A rapid millifluidic synthesis of tunable polymer-protein nanoparticles

A do-it-yourself benchtop device for highly scalable flow synthesis of protein-based nanoparticles

Synthesis of nanoparticles is typically carried out in batch procedures, which offer limited control of parameters, and a narrow range of possible batch volumes. In contrast, flow synthesis systems, usually having a microfluidic chip as a crucial part, are devoid of these drawbacks. However, large scale devices - millifluidic systems - may offer several advantages over microfluidic systems, such as easier and cheaper production, enhanced throughput, and reduced channel clogging. Here we report a millifluidic system for the generation of protein nanoparticles, using the flow format of the original swift thermal formation technology (STF), which can process batch volume ranging from 100 µl to any practically significant amount. Capabilities of the system are demonstrated with model synthesis of Epirubicin-encapsulated BSA nanoparticles. A better degree of scalability of the synthesis over batch procedure is shown: with a 10-fold working volume increase, hydrodynamic diameter and loading capacity changed by only 10 % and 1 % respectively, compared to 60 % and 30 % for the batch synthesis. Additionally, we provide all engineering drawings, electrical circuits, programming code and nuances of assembly and operation, so that our findings can be easily reproduced. The ease of construction of the device and the superior characteristics of the resulting nanoparticles compared to the batch method indicate application potential in both the biomedical research and industrial spheres.

Recent developments in the fabrication of food microparticles and nanoparticles using microfluidic systems

Microfluidics is revolutionizing the production of microparticles and nanoparticles, offering precise control over dimensions and internal structure. This technology facilitates the creation of colloidal delivery systems capable of encapsulating and releasing nutraceuticals. Nutraceuticals, often derived from food-grade ingredients, can be used for developing functional foods. This review focuses on the principles and applications of microfluidic systems in crafting colloidal delivery systems for nutraceuticals. It explores the foundational principles behind the development of microfluidic devices for nutraceutical encapsulation and delivery. Additionally, it examines the prospects and challenges with using microfluidics for functional food development. Microfluidic systems can be employed to form emulsions, liposomes, microgels and microspheres, by manipulating minute volumes of fluids flowing within microchannels. This versatility can enhance the dispersibility, stability, and bioavailability of nutraceuticals. However, challenges as scaling up production, fabrication complexity, and microchannel clogging hinder the widespread application of microfluidic technologies. In conclusion, this review highlights the potential role of microfluidics in design and fabrication of nutraceutical delivery systems. At present, this technology is most suitable for exploring the role of specific delivery system features (such as particle size, composition and morphology) on the stability and bioavailability of nutraceuticals, rather than for large-scale production of nutraceutical delivery systems.

Self-Therapeutic Nanomaterials: Applications in Biology and Medicine

Over past decades, nanotechnology has contributed to the biomedical field in areas including detection, diagnosis, and drug delivery via opto-electronic properties or enhancement of biological effects. Though generally considered inert delivery vehicles, a plethora of past and present evidence demonstrates that nanomaterials also exude unique intrinsic biological activity based on composition, shape, and surface functionalization. These intrinsic biological activities, termed self-therapeutic properties, take several forms, including mediation of cell-cell interactions, modulation of interactions between biomolecules, catalytic amplification of biochemical reactions, and alteration of biological signal transduction events. Moreover, study of biomolecule-nanomaterial interactions offers a promising avenue for uncovering the molecular mechanisms of biology and the evolution of disease. In this review, we observe the historical development, synthesis, and characterization of self-therapeutic nanomaterials. Next, we discuss nanomaterial interactions with biological systems, starting with administration and concluding with elimination. Finally, we apply this materials perspective to advances in intrinsic nanotherapies across the biomedical field, from cancer therapy to treatment of microbial infections and tissue regeneration. We conclude with a description of self-therapeutic nanomaterials in clinical trials and share our perspective on the direction of the field in upcoming years.

Microfluidic Nanoparticles for Drug Delivery

Nanoparticles (NPs) have attracted tremendous interest in drug delivery in the past decades. Microfluidics offers a promising strategy for making NPs for drug delivery due to its capability in precisely controlling NP properties. The recent success of mRNA vaccines using microfluidics represents a big milestone for microfluidic NPs for pharmaceutical applications, and its rapid scaling up demonstrates the feasibility of using microfluidics for industrial-scale manufacturing. This article provides a critical review of recent progress in microfluidic NPs for drug delivery. First, the synthesis of organic NPs using microfluidics focusing on typical microfluidic methods and their applications in making popular and clinically relevant NPs, such as liposomes, lipid NPs, and polymer NPs, as well as their synthesis mechanisms are summarized. Then, the microfluidic synthesis of several representative inorganic NPs (e.g., silica, metal, metal oxide, and quantum dots), and hybrid NPs is discussed. Lastly, the applications of microfluidic NPs for various drug delivery applications are presented.

Sustainable, Green, and Continuous Synthesis of Fivefold Palladium Nanorods Using l-Ascorbic Acid in a Segmented Millifluidic Flow Reactor

Pd nanorods (PdNRs) have recently come to attention due to their wide array of applications. The green synthesis of PdNR with a relatively high yield and high aspect ratio is challenging. A continuous millifluidic flow reactor (CMFR) has been explored to precisely control mass and heat transfer as well as mixing in the PdNR synthesis processes. CMFRs demonstrate a few drawbacks, such as the presence of parabolic velocity profile in the laminar flow of the reaction solution, causing uneven axial residence time distribution. The CMFRs are likely to show irreversible fouling, which may cause the product quality to deteriorate or result in the channel being clogged. These shortcomings can be avoided or minimized using a segmented millifluidic flow reactor (SMFR) that consists of the solution forming a train of individual segments in another inert medium. This study explores the use of a sustainable reducing agent (l-ascorbic acid) in the presence of potassium bromide (KBr) as the capping agent and poly(vinyl pyrrolidone) (PVP) as the stabilizing agent for PdNR synthesis in an SMFR employing compartmentalized flow of a reaction solution, in which liquid segments consisting of a reaction solution will be immersed in the steam generated by boiling of the solvent water. The effect of reaction parameters such as reagent concentration has been studied on the size and morphology of synthesized Pd nanostructures. A kinetic study has been conducted to calculate the rate of reduction that can be used as a quantitative measure for manipulation of the type and relative concentration of initially formed seeds. It has been shown that the initial reduction rate during the first 45 min of residence time of the millifluidic reactor is about 66% faster compared to the rest of the reaction. A filtration procedure has been utilized to separate Pd nanostructures other than nanorods synthesized in the SMFR.

Estimating the density of deep eutectic solvents applying supervised machine learning techniques

Deep eutectic solvents (DES) are recently synthesized to cover limitations of conventional solvents. These green solvents have wide ranges of potential usages in real-life applications. Precise measuring or accurate estimating thermophysical properties of DESs is a prerequisite for their successful applications. Density is likely the most crucial affecting characteristic on the solvation ability of DESs. This study utilizes seven machine learning techniques to estimate the density of 149 deep eutectic solvents. The density is anticipated as a function of temperature, critical pressure and temperature, and acentric factor. The LSSVR (least-squares support vector regression) presents the highest accuracy among 1530 constructed intelligent estimators. The LSSVR predicts 1239 densities with the mean absolute percentage error (MAPE) of 0.26% and R² = 0.99798. Comparing the LSSVR and four empirical correlations revealed that the earlier possesses the highest accuracy level. The prediction accuracy of the LSSVR (i.e., MAPE = 0. 26%) is 74.5% better than the best-obtained results by the empirical correlations (i.e., MAPE = 1.02%).

Extraction of Time-Domain Characteristics and Selection of Effective Features Using Correlation Analysis to Increase the Accuracy of Petroleum Fluid Monitoring Systems

In the current paper, a novel technique is represented to control the liquid petrochemical and petroleum products passing through a transmitting pipe. A simulation setup, including an X-ray tube, a detector, and a pipe, was conducted by Monte Carlo N Particle-X version (MCNPX) code to examine a two-by-two mixture of four diverse petroleum products (ethylene glycol, crude oil, gasoline, and gasoil) in various volumetric ratios. As the feature extraction system, twelve time characteristics were extracted from the received signal, and the most effective ones were selected using correlation analysis to present reasonable inputs for neural network training. Three Multilayers perceptron (MLP) neural networks were applied to indicate the volume ratio of three kinds of petroleum products, and the volume ratio of the fourth product can be feasibly achieved through the results of the three aforementioned networks. In this study, increasing accuracy was placed on the agenda, and an RMSE < 1.21 indicates this high accuracy. Increasing the accuracy of predicting volume ratio, which is due to the use of appropriate characteristics as the neural network input, is the most important innovation in this study, which is why the proposed system can be used as an efficient method in the oil industry.

Hybrid Nanosystems for Biomedical Applications

Inorganic/organic hybrid nanosystems have been increasingly developed for their versatility and efficacy at overcoming obstacles not readily surmounted by nonhybridized counterparts. Currently, hybrid nanosystems are implemented for gene therapy, drug delivery, and phototherapy in addition to tissue regeneration, vaccines, antibacterials, biomolecule detection, imaging probes, and theranostics. Though diverse, these nanosystems can be classified according to foundational inorganic/organic components, accessory moieties, and architecture of hybridization. Within this Review, we begin by providing a historical context for the development of biomedical hybrid nanosystems before describing the properties, synthesis, and characterization of their component building blocks. Afterward, we introduce the architectures of hybridization and highlight recent biomedical nanosystem developments by area of application, emphasizing hybrids of distinctive utility and innovation. Finally, we draw attention to ongoing clinical trials before recapping our discussion of hybrid nanosystems and providing a perspective on the future of the field.

A review on the green and sustainable synthesis of silver nanoparticles and one-dimensional silver nanostructures

The significance of silver nanostructures has been growing considerably, thanks to their ubiquitous presence in numerous applications, including but not limited to renewable energy, electronics, biosensors, wastewater treatment, medicine, and clinical equipment. The properties of silver nanostructures, such as size, size distribution, and morphology, are strongly dependent on synthesis process conditions such as the process type, equipment type, reagent type, precursor concentration, temperature, process duration, and pH. Physical and chemical methods have been among the most common methods to synthesize silver nanostructures; however, they possess substantial disadvantages and short-comings, especially compared to green synthesis methods. On the contrary, the number of green synthesis techniques has been increasing during the last decade and they have emerged as alternative routes towards facile and effective synthesis of silver nanostructures with different morphologies. In this review, we have initially outlined the most common and popular chemical and physical methodologies and reviewed their advantages and disadvantages. Green synthesis methodologies are then discussed in detail and their advantages over chemical and physical methods have been noted. Recent studies are then reviewed in detail and the effects of essential reaction parameters, such as temperature, pH, precursor, and reagent concentration, on silver nanostructure size and morphology are discussed. Also, green synthesis techniques used for the synthesis of one-dimensional (1D) silver nanostructures have been reviewed, and the potential of alternative green reagents for their synthesis has been discussed. Furthermore, current challenges regarding the green synthesis of 1D silver nanostructures and future direction are outlined. To sum up, we aim to show the real potential of green nanotechnology towards the synthesis of silver nanostructures with various morphologies (especially 1D ones) and the possibility of altering current techniques towards more environmentally friendly, more energy-efficient, less hazardous, simpler, and cheaper procedures.

Continuous-Flow Production of Liposomes with a Millireactor under Varying Fluidic Conditions

Continuous-flow production of liposomes using microfluidic reactors has demonstrated advantages compared to batch methods, including greater control over liposome size and size distribution and reduced reliance on post-production processing steps. However, the use of microfluidic technology for the production of nanoscale vesicular systems (such as liposomes) has not been fully translated to industrial scale yet. This may be due to limitations of microfluidic-based reactors, such as low production rates, limited lifetimes, and high manufacturing costs. In this study, we investigated the potential of millimeter-scale flow reactors (or millireactors) with a serpentine-like architecture, as a scalable and cost-effective route to the production of nanoscale liposomes. The effects on liposome size of varying inlet flow rates, lipid type and concentration, storage conditions, and temperature were investigated. Liposome size (i.e., mean diameter) and size dispersity were characterised by dynamic light scattering (DLS); z-potential measurements and TEM imaging were also carried out on selected liposome batches. It was found that the lipid type and concentration, together with the inlet flow settings, had significant effects on the properties of the resultant liposome dispersion. Notably, the millifluidic reactor was able to generate liposomes with size and dispersity ranging from 54 to 272 nm, and from 0.04 to 0.52 respectively, at operating flow rates between 1 and 10 mL/min. Moreover, when compared to a batch ethanol-injection method, the millireactor generated liposomes with a more therapeutically relevant size and size dispersity.