Diffusion Of Nanoparticles Research Articles

Photo-Controlled Dynamics and Transport in Entangled Wormlike Micellar Nanocomposites Studied by XPCS

Dynamics of nanoparticles (NPs) in microscopic networks, in particular, localization and transport, play a key role in designing new functional nanocomposites and drug delivery systems. To this aim, it is crucial to understand the interplay between the network structure and dynamics on the microscopic scale which determines NP diffusion. Here, we study the localization and transport of spherical NPs in photorheological wormlike micellar nanocomposites where the mobility of the NPs is controlled by the network mesh size and the micelle length, which can be tuned by UV-illumination. The macroscopic viscoelastic properties are measured by classical rheology, while X-ray photon correlation spectroscopy and nanorheology provide information on the microscopic NP dynamics on length scales on the order of the network mesh size. On long time scales, the data reveal that transport through the network is determined by the ratio between the NP size and the network mesh size, while upon UV illumination, the NP mobility is drastically enhanced. On shorter time scales, the influence of the dynamical and structural micelle properties on the NP dynamics under confinement is explored and indicates an anomalous speed-up of the dynamics, which is discussed in the context of changes in the local structure and non-linear phenomena such as strain stiffening and hopping motion.

Influence of thermophoretic diffusion of nanoparticles with Joule heating in flow of Maxwell nanofluid

AbstractThe aspects of activation energy in magnetized Maxwell nanofluid flow with Brownian movement and thermophoretic diffusion have been elaborated here. Furthermore, Joule heating, variable conductivity and chemical reaction are scrutinized. The Buongiorno nanofluid thought is ratify to incorporate the importance of thermophoretic and Brownian diffusion. The attained ODEs have been solved via homotopic algorithm. The performance of operational variables is inspected. The Maxwell temperature field for Eckert number and variable conductivity factor have similar trend. The fluid concentration exaggerates for activation energy and decelerates for Brownian motion parameter. Furthermore, the brilliant outcomes attained and associated with possible existing prose accurately.

Who wins the race near the interface? Stratification of colloids, nano-surfactants, and others

The diffusion of colloids, nanoparticles, and small molecules near the gas–liquid interface presents interesting multiphase transport phenomena and unique opportunities for understanding interactions near the surface and interface. Stratification happens when different species preside over the interfaces in the final dried coating structure. Understanding the principles of stratification can lead to emerging technologies for materials’ fabrication and has the potential to unlock innovative industrial solutions, such as smart coatings and drug formulations for controlled release. However, stratification can be perplexing and unpredictable. It may involve a complicated interplay between particles and interfaces. The surface chemistry and solution conditions are critical in determining the race of particles near the interface. Current theory and simulation cannot fully explain the observations in some experiments, especially the newly developed stratification of nano-surfactants. Here, we summarize the efforts in the experimental work, theory, and simulation of stratification, with an emphasis on bridging the knowledge gap between our understanding of surface adsorption and bulk diffusion. We will also propose new mechanisms of stratification based on recent observations of nano-surfactant stratification. More importantly, the discussions here will lay the groundwork for future studies beyond stratification and nano-surfactants. The results will lead to the fundamental understanding of nanoparticle interactions and transport near interfaces, which can profoundly impact many other research fields, including nanocomposites, self-assembly, colloidal stability, and nanomedicine.

Molecular simulation of hopping mechanisms of nanoparticles in regular cross-linked polymer networks.

We use coarse-grained simulations to explore the diffusion mechanism of nanoparticles with different sizes at various nanoparticle-polymer interactions in regular cross-linked polymer networks. The long time diffusivities of nanoparticles show a non-monotonic tendency at various nanoparticle-polymer interactions due to the intermittent hopping of nanoparticles through network cells. The preferred locations of small nanoparticles switch from the cell centers to the corners of cells as they interact with the network more strongly, which results in the hopping energy barrier between different cells switching from cell center localization to adsorption on networks. Steric hindrance seriously hampers large nanoparticles from hopping to neighboring network cells, and the interactions between the nanoparticle and network enhance the network deformability and also affect the hopping of nanoparticles. The multiple constraint mechanisms result in the non-monotonic diffusivities of nanoparticles with different interactions and non-Brownian motions at different time scales. Our work illustrates the hopping mechanisms of nanoparticles in polymer networks from thermodynamic and dynamic points of view.

Diffusion and thermo-driven migration of silver, palladium, and ruthenium nanoparticles in cubic SiC matrix using molecular dynamics

The diffusion and thermo-driven migration behaviors of metal fission products in cubic SiC are critical for determining the safety of a high-temperature gas-cooled reactor, and the molecular dynamics (MD) approach can describe the phenomenon from a microscopic perspective. The interactions of three metal elements, Ag, Pd, Ru, and SiC, were described using the Analytical Bond-Order Potential (ABOP). The diffusion coefficient of metal nanoparticles within the SiC matrix was calculated at various temperatures, and the results revealed that Ag > Pd > Ru. Furthermore, thermo-driven migration simulations were carried out using three alternative matrix morphologies: pure cubic SiC, nano-polycrystalline SiC, and SiC with a nanochannel. It is illustrated that Ag nanoparticles transport farthest in the SiC nanocrack from the high-temperature region to the low-temperature region and the magnitude is considerably greater than that in the other two cases. Therefore, the size of the SiC nanochannel and metal nanoparticles were investigated additionally, indicating that there are optimal-matching geometric parameters for Ag and Ru, but no noticeable effect on Pd nanoparticles. The findings of this study allow for the calculation of the diffusion coefficient used in source term analysis, as well as the examination of fission product migration behavior in a large temperature gradient field.

Studying Diffusion of Colloidal Nanoparticles in Solution Using Liquid Phase TEM and Machine Learning

Studying Diffusion of Colloidal Nanoparticles in Solution Using Liquid Phase TEM and Machine Learning

Effect of hybrid nanoparticles on conjugate mixed convection of a viscoplastic fluid in a ventilated enclosure with wall mounted heated block

We consider the thermal performance due to mixed convection and conjugate heat transfer of a Al2O3- Cu/viscoplastic hybrid nanofluid in a ventilated enclosure. A cold viscoplastic hybrid nanofluid is injected through the inlet port placed at the lower left corner of the enclosure and an outlet is placed at lower right corner. A heated solid obstacle is mounted at the bottom wall of the enclosure and the left wall of the enclosure is considered to be uniformly heated. The viscoplastic nanofluid is modeled as the Casson fluid, in which the plastic viscosity is considered to be temperature dependent. Nanoparticles mass flux due to both Brownian and thermophoretic diffusion along with convection is taken into account. The Corcione model for the thermal conductivity and viscosity of the hybrid nanofluid is adopted. The presence of the heated obstacle at the lower wall induces a recirculating vortex above it, which reduces the heat transfer from the enclosure. This vortex disappears when higher range of Reynolds number is considered. Our results show that the inclusion of Cu-nanoparticles in the Al2O3-viscoplastic fluid manifests the heat transfer. The yield stress of the fluid reduces the heat transfer but enhances the entropy generation. The thermal performance of the system is evaluated by presenting the heat transfer to entropy generation ratio. An enhancement of the solid-to-fluid conductivity ratio intensifies the heat transfer as well as entropy generation. Hybrid nanofluid enhances both heat transfer as well as entropy generation with the rate of heat transfer higher than the rate of entropy generation. A comparison with the corresponding homogeneous model is provided to analyze the effect of slip velocity created by Brownian diffusion and thermophoresis of nanoparticles.

Multi-scale modelling of nanoparticle delivery and heat transport in vascularised tumours.

We focus on modelling of cancer hyperthermia driven by the application of the magnetic field to iron oxide nanoparticles. We assume that the particles are interacting with the tumour environment by extravasating from the vessels into the interstitial space. We start from Darcy's and Stokes' problems in the interstitial and fluid vessels compartments. Advection-diffusion of nanoparticles takes place in both compartments (as well as uptake in the tumour interstitium), and a heat source proportional to the concentration of nanoparticles drives heat diffusion and convection in the system. The system under consideration is intrinsically multi-scale. The distance between adjacent vessels (the micro-scale) is much smaller than the average tumour size (the macro-scale). We then apply the asymptotic homogenisation technique to retain the influence of the micro-structure on the tissue scale distribution of heat and particles. We derive a new system of homogenised partial differential equations (PDEs) describing blood transport, delivery of nanoparticles and heat transport. The new model comprises a double Darcy's law, coupled with two double advection-diffusion-reaction systems of PDEs describing fluid, particles and heat transport and mass, drug and heat exchange. The role of the micro-structure is encoded in the coefficients of the model, which are to be computed solving appropriate periodic problems. We show that the heat distribution is impaired by increasing vessels' tortuosity and that regularization of the micro-vessels can produce a significant increase (1-2 degrees) in the maximum temperature. We quantify the impact of modifying the properties of the magnetic field depending on the vessels' tortuosity.

Mouse Strain- and Charge-Dependent Vessel Permeability of Nanoparticles at the Lower Size Limit.

Remarkable advancement has been made in the application of nanoparticles (NPs) for cancer therapy. Although NPs have been favorably delivered into tumors by taking advantage of the enhanced permeation and retention (EPR) effect, several physiological barriers present within tumors tend to restrict the diffusion of NPs. To overcome this, one of the strategies is to design NPs that can reach lower size limits to improve tumor penetration without being rapidly cleared out by the body. Several attempts have been made to achieve this, such as selecting appropriate nanocarriers and modifying surface properties. While many studies focus on the optimal design of NPs, the influence of mouse strains on the effectiveness of NPs remains unknown. Therefore, this study aimed to assess whether the vascular permeability of NPs near the lower size limit differs among mouse strains. We found that the vessel permeability of dextran NPs was size-dependent and dextran NPs with a size below 15 nm exhibited leakage from postcapillary venules in all strains. Most importantly, the leakage rate of 8-nm fluorescein isothiocyanate dextran was significantly higher in the BALB/c mouse strain than in other strains. This strain dependence was not observed in slightly positive TRITC-dextran with comparable sizes. Our results indicate that the influence on mouse strains needs to be taken into account for the evaluation of NPs near the lower size limit.

Tumor extracellular matrix modulating strategies for enhanced antitumor therapy of nanomedicines

Nanomedicines have shown a promising strategy for cancer therapy because of their higher safety and efficiency relative to small-molecule drugs, while the dense extracellular matrix (ECM) in tumors often acts as a physical barrier to hamper the accumulation and diffusion of nanoparticles, thus compromising the anticancer efficacy. To address this issue, two major strategies including degrading ECM components and inhibiting ECM formation have been adopted to enhance the therapeutic efficacies of nanomedicines. In this review, we summarize the recent progresses of tumor ECM modulating strategies for enhanced antitumor therapy of nanomedicines. Through degrading ECM components or inhibiting ECM formation, the accumulation and diffusion of nanoparticles in tumors can be facilitated, leading to enhanced efficacies of chemotherapy and phototherapy. Moreover, the ECM degradation can improve the infiltration of immune cells into tumor tissues, thus achieving strong immune response to reject tumors. The adoptions of these two ECM modulating strategies to improve the efficacies of chemotherapy, phototherapy, and immunotherapy are discussed in detail. A conclusion, current challenges and outlook are then given.

Shrinkable Hydrogel-Enhanced Biomarker Detection with X-ray Fluorescent Nanoparticles.

This paper reports a new method to enhance the sensitivity of nanoparticle-based protein detection with X-ray fluorescence by exploiting the large volume reduction of hydrogel upon dehydration. A carboxylated agarose hydrogel with uniaxial microchannels is used to allow rapid diffusion of nanoparticles and biomolecules into the hydrogel and water molecules out of the hydrogel. Carboxylated hydrogels are modified to capture protein biomarkers and X-ray fluorescence nanoparticles (iron oxide nanoparticles) are modified with antibodies that are specific to protein biomarkers. The presence of protein biomarkers in solution binds the nanoparticles on the hydrogel channels. The dehydration of hydrogels leads to a size reduction of over 80 times, which increases the number of nanoparticles in the interaction volume of the primary X-ray beam and the intensity of characteristic X-ray fluorescence signal. A detection limit of 2 μg/mL for protein detection has been established by determining the number of nanoparticles using X-ray fluorescence.

High-Density Branched PEGylation for Nanoparticle Drug Delivery.

The surface modification of nanoparticles (NP) with a dense layer of polyethylene glycol (PEG) has been widely used to improve NP circulation time, bioavailability, and diffusion through biological barriers [e.g. extracellular matrix (ECM), mucus]. While linear PEG coatings are commonly used, branched PEG coatings have not been widely explored as a design parameter for NP drug delivery systems. NPs were densely coated with either linear 2, 5, 10kDa linear PEG or with 10kDa star-shaped, 4-arm branched PEG. NP cellular uptake was evaluated in HEK-293T and A549 cells. NP stability was evaluated in fetal bovine serum over 24h using dynamic light scattering. Diffusion of NPs within a Matrigel ECM model and sputum (mucus) collected from individuals with cystic fibrosis (CF) lung disease were analyzed through multiple particle tracking. PEG-coated NPs appeared more stable in serum compared to uncoated NPs, but the reduction in total protein adsorbed was most significant for branched PEG coated NP. All PEGylated NPs had similar cellular uptake in HEK-293T and A549 cells. Interestingly, branched-PEG coated NPs had the largest diffusion coefficient and moved most rapidly through Matrigel. However in CF mucus, linear 2 and 5 kDa PEG coated NPs had the largest fraction of rapidly diffusing particles while branched PEG coated NPs had less hindered mobility compared to linear 10 kDa PEG coated NPs. Branched PEGylation may have the potential to increase NP efficiency in reaching target cells based on an apparent increase in diffusion through an ECM model while maintaining NP stability and uptake in target cells comparable to their linear PEG counterparts.

Effect of ultrasound amplitude and frequency on nanoparticle diffusion in an agarose hydrogel

Exposure of nanoparticles in a porous medium, such as a hydrogel, to low-intensity ultrasound has been observed to dramatically enhance particle penetration rate. Enhancement of nanoparticle penetration is a key issue affecting applications such as biofilm mitigation and targeted drug delivery in human tissue. The current study used fluorescent imaging to obtain detailed experimental measurements of the effect of ultrasound amplitude and frequency on diffusion of nanoparticles of different diameters in an agarose hydrogel, which is often used as a simulant for biofilms and biological tissues. We demonstrate that the acoustic enhancement occurs via the phenomenon of oscillatory diffusion, in which a combination of an oscillatory flow together with random hindering of the particles by interaction with hydrogel proteins induces a stochastic random walk of the particles. The measured variation of acoustic diffusion coefficients with amplitude and frequency were used to validate a previous statistical theory of oscillatory diffusion based on the continuous time random walk approach.

Tracking Exciton Diffusion and Exciton Annihilation in Single Nanoparticles of Conjugated Polymers by Photon Correlation Spectroscopy

AbstractA fundamental question relating to the nature of light emission and absorption in organic semiconductors is the dimension of the domain within a bulk material responsible for the interaction of light and matter. How large can a nanoparticle become to retain the quantized nature of light emission? Excitons are only a few nanometers in size, but because they diffuse in space, they probe a much larger volume than the single molecule. When excitons meet, they may decay non‐radiatively by singlet–singlet or singlet–triplet annihilation (SSA or STA). Fluorescence photon statistics reveal whether single photons are emitted (photon antibunching) or arrive in randomly spaced packets (photon bunching), offering direct insight into excitonic mobility. Single multichain nanoparticles of ladder‐type poly(para‐phenylene) (LPPP) are examined. The effect of SSA and STA is seen in the photon antibunching and bunching, respectively, which both decrease in fidelity as the size of the nanoparticle increases. Time resolving the photon correlation measurement yields microscopic annihilation rates for SSA and STA in agreement with values obtained from bulk LPPP films. Even though triplets in LPPP are known to be highly mobile, the results show that, on the timescale of the singlet exciton lifetime, triplet diffusion is not of significance in the STA process.

Significance of bioconvection and mass transpiration for MHD micropolar Maxwell nanofluid flow over an extending sheet*

Motivated by several practical submissions, the current modeling addresses the theoretical and numerical aspects of Maxwell micropolar nanofluids with diluted homogeneous diffusion of nanoparticles and gyrotactic microorganisms. Nanoparticles are considered due to extraordinary thermal conductivity, which are very useful in modern technology, electronics, heat exchangers, and material sciences. Further, gyrotactic microorganisms are incorporated to avoid possible sedimentation. The similarity variables are used to transform the flow equations into corresponding non-dimensional ODEs, furthermore these ODEs are transmuted into linear form by adopting shooting technique. The graphical and numerical results are utilized by computational software Matlab with Runge–Kutta order 4 method. Numerical and graphical consequences of velocity, micro-rotation, temperature, concentration and motile density profiles are displayed. As uplifting values of magnetic parameter, a twisting behavior is observed on micro-rotational profile but velocity profile is diminishing. The motile density profile is decline when Lewis and Peclet numbers are boosted. Temperature distribution increased for larger values of Brownian motion, Rayleigh number, and thermophoresis parameters.

Organotypic whole hemisphere brain slice models to study the effects of donor age and oxygen-glucose-deprivation on the extracellular properties of cortical and striatal tissue

BackgroundThe brain extracellular environment is involved in many critical processes associated with neurodevelopment, neural function, and repair following injury. Organization of the extracellular matrix and properties of the extracellular space vary throughout development and across different brain regions, motivating the need for platforms that provide access to multiple brain regions at different stages of development. We demonstrate the utility of organotypic whole hemisphere brain slices as a platform to probe regional and developmental changes in the brain extracellular environment. We also leverage whole hemisphere brain slices to characterize the impact of cerebral ischemia on different regions of brain tissue.ResultsWhole hemisphere brain slices taken from postnatal (P) day 10 and P17 rats retained viable, metabolically active cells through 14 days in vitro (DIV). Oxygen-glucose-deprivation (OGD), used to model a cerebral ischemic event in vivo, resulted in reduced slice metabolic activity and elevated cell death, regardless of slice age. Slices from P10 and P17 brains showed an oligodendrocyte and microglia-driven proliferative response after OGD exposure, higher than the proliferative response seen in DIV-matched normal control slices. Multiple particle tracking in oxygen-glucose-deprived brain slices revealed that oxygen-glucose-deprivation impacts the extracellular environment of brain tissue differently depending on brain age and brain region. In most instances, the extracellular space was most difficult to navigate immediately following insult, then gradually provided less hindrance to extracellular nanoparticle diffusion as time progressed. However, changes in diffusion were not universal across all brain regions and ages.ConclusionsWe demonstrate whole hemisphere brain slices from P10 and P17 rats can be cultured up to two weeks in vitro. These brain slices provide a viable platform for studying both normal physiological processes and injury associated mechanisms with control over brain age and region. Ex vivo OGD impacted cortical and striatal brain tissue differently, aligning with preexisting data generated in in vivo models. These data motivate the need to account for both brain region and age when investigating mechanisms of injury and designing potential therapies for cerebral ischemia.

Double-Spring Model for Nanoparticle Diffusion in a Polymer Network

The transport of nanoparticles (NPs) in polymer networks, as a typical simplified model describing various structures in living systems, is profoundly important in biomedical engineering and nanotechnology. Predicting the effective diffusivity of NP confined in an ordered network has been an intriguing focus in this frontier field. In the present study, the diffusion of NPs in an unentangled polymer network for different NP radii and network stiffness is numerically investigated by single particle dissipative particle dynamics (DPD). It is found that, the deformation due to the junction deviation contributes significantly to the the potential barrier $U$ for the NP to overcome during hopping, and it is dominated over the strain energy induced by loop stretching for larger NPs and lower network rigidity. Analyses based on the theory of continuum mechanics reveal that the relation between this deformed energy and the junction deviation can be described by a non-linear spring. Taking into account both effects of the loop stretching and junction deviation, a double-spring model is proposed to characterize the diffusivity of the NPs in the ordered network. The theoretical prediction is in good agreement with our numerical simulations, and qualitatively consistent with the investigations available. This model is helpful to improve our understanding on the dynamic behavior of nanoparticle in complex biological environment, and provide theoretical guidance in designing biomedical applications.

Machine learning-informed predictions of nanoparticle mobility and fate in the mucus barrier.

Nanomaterial diffusion through mucus is important to basic and applied areas of research such as drug delivery. However, it is often challenging to interpret nanoparticle dynamics within the mucus gel due to its heterogeneous microstructure and biochemistry. In this study, we measured the diffusion of polyethylene glycolylated nanoparticles (NPs) in human airway mucus ex vivo using multiple particle tracking and utilized machine learning to classify diffusive vs sub-diffusive NP movement. Using mathematic models that account for the mode of NP diffusion, we calculate the percentage of NPs that would cross the mucus barrier over time in airway mucus with varied total solids concentration. From this analysis, we predict rapidly diffusing NPs will cross the mucus barrier in a physiological timespan. Although less efficient, sub-diffusive “hopping” motion, a characteristic of a continuous time random walk, may also enable NPs to cross the mucus barrier. However, NPs exhibiting fractional Brownian sub-diffusion would be rapidly removed from the airways via mucociliary clearance. In samples with increased solids concentration (>5% w/v), we predict up to threefold reductions in the number of nanoparticles capable of crossing the mucus barrier. We also apply this approach to explore diffusion and to predict the fate of influenza A virus within human mucus. We predict only a small fraction of influenza virions will cross the mucus barrier presumably due to physical obstruction and adhesive interactions with mucin-associated glycans. These results provide new tools to evaluate the extent of synthetic and viral nanoparticle penetration through mucus in the lung and other tissues.

Relationship between Gel Mesh and Particle Size in Determining Nanoparticle Diffusion in Hydrogel Nanocomposites.

The diffusion of poly(ethylene glycol) methyl ether thiol (PEGSH)-functionalized gold nanoparticles (NPs) was measured in polyacrylamide gels with various cross-linking densities. The molecular weight of the PEGSH ligand and particle core size were both varied to yield particles with hydrodynamic diameters ranging from 7 to 21 nm. The gel mesh size was varied from approximately 36 to 60 nm by controlling the cross-linking density of the gel. Because high-molecular-weight ligands are expected to yield more compressible particles, we expected the diffusion constants of the NPs to depend on their hard/soft ratios (where the hard component of the particle consists of the particle core and the soft component of the particle consists of the ligand shell). However, our measurements revealed that NP diffusion coefficients resulted primarily from changes in the overall hydrodynamic diameter and not the ratio of particle core size to ligand size. Across all particles and gels, we found that the diffusion coefficient was well predicted by the confinement ratio calculated from the diameter of the particle and an estimate of the gel mesh size obtained from the elastic blob model and was well described using a hopping model for nanoparticle diffusion. These results suggest that the elastic blob model provides a reasonable estimate of the mesh size that particles "see" as they diffuse through the gel. This work brings new insights into the factors that dictate how NPs move through polymer gels and will inform the development of hydrogel nanocomposites for applications such as drug delivery in heterogeneous, viscoelastic biological materials.

Effect of cassava starch biofilm with diffusion of silver nanoparticles on the conservation of banana 'prata'

Brazil is now the world's fourth-largest banana producer in the world with an annual production of 6.953,747 tons per year. In Brazil, the banana (Musa spp.) stands out, not only because it is the most widespread, but also because it is the most consumed by all social classes. Cassava is a renewable, almost unlimited resource and one of the most abundant substances in nature. It is one of the most important starchy root crops of the tropics used for food and industrial purposes. The present study aimed to evaluate the use of biofilms based on cassava starch with the diffusion of silver nanoparticles (AgNP) on the conservation of banana 'Prata'. Initially, filmogenic solutions were produced using the casting technique for five treatments. Additionally, transparency, thickness, grammage, and, subsequently, the biofilms were applied in the film-forming solution for 1 min and suspended for further drying at room temperature. After this process, were evaluated the fresh mass loss and total soluble solids. This study revealed the efficiency of cassava starch biofilm with gelatin addition to reduce the enzymatic browning rate and increase the shelf life of bananas (Musa Subgroup Prata). However, no significant results were observed with the addition of commercial silver nanoparticles .