Flow Rate Ratio Research Articles

Effect of cap layer and post growth on-site hydride passivation on the surface and interface quality of InAsP/InP hetero and QW structures

The performance of devices made from III-V compound semiconductors relies heavily on their surface and interface properties. The InAsP/InP material system is recently gaining interest due to its suitability for the next generation of long-haul classical and quantum communication applications. Researchers are studying how surface and interface properties affect the efficiency of the device and concludes that the epitaxial growth conditions responsible for creating surface and interface states require further improvement. To address this, we have studied the effect of the top (cap) layer and post-growth on-site hydride passivation on the properties of InAsP/InP hetero-structures grown using metal-organic vapor phase epitaxy technique. The flow rate and flux ratios of the hydrides significantly affect the surface reaction rates and gas-phase diffusion coefficients, which in turn impact the As↔P exchange mechanisms. Our findings suggest that post-growth on-site arsine passivation encourages the As↔P substitutions at the vicinity of the desorption sites of phosphorus, leading to the arsenic-rich surface of InAsP with the diffused hetero-interfaces. The activation energy for such As↔P exchange reaction mechanism is evaluated as ∼ (1.4 ± 0.3) eV. On the other hand, it has been observed that the thin cap layer of InP protects the surface of the InAsP epilayer and thereby preserving the sharp interface. Further, surface photovoltage and photoluminescence spectroscopy is employed to examine the role of the diffused and sharp interface of InAsP/InP hetero-structures in charge carrier transport, their redistribution and recombination process. Our analysis of the energy transitions occurring in the surface photovoltage and photoluminescence spectrum reveal that the energy band alignment and the subsequent charge carrier redistribution processes is influenced by the surface and interface states. These changes in the surface photovoltage phase spectra of InAsP/InP system also support the role of surface and interface states in the generation and separation of the charge carriers. The study provides insights into the effects of As↔P exchange on surface and interfacial quality, highlighting the implications for optoelectronic device development using InAsP/InP material system.

An Investigation of Secondary Cooling Effect on the Endwall Surface With Vane Trailing Edge Coolant Injection

Abstract Considering the adequate use of coolant, the secondary cooling effect of trailing edge coolant injection on the downstream endwall surface is investigated in this study. Distributions of adiabatic cooling effectiveness on the endwall surface are obtained through pressure-sensitive paint (PSP) technique in a linear cascade at four mass flowrate ratios (MFR = 1%, 2%, 3%, and 4%) and two density ratios (DR = 1.0 and 1.5). The configurations of trailing edge pressure-side cutback (PC) and central cutback (CC) with three compound angles (β = 15 deg, 30 deg, and 45 deg) are implemented in this study. Reynolds-averaged Navier–Stokes simulations are performed to present the flow field. Results show that the geometry of the cutback slot has a significant effect on the endwall cooling performance. As the compound angle increases, the coolant coverage is expanded in width. A higher density ratio leads to a decrease in the area of coolant coverage, while the distribution is more uniform. Generally, with a higher mass flow ratio, the coolant coverage is greatly improved in area and value, which almost covers the entire downstream endwall surface.

Effects of Diethoxymethylsilane/Helium Flow Rate Ratio on Low-k Films Deposited by Plasma-Enhanced Chemical Vapor Deposition

As the semiconductor industry has continuously reduced the integrated circuit (IC) chip size, a resistance-capacitance (RC) delay emerged, causing deterioration of the chip performance. To reduce the RC delay, low dielectric constant (low-k) films with suitable mechanical strengths have been adopted as intermetal dielectrics (IMDs). In this study, low-k plasma-polymerized diethoxymethylsilane (ppDEMS) films were fabricated by plasma-enhanced chemical vapor deposition of the DEMS precursor with a flow rate ratio of the DEMS precursor to helium (He) carrier gas (DEMS/He FRR) as a key parameter. As the DEMS/He FRR increased, the refractive index was reduced from 1.401 to 1.386, and the k value decreased from 2.77 to 2.10. From high-resolution scans of C1s, O1s, and Si2p peaks of X-ray photoelectron spectroscopy, the carbon contents increased, and the oxygen contents decreased, along with a decrease in the film density. With the increased DEMS/He FRR, hardness decreased from 2.5 to 1.8 GPa, and elastic modulus decreased from 17.08 to 11.50 GPa. Leakage current densities for all the ppDEMS films were less than 10−7 A cm−2 at 1 MV cm−1. The ppDEMS films could be suggested as the IMDs according to their electrical and mechanical performance.

Niobium Oxide Thin Films Grown on Flexible ITO-Coated PET Substrates

Niobium oxide thin films were grown on both rigid and flexible substrates using DC magnetron sputtering for electrochromic applications. Three experimental series were conducted, varying the oxygen to argon flow rate ratio and deposition time. In the first series, the oxygen to argon ratio was adjusted from 0 to 0.32 while maintaining a constant growth time of 30 min. For the second and third series, the oxygen to argon ratios were fixed at 0.40 and 0.56, respectively, with deposition times ranging from 15 to 60 min. A structural transition from crystalline to amorphous was observed at an oxygen to argon flow rate ratio of 0.32. This transition coincided with a change in appearance, from non-transparent with metallic-like electrical conductivity to transparent with dielectric behavior. The transparent niobium oxide films exhibited thicknesses between 51 nm and 198 nm, with a compact, dense, and featureless morphology, as evidenced by both top-view and cross-sectional images. Films deposited on flexible indium tin oxide (ITO)-coated polyethylene terephthalate (PET) substrates displayed a maximum surface roughness (Sq) of 9 nm and a maximum optical transmission of 83% in the visible range. The electrochromic response of niobium oxide thin films on ITO-coated PET substrates demonstrated a maximum coloration efficiency of 30 cm2 C−1 and a reversibility of 96%. Mechanical performance was assessed through bending tests. The ITO-coated PET substrate exhibited a critical bending radius of 6.5 mm. Upon the addition of the niobium oxide layer, this decreased to 5 mm. Electrical resistance measurements indicated that the niobium oxide film mitigated rapid mechanical degradation of the underlying ITO electrode beyond the critical bending radius.

Can We Simplify Liposome Manufacturing Using a Complex DoE Approach?

Microfluidic liposome production presents a streamlined pathway for expediting the translation of liposomal formulations from the laboratory setting to clinical applications. Using this production method, resultant liposome characteristics can be tuned through the control of both the formulation parameters (including the lipids and solvents used) and production parameters (including the production speed and mixing ratio). Therefore, the aim of this study was to investigate the relationship between not only total flow rate (TFR), the fraction of the aqueous flow rate over the organic flow rate (flow rate ratio (FRR)), and the lipid concentration, but also the solvent selection, aqueous buffer, and production temperature. To achieve this, we used temperature, applying a design of experiment (DoE) combined with machine learning. This study demonstrated that liposome size and polydispersity were influenced by manipulation of not only the total flow rate and flow rate ratio but also through the lipids, lipid concentration, and solvent selection, such that liposome attributes can be in-process controlled, and all factors should be considered within a manufacturing process as impacting on liposome critical quality attributes.

SYNTHESIS of P(N-ISOPROPYL ACRYLAMIDE - HYDROXYPROPYL METHACRYLATE) THERMO RESPONSIVE COPOLYMER FILMs BY INITIATED CHEMICAL VAPOR DEPOSITION METHOD

This study illustrates the deposition of thermo responsive p(N-isopropyl acrylamide-hydroxypropyl methacrylate) p(NIPAAm-HPMA) copolymer thin films by initiated chemical vapor deposition (iCVD) method using tert-butyl peroxide (TBPO) as the initiator. Copolymers were deposited at three different HPMA flow rates and the effects of NIPAAm/HPMA flow rate ratio on the deposition rate, structure and responsive properties of the as-deposited films were investigated. The highest deposition rate of 50 nm/min was observed for the copolymer deposited using lowest NIPAAm/HPMA monomer ratio studied. The deposition rate showed a significant increase with decreasing NIPAAm/HPMA flow ratio. Results of FTIR and XPS spectroscopy analyses revealed a significant preservation of structural retention in iCVD p(NIPAAm-HPMA) thermo-responsive films. Lower critical solution temperatures (LCST) of p(NIPAAm-HPMA) films were determined by carrying out a temperature-dependent contact angle analysis. Accordingly, it was shown that LCST was varied between 19 and 23 oC, which was observed to be dependent on the NIPAAm/HPMA monomer ratio. That LCST range is considerably below the literature- reported values for pNIPAAM, which makes the as-deposited copolymer suitable for applications that require thermos-responsive properties at lower temperatures.

A simple guideline for designing droplet microfluidic chips to achieve an improved single (bio)particle encapsulation rate using a stratified flow-assisted particle ordering method

Encapsulation of a single (bio)particle into individual droplets (referred to as single encapsulation) presents tremendous potential for precise biological and chemical reactions at the single (bio)particle level. Previously demonstrated successful strategies often rely on the use of high flow rates, gel, or viscoelastic materials for initial cell ordering prior to encapsulation into droplets, which could potentially challenge the system's operation. We propose to enhance the single encapsulation rate by using a stratified flow structure to focus and pre-order the (bio)particles before encapsulation. The stratified flow structure is formed using two simple aqueous Newtonian fluids with a viscosity contrast, which together serve as the dispersed phase. The single encapsulation rate is influenced by many parameters, including fluid viscosity contrast, geometric conditions, flow conditions and flow rate ratios, and dimensionless numbers such as the capillary number. This study focuses on investigating the influences of these parameters on the focused stream of the stratified flow, which is key for single encapsulation. The results allow the proposal of a simple guideline that can be adopted to design droplet microfluidic chips with an improved single encapsulation rate demanded by a wide range of applications. The guideline was validated by performing the single encapsulation of mouse embryonic stem cells suspended in a gelatin-methacryloyl solution in individual droplets of phosphate buffer saline, achieving a single encapsulation efficiency of up to 70%.

Arrangement and feedback effects of droplet swarms in a parallel microchannel device

Droplet swarms are the dominant form of highly dispersed microdroplets in cavities. During the self-assembly of droplet swarms, the continuous phase is inclined to flow along the path of the minimum resistance, while the arrangement of the droplet swarms seeks to minimize the potential energy, and the two mechanisms compromise in competition. In this paper, the ability of droplet swarms to timely adjust the morphology is measured by the ratio of the average flow rate of the two-phase flow to that of the droplet swarms, thereby clarifying the dominant mechanism of the arrangement of droplet swarms. The arrangement of droplet swarms dominated by different mechanisms and their distribution are introduced, and the prediction method for the arrangement of droplet swarms is proposed. The mechanism underlying the breakup of the microdroplets in the cavity is elucidated, and three modes of the breakup in the cavity are introduced. Furthermore, a resistance model for the microdevice is established to quantify the fluctuations of pressure difference and flow rate resulting from the formation of droplet swarms. The feedback effects of droplet swarms on the uniformity of droplet formation and flow patterns are analyzed, revealing the ideal flow range for the formation of highly dispersed droplets in microchannels. This paper elucidates the arrangement and the feedback effects of droplet swarms, which will guide the application of microdevices in reaction and mass transfer processes.

Production of liposomes by microfluidics: The impact of post-manufacturing dilution on drug encapsulation and lipid loss

Microfluidic mixing is recognized as a convenient method to produce liposomes for its scalability and reproducibility. Numerous studies have described the effect of process parameters such as flow rate ratios and total flow rate on size and size distribution of vesicles. In this work, we focused our attention on the effect of flow rate ratios on the encapsulation efficiency of liposomes, as we hypothesized that different amount of residual organic solvent could affect the retention of lipophilic drug molecules within the bilayer. In a further step, we investigated how the liposomes integrity and loading were impacted by different methods of solvent removal: direct dialysis and dilution & dialysis. Liposomes were prepared by rapidly mixing an ethanolic solution of lipids and a model drug with buffer in a herringbone micromixer, employing four different flow rate ratios (FRR, 4:1, 7:3, 3:2, 1:1). Quercetin, resveratrol and ascorbyl palmitate were used as model antioxidant drugs with different lipophilicity. Data showed that liposomes produced using lower flow rate ratios (i.e., with more residual ethanol) had lower encapsulation efficiencies as well as a more prominent loss of lipids from the bilayer following purification with direct dialysis. If the amount of residual ethanol was reduced to 5% (dilution & dialysis method), the lipids and drug leakage was prevented. Such effect was correlated with the drug aggregation propensity in different ethanol/water mixtures measured by molecular dynamics simulations. Overall, these results highlight the need to tailor the purification method basing on the molecular properties of the loaded drug to ensure high encapsulation and limit the waste of material.

Asymmetric droplet splitting in a T-junction under a pressure difference

In this paper, the phase-field multiphase lattice Boltzmann method is employed to simulate droplet breakup in a T-junction under different outlet pressures. Three behaviors of droplet breakup: non-breakup (flow pattern I), breakup with tunnels (flow pattern II), and breakup with permanent obstruction (flow pattern Ⅲ) are identified. The evolution of morphological characteristics of droplet breakup is quantitatively characterized, based on which the asymmetric splitting mechanisms and the influencing factors are clarified. Additionally, the factors influencing the droplet splitting volume ratio (VII/VI) are elucidated. The results indicate that there is a non-linear relationship between the VII/VI and the flow rate ratio. Moreover, the curve depicting the final VII/VI versus the initial droplet length exhibits a V-shape and has a minimum value. A conclusion is drawn that the Capillary number mainly influences flow pattern II, with the final VII/VI decreasing as the Capillary number increases. Additionally, for flow pattern III, the final VII/VI increases linearly with rising droplet size at low viscosity ratios, whereas it decreases linearly at high viscosity ratios. The growing outlet pressure difference enlarges the flow difference between the two branches, leading to an increase in the final VII/VI.

EchoAGE: Echocardiography-based Neural Network Model Forecasting Heart Biological Age.

Biological age is a personalized measure of the health status of an organism, organ, or system, as opposed to simply accounting for chronological age. To date, there have been known attempts to create estimators of biological age based on various biomedical data. In this work, we focused on developing an approach for assessing heart biological age using echocardiographic data. The current study included echocardiographic data from more than 5,000 different cases. As a result, we created EchoAGE - neural network model to determine heart biological age, that was tested on echocardiographic data from patients with age-related diseases, patients with multimorbidity, children with progeria syndrome, and diachronic data series. The model estimates biological age with a Mean Absolute Error of approximately 3.5 years, an R-squared value of around 0.88, and a Spearman's rank correlation coefficient greater than 0.9 in men and women. EchoAGE uses indicators such as E/A ratio of maximum flow rates in the first and second phases, thicknesses of the interventricular septum and the posterior left ventricular wall, cardiac output, and relative wall thickness. In addition, we have applied an AI explanation algorithm to improve understanding of how the model performs an assessment.

Machine learning-based process design of a novel sustainable cooling system

An exponential rise in cooling requirements occurred in the last few years because of rising global surface temperatures, population growth, faster urbanization, and income growth. Developing countries are facing major issues because of the larger impact of these cooling drivers. Conventional vapor compression systems are energy-demanding and involve dangerous chemicals. The current paper proposed an innovative indirect evaporative cooling system with high energy performance, less emissions, and chemical-free operation. To map the full-scale performance, a prototype was developed,and tested in a variety of outside air conditions. Then artificial neural network (ANN)-based machine learning model was developed incorporating important input parameters including outdoor air temperature, air flow rate ratio, working air temperature, and working air wet bulb temperature to predict the supply air temperature. The ANN model having nine neurons in the hidden layer exhibits excellent modeling performance with a coefficient of determination (R2) value of ∼ 1 and root mean square error of 0.046 °C, 0.06 °C, and 0.06 °C in the training, testing, and validation phases respectively. The variable significance analysis carried out by one factor at a time (OFAT) technique reveals that working air inlet temperature is the most important parameter to predict supply temperature with a significance factor of 33 %. According to the combined experimental and ML model, the proposed system generated 130 W of cooling capacity and dropped the temperature by more than 20 °C at 48 °C of outdoor air. The corresponding coefficient of performance achieved (just for cooling) was 32. It is also shown that the enhanced IEC operates steadily in ambient temperatures ranging from 30 to 48 °C and maintains supply air temperatures within the comfort zone of ASHRAE-55 and ISO7730.

Effects of slit geometric parameters on spray characteristics of double-slit pintle injectors

Pintle injectors have garnered significant research attention in recent years, particularly for their applicability in reusable launch vehicles, owing to their wide thrust control range and excellent combustion stability. While research has explored the characteristics of pintle injectors in the context of developing these components for actual engine applications, studies focusing on the effects of design parameters on injector performance have been limited. This study investigated the effects of slit geometric parameters, specifically the blockage factor (BF) and slit area ratio (γ), on the spray characteristics of double-slit pintle injectors. Cold-flow tests were conducted using planar pintle injectors with water and ethanol as simulants. The spray angle and Sauter mean diameter (SMD) were measured using the shadowgraph technique, and the distribution of mass flow rate and mixture ratio was analyzed using a mechanical patternator. The experimental results revealed that two distinct streams were injected at different angles from each row of slits, resulting in a division of spray shape, SMD, and mass flow distribution into three regions based on the two streams. These spray angles, termed primary and secondary spray angles, were quantified as functions of the local momentum ratio, determined by BF and γ. To correlate the spray characteristics with combustion performance, mixing quality and a representative droplet size metric, the integral Sauter mean diameter (ID32), were presented. The study found that higher values of BF and γ corresponded to improved mixing quality.

Artificial intelligence-based droplet size prediction for microfluidic system

PurposeThis study aims to introduce a vision-based model to generate droplets with auto-tuned parameters. The model can auto-adjust the inherent uncertainties and errors involved with the fabrication and operating parameters in microfluidic platform, attaining precise size and frequency of droplet generation.Design/methodology/approachThe photolithography method is utilized to prepare the microfluidic devices used in this study, and various experiments are conducted at various flow-rate and viscosity ratios. Data for droplet shape is collected to train the artificial intelligence (AI) models.FindingsGrowth phase of droplets demonstrated a unique spring back effect in droplet size. The fully developed droplet sizes in the microchannel were modeled using least absolute shrinkage and selection operators (LASSO) regression model, Gaussian support vector machine (SVM), long short term memory (LSTM) and deep neural network models. Mean absolute percentage error (MAPE) of 0.05 and R2 = 0.93 were obtained with a deep neural network model on untrained flow data. The shape parameters of the droplets are affected by several uncontrolled parameters. These parameters are instinctively captured in the model.Originality/valueExperimental data set is generated for varying viscosity values and flow rates. The variation of flow rate of continuous phase is observed here instead of dispersed phase. An automated computation routine is developed to read the droplet shape parameters considering the transient growth phase of droplets. The droplet size data is used to build and compare various AI models for predicting droplet sizes. A predictive model is developed, which is ready for automated closed loop control of the droplet generation.

Growth mechanism of a batch deposited SiC coating on large-size graphite plates based on multi-scale simulation

Graphite plate was used as a substrate material for growing semiconductor films in the MOCVD process. The graphite plate was protected in the MOCVD process by the SiC coating deposited on its surface. Achieving batch production of SiC coating deposited on large-size graphite plates was critical. In our previous work, the CVD SiC process was investigated via simulations and experiments within a specific parameter range. Experimentally compatible simulation models were established, and parametric conditions for depositing high-quality coatings were obtained. However, in our recent investigation, outstanding deposition was found at simply achievable low-pressure conditions outside the previously reported deposition parameter range. Here, CVD experiments were conducted over broad parameter ranges, and previous models were partially corrected. The mechanism of outstanding deposition in low-pressure conditions and coating growth was explained by multi-scale simulations and experiments. The impact of parameters on CVD SiC was investigated by varying the gas flow rate, deposition pressure, and molar ratio of methyltrichlorosilane(MTS) to H2(nMTS:nH2) during the simulation. The simulation and experimental results were provided as a scientific basis for the process modification of large-scale batch preparation of CVD SiC.

The manufacturing and characterization of pentamidine-loaded poly(lactic-co-glycolic acid) nanoparticles produced by microfluidic method

In recent years, special attention has been paid to the study of manufacturing processes that can precisely control the physicochemical properties of nanoparticles (NPs) and reduce batch-to-batch variability. Microfluidics has recently emerged as an advanced production method that can manage NP properties by monitoring the diffusion/emulsification mechanism. Pentamidine free base (PTM-B), a diamidine compound positively charged at physiological pH, has already been used as a model drug for incorporation into poly(lactic-co-glycolic acid) (PLGA) via an ion-pairing strategy using a conventional bulk production method. The same formulation was chosen to study the scaling-up process and preparation using the microfluidic technique. The formulation of PLGA NP loaded with PTM-B by the microfluidic technique was optimized by adding 1 % Lutrol F68 as a surfactant agent to stabilize the nanosuspension during the solvent diffusion in the microchannel of the chip, and then, washed away in the final suspension. A thorough investigation of process parameters (i.e., total flow rate, flow rate ratio) was conducted to obtain a monodisperse suspension characterized by a mean diameter of less than 150 nm. In addition, in vitro studies on mammalian cancer cell lines demonstrated the potential antitumor activity of PTM-B-loaded NPs prepared by the microfluidic technique.

Modeling and experimental study on a photochemical microscale continuous oscillatory baffled reactor

AbstractHerein, the first photochemical microscale continuous oscillatory baffled reactor, that is, Photo‐μCOBR, was designed and evaluated. Computational fluid dynamics simulations were used to optimize the key structural parameter and operating conditions. Then, the mixing process was simulated and the μCOBR was shown to be more than 23 times faster than the straight channel both under oscillating conditions. Finally, a glass Photo‐μCOBR was fabricated by femtosecond laser internal engraving technology, and the photocatalytic gas–liquid oxidation of dihydroartemisinic acid was performed. A yield of 65.9% was achieved in a residence time of ~120 s and at a gas–liquid flow rate ratio of 1:3 (vs. 18.6% in the capillary photomicroreactor under identical conditions). The results in this work offer guidelines for the design and operation of microscale COBRs, and the as‐fabricated Photo‐μCOBR displays good potential for gas–liquid photochemical reactions.

Off-design behaviors of a solar-powered HDH system for water and power cogeneration

A solar-powered humidification-dehumidification (HDH) desalination system offers flexible water and power cogeneration, promising in addressing energy crisis. However, the system’s operation frequently deviates from the on-design condition, making it crucial to study its off-design behaviors. This paper develops an off-design model to investigate the operation performance in response to variations in liquid–gas mass flow rate ratio (MFRR) and solar intensity. Furthermore, the heat and mass transfer mechanisms in humidifier and dehumidifier are inquired under specific conditions. The results exhibit that the system performance sensitivity to changes in the liquid–gas mass flow rate ratio and solar intensity aligns with the expectations under on-design conditions. The combined heat and mass transfer process weakens first and then strengthens from the bottom to the top in the humidifier, and vice versa in the dehumidifier. Notably, a higher freshwater flow rate enhances dehumidification efficiency, raising gained-output-ratio (GOR) by 7.13% and water production by 1.5%. Validation experiments confirm the off-design model’s accuracy and credibility, to offer methodological insights for the effective prediction of off-design behaviors.

Effects of phospholipid type and particle size on lipid nanoparticle distribution in vivo and in pancreatic islets

Lipid nanoparticles (LNPs) have recently been used as nanocarriers in drug delivery systems for nucleic acid drugs. Their practical applications are currently primarily limited to the liver and specific organs. However, altering the type and composition ratio of phospholipids improves their distribution in organs other than the liver, such as the spleen and lungs. This study aimed to elucidate the effects of LNP components and particle size on in vivo distribution through systemic circulation to pancreatic islets to achieve better targeting of islets, which are a fundamental therapeutic target for diabetes. Fluorescence-labeled LNPs were prepared using three phospholipids: 1,2-distearoyl-sn-glycero-3-phosphocholine (DSPC), 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC), and 1,2-dioleoyl-sn-glycero-3-phosphoethanolamine (DOPE), with particle sizes of 30–160 nm (diameter) using a microfluidic device. Baffled-structured iLiNP devices with adjusted flow-rate ratios and total flow rates were used. After the intravenous administration of LNPs to C57BL/6 J mice, the distribution of each LNP type to the major organs, including the pancreas and pancreatic islets, was compared using ex vivo fluorescence imaging and observation of pancreatic tissue sections. DSPC-LNPs- and DOPE-LNPs showed the highest distribution in the spleen and liver, respectively. In contrast, the DOPC-LNPs showed the highest distribution in the pancreas and the lowest distribution in the liver and spleen. In addition, smaller particles showed better distribution throughout the pancreas. The most significant LNP distribution in the islets was observed for DOPC-LNPs with a particle size of 160 nm. Furthermore, larger LNPs tended to be distributed in the islets, whereas smaller LNPs tended to be distributed in the exocrine glands. DOPC-LNPs were distributed in the islets at all cholesterol concentrations, with a high distribution observed at >40% cholesterol and > 3% PEG and the distribution was higher at 24 h than at 4 h. Thus, LNP composition and particle size significantly affected islet distribution characteristics, indicating that DOPC-LNPs may be a drug delivery system for effectively targeting the pancreas and islets.

Computational-Aided Approach for the Optimization of Microfluidic-Based Nanoparticles Manufacturing Process

In the last few years, the microfluidic production of nanoparticles (NPs) is becoming a promising alternative to conventional industrial approaches (e.g., nanoprecipitation, salting out, and emulsification-diffusion) thanks to the production efficiency, low variability, and high controllability of the production parameters. Nevertheless, the development of new formulations and the switching of the production process toward microfluidic platforms requires expensive and time-consuming number of experiments for the tuning of the formulation to obtain NPs with specific morphological and functional characteristics. In this work, we developed a computational fluid dynamic pipeline, validated through an ad hoc experimental strategy, to reproduce the mixing between the solvent and anti-solvent (i.e., acetonitrile and TRIS–HCl, respectively). Moreover, beyond the classical variables able to describe the mixing performances of the microfluidic chip, novel variables were described in order to assess the region of the NPs formation and the changing of the amplitude of the precipitation region according to different hydraulic conditions. The numerical approach proved to be able to capture a progressive reduction of the nanoprecipitation region due to an increment of the flow rate ratio; in parallel, through the experimental production, a progressive increment of the NPs size heterogeneity was observed with the same fluid dynamic conditions. Hence, the preliminary comparison between numerical and experimental evidence proved the effectiveness of the computational strategy to optimize the NPs manufacturing process.Graphical