Browse
Submit Data
Databases
API
Help

Dataset Information

20 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Multi-Scale Modelling of Aggregation of TiO₂ Nanoparticle Suspensions in Water.

ABSTRACT: Titanium dioxide nanoparticles have risen concerns about their possible toxicity and the European Food Safety Authority recently banned the use of TiO₂ nano-additive in food products. Following the intent of relating nanomaterials atomic structure with their toxicity without having to conduct large-scale experiments on living organisms, we investigate the aggregation of titanium dioxide nanoparticles using a multi-scale technique: starting from ab initio Density Functional Theory to get an accurate determination of the energetics and electronic structure, we switch to classical Molecular Dynamics simulations to calculate the Potential of Mean Force for the connection of two identical nanoparticles in water; the fitting of the latter by a set of mathematical equations is the key for the upscale. Lastly, we perform Brownian Dynamics simulations where each nanoparticle is a spherical bead. This coarsening strategy allows studying the aggregation of a few thousand nanoparticles. Applying this novel procedure, we find three new molecular descriptors, namely, the aggregation free energy and two numerical parameters used to correct the observed deviation from the aggregation kinetics described by the Smoluchowski theory. Ultimately, molecular descriptors can be fed into QSAR models to predict the toxicity of a material knowing its physicochemical properties, enabling safe design strategies.

SUBMITTER: Mancardi G

PROVIDER: S-EPMC8778026 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Experimental measurement and modelling of reactive species generation in TiO2 nanoparticle photocatalysis.

Project description:The generation of reactive species in titanium dioxide (TiO2) nanoparticle photocatalysis was assessed in a laboratory scale setup, in which P25 Aeroxide TiO2 suspensions were photoactivated by means of UV-A radiation. Photogenerated holes and hydroxyl radicals were monitored over time by observing their selective reaction with probe compounds, iodide and terephthalic acid, respectively. TiO2 aggregate size and structure were characterized over the reaction time. Reactive species quenching was then described by a model, accounting for radiative phenomena, TiO2 nanoparticle aggregation and kinetic reactions. The interaction between iodide and photogenerated holes was influenced by iodide adsorption on TiO2 surface, described by a Langmuir-Hinshelwood mechanism, whose parameters were studied as a function of TiO2 concentration and irradiation time. Iodide oxidation was effectively simulated by modelling the reaction volume as a completely stirred two-dimensional domain, in which irradiation phenomena were described by a two-flux model and the steady state for reactive species was assumed. The kinetic parameters for iodide adsorption and oxidation were estimated and successfully validated in a different experimental setup. The same model was adapted to describe the oxidation of terephthalic acid by hydroxyl radicals. The kinetic parameters for terephthalic acid oxidation were estimated and validated, while the issues in investigating the interaction mechanisms among the involved species have been discussed. The sensitivity of operating parameters on model response was assessed and the most relevant parameters were highlighted.

| S-EPMC5119892 | biostudies-literature

Long-term stability and scale-up of noncovalently bound gold nanoparticle-siRNA suspensions.

Project description:Gold nanoparticles (AuNPs) are a platform for the creation of nanoconstructions that can have a variety of functions, including the delivery of therapeutic nucleic acids. We previously designed a AuNP/small interfering RNA (siRNA) nanoconstruction consisting of siRNA noncovalently bound on the AuNP surface and showed that this construction, when coated with a lipid shell, was an efficient vehicle for the delivery of siRNA into cells. The goal of the present work was to study the possibility of scaling up the synthesis of AuNP-siRNA and its long-term storage without loss of physicochemical characteristics and siRNA duplex integrity as well as siRNA surface density. Dynamic light scattering, transmission electron microscopy, UV-vis spectroscopy, and electrophoresis were used to study the effect of scaling up the AuNP-siRNA synthesis and long term storage of its suspension on physicochemical properties of the samples and integrity of the siRNA duplex. It was shown that a ten-fold increase in the volume of the reaction mixture decreased the surface density of siRNA by about 10%, which influenced the corresponding physicochemical characteristics of the AuNP-siRNA suspension. The storage of the AuNP-siRNA suspension at 4 °C for different times resulted in the formation of particle clusters of high colloidal stability as demonstrated by conventional methods. These clusters completely disintegrated when albumin was added, indicating that they are agglomerates (and not aggregates) of AuNP-siRNA. The AuNPs-siRNA nanoconstruction demonstrated integrity of the siRNA duplex and high stability of the siRNA surface density during storage for seven months at 4 °C. Thus, it can be concluded that it is possible to scale-up the synthesis of noncovalent AuNP-siRNA and to obtain a nanoconstruction possessing high stability in terms of physicochemical characteristics and siRNA surface density for a long period.

| S-EPMC6941443 | biostudies-literature

New, rapid method to measure dissolved silver concentration in silver nanoparticle suspensions by aggregation combined with centrifugation.

Project description:It is unclear whether the antimicrobial activities of silver nanoparticles (AgNPs) are exclusively mediated by the release of silver ions (Ag+) or, instead, are due to combined nanoparticle and silver ion effects. Therefore, it is essential to quantify dissolved Ag in nanosilver suspensions for investigations of nanoparticle toxicity. We developed a method to measure dissolved Ag in Ag+/AgNPs mixtures by combining aggregation of AgNPs with centrifugation. We also describe the reproducible synthesis of stable, uncoated AgNPs. Uncoated AgNPs were quickly aggregated by 2 mM Ca2+, forming large clusters that could be sedimented in a low-speed centrifuge. At 20,100g, the sedimentation time of AgNPs was markedly reduced to 30 min due to Ca2+-mediated aggregation, confirmed by the measurements of Ag content in supernatants with graphite furnace atomic absorption spectrometry. No AgNPs were detected in the supernatant by UV-Vis absorption spectra after centrifuging the aggregates. Our approach provides a convenient and inexpensive way to separate dissolved Ag from AgNPs, avoiding long ultracentrifugation times or Ag+ adsorption to ultrafiltration membranes.

| S-EPMC5003901 | biostudies-literature

Microscale Testing and Modelling of Cement Paste as Basis for Multi-Scale Modelling.

Project description:This work aims to provide a method for numerically and experimentally investigating the fracture mechanism of cement paste at the microscale. For this purpose, a new procedure was proposed to prepare micro cement paste cubes (100 × 100 × 100 µm³) and beams with a square cross section of 400 × 400 µm². By loading the cubes to failure with a Berkovich indenter, the global mechanical properties of cement paste were obtained with the aid of a nano-indenter. Simultaneously the 3D images of cement paste with a resolution of 2 µm³/voxel were generated by applying X-ray microcomputed tomography to a micro beam. After image segmentation, a cubic volume with the same size as the experimental tested specimen was extracted from the segmented images and used as input in the lattice model to simulate the fracture process of this heterogeneous microstructure under indenter loading. The input parameters for lattice elements are local mechanical properties of different phases. These properties were calibrated from experimental measured load displacement diagrams and failure modes in which the same boundary condition as in simulation were applied. Finally, the modified lattice model was applied to predict the global performance of this microcube under uniaxial tension. The simulated Young's modulus agrees well with the experimental data. With the method presented in this paper the framework for fitting and validation of the modelling at microscale was created, which forms a basis for multi-scale analysis of concrete.

| S-EPMC5457268 | biostudies-other

Deep Photometric Stereo Network with Multi-Scale Feature Aggregation.

Project description:We present photometric stereo algorithms robust to non-Lambertian reflection, which are based on a convolutional neural network in which surface normals of objects with complex geometry and surface reflectance are estimated from a given set of an arbitrary number of images. These images are taken from the same viewpoint under different directional illumination conditions. The proposed method focuses on surface normal estimation, where multi-scale feature aggregation is proposed to obtain a more accurate surface normal, and max pooling is adopted to obtain an intermediate order-agnostic representation in the photometric stereo scenario. The proposed multi-scale feature aggregation scheme using feature concatenation is easily incorporated into existing photometric stereo network architectures. Our experiments were performed with a DiLiGent photometric stereo benchmark dataset consisting of ten real objects, and they demonstrated that the accuracies of our calibrated and uncalibrated photometric stereo approaches were improved over those of baseline methods. In particular, our experiments also demonstrated that our uncalibrated photometric stereo outperformed the state-of-the-art method. Our work is the first to consider the multi-scale feature aggregation in photometric stereo, and we showed that our proposed multi-scale fusion scheme estimated the surface normal accurately and was beneficial to improving performance.

| S-EPMC7675179 | biostudies-literature

Multi-scale modelling to evaluate building energy consumption at the neighbourhood scale.

Project description:A new methodology is proposed to couple a meteorological model with a building energy use model. The aim of such a coupling is to improve the boundary conditions of both models with no significant increase in computational time. In the present case, the Canopy Interface Model (CIM) is coupled with CitySim. CitySim provides the geometrical characteristics to CIM, which then calculates a high resolution profile of the meteorological variables. These are in turn used by CitySim to calculate the energy flows in an urban district. We have conducted a series of experiments on the EPFL campus in Lausanne, Switzerland, to show the effectiveness of the coupling strategy. First, measured data from the campus for the year 2015 are used to force CIM and to evaluate its aptitude to reproduce high resolution vertical profiles. Second, we compare the use of local climatic data and data from a meteorological station located outside the urban area, in an evaluation of energy use. In both experiments, we demonstrate the importance of using in building energy software, meteorological variables that account for the urban microclimate. Furthermore, we also show that some building and urban forms are more sensitive to the local environment.

| S-EPMC5589157 | biostudies-literature

Inferring multi-scale neural mechanisms with brain network modelling.

Project description:The neurophysiological processes underlying non-invasive brain activity measurements are incompletely understood. Here, we developed a connectome-based brain network model that integrates individual structural and functional data with neural population dynamics to support multi-scale neurophysiological inference. Simulated populations were linked by structural connectivity and, as a novelty, driven by electroencephalography (EEG) source activity. Simulations not only predicted subjects' individual resting-state functional magnetic resonance imaging (fMRI) time series and spatial network topologies over 20 minutes of activity, but more importantly, they also revealed precise neurophysiological mechanisms that underlie and link six empirical observations from different scales and modalities: (1) resting-state fMRI oscillations, (2) functional connectivity networks, (3) excitation-inhibition balance, (4, 5) inverse relationships between α-rhythms, spike-firing and fMRI on short and long time scales, and (6) fMRI power-law scaling. These findings underscore the potential of this new modelling framework for general inference and integration of neurophysiological knowledge to complement empirical studies.

| S-EPMC5802851 | biostudies-literature

Nanoparticle corona artefacts derived from specimen preparation of particle suspensions.

Project description:Progress in the implementation of nanoparticles for therapeutic applications will accelerate with an improved understanding of the interface between nanoparticle surfaces and the media they are dispersed in. We examine this interface by analytical scanning transmission electron microscopy and show that incorrect specimen preparation or analysis can induce an artefactual, nanoscale, calcium phosphate-rich, amorphous coating on nanoparticles dispersed in cell culture media. We report that this ionic coating can be induced on five different types of nanoparticles (Au, BaTiO3, ZnO, TiO2 and Fe2O3) when specimen preparation causes a significant rise in pH above physiological levels. Such a pH change reduces ionic solubility in the suspending media to permit precipitation of calcium phosphate. Finally, we demonstrate that there is no indication of a calcium-phosphorus-rich coating on BaTiO3 nanoparticles suspended in culture media when prepared without alteration of the pH of the suspending media and imaged by cryo-STEM. Therefore we recommend that future reports utilising nanoparticles dispersed in cell culture media monitor and report the pH of suspensions during sample preparation.

| S-EPMC7093507 | biostudies-literature

Simultaneous Sizing and Refractive Index Analysis of Heterogeneous Nanoparticle Suspensions.

Project description:Rapid and reliable characterization of heterogeneous nanoparticle suspensions is a key technology across the nanosciences. Although approaches exist for homogeneous samples, they are often unsuitable for polydisperse suspensions, as particles of different sizes and compositions can lead to indistinguishable signals at the detector. Here, we introduce holographic nanoparticle tracking analysis, holoNTA, as a straightforward methodology that decouples size and material refractive index contributions. HoloNTA is applicable to any heterogeneous nanoparticle sample and has the sensitivity to measure the intrinsic heterogeneity of the sample. Specifically, we combined high dynamic range k-space imaging with holographic 3D single-particle tracking. This strategy enables long-term tracking by extending the imaging volume and delivers precise and accurate estimates of both scattering amplitude and diffusion coefficient of individual nanoparticles, from which particle refractive index and hydrodynamic size are determined. We specifically demonstrate, by simulations and experiments, that irrespective of localization uncertainty and size, the sizing sensitivity is improved as our extended detection volume yields considerably longer particle trajectories than previously reported by comparable technologies. As validation, we measured both homogeneous and heterogeneous suspensions of nanoparticles in the 40-250 nm size range and further monitored protein corona formation, where we identified subtle differences between the nanoparticle-protein complexes derived from avidin, bovine serum albumin, and streptavidin. We foresee that our approach will find many applications of both fundamental and applied nature where routine quantification and sizing of nanoparticles are required.

| S-EPMC9835976 | biostudies-literature

Multi-Scale-Porosity TiO2 scaffolds grown by innovative sputtering methods for high throughput hybrid photovoltaics.

Project description:We propose an up-scalable, reliable, contamination-free, rod-like TiO2 material grown by a new method based on sputtering deposition concepts which offers a multi-scale porosity, namely: an intra-rods nano-porosity (1-5?nm) arising from the Thornton's conditions and an extra-rods meso-porosity (10-50?nm) originating from the spatial separation of the Titanium and Oxygen sources combined with a grazing Ti flux. The procedure is simple, since it does not require any template layer to trigger the nano-structuring, and versatile, since porosity and layer thickness can be easily tuned; it is empowered by the lack of contaminations/solvents and by the structural stability of the material (at least) up to 500?°C. Our material gains porosity, stability and infiltration capability superior if compared to conventionally sputtered TiO2 layers. Its competition level with chemically synthesized reference counterparts is doubly demonstrated: in Dye Sensitized Solar Cells, by the infiltration and chemisorption of N-719 dye (?1?×?1020 molecules/cm3); and in Perovskite Solar Cells, by the capillary infiltration of solution processed CH3NH3PbI3 which allowed reaching efficiency of 11.7%. Based on the demonstrated attitude of the material to be functionalized, its surface activity could be differently tailored on other molecules or gas species or liquids to enlarge the range of application in different fields.

| S-EPMC5175132 | biostudies-literature