Ensemble Of Particles Research Articles

Which filter for data assimilation in water quality models? Focus on oxygen reaeration and heterotrophic bacteria activity

With the development of sophisticated water quality models and the advances in computational power, data assimilation (DA) techniques, especially ensemble-based methods (the ensemble Kalman filter and particle filter), are attracting considerable attention in water quality modeling for improving the estimation of state variables and parameters in water quality models. The ensemble Kalman filter (EnKF) has become the most popular DA method while the particle filter (PF), which does not rely on Gaussian or quasi-linearity assumptions, is seldom applied in water quality modeling. Here, we present a comparison between the PF and EnKF for the update of model parameters related to river metabolism. The two filters are implemented in ProSe-PA, a hydro-biogeochemical software, and their performance is assessed on two synthetic case studies. The results indicate that PF and EnKF can estimate dissolved oxygen concentrations and the posterior probability distribution function of the associated parameters, either precisely for both filters in the case of a slightly nonlinear system (reaeration at the air–water interface) or more precisely for the PF in the case of a strongly nonlinear system (organic matter degradation) dominated by heterotrophic bacterial activities. Since the PF is more accurate, its usage is recommended for water quality modeling and guidelines are provided for its set-up.

Active Colloids as Models, Materials, and Machines.

Active colloids use energy input at the particle level to propel persistent motion and direct dynamic assemblies. We consider three types of colloids animated by chemical reactions, time-varying magnetic fields, and electric currents. For each type, we review the basic propulsion mechanisms at the particle level and discuss their consequences for collective behaviors in particle ensembles. These microscopic systems provide useful experimental models of nonequilibrium many-body physics in which dissipative currents break time-reversal symmetry. Freed from the constraints of thermodynamic equilibrium, active colloids assemble to form materials that move, reconfigure, heal, and adapt. Colloidal machines based on engineered particles and their assemblies provide a basis for mobile robots with increasing levels of autonomy. This review provides a conceptual framework for understanding and applying active colloids to create material systems that mimic the functions of living matter. We highlight opportunities for chemical engineers to contribute to this growing field.

Voltage-Modulated Untwist Deformations and Multispectral Optical Effects from Ion Intercalation into Chiral Ceramic Nanoparticles.

Reconfiguration of chiral ceramic nanostructures after ion intercalation should favor specific nanoscale twists leading to strong chiroptical effects. In this work, V2 O3 nanoparticles are shown to have "built-in" chiral distortions caused by binding of tartaric acid enantiomers to the nanoparticle surface. As evidenced by spectroscopy/microscopy techniques and calculations of nanoscale chirality measures, the intercalation of Zn2+ ions into the V2 O3 lattice results in particle expansion, untwist deformations, and chirality reduction. Coherent deformations in the particle ensemble manifest as changes in sign and positions of circular polarization bands at ultraviolet, visible, mid-infrared (IR), near-IR (NIR), and IR wavelengths. The g-factors observed for IR and NIR spectral diapasons are ≈100-400 times higher than those for previously reported dielectric, semiconductor, and plasmonic nanoparticles. Nanocomposite films layer-by-layer assembled (LBL) from V2 O3 nanoparticles reveal cyclic-voltage-driven modulation of optical activity. Device prototypes for IR and NIR range problematic for liquid crystals and other organic materials are demonstrated. High optical activity, synthetic simplicity, sustainable processability, and environmental robustness of the chiral LBL nanocomposites provide a versatile platform for photonic devices. Similar reconfigurations of particle shapes are expected for multiple chiral ceramic nanostructures, leading to unique optical, electrical, and magnetic properties.

Optical characteristics of a monolayer of identical spherical particles in an absorbing host medium.

The problem of light interaction with a 2D ensemble of homogeneous spherical particles embedded into an unbounded homogeneous absorbing host medium is considered. Based on the statistical approach, the equations are derived to characterize optical response of such a system with taking into account multiple scattering of light. Numerical data are presented for the spectral behavior of coherent transmission and reflection, incoherent scattering, and absorption coefficients of thin dielectric, semiconductor, and metal films containing a monolayer of particles with various spatial organization. The results are compared with the characteristics of the inverse structure: particles consist of the host medium material and vice versa. Data for the redshift of the surface plasmon resonance of the monolayer of gold (Au) nanoparticles in the fullerene (C 60) matrix are presented as a function of the monolayer filling factor. They are in qualitative agreement with the known experimental results. The findings have potential applications in the development of new electro-optical and photonic devices.

Regularity of weak solutions for the relativistic Vlasov–Klein–Gordon system

This article is devoted to the study of the relativistic Vlasov–Klein–Gordon system in space dimension three. The dynamical model describes a collisionless ensemble of classical particles coupled with a Klein–Gordon field. By combining the Fourier method and smoothing effect of low velocity particles, we prove a higher regularity of the field, which is widely used for the study of Vlasov equation.

Negative Polarization of Celestial Bodies: Review and Computer Simulation

A brief review of the main causes of a negative degree of linear polarization of radiation scattered by regolith surfaces of atmosphereless cosmic bodies and ensembles of particles in the opposition region is presented. The results of computer simulation are provided, which made it possible to calculate the polariza tion degree of light scattered by pairs of irregular particles. The distance between the particles changed, which made it possible to obtain a visual representation of the total effect of the nature of negative polarization in the case of two-particle scattering (scattering in which two particles participate). Previously, a similar study was carried out for the case of two spherical particles, and showed that two-particle scattering by spheres only changes the degree of linear polarization in absolute value. We showed that two-particle scattering by irregular particles has a variable effect on the degree of linear polarization, both increasing and decreasing it. We also demonstrated that two-particle scattering by irregular particles can form a negative polarization even if the light scattered by a single particle is positively polarized. Therefore, in theoretical studies of the appearance of negative polarization, it is important to take into account two-particle scattering.

Coupled-oscillator model for hybridized optical phonon modes in contacting nanosize particles and quantum dot molecules

Modification of optical phonon spectra in contacting nonpolar nanoparticles compared to single particles is studied. Optical phonons in dielectric and semiconducting particles obey the Euclidean metric Klein-Fock-Gordon equation with Dirichlet boundary conditions. This equation is supposed to be solved numerically for manifolds of cojoined spheres. It is proposed to replace this problem with the simpler-to-solve coupled-oscillator model (COM), where an oscillator is attributed to each phonon mode of a particle and the particle overlap leads to the appearance of additional couplings for these oscillators with the magnitude proportional to the overlap volume. For not too big overlaps, this model describes solutions of the original eigenvalue problem with a quantitative level of accuracy. In particular, it works beyond isotropic $s$ modes in dimers, which has been demonstrated for $p$ modes in dimers and for tetramers. It is proposed to apply the COM for the description of recently manufactured dimer nanoparticles and quantum dots. The obtained results are in agreement with the dynamical matrix method for optical phonons in nanodiamonds. The dynamical matrix method is also used to demonstrate that the van der Waals contacts between faceted particles lead to very small modifications of the optical phonon spectra, which therefore could be neglected when discussing the propagation of vibrational excitations via a nanopowder. The possibility to distinguish between dimerized and size-distributed single particles from their Raman spectra is also considered. The proposed COM paves a way towards the description of propagation of vibrational modes in the ensembles of particles in contact including tight agglomerates, nanocrystal solids, and porous media.

Large Ensemble Particle Filter for Spatial Climate Reconstructions Using a Linear Inverse Model

AbstractProxy records that document the last 2000 years of climate provide evidence for the wide range of the natural climate variability from inter‐annual to secular timescales not captured by the short window of recent direct observations. Assessing climate models ability to reproduce such natural variations is crucial to understand climate sensitivity and impacts of future climate change. Paleoclimate data assimilation (PDA) offers a powerful way to extend the short instrumental period by optimally combining the physics described by General Circulation Climate Models (GCMs) with information from available proxy records while taking into account their uncertainties. Here we present a new PDA approach based on a sequential importance resampling (SIR) Particle filter (PF) that uses Linear Inverse Modeling (LIM) as an emulator of several CMIP‐class GCMs. We examine in a perfect‐model framework the skill of the various LIMs to forecast the dynamics of the surface temperatures and provide spatial field reconstructions over the last millennium in a SIR PF. Our results show that the LIMs allow for skillful ensemble forecasts at 1‐year lead‐time based on GCMs dynamical knowledge with best prediction in the tropics and the North Atlantic. The PDA further provides a set of physically consistent spatial fields allowing robust uncertainty quantification related to climate models biases and proxy spatial sampling. Our results indicate that the LIM yields dynamical memory improving climate variability reconstructions and support the use of the LIM as a GCM‐emulator in real reconstruction to propagate large ensembles of particles at low cost in SIR PF.

A simple trick to improve the accuracy of PIV/PTV data

Particle Image Velocimetry (PIV) estimates velocities through correlations of particle images within interrogation windows, leading to a spatial modulation of the velocity field. Although in principle Particle Tracking Velocimetry (PTV) estimates locally non-modulated particle displacements, to exploit the scattered data from PTV it is necessary to interpolate these data on a structured grid, which implies a spatial modulation effect that biases the resulting velocity field. This systematic error due to finite spatial resolution inevitably depends on the interrogation window size and on the interparticle spacing. It must be observed that all these operations (cross-correlation, direct interpolation or averaging in windows) induce modulation on both the mean and the fluctuating part. We introduce a simple trick to reduce this systematic error source of PIV/PTV measurements exploiting ensemble statistics. Ensemble Particle Tracking Velocimetry (EPTV) can be leveraged to obtain the high-resolution mean flow by merging the different instantaneous realisations. The mean flow can be estimated with EPTV, and the fluctuating part can be measured from PIV/PTV. The high-resolution mean can then be superposed to the instantaneous fluctuating part to obtain velocity fields with lower systematic error. The methodology is validated against datasets with a progressively increasing level of complexity: two virtual experiments based on direct numerical simulations (DNS) of the wake of a fluidic pinball and a channel flow and the experimental data of a turbulent boundary layer. For all the cases both PTV and PIV are analysed.

Optimal cooling of multiple levitated particles: Theory of far-field wavefront shaping

The opportunity to manipulate small-scale objects pushes us to the limits of our understanding of physics. Particularly promising in this regard is the interdisciplinary field of levitation, in which light fields can be harnessed to isolate nano-particles from their environment by levitating them optically. When cooled down towards their motional quantum ground state, levitated systems offer the tantalizing prospect of displaying mesoscopic quantum properties. Currently restricted to single objects with simple shapes, the interest in levitation is currently moving towards the manipulation of more complex structures, such as those featuring multiple particles or different degrees of freedom. Unfortunately, current cooling techniques are mostly designed for single objects and thus cannot easily be multiplexed to address such coupled many-body systems. Here, we present an approach based on the spatial modulation of light in the far-field to cool down multiple nano-objects in parallel. Our procedure is based on the experimentally measurable scattering matrix and on its changes with time. We demonstrate how to compose from these ingredients a linear energy-shift operator, whose eigenstates are identified as the incoming wavefronts that implement the most efficient cooling of complex moving ensembles of levitated particles. Submitted in parallel with arxiv:2103.12592, this article provides a theoretical and numerical study of the expected cooling performance as well as of the robustness of the method against environmental parameters.

Studies of Transient Photoplasma Evolution in an Electrostatic Field: Single Particle Motion to Its Collective Behavior

Though the plasma is an ensemble of charged particles, its behavior in an electrostatic field is different from that of individual particles. It shows a collective behavior as a result of long-range Coulomb interactions among the charged particles. To elucidate the plasma behavior, the transient evolution of photoplasma in an applied electrostatic field is carried out in two different density regimes where the plasma shows its single particle motion and collective behavior. In the case of low-density plasma, the external electric field dominates the plasma motion. The electrons and ions act as two independent entities and the plasma shows its single particle behavior in the external field, whereas in the high-density plasma regime, the self-generated electric field in the plasma is comparable to the applied external field. The plasma motion is governed by both the internal ambipolar electric field in the plasma as well as the applied electrostatic field. Thus, the plasma shows its collective motion due to Coulomb interactions among the charged particles.

Micromixing and Co-Precipitation in Continuous Microreactors with Swirled Flows and Microreactors with Impinging Swirled Flows

One of the promising methods for process intensification for micromixing, co-precipitation, and crystallization in continuous reactors is the use of vigorous vortices. A combination of the high intensity of the kinetic energy input with the small volume of the micromixing volume allows to concentrate the energy dissipation rate up to 104 W/kg and more. As the embodiment of such an idea, four new types of microreactors with intensively swirled flows were created and studied as a tool for continuous co-precipitation and crystallization. A correlation between residence time and segregation index was found: the smaller residence time, the higher energy dissipation rate and better quality of micromixing. A method for the synthesis of oxides of a number of transition metals in microreactors with intensively swirled flows with subsequent thermal treatment of co-precipitation products has been developed. This method was used to obtain ensembles of nanosized particles of zirconium oxides, as well as calcium and strontium fluorides. In comparison with the currently widely used hydro- and solvothermal methods, the proposed method has high productivity (around 10 m3/day for lab scale device), can significantly reduce the duration of the process, provides low energy consumption, does not require a large number of labor-intensive operations, is technologically advanced and easily scalable.

Counting and mapping of subwavelength nanoparticles from a single shot scattering pattern.

Particle counting is of critical importance for nanotechnology, environmental monitoring, pharmaceutical, food and semiconductor industries. Here we introduce a super-resolution single-shot optical method for counting and mapping positions of subwavelength particles on a surface. The method is based on the deep learning analysis of the intensity profile of the coherent light scattered on the group of particles. In a proof of principle experiment, we demonstrated particle counting accuracies of more than 90%. We also demonstrate that the particle locations can be mapped on a 4 × 4 grid with a nearly perfect accuracy (16-pixel binary imaging of the particle ensemble). Both the retrieval of number of particles and their mapping is achieved with super-resolution: accuracies are similar for sets with closely located optically unresolvable particles and sets with sparsely located particles. As the method does not require fluorescent labelling of the particles, is resilient to small variations of particle sizes, can be adopted to counting various types of nanoparticulates and high rates, it can find applications in numerous particles counting tasks in nanotechnology, life sciences and beyond.

Multiscale Electrochemistry of Lithium Manganese Oxide (LiMn2O4): From Single Particles to Ensembles and Degrees of Electrolyte Wetting.

Scanning electrochemical cell microscopy (SECCM) facilitates single particle measurements of battery materials using voltammetry at fast scan rates (1 V s-1), providing detailed insight into intrinsic particle kinetics, otherwise obscured by matrix effects. Here, we elucidate the electrochemistry of lithium manganese oxide (LiMn2O4) particles, using a series of SECCM probes of graded size to determine the evolution of electrochemical characteristics from the single particle to ensemble level. Nanometer scale control over the SECCM meniscus cell position and height further allows the study of variable particle/substrate electrolyte wetting, including comparison of fully wetted particles (where contact is also made with the underlying glassy carbon substrate electrode) vs partly wetted particles. We find ensembles of LiMn2O4 particles show voltammograms with much larger peak separations than those of single particles. In addition, if the SECCM meniscus is brought into contact with the substrate electrode, such that the particle-support contact changes from dry to wet, a further dramatic increase in peak separation is observed. Finite element method modeling of the system reveals the importance of finite electronic conductivity of the particles, contact resistance, surface kinetics, particle size, and contact area with the electrode surface in determining the voltammetric waveshape at fast scan rates, while the responses are relatively insensitive to Li+ diffusion coefficients over a range of typical values. The simulation results explain the variability in voltammetric responses seen at the single particle level and reveal some of the key factors responsible for the evolution of the response, from ensemble, contact, and wetting perspectives. The variables and considerations explored herein are applicable to any single entity (nanoscale) electrochemical study involving low conductivity materials and should serve as a useful guide for further investigations of this type. Overall, this study highlights the potential of multiscale measurements, where wetting, electronic contact, and ionic contact can be varied independently, to inform the design of practical composite electrodes.

Особенности макроскопического транспорта зарядов в ансамблях плотноупакованных наночастиц анатаза вблизи порога протекания

The results of experimental studies of the effect of degradation of macroscopic charge transport in ensembles of close-packed anatase nanoparticles under long-term action of a constant electric field are presented. The degradation is presumably due to the increasing degree of blocking of statistically independent conduction channels formed in ensembles of particles under the field action. A phenomenological model is considered for estimating the number of active conduction channels in an ensemble of particles near the percolation threshold in the system.

Features of macroscopic charge transfer in the ensembles of close-packed anatase nanoparticles near the percolation threshold

The results of experimental studies of the effect of degradation of macroscopic charge transport in ensembles of close-packed anatase nanoparticles under long-term action of a constant electric field are presented. The degradation is presumably due to the increasing degree of blocking of statistically independent conduction channels formed in ensembles of particles under the field action. A phenomenological model is considered for estimating the number of active conduction channels in an ensemble of particles near the percolation threshold in the system. Keywords: nanoparticles, anatase, charge transfer, percolation threshold.

Composite ligand shells on gold nanoprisms - an ensemble and single particle study.

The attachment of thiolated molecules onto gold surfaces is one of the most extensively used and robust ligand exchange approaches to exploit the nanooptical features of nanoscale and nanostructured plasmonic materials. In this work, the impact of thiol adsorption on the optical properties of wet-chemically synthesized gold nanoprisms is studied both at the ensemble and single particle level to investigate the build-up of more complex ligand layers. Two prototypical ligands with different lengths have been investigated ((16-mercaptohexadecyl)trimethylammonium bromide - MTAB and thiolated polyethylene glycol - mPEG-SH). From ensemble experiments it is found that composite ligand layers are obtained by the sequential addition of the two thiols, and an island-like surface accumulation of the molecules can be anticipated. The single particle experiment derived chemical interface damping and resonance energy changes further support this and show additionally that when the two thiols are used simultaneously, a higher density, intermixed layer is formed. Hence, when working with more than a single type of ligand during surface modification, sequential adsorption is preferred for the combination of accessible essential surface functionalities, whereas for high overall loading the simultaneous use of the different ligand types is favourable.

A Statistical Hypothesis Testing Strategy for Adaptively Blending Particle Filters and Ensemble Kalman Filters for Data Assimilation

Abstract Particle filters avoid parametric estimates for Bayesian posterior densities, which alleviates Gaussian assumptions in nonlinear regimes. These methods, however, are more sensitive to sampling errors than Gaussian-based techniques such as ensemble Kalman filters. A recent study by the authors introduced an iterative strategy for particle filters that match posterior moments—where iterations improve the filter’s ability to draw samples from non-Gaussian posterior densities. The iterations follow from a factorization of particle weights, providing a natural framework for combining particle filters with alternative filters to mitigate the impact of sampling errors. The current study introduces a novel approach to forming an adaptive hybrid data assimilation methodology, exploiting the theoretical strengths of nonparametric and parametric filters. At each data assimilation cycle, the iterative particle filter performs a sequence of updates while the prior sample distribution is non-Gaussian, then an ensemble Kalman filter provides the final adjustment when Gaussian distributions for marginal quantities are detected. The method employs the Shapiro–Wilk test to determine when to make the transition between filter algorithms, which has outstanding power for detecting departures from normality. Experiments using low-dimensional models demonstrate that the approach has a significant value, especially for nonhomogeneous observation networks and unknown model process errors. Moreover, hybrid factors are extended to consider marginals of more than one collocated variables using a test for multivariate normality. Findings from this study motivate the use of the proposed method for geophysical problems characterized by diverse observation networks and various dynamic instabilities, such as numerical weather prediction models. Significance Statement Data assimilation statistically processes observation errors and model forecast errors to provide optimal initial conditions for the forecast, playing a critical role in numerical weather forecasting. The ensemble Kalman filter, which has been widely adopted and developed in many operational centers, assumes Gaussianity of the prior distribution and solves a linear system of equations, leading to bias in strong nonlinear regimes. On the other hand, particle filters avoid many of those assumptions but are sensitive to sampling errors and are computationally expensive. We propose an adaptive hybrid strategy that combines their advantages and minimizes the disadvantages of the two methods. The hybrid particle filter–ensemble Kalman filter is achieved with the Shapiro–Wilk test to detect the Gaussianity of the ensemble members and determine the timing of the transition between these filter updates. Demonstrations in this study show that the proposed method is advantageous when observations are heterogeneous and when the model has an unknown bias. Furthermore, by extending the statistical hypothesis test to the test for multivariate normality, we consider marginals of more than one collocated variable. These results encourage further testing for real geophysical problems characterized by various dynamic instabilities, such as real numerical weather prediction models.

A Novel Sequential Ensemble Approach and Particle Swarm Optimization Algorithm for Forecasting: Applied for Covid-19 Cases as Case Study

A Novel Sequential Ensemble Approach and Particle Swarm Optimization Algorithm for Forecasting: Applied for Covid-19 Cases as Case Study

Thermophysical properties and stabilization mechanism of nano- and microfluids with [Ni5(μ5-pppmda)4Cl2] metal string complex particles

The results of thermophysical properties studies and stabilization of nano- and microfluids prepared on the basis of glycerol aqueous solutions are presented. The results of determination of thermal conductivity, rheology, interfacial tension and stability of the studied solutions are presented. Cu, Ni and Al nanoparticles were used for the preparation of nanofluids, and microparticles of the metal-string complex [Ni5(μ5-pppmda)4Cl2] synthesized in laboratory conditions were used for the preparation of microfluids. It was shown that the Ni5 microfluid has a higher stability than the studied nanofluids due to the formation of hydrogen bonds, lower density of microparticles and the formation of ensembles of particles whose sizes are determined by the buoyancy conditions. The rheology of Ni5 microfluids exhibiting thixotropic behavior is also significantly different. The investigated Ni5 microfluids exhibited almost the same increase in thermal conductivity compared to the base fluid as the nanofluids. It is shown that the increase in thermal conductivity of the microfluids is related to the single-crystal structure of the used microparticles. An equation predicting a 10-fold increase in thermal conductivity for Ni5 nanofluid solutions as compared to microfluids is proposed. Keywords: nanofluid; microfluid; thermal conductivity; viscosity; stability.