary systems and, thus, represents a general approach for using different material systems in the SFC.