Individual Particle Level Research Articles

Shear rheology of confined double rings of dust particles in a dusty plasma

Abstract Shear rheology is a fundamental property of soft matter, which can be deformed. Although the shear rheology of fluids has been well studied at the macroscopic scale, understanding the microscopic processes of rheology at the single-particle level remains a challenging issue. Dusty plasma serves as an ideal platform for exploring microscopic dynamics of system at the individual particle level. Here, we study the shear rheology of confined double rings of strongly coupled dust particles in a dusty plasma. The outer ring is actively driven to rotate using laser illumination. Depending on the particle number, the inner ring may passively rotate following the outer ring at different angular speeds, resulting in shear rheology. The number of dust particles influences particle arrangement, which is characterized by the pair correlation function, bond-orientational order parameter, and triangle skewness. That further alters structural stability, significantly affecting the shear rheology.

Insights into chemical aging of urban aerosols over Delhi, India

Atmospheric particles can undergo aging as they are transported over long distances and mix with particles from other sources. This can lead to the accumulation of pollutants and the formation of complex aerosol mixtures with diverse chemical and physical properties. To investigate the process of aging in ambient atmosphere, 24h sampling of PM2.5 aerosol particles on Quartz microfiber filter with a tin substrate was carried out from November 2020 to March 2021 at CSIR-National Physical Laboratory, New Delhi (28°38'10″ N and 77°10′17" E), using fine particle sampler. Based on the observations of weather and meteorological parameters, a few episodic cases have been selected, and samples were analyzed at bulk and individual particle level. The objective of the present study is to investigate the aging characteristics of aerosols, enabling us to understand the mixing of aerosols (at both bulk and individual particle levels) and the variation in fresh and deformed (aged with other species) graphitic content in the episodic cases. The Raman Spectroscopy technique employed measures the intensity of graphitic (G band; around 1580 cm−1) and disordered graphitic (D band; around 1320 cm−1) content of aerosols. Individual particle microscopic observations reveal the occurrence of open chain fractals of black carbon in variable monomer sizes, sometimes agglomerated with metals like Cu, Cr, Ca etc., along with the presence of S- rich and organic aerosols while the Raman Spectrum (bulk sample analysis) highlights graphitic and disordered (when graphite interacts with other chemical species) graphitic intensities. Comparing the intensities of heavy haze and moderate haze with non-haze days (for comparison purpose, March 23, 2021 with the lowest PM2.5 concentration ∼ 62 μg/m3, has been considered as a non-haze day), it was observed that the intensities recorded on haze days were 45 to 200 times higher for the G band and 43 to 93 times higher for the D band; while for moderate haze days, the intensities were 4 to 61 times higher for the G band and 2 to 29 times higher for the D band. These findings suggest chemical processing of BC during haze days.

A software-agnostic benchmark for DEM simulation of cohesive and non-cohesive materials

Although DEM (Discrete Element Method) was introduced >40 years ago, there are still various challenges in applying it with a certain level of confidence. To develop a realistic material model, calibration, validation, particle shape representation and scaling are well-known challenges that have been studied by various researchers over the past two decades. In addition, once a realistic DEM material model is developed and published in line with open science principles, it is unknown to what extent the calibrated values can be used across software packages. Although a benchmark between 8 open source codes was recently published, it did not cover cohesive materials, rolling friction models, realistic calibrated material behaviour, and commercial software that is widely used in industries.The aim of this study is to investigate the portability of input parameters between different codes and to identify if software independent calibration is possible. We propose a framework to assist DEM users in industry and academia to reach a software independent DEM simulation when required.To compare the results between software packages, the framework considers the following aspects: 1) identical implementation of contact models, 2) single contact modelling, 3) bulk level simulation, and 4) identical post-processing. This framework is demonstrated for two contact models (Hertz-Mindlin and Edinburgh Elasto Plastic Adhesive) with rolling friction model and two commercial software packages (EDEM and PFC) but is applicable for any other (open-source) software. Moreover, two realistic calibrated material models are included to cover a range of material characteristics, from free-flowing incompressible materials to cohesive compressible materials. This study shows that individual particle level simulations give identical results, bulk level simulations show differences for both contact models. In general, users should use parameter values from other software packages with caution, especially where critical or sensitive applications are modelled. This paper also highlights the use of novel computation techniques, such as the GPU engine, to achieve practical computation times when modelling industrial applications.

Oral bioaccessibility of potentially toxic elements in various urban environmental media

An important aspect of geochemical studies is determining health hazard of potentially toxic elements (PTEs). Key information on PTEs behaviour in the human body in case of their ingestion is provided with the use of in vitro bioaccessibility tests. We analysed and compared oral bioaccessibility of a wide range of PTEs (As, Cd, Ce, Cr, Cu, Hg, La, Li, Ni, Pb, Sb, Sn, Zn), including some that are not often studied but might pose a human health hazard, in soil, attic dust, street dust, and household dust, using Unified BARGE Method (UBM). Additionally, feasibility of usage of scanning electron microscope techniques in analyses of solid residuals of UBM phases was tested. Results show that bioaccessible fractions (BAFs) of PTEs vary significantly between individual samples of the same medium, between different media and between the gastric and gastro-intestinal phases. In soil, attic dust and street dust, bioaccessibility of individual PTE is mostly higher in gastric than in gastro-intestinal phase. The opposite is true for PTEs in household dust. In all four media, with the exception of Pb in household dust, among the most bioaccessible PTEs in gastric phase are Cd, Cu, Pb, and Zn. During the transition from the stomach to small intestine, the mean BAFs of most elements in soil, attic dust, and street dust decreases. The most bioaccessible PTEs in gastro-intestinal phase are Cu, Cd, Ni, and As. Micromorphological and chemical characterisation at individual particle level before and after bioaccessibility test contribute significantly to the understanding of oral bioaccessibility.

Artificial Intelligence-Assisted Multiparameter Size Discrimination of Silver Nanoparticles through Electrochemical Collision.

Single particle collision is an important tool for size analysis at the individual particle level; however, due to complex dynamic behaviors of nanoparticles on the surface of an electrode, the accuracy of size discrimination is limited. A silver (Ag) nanoparticle (NP) was chosen as the research target, and the dynamic behavior of Ag NPs was simplified by enhancing adsorption between Ag NP and Au ultramicroelectrode (UME) in alkaline media. Immediately after, accurate dynamic and thermodynamic information on single Ag NP was accurately extracted from collision events, including current intensity, transferred charge, and duration time. On the basis that there were differences between parameters of different-sized Ag NPs, multiparameter size discrimination was proposed, which improved the accuracy compared to single-parameter discrimination. More intriguingly, multiparameter analysis was combined with artificial intelligence, a tool adept at processing multidimensional data, for the first time. Finally, artificial intelligence-assisted multiparameter size discrimination was successfully used to intelligently distinguish mixed Ag NPs, with an optimal accuracy of more than 95%. To sum up, the artificial intelligence-assisted multiparameter method showed an excellent ability to quickly achieve the most accurate size discrimination of nanoparticles at the level of individual particle and provide an effective guidance for the application of nanoparticles.

Fabrication of quantum dot-immobilized Y2O3 microspheres with effective photoluminescence for cancer radioembolization therapy

ABSTRACT Microspheres composed of Y-containing materials are effective agents for cancer radioembolization therapy using β-rays. The distribution and dynamics of these microspheres in tissues can be easily determined by providing the microspheres with an imaging function. In addition, the use of quantum dots will enable the detection of microspheres at the individual particle level with high sensitivity. In this study, core – shell quantum dots were bound to chemically modified yttria microspheres under various conditions, and the effect of reaction conditions on the photoluminescence properties of the microspheres was investigated. The quantum dots were immobilized on the surfaces of the microspheres through dehydration – condensation reactions between the carboxy groups of quantum dots and the amino groups of silane-treated microspheres. As the reaction time increased, the photoluminescence peak blue shifted, and the photoluminescence intensity and lifetime decreased. Therefore, a moderate period of the immobilization process was optimal for imparting effective photoluminescence properties. This study is expected to facilitate particle-level tracking of microsphere dynamics in biological tissues for the development of minimally invasive cancer radiotherapy of deep-seated tumors.

Extended relativistic kinetic model composed of the scalar and two vector distribution functions: Application to the spin-electron-acoustic waves

Detailed deterministic derivation of kinetic equations for relativistic plasmas is given. Focus is made on the dynamic of one-coordinate distribution functions of various tensor dimensions, but the closed set of kinetic equations is constructed of three functions: the scalar distribution function, the vector distribution function of dipole moment, and the vector distribution function of velocity (or the dipole moment in the momentum space). All two-coordinate distribution functions are discussed as well. They are presented together with their limits existing in the self-consistent field approximation. The dynamics of the small amplitude spin-electron-acoustic waves in the dense degenerate plasmas is studied within the kinetic model. This work presents the deterministic approach to the derivation and interpretation of the kinetic equations. So, no probability is introduced during the transition from the level of individual particles to the collective functions. The problem of thermalization is not considered, but we can see that the structure of kinetic equations is kept for the system before and after thermalization. Hence, the kinetic equations can be used to approach this item.

Unraveling the Crystal Facet and Support Effects on the Oxygen Evolution Activity of Cobalt Oxide Using Single Nanoparticle Electrocatalysis

Transition metal oxide catalysts have recently gained special interest in alkaline water electrolysis due to their relatively high abundancy and high catalytic activity. However, their catalytic performance has typically been evaluated based on measurements at composite electrodes, that is by immobilizing a large number of these nanoparticles together with inactive binders and additives on a current collector/support and measuring only their integral activity. In such studies, it is challenging to deconvolute the catalyst intrinsic properties from matrix effects. For example, the measured catalytic trends can be influenced by blocking of catalyst active sites by the additives or by non-optimal iR compensation or by different porosity within the composite, impeding a direct comparison of nanocatalysts.[1] Alternatively, single-particle electrocatalysis by the “nano impact” approach has been applied to assess the intrinsic activity of nanoparticles (NPs) at the individual particle level.[2] Exploiting this method, we demonstrate how the catalyst’s crystal facet/shape influences the OER activity by comparing the activity of cubes and spheres of Co3O4.[3] In contrast to the tentative differences in OER activity recorded on ensembles, the single particle studies unambiguously reveal that Co3O4 cubes are more active than spheres when both NPs have otherwise identical parameters. We also can link our experimental data to theory data obtained from DTU+U calculations. Furthermore, we investigate catalyst-support effects and show the higher activity of Pt support than carbon.[4]. This approach enables the identification of highly active facets to guide shape-selective syntheses of improved metal oxide nanocatalysts for water oxidation.

Introducing a Novel Light Scattering Technique for Visualising Operando State-of-Charge Changes Within Individual Active Particles and Across the Electrode

In our presentation we will demonstrate the application of a recently developed operando optical microscopy technique to mechanistic studies of lithium-ion battery electrodes and active material characterisation. Our technique probes state-of-charge (SoC) changes in the active particles within the electrode during battery operation, based on the intensity variation of scattered light across each active particle. This enables detailed spatially resolved data on an individual particle level to be utilised for furthering mechanistic understanding of battery capability and degradation, and it also allows global statistics to be established for the optimisation and screening of new electrode materials. The technique is agnostic to the underlying battery chemistry, so in principle can be applied to study any battery electrode.In this talk, we will demonstrate how our technique can be used in the study of two key dynamic processes, solid-state ion transport and mechanical degradation. The ability to quantify ion transport during battery operation helps to provide insights into how lithium-ion dynamics affect the (de)lithiation mechanisms and degradation mechanisms of battery electrodes, which is crucial to improving their electrochemical performance. Using lithium cobalt oxide (LCO) as a case study, we will show how ion-transport mechanisms can be deduced by observing moving phase boundaries within particles during cycling.We will then demonstrate how local SoC changes within Ni-rich nickel manganese cobalt oxide (NMC) active particles can be visualised during operation, and how the intra-particle ion gradients identified can be used to determine the mechanistic origins of first-cycle capacity losses. Building on this, we will highlight how variation in the rates of (dis)charge between a population of active particles could be used to characterise the performance of new electrode compositions.In addition, we will highlight how lithium-ion concentration gradients can also be identified in high-rate niobium tungsten oxide (NWO) anode materials during initial lithiation and under initial rapid delithiation conditions and demonstrate how this can lead to particle cracking. Expanding on this, we illustrate how the proportion of cracked particles within an electrode can be quantified and then monitored over successive cycles as a potential metric for screening the stability of new electrode materials.

On the Application Potential of Chemically Tailored Metal Oxide and Higher Chalcogenide Nanoparticles for Nanoscale Resistive Switching Devices

Resistive switching (RS) for nonvolatile data storage is a highly relevant field of research. Up to now, RS devices are fabricated via semiconductor processing technologies. This poses the question of whether integration of chemically tailored nanoparticles, either consisting of valence change or phase change materials, can be integrated in nanoelectrode configurations in order to explore their functionality for RS applications. This review discusses the RS properties of such nanoparticles by means of selected examples of both nanoparticle assemblies as well as on the individual particle level. Although this field of research is rather unexplored, it becomes evident that chemically tailored nanoparticles bear great potential for RS applications.

Numerical Simulation of Conveying Fine Powders in a Screw Conveyor Using the Discrete Element Method

Due to their high efficiency and spatial utilization, screw conveyors are widely used in pharmacy, agriculture, and industry. Recently, this has made it a popular research subject in the numerical modelling of the transport of bulk solids. Modelling of granular systems at the level of individual particles is mainly possible due to the use of discrete numerical methods. The most common is the use of the Discrete Element Method (DEM), which is still limited from the point of view of simulations on an industrial scale, as increasing the size of the system also increases the cost of simulation. Certain powders with low density, large angles of repose, poor fluidity, and bad flowability can accumulate during transportation, causing inaccurate and non-uniform movement. Additionally, the friction and impact between the particles can cause wear. To address these issues, the present study utilizes the discrete element method to simulate and analyse powder transportation in an inclined screw conveyor using the commercial software ANSYS-ROCKY. Numerous phenomena that arise while transporting and feeding small-sized or irregularly shaped particles, often present in industrial processes, remain insufficiently investigated. This paper aims to analyse the transportation process of adhesive powders in a screw conveyor, with a focus on evaluating the impact of different screw blade speeds on transport. Multiple simulations were conducted, along with the implementation of an additional wear model, to better understand the transport phenomena and wear. An example was used to demonstrate the impact of screw speed on the wear of the transporter due to the interaction between the material and the structure of the conveyor, power consumption, and performance.

Energy material analysis via in-situ/operando scanning transmission x-ray microscopy: A review

The development of advanced energy systems is essential for replacing fossil fuel-based societies, and progress in the fundamental understanding of solid-state energy materials has revolutionized this field. In particular, investigating the inhomogeneity of reactions in energy systems requires analysis at the level of individual particles, which are the smallest units in the system. Synchrotron-based scanning transmission X-ray microscopy (STXM) is a valuable tool for exploring reaction and degradation mechanisms, and providing nanoscale site-specific information on chemical and structural changes within single particles. In-situ/operando STXM is particularly useful for observing reactions under well-controlled conditions in real time, thus providing insights into local phenomena obscured by the ensemble effect. This review highlights the research achievements of in-situ/operando STXM in the field of energy materials and provides perspectives for advanced X-ray imaging techniques that can further enhance STXM capabilities.

Two electrons interacting at a mesoscopic beam splitter.

The nonlinear response of a beam splitter to the coincident arrival of interacting particles enables numerous applications in quantum engineering and metrology. Yet, it poses considerable challenges to control interactions on the individual particle level. Here, we probe the coincidence correlations at a mesoscopic constriction between individual ballistic electrons in a system with unscreened Coulomb interactions and introduce concepts to quantify the associated parametric nonlinearity. The full counting statistics of joint detection allows us to explore the interaction-mediated energy exchange. We observe an increase from 50% up to 70% in coincidence counts between statistically indistinguishable on-demand sources and a correlation signature consistent with the independent tomography of the electron emission. Analytical modelling and numerical simulations underpin the consistency of the experimental results with Coulomb interactions between two electrons counterpropagating in a quadratic saddle potential. Coulomb repulsion energy and beam splitter dispersion define a figure of merit, which in this experiment is demonstrated to be sufficiently large to enable future applications, such as single-shot in-flight detection and quantum logic gates.

Receptor Density-Dependent Motility of Influenza Virus Particles on Surface Gradients.

Influenza viruses can move across the surface of host cells while interacting with their glycocalyx. This motility may assist in finding or forming locations for cell entry and thereby promote cellular uptake. Because the binding to and cleavage of cell surface receptors forms the driving force for the process, the surface-bound motility of influenza is expected to be dependent on the receptor density. Surface gradients with gradually varying receptor densities are thus a valuable tool to study binding and motility processes of influenza and can function as a mimic for local receptor density variations at the glycocalyx that may steer the directionality of a virus particle in finding the proper site of uptake. We have tracked individual influenza virus particles moving over surfaces with receptor density gradients. We analyzed the extracted virus tracks first at a general level to verify neuraminidase activity and subsequently with increasing detail to quantify the receptor density-dependent behavior on the level of individual virus particles. While a directional bias was not observed, most likely due to limitations of the steepness of the surface gradient, the surface mobility and the probability of sticking were found to be significantly dependent on receptor density. A combination of high surface mobility and high dissociation probability of influenza was observed at low receptor densities, while the opposite occurred at higher receptor densities. These properties result in an effective mechanism for finding high-receptor density patches, which are believed to be a key feature of potential locations for cell entry.

Droplet microreactor for high-throughput fluorescence-based measurements of single catalyst particle acidity

The particles of heterogeneous catalysts differ greatly in size, morphology, and most importantly, in activity. Studying these catalyst particles in batch typically results in ensemble averages, without any information at the level of individual catalyst particles. To date, the study of individual catalyst particles has been rewarding but is still rather slow and often cumbersome1. Furthermore, these valuable in-depth studies at the single particle level lack statistical relevance. Here, we report the development of a droplet microreactor for high-throughput fluorescence-based measurements of the acidities of individual particles in fluid catalytic cracking (FCC) equilibrium catalysts (ECAT). This method combines systematic screening of single catalyst particles with statistical relevance. An oligomerization reaction of 4-methoxystyrene, catalyzed by the Brønsted acid sites inside the zeolite domains of the ECAT particles, was performed on-chip at 95 °C. The fluorescence signal generated by the reaction products inside the ECAT particles was detected near the outlet of the microreactor. The high-throughput acidity screening platform was capable of detecting ~1000 catalyst particles at a rate of 1 catalyst particle every 2.4 s. The number of detected catalyst particles was representative of the overall catalyst particle population with a confidence level of 95%. The measured fluorescence intensities showed a clear acidity distribution among the catalyst particles, with the majority (96.1%) showing acidity levels belonging to old, deactivated catalyst particles and a minority (3.9%) exhibiting high acidity levels. The latter are potentially of high interest, as they reveal interesting new physicochemical properties indicating why the particles were still highly acidic and reactive.

Alignment rule and geometric confinement lead to stability of a vortex in active flow.

Vortices are hallmarks of a wide range of nonequilibrium phenomena in fluids at multiple length scales. In this work, we numerically study the whirling motion of self-propelled soft point particles confined in circular domain, and aim at addressing the stability issue of the coherent vortex structure. By the combination of dynamical and statistical analysis at the individual particle level, we reveal the persistence of the whirling motion resulting from the subtle competition of activity and geometric confinement. In the stable whirling motion, the scenario of the coexistence of the irregular microscopic motions of individual particles and the regular global whirling motion is fundamentally different from the motion of a vortex in passive fluid. Possible orientational order coexisting with the whirling are further explored. This work shows the stability mechanism of vortical dynamics in active media under the alignment rule in confined space and may have implications in creating and harnessing macroscale coherent dynamical states by tuning the confining geometry.

Effect of terminal velocities on macroscopic and microscopic hydrodynamic mixing of stratified suspensions.

We performed numerical experiments to investigate the mixing of stratified suspensions composed of different particle types by gravitational sedimentation. The mixing process is controlled by a dimensionless group Y_{m}∼U_{f}/U_{St1}, where U_{f} is a typical velocity of a macroscopic sedimenting finger and U_{St1} is the Stokes settling velocity of a single spherical particle in the upper suspension. The effects of components of Y_{m}, in particular, terminal velocities of particles, were investigated. For Y_{m}=100, no large difference was observed for the difference of components of Y_{m}, and it was confirmed that the mixing rate is determined by Y_{m}, because macroscopic (vessel-scale) mixing is dominant for large Y_{m}. For Y_{m}=5, macroscopic mixing and microscopic (individual particle-level) mixing due to the particle terminal velocity difference are of the same order, while completely different mixing patterns were observed for positive, zero, and negative terminal velocity differences: macroscopic mixing is promoted by the increase in apparent density due to microscopic mixing, small macroscopic mixing is suppressed by the individual particle settling, and jetting mixing occurs owing to pure liquid layer formation.

Application of Isotopically Labeled Engineered Nanomaterials for Detection and Quantification in Soils via Single-Particle Inductively Coupled Plasma Time-of-Flight Mass Spectrometry.

Finding and quantifying engineered nanomaterials (ENMs) in soil are challenging because of the abundance of natural nanomaterials (NNMs) with the same elemental composition, for example, TiO2. Isotopically enriched ENMs may be distinguished from NNMs with the same elemental composition using single-particle inductively coupled plasma time-of-flight mass spectrometry (spICP-TOF-MS) to measure multiple isotopes simultaneously within each ENM and NNM in soil, but the minimum isotope enrichment needed for detection of ENMs in soil is not known. Here, we determined the isotope enrichment needed for 47Ti-enriched TiO2 ENMs to be detectable in soil and assessed the effects of weathering on those requirements for less soluble TiO2 and more soluble CuO ENMs. The isotope-enriched ENMs were dosed into two different soils and were extracted and measured by spICP-TOF-MS after 1, 7, and 30 days. Isotope-enriched ENMs were recovered and detected for all three time points. The 47Ti-enriched TiO2 ENMs were detectable in Lufa 2.2 soil at a nominal dosed concentration of 10 mg-TiO2 kg-1 which is an environmentally relevant concentration in biosolid-amended soils. For distinguishing an ∼70 nm diameter TiO2 ENM from TiO2 NNMs in Lufa 2.2 soil, an ∼10 wt % 47Ti isotope-enrichment was required, and this enrichment requirement increases as the particle size decreases. This study is the first to evaluate the tracking ability of isotope-enriched ENMs at an individual particle level in soil and provides guidance on the isotope enrichment requirements for quantification of ENMs made from Earth-abundant elements in soils.

Unraveling the Complex Chirality Evolution in DNA‐Assembled High‐Order, Hybrid Chiroplasmonic Superstructures from Multi‐Scale Chirality Mechanisms

AbstractHierarchical, chiral hybrid superstructures of chromophores and nanoparticles are expected to give rise to intriguing unveiled chiroptical responses originating from the complex chiral interactions among the components. Herein, DNA origami cavity that could self‐assemble into one‐dimensional (1D) DNA tubes was employed as a scaffold to accurately organize metal nanoparticles and chromophores. The chiral interactions were studied at the level of individual hybrid particles and their 1D hybrid superstructures. Complex chirality mechanisms involving global structural chirality, plasmon‐induced circular dichroism (PICD) and exciton‐coupled circular dichroism (ECCD) were disentangled. The multiplexed CD spectrum superposition revealed the chirality evolution at different length scales. These results can offer a model for boosting the theoretical understanding of classical‐quantum hybrid systems, and would inspire the future design of optically‐active substances across length scales.

Unraveling the Complex Chirality Evolution in DNA-Assembled High-Order, Hybrid Chiroplasmonic Superstructures from Multi-Scale Chirality Mechanisms.

Hierarchical, chiral hybrid superstructures of chromophores and nanoparticles are expected to give rise to intriguing unveiled chiroptical responses originating from the complex chiral interactions among the components. Herein, DNA origami cavity that could self-assemble into one-dimensional (1D) DNA tubes was employed as a scaffold to accurately organize metal nanoparticles and chromophores. The chiral interactions were studied at the level of individual hybrid particles and their 1D hybrid superstructures. Complex chirality mechanisms involving global structural chirality, plasmon-induced circular dichroism (PICD) and exciton-coupled circular dichroism (ECCD) were disentangled. The multiplexed CD spectrum superposition revealed the chirality evolution at different length scales. These results can offer a model for boosting the theoretical understanding of classical-quantum hybrid systems, and would inspire the future design of optically-active substances across length scales.