Single Particle Research Articles

Intelligent optimization of inspection route based on multi-population integer coding particle swarm optimization algorithm

Aiming at the problems of premature convergence and slow convergence speed in the optimization process of single population particle swarm optimization algorithm, in order to improve the global convergence performance of particle swarm optimization algorithm, a hierarchical three-population integer coded particle swarm optimization algorithm based on grade evaluation with parallel structure is proposed and used to solve the traveling salesman problem (TSP). The algorithm imitates the form of biological aggregation in nature. In the initialization stage, three independent populations are generated according to different particle fitness, including an elite population composed of small-scale individuals with high fitness and two large-scale civilian populations composed of remaining individuals. The three populations apply the immigration strategy based on grade evaluation to exchange particles after a certain number of evolutionary generations. By applying the grade evaluation strategy, the natural law of the biological cluster is integrated into the particle swarm optimization algorithm, which effectively improves the optimization efficiency of the particle swarm optimization algorithm. The above algorithm is applied to the inspection route optimization of one of the traveling salesman problems. The results show that the improved algorithm is superior to the single population particle swarm optimization algorithm in terms of convergence speed, global optimization ability and stability.

Identification of tephra horizons in a glacier on the Ushkovsky volcano (Kamchatka)

Identification of tephra and its allocation (association) with known eruptive events allows obtainng chronostratigraphic markers, on the basis of which an age scale for dating glacial strata can be developed. To determine the sources of ash in the ice core obtained in 2022 during drilling of glacier in the crater of the Ushkovsky volcano in Kamchatka, the chemical composition of volcanic glass in individual ash particles was analyzed. The accuracy of determination of the volcanic glass composition was verified by analyzing of international standard samples of volcanic and synthetic glass. Based on a comparison of the data we obtained with published data on the composition of tephra glasses from the present-day eruptions in Kamchatka, we determined affiliation of each tephra horizon to specific volcano-source. We have found that the main source of tephra in the ice core of the Ushkovsky Glacier is the Kliuchevskoi volcano, which is the closest and the most productive one among the Kamchatka volcanoes. Ash particles from Bezymyannyi volcano were identified in two horizons. A mixed population of particles was found in one of the horizons, including the ash particles from volcanoes Kizimen, Kliuchevskoi and Bezymyannyi. Analysis of published data on the chronology and distribution of ash plumes from known eruptive events made it possible to confidently correlate the tephra horizon at a depth of 762–777 cm with the initial phase of the eruption of the Kizimen volcano in late 2010–early 2011. Ash from the uppermost tephra buried in the glacier at depths of 89–94 cm belongs to the Bezymyannyi volcano eruption, which the most likely occurred in October 2020. Single particles with rhyolitic composition of glass in the sample from the depth of 348–354 cm may belong to the eruption of the Shiveluch volcano in December 2018. The results of our work can be used on further studying of the ice core from the Ushkovsky volcano, in particular for comparison and correlation with the chronostratigraphic data obtained by glacio-chemical and isotope methods.

Structure-Guided Design of Partial Agonists at an Opioid Receptor.

The persistence of chronic pain and continuing overdose deaths from pain-relieving opioids targeting μ opioid receptor (μOR) have fueled the need for reliable long-term analgesics which use different targets and mechanisms. The δ opioid receptor (δOR) is a potential alternative target for non-addictive analgesics to alleviate chronic pain, made more attractive by its lack of respiratory depression associated with μOR agonists. However, early δOR full agonists were found to induce seizures, precluding clinical use. Partial δOR agonists may offer more controlled activation of the receptor compared to full agonists, but the development of such ligands has been hindered by uncertainty over the molecular mechanism mediating partial agonism. Using a structure-based approach, we explored the engagement of the sodium binding pocket in δOR and developed a bitopic ligand, C6-Quino, predicted to be a selective δOR partial agonist. Functional studies of C6-Quino revealed that it displayed δOR partial agonist activity at both G-protein and arrestin pathways. Its interaction with the sodium pocket was confirmed and analyzed using a single particle cryo-EM. Additionally, C6-Quino demonstrated favorable chemical and physiological properties like oral activity, and analgesic activity in multiple chronic pain models. Notably, μOR-related hyperlocomotion and respiratory depression, and δOR-related convulsions, were not observed at analgesic doses of C6-Quino. This fundamentally new approach to designing δOR ligands provides a blueprint for the development of partial agonists as safe analgesics and acts as a generic method to optimize signaling profiles of other Class A GPCRs.

Mass distributions in 12C + 232Th fission: role of shell effects and excitation energy

This article reports the measurement of cross sections of charge and mass identified fission products and the mass distributions in 232Th(12C,f) reaction at 62.5, 70.7 and 102.9 MeV beam energies to investigate the role of single particle effects. The study was carried out using the recoil catcher technique followed by off-line γ-ray spectrometry. Cross sections of 32, 54 and 64 fission products were measured for 62.5, 70.7 and 102.9 MeV beam energies, respectively. The mass distributions obtained at 62.5 and 70.7 MeV show a flat-top nature indicating significant asymmetric fission contribution (heavy mass peak corresponding to Z range of 54–56), whereas, a nearly Gaussian behaviour was observed at 102.9 MeV indicating dominant contribution from symmetric fission. The experimental mass distributions were in gross agreement with the “GEF, 2021/1.1” calculations which predicted significant asymmetric fission contribution dominated by Z ≈ 55 (‘Standard 2’ mode) at 62.5 and 70.7 MeV. The present study shows the significant role of charge polarization resulting in the deviation of the most probable charge (ZP) values from those obtained using UCD hypothesis. “GEF, 2023/2.1” calculations were unable to explain the observed mass distributions with significant asymmetric fission contribution due to comparatively lower contribution from higher chance fission resulting from the lower saddle point energies. An attempt has been made to estimate the mass distributions arising from the complete fusion fission and α-transfer induced fission. The trend shows an increase in the α-transfer induced fission contribution with increasing beam energy which is in qualitative agreement with the sum-rule model calculations.

An active fractional Ornstein–Uhlenbeck particle: diffusion and dissipation

In this work, we consider a particle subjected to active fluctuations due to the presence of an active bath. The active fluctuation driving the particle is modeled as an Ornstein–Uhlenbeck process with memory, due to the recent experimental result in that a bacterial bath under a chemotactic mechanism exhibits a large distribution of persistence time, which may result in long-range persistence of a probe particle that cannot be captured by the conventional Ornstein–Uhlenbeck model for active noise. As a paradigmatic model, we consider introducing a fractional Ornstein–Uhlenbeck process with a power-law kernel, which includes a fractional order variable 0<α⩽1 , to model an active noise acting on a particle. We present the relevant properties of the active noise and its implications for the diffusion of free and harmonically confined single particles. This is also supported by the derived active Smoluchowski description. More importantly, we find that the effect of α can either reduce or increase the effective temperature at long time, depending on the competition between the harmonic timescale and persistence time. Lastly, the effects of presented active noise on the spectral density of the energy dissipation rate and the dissipation energy from both the thermal and active bath are explored.

A closer look at the effects of oxygen on the photoluminescence properties of CdSe/CdS quantum dots.

We present a detailed study on the effects of oxygen on the photoluminescence properties of CdSe/CdS quantum dots (QDs). We investigated the role of oxygen by performing confocal measurements on thin films as well as on single particles while rapidly exchanging the gaseous environment between oxygen and an inert gas atmosphere. We found that the deionization of negatively charged particles by oxygen depends on both the excitation power and the shell thickness of the QDs. For QDs with thin shells, which exhibit strong photoluminescence blinking, we observed that the presence of oxygen affects both band-edge carrier blinking and hot-carrier blinking.

Localization in quantum field theory

We review the issue of localization in quantum field theory and detail the nonrelativistic limit. Three distinct localization schemes are examined: the Newton–Wigner, the algebraic quantum field theory, and the modal scheme. Among these, the algebraic quantum field theory provides a fundamental concept of localization, rooted in its axiomatic formulation. In contrast, the Newton–Wigner scheme draws inspiration from the Born interpretation, applying mainly to the nonrelativistic regime. The modal scheme, relying on the representation of single particles as positive frequency modes of the Klein–Gordon equation, is found to be incompatible with the algebraic quantum field theory localization.This review delves into the distinctive features of each scheme, offering a comparative analysis. A specific focus is placed on the property of independence between state preparations and observable measurements in spacelike separated regions. Notably, the notion of localization in algebraic quantum field theory violates this independence due to the Reeh–Schlieder theorem. Drawing parallels with the quantum teleportation protocol, it is argued that causality remains unviolated. Additionally, we consider the nonrelativistic limit of quantum field theory, revealing the emergence of the Born scheme as the fundamental concept of localization. Consequently, the nonlocality associated with the Reeh–Schlieder theorem is shown to be suppressed under nonrelativistic conditions.

A reduced model for particle calcination for use in DEM/CFD simulations

We treat the accurate simulation of the calcination reaction in particles, where the particles are large and, thus, the inner-particle processes must be resolved. Because these processes need to be described with coupled partial differential equations (PDEs) that must be solved numerically, the computation times for a single particle are too high for use in simulations that involve many particles. Simulations of this type arise when the Discrete Element Method (DEM) is combined with Computational Fluid Dynamics (CFD) to investigate industrial systems such as quicklime production in lime shaft kilns.We show that, based on proper orthogonal decomposition and Galerkin projection, reduced models can be derived for single particles that provide the same spatial and temporal resolution as the original PDE models at a considerably reduced computational cost. Replacing the finite volume particle models with the reduced models results in an overall reduction of the reactor simulation time by about 40% for the sample system treated here.

High-resolution electron cryomicroscopy of V-ATPase in native synaptic vesicles.

Intercellular communication in the nervous system occurs through the release of neurotransmitters into the synaptic cleft between neurons. In the presynaptic neuron, the proton pumping vesicular- or vacuolar-type ATPase (V-ATPase) powers neurotransmitter loading into synaptic vesicles (SVs), with the V1 complex dissociating from the membrane region of the enzyme before exocytosis. We isolated SVs from rat brain using SidK, a V-ATPase-binding bacterial effector protein. Single-particle electron cryomicroscopy allowed high-resolution structure determination of V-ATPase within the native SV membrane. In the structure, regularly spaced cholesterol molecules decorate the enzyme's rotor and the abundant SV protein synaptophysin binds the complex stoichiometrically. ATP hydrolysis during vesicle loading results in a loss of the V1 region of V-ATPase from the SV membrane, suggesting that loading is sufficient to induce dissociation of the enzyme.

Highly Selective Electrocatalytic CO2 Conversion to Tailored Products through Precise Regulation of Hydrogenation and C-C Coupling.

The electrochemical reduction reaction of carbon dioxide (CO2RR) into valuable products offers notable economic benefits and contributes to environmental sustainability. However, precisely controlling the reaction pathways and selectively converting key intermediates pose considerable challenges. In this study, our theoretical calculations reveal that the active sites with different states of copper atoms (1-3-5-7-9) play a pivotal role in the adsorption behavior of the *CHO critical intermediate. This behavior dictates the subsequent hydrogenation and coupling steps, ultimately influencing the formation of the desired products. Consequently, we designed two model electrocatalysts comprising Cu single atoms and particles supported on CeO2. This design enables controlled *CHO intermediate transformation through either hydrogenation with *H or coupling with *CO, leading to a highly selective CO2RR. Notably, our selective control strategy tunes the Faradaic efficiency from 61.1% for ethylene (C2H4) to 61.2% for methane (CH4). Additionally, the catalyst demonstrated a high current density and remarkable stability, exceeding 500 h of operation. This work not only provides efficient catalysts for selective CO2RR but also offers valuable insights into tailoring surface chemistry and designing catalysts for precise control over catalytic processes to achieve targeted product generation in CO2RR technology.

Sensitivity and perturbation analysis of alpha-eigenvalue with time-dependent Monte Carlo perturbation techniques

Sensitivity analysis and perturbation calculation methods for prompt neutron decay constants α using the Monte Carlo method, such as iterative fission probability (IFP), differential operator sampling (DOS), and correlated sampling (CS), have been proposed thus far. However, these methods require a significant amount of memory storage. The method developed in this study applies DOS and CS techniques during a time-dependent Monte Carlo simulation for the pulsed neutron method in subcritical systems. The time variation of the neutron flux is fitted to an exponential function during the time range when the flux decays with the fundamental mode α. By applying the least squares method to the results of time-dependent DOS and CS, the sensitivity coefficients with respect to nuclear data and the change in α due to perturbation can be calculated. In contrast to the existing methods that require storing the total fission or time sources per generation over several (∼10) generations, the proposed method only needs to store the weighting coefficient of a single source particle until it dies. The additional memory storage per parameter is comparable to that of conventional time-dependent Monte Carlo simulations and much less than that of existing methods. Numerical tests for the proposed method have demonstrated the accuracy and usefulness of the time-dependent DOS and CS methods.

Impedimetric Measurement of Exchange Currents and Ionic Diffusion Coefficients in Individual Pseudocapacitive Nanoparticles.

Among electroanalytical techniques, electrochemical impedance spectroscopy (EIS) offers the unique advantage of a high degree of frequency resolution. This enables EIS to readily deconvolute between the capacitive, resistive, and diffusional processes that underlie electrochemical devices. Here, we report the measurement of impedance spectra of individual, pseudocapacitive nanoparticles. We chose Prussian blue as our model system, as it couples an electron-transfer reaction with sodium ion intercalation-processes which, while intrinsically convoluted, can be readily resolved using EIS. We used a scanning electrochemical cell microscope (SECCM) to isolate single Prussian blue particles in a microdroplet and measured their impedance spectra using the multi-sine, fast Fourier transform technique. In doing so, we were able to extract the exchange current density and sodium ion diffusivity for each particle, which respectively inform on their electronic and ionic conductivities. Surprisingly, these parameters vary by over an order of magnitude between particles and are not correlated to particle size nor to each other. The implication of this apparent heterogeneity is that in a hypothetical battery cathode, one active particle may transfer electrons 10 times faster than its neighbor; another may suffer from sluggish sodium ion transport and have restricted charging rate capabilities compared to a better-performing particle elsewhere in the same electrode. Our results inform on this intrinsic heterogeneity while demonstrating the utility of EIS in future single-particle studies.

CryoEM Workflow Acceleration with Feret Signatures.

Common challenges in cryogenic electron microscopy, such as orientation bias, conformational diversity, and 3D misclassification, complicate single particle analysis and lead to significant resource expenditure. We previously introduced an in silico method using the maximum Feret diameter distribution, the Feret signature, to characterize sample heterogeneity of disc-shaped samples. Here, we expanded the Feret signature methodology to identify preferred orientations of samples containing arbitrary shapes with only about 1000 particles required. This method enables real-time adjustments of data acquisition parameters for optimizing data collection strategies or aiding in decisions to discontinue ineffective imaging sessions. Beyond detecting preferred orientations, the Feret signature approach can serve as an early-warning system for inconsistencies in classification during initial image processing steps, a capability that allows for strategic adjustments in data processing. These features establish the Feret signature as a valuable auxiliary tool in the context of single particle analysis, significantly accelerating the structure determination process.

Defect-Engineered Metal-Organic Frameworks as Nanocarriers for Pharmacotherapy: Insights into Intracellular Dynamics at The Single Particle Level.

Nanoscale Metal-Organic Frameworks (nanoMOFs) are widely implemented in a host of assays involving drug delivery, biosensing catalysis, and bioimaging. However, the cell pathways and cell fate remain poorly understood. Here, a new fluorescent nanoMOF integrating ATTO 655 into surface defects of colloidal UiO-66 is synthesized, allowing to track the spatiotemporal localization of Single nanoMOF in live cells. Density functional theory reveals the stronger binding of ATTO 655 to the Zr6 cluster nodes compared with phosphate and Alendronate Sodium. Parallelized tracking of the spatiotemporal localization of thousands of nanoMOFs and analysis using machine learning platforms reveals whether nanoMOFs remain outside as well as their cellular internalization pathways. To quantitatively assess their colocalization with endo/lysosomal compartments, a colocalization proxy approach relying on the nanoMOF detection of particles in one channel to the signal in the corresponding endo/lysosomal compartments channel, considering signal versus local background intensity ratio and signal-to-noise ratio is developed. This strategy mitigates colocalization value inflation from high or low signal expression in endo/lysosomal compartments. The results accurately measure the nanoMOFs' colocalization from early to late endosomes and lysosomes and emphasize the importance of understanding their intracellular dynamics based on single-particle tracking for optimal and safe drug delivery.

Quantifying the influence of single particle shape on crushing characteristics of recycled aggregates: Experimental and numerical insights

Exploring the interplay between shapes and crushing characteristics of recycled aggregates (RA) is pivotal for understanding their macro-mechanical behavior in bulk materials. This investigation quantitatively characterizes the shapes of recycled bricks (RB), recycled concrete (RC), and recycled mortar (RM) particles, and assesses their single-particle crushing characteristic. Key focus areas include the analysis of crushing modes, fractal attributes, strength, and energy, supplemented by a comparative study using discrete element method (DEM) simulations to predict outcomes for particles of specific sphericity. Findings reveal that the shapes of RA particles are mainly disk, block, blade and bar, with particle size showing negligible influence on these forms. Crushing behaviors are categorized into penetrating fracture, corner rupture, and overall fragmentation, closely linked to particle sphericity. Notably, an increase in sphericity leads to a reduction in fractal characteristics of RA, refining the gradation distribution from broad to narrow spectrums. An exponential relationship is identified between the crushing strength of RA and particle sphericity, a pattern also mirrored in the correlation between crushing energy and sphericity, thereby underscoring the significant influence of particle shape. These relationships facilitate predictions regarding the crushing strength and energy based on sphericity. While numerical simulations broadly align with experimental data, discrepancies in the crushing energy of highly spheric particles necessitate adjustments, resulting in a modified predictive equation for crushing energy. This work enriches the understanding of RA crushing behavior, offering invaluable insights for predicting the single-particle strength and deformation characteristics across different sphericities, thus advancing material engineering and recycling practices.

Ligand Equilibrium Influences Photoluminescence Blinking in CsPbBr3: A Change Point Analysis of Widefield Imaging Data.

Photoluminescence intermittency remains one of the biggest challenges in realizing perovskite quantum dots (QDs) as scalable single photon emitters. We compare CsPbBr3 QDs capped with different ligands, lecithin, and a combination of oleic acid and oleylamine, to elucidate the role of surface chemistry on photoluminescence intermittency. We employ widefield photoluminescence microscopy to sample the blinking behavior of hundreds of QDs. Using change point analysis, we achieve the robust classification of blinking trajectories, and we analyze representative distributions from large numbers of QDs (Nlecithin = 1308, Noleicacid/oleylamine = 1317). We find that lecithin suppresses blinking in CsPbBr3 QDs compared with oleic acid/oleylamine. Under common experimental conditions, lecithin-capped QDs are 7.5 times more likely to be nonblinking and spend 2.5 times longer in their most emissive state, despite both QDs having nearly identical solution photoluminescence quantum yields. We measure photoluminescence as a function of dilution and show that the differences between lecithin and oleic acid/oleylamine capping emerge at low concentrations during preparation for single particle experiments. From experiment and first-principles calculations, we attribute the differences in lecithin and oleic acid/oleylamine performance to differences in their ligand binding equilibria. Consistent with our experimental data, density functional theory calculations suggest a stronger binding affinity of lecithin to the QD surface compared to oleic acid/oleylamine, implying a reduced likelihood of ligand desorption during dilution. These results suggest that using more tightly binding ligands is a necessity for surface passivation and, consequently, blinking reduction in perovskite QDs used for single particle and quantum light experiments.

Combustion of single micron-sized magnesium particles in carbon dioxide

An experimental system integrating micro-sized single particle generation, ignition, and observation was proposed and constructed for investigating the combustion characteristics of magnesium single particles in carbon dioxide. Defining the onset of combustion using the boiling point temperature allows for precise measurement of combustion time without artificial interference. Results revealed four modes of combustion for magnesium particles (Vapor-phase combustion, surface reaction, Micro explosion and flash-out mode) in carbon dioxide. Vapor-phase combustion is diffusion-controlled (with a D01.76 scaling, where D0 is the initial particle diameter). Additionally, the micro-explosion mode primarily occurs in particles with diameters exceeding 70 μm, and the combustion time is rather insensitive to the particle size (Typically 0.5 ∼ 2.2 ms in this study). The characteristic temperatures of the particles were determined using two-color pyrometry, indicating that the particle combustion temperature decreases with increasing particle size. Magnesium particles typically reach temperatures approximately 800 K higher than normal vapor-phase combustion temperatures before experiencing micro-explosions. Analysis of combustion products shows that the oxide shell formed by the combustion of magnesium particles has a three-layer structure. Both the outer and inner layers are mixed layers of magnesium oxide and solid carbon produced during combustion reactions, and the middle layer is the initial oxidation layer of the particles.

Topologically controlled synthesis of active colloidal bipeds

Topological growth control allows to produce a narrow distribution of outgrown colloidal rods with defined and adjustable length. We use an external magnetic field to assemble paramagnetic colloidal spheres into colloidal rods of a chosen length. The rods reside above a metamorphic hexagonal magnetic pattern. The periodic repetition of specific loops of the orientation of an applied external field renders paramagnetic colloidal particles and their assemblies into active bipeds that walk on the pattern. The metamorphic patterns allow the robust and controlled polymerization of single colloids to bipeds of a desired length. The colloids are exposed to this fixed external control loop that causes multiple simultaneous responses: Small bipeds and single colloidal particles interpret the external magnetic loop as an order to walk toward the active zone, where they assemble and polymerize. Outgrown bipeds interpret the same loop as an order to walk away from the active zone. The topological transition occurs solely for the growing biped and nothing is changed in the environment nor in the magnetic control loop. As in many biological systems the decision of a biped that reached its outgrown length to walk away from the reaction site is made internally, not externally.

Towards interpretable Cryo-EM: disentangling latent spaces of molecular conformations.

Molecules are essential building blocks of life and their different conformations (i.e., shapes) crucially determine the functional role that they play in living organisms. Cryogenic Electron Microscopy (cryo-EM) allows for acquisition of large image datasets of individual molecules. Recent advances in computational cryo-EM have made it possible to learn latent variable models of conformation landscapes. However, interpreting these latent spaces remains a challenge as their individual dimensions are often arbitrary. The key message of our work is that this interpretation challenge can be viewed as an Independent Component Analysis (ICA) problem where we seek models that have the property of identifiability. That means, they have an essentially unique solution, representing a conformational latent space that separates the different degrees of freedom a molecule is equipped with in nature. Thus, we aim to advance the computational field of cryo-EM beyond visualizations as we connect it with the theoretical framework of (nonlinear) ICA and discuss the need for identifiable models, improved metrics, and benchmarks. Moving forward, we propose future directions for enhancing the disentanglement of latent spaces in cryo-EM, refining evaluation metrics and exploring techniques that leverage physics-based decoders of biomolecular systems. Moreover, we discuss how future technological developments in time-resolved single particle imaging may enable the application of nonlinear ICA models that can discover the true conformation changes of molecules in nature. The pursuit of interpretable conformational latent spaces will empower researchers to unravel complex biological processes and facilitate targeted interventions. This has significant implications for drug discovery and structural biology more broadly. More generally, latent variable models are deployed widely across many scientific disciplines. Thus, the argument we present in this work has much broader applications in AI for science if we want to move from impressive nonlinear neural network models to mathematically grounded methods that can help us learn something new about nature.

Direct evidence for the occurrence of indigenous cadmium-based nanoparticles in paddy soils

Speciation of heavy metal-based nanoparticles (NPs) in paddy soils greatly determines their fate and potential risk towards food safety. However, quantitative understanding of such distinctive species remains challenging, because they are commonly presented at trace levels (e.g., sub parts-per-million) and extremely difficult to be fractionated in soil matrices. Herein, we propose a state-of-art non-destructive strategy for effective extraction and quantification of cadmium (Cd)-NPs – the most widespread heavy metal in paddy soils – by employing single particle inductively coupled plasma mass spectrometry (spICP-MS) and tetrasodium pyrophosphate (TSPP) as the extractant. Acceptable extraction efficiencies (64.7–80.4 %) were obtained for spiked cadmium sulfide nanoparticles (CdS-NPs). We demonstrate the presence of indigenous Cd-NPs in all six Cd-contaminated paddy soils tested, with a number concentration ranging from 2.20 × 108 to 3.18 × 109 particles/g, representing 17.0–50.4 % of the total Cd content. Furthermore, semi-spherical and irregular CdS-NPs were directly observed as an important form of the Cd-NPs in paddy soils, as characterized by transmission electron microscopy coupled with energy-dispersive X-ray spectroscopy (TEM-EDX). This research marks a significant step towards directly observing indigenous Cd-NPs at trace levels in paddy soil, offering a useful tool for quantitative understanding of the biogeochemical cycling of heavy metal-based NPs in complex matrices.