Population Of Large Particles Research Articles

Local Probe Measurements for Designing More Efficient Photocatalyst Systems

Photocatalytic water splitting is one promising route to reducing the cost of H2 production to industrially relevant levels. However, these particle-based systems are currently limited in their solar-to-hydrogen efficiency, requiring further development in photoabsorber and co-catalyst materials that can achieve both high activity and selectivity. One scientific challenge to advancing development of photocatalytic particles is that conventional analytical methods used to assess the performance of particle suspensions or sheets tend to measure the average or ensemble performance of a large population of particles having a distribution of sizes and compositions while often being exposed to both optical and chemical gradients within the reaction vessel. As a result, it is very difficult to uncover the structure-property-performance relationships that can guide rational design of photocatalysts. Local measurements, such as scanning electrochemical microscopy (SECM) and Raman microscopy, provide information at smaller length scales which can aid in understanding structure-property-performance relationships of individual photocatalyst particles as well as interactions between neighboring particles. Additionally, these tools can be utilized with model systems to understand how different phenomena are coupled, as well as with the introduction of selective coatings which are common in the field. As a part of broader efforts within the EFRC Ensembles of Photosynthetic Nanoreactors (EPN), our team is also advancing the use of these local techniques to correlate multiple measurements on identical particle, location or particle systems across of network of microscopists. Here, we explore the usage of Raman and SECM on model photocatalysts within the EPN correlative microscopy network. Extension of these observations to ensemble systems based on multiple particles will additionally be discussed.

Artificial Intelligence‐Driven Smart Scan: A Rapid, Automatic Approach for Comprehensive Imaging and Spectroscopy for Fast Compositional Analysis

Nanomaterial properties and functionalities are influenced by their shape, size, and chemical composition. The importance of these parameters highlights the need for a statistically robust analysis of a large particle population, necessitating automation. This study introduces a neural network‐empowered smart scan technique that achieves a relative increase in speed compared to traditional energy‐dispersive X‐ray spectroscopy (EDX) mapping. The main advantage is that it reduces the required dose, decreasing potential damage to the sample by avoiding unnecessary exposure. It holds potential use in other multimodal scanning transmission electron microscopy or scanning‐based imaging approaches. In the first example, identifying particles in a matrix with a trained neural network reduces the acquisition time by two orders of magnitude. This acceleration enables a statistical compositional analysis of thousands of particles in less than 1 h. Similar improvements are observed for atomic resolution. The discrete positions of atoms identified by the trained network allow for selective EDX sampling at these centers, thereby identifying the atomic species of the column with much‐reduced sampling. Consequently, a lower sampling dose is required, enabling mapping of more delicate materials with high lateral resolution and at a high statistical confidence interval. Even though manual training is still required, this approach greatly benefits repetitive quality control tasks.

Evaluation of Individual and Crystal Population Dissolution Rates by Time-Resolved X-ray Microtomography.

The intrinsic dissolution rate (IDR) is an important parameter in pharmaceutical science that measures the rate at which a pure crystalline active pharmaceutical ingredient dissolves in the absence of diffusion limitations. Traditional IDR measurement techniques do not capture the complex interplay between particle morphology, fluid flow, and dissolution dynamics. The dissolution rate of individual particles can differ from the population average because of factors such as particle size, surface roughness, or exposure of individual crystal facets to the dissolution medium. The aim of this work was to apply time-resolved X-ray microtomography imaging and simultaneously measure the individual dissolution characteristics of a large population of crystalline particles placed in a packed bed perfused by the dissolution medium. Using NaCl crystals in three different size fractions as a model, time-resolved microtomography made it possible to visualize the dissolution process in a custom-built flow cell. Subsequent 3D image analysis was used to evaluate changes in the shape, size, and surface area of individual particles by tracking them as they are dissolved. Information about the particle population statistics and intrabatch variability provided a deeper insight into the dissolution process that can complement established IDR measurements.

CLASS Observations of Atmospheric Cloud Polarization at millimeter Wavelengths

The dynamic atmosphere imposes challenges to ground-based cosmic microwave background observation, especially for measurements on large angular scales. The hydrometeors in the atmosphere, mostly in the form of clouds, scatter the ambient thermal radiation and are known to be the main linearly polarized source in the atmosphere. This scattering-induced polarization is significantly enhanced for ice clouds due to the alignment of ice crystals under gravity, which are also the most common clouds seen at the millimeter-astronomy sites at high altitudes. This work presents a multifrequency study of cloud polarization observed by the Cosmology Large Angular Scale Surveyor experiment on Cerro Toco in the Atacama Desert of northern Chile, from 2016–2022, at the frequency bands centered around 40, 90, 150, and 220 GHz. Using a machine-learning-assisted cloud classifier, we made connections between the transient polarized emission found in all four frequencies with the clouds imaged by monitoring cameras at the observing site. The polarization angles of the cloud events are found to be mostly 90° from the local meridian, which is consistent with the presence of horizontally aligned ice crystals. The 90 and 150 GHz polarization data are consistent with a power law with a spectral index of 3.90 ± 0.06, while an excess/deficit of polarization amplitude is found at 40/220 GHz compared with a Rayleigh scattering spectrum. These results are consistent with Rayleigh-scattering-dominated cloud polarization, with possible effects from supercooled water absorption and/or Mie scattering from a population of large cloud particles that contribute to the 220 GHz polarization.

COSMIC RAY SOURCE AND SOLAR ENERGETIC PARTICLES

The acceleration of particles to the high energy is one of the key issues of solar physics, cis-lunar irradiations, astrophysics, and astroparticle physics. With the development of space astronomy, people started to realize that plasma disturbances in solar flares, Earth’s magnetosphere, and interplanetary space can also produce a large population of non-thermal particles. Cosmic ray promotion i.e. selective energization of matter in the cosmos requires, as on earth, three distinct stages: ionization, injection and acceleration to high energy. Supernova remnants and stellar winds of massive stars grouped in associations appear to be excellent celestial accelerators or re-accelerators through the shock waves they induce in their superbubbles. The injection of ions seems devoted to stars, except the smaller ones. In cosmic several mechanisms lead charged particle acceleration. Electrons are accelerated in direction of Earth’s poles by long train of electric double layers of small amplitudes. Charged particles are accelerated by the pondermotive force of electromagnetic radiation. Also, in a nonequilibrium current plasma or a plasma with particle flows, a strong electric double layer can be formed, which accelerates charged particles to high energies. The reconnection of the magnetic field lines also leads to the acceleration of charged particles.

Synthesis and Characterization of a Thermoresponsive Copolymer with an LCST-UCST-like Behavior and Exhibiting Crystallization.

In this work, the diblock copolymer methoxy-poly(ethylene glycol)-block-poly(ε-caprolactone) (MPEG-b-PCL) was synthesized with a block composition that allows this polymer in aqueous media to possess both an upper critical solution temperature (UCST) and a lower critical solution temperature (LCST) over a limited temperature interval. The value of the UCST, associated with crystallization of the PCL-block, depended on heating (H) or cooling (C) of the sample and was found to be CPUCSTH = 32 °C and CPUCSTC = 23 °C, respectively. The LCST was not affected by the heating or cooling scans; assumed a value of 52 °C (CPLCSTH = CPLCSTC). At intermediate temperatures (e.g., 45 °C), dynamic light scattering (DLS), small-angle X-ray scattering (SAXS), and cryogenic transmission electron microscopy (cryo-TEM) showed that the solution consisted of a large population of spherical core-shell particles and some self-assembled rodlike objects. At low temperatures (below 32 °C), differential scanning calorimetry (DSC) and wide-angle X-ray scattering (WAXS) in combination with SAXS disclosed the formation of crystals with a cylindrical core-shell structure. Cryo-TEM supported a thread-like appearance of the self-assembled polymer chains. At temperatures above 52 °C, incipient phase separation took place and large aggregation complexes of amorphous morphology were formed. This work provides insight into the intricate interplay between UCST and LCST and the type of structures formed at these conditions in aqueous solutions of MPEG-b-PCL diblock copolymers.

Heavy snowfall event over the Swiss Alps: did wind shear impact secondary ice production?

Abstract. The change in wind direction and speed with height, referred to as vertical wind shear, causes enhanced turbulence in the atmosphere. As a result, there are enhanced interactions between ice particles that break up during collisions in clouds which could cause heavy snowfall. For example, intense dual-polarization Doppler signatures in conjunction with strong vertical wind shear were observed by an X-band weather radar during a wintertime high-intensity precipitation event over the Swiss Alps. An enhancement of differential phase shift (Kdp>1∘ km−1) around −15 ∘C suggested that a large population of oblate ice particles was present in the atmosphere. Here, we show that ice–graupel collisions are a likely origin of this population, probably enhanced by turbulence. We perform sensitivity simulations that include ice–graupel collisions of a cold frontal passage to investigate whether these simulations can capture the event better and whether the vertical wind shear had an impact on the secondary ice production (SIP) rate. The simulations are conducted with the Consortium for Small-scale Modeling (COSMO), at a 1 km horizontal grid spacing in the Davos region in Switzerland. The rime-splintering simulations could not reproduce the high ice crystal number concentrations, produced too large ice particles and therefore overestimated the radar reflectivity. The collisional-breakup simulations reproduced both the measured horizontal reflectivity and the ground-based observations of hydrometeor number concentration more accurately (∼20 L−1). During 14:30–15:45 UTC the vertical wind shear strengthened by 60 % within the region favorable for SIP. Calculation of the mutual information between the SIP rate and vertical wind shear and updraft velocity suggests that the SIP rate is best predicted by the vertical wind shear rather than the updraft velocity. The ice–graupel simulations were insensitive to the parameters in the model that control the size threshold for the conversion from ice to graupel and snow to graupel.

Beetle Antennae Search: Using Biomimetic Foraging Behaviour of Beetles to Fool a Well-Trained Neuro-Intelligent System.

Deep Convolutional Neural Networks (CNNs) represent the state-of-the-art artificially intelligent computing models for image classification. The advanced cognition and pattern recognition abilities possessed by humans are ascribed to the intricate and complex neurological connection in human brains. CNNs are inspired by the neurological structure of the human brain and show performance at par with humans in image recognition and classification tasks. On the lower extreme of the neurological complexity spectrum lie small organisms such as insects and worms, with simple brain structures and limited cognition abilities, pattern recognition, and intelligent decision-making abilities. However, billions of years of evolution guided by natural selection have imparted basic survival instincts, which appear as an “intelligent behavior”. In this paper, we put forward the evidence that a simple algorithm inspired by the behavior of a beetle (an insect) can fool CNNs in image classification tasks by just perturbing a single pixel. The proposed algorithm accomplishes this in a computationally efficient manner as compared to the other adversarial attacking algorithms proposed in the literature. The novel feature of the proposed algorithm as compared to other metaheuristics approaches for fooling a neural network, is that it mimics the behavior of a single beetle and requires fewer search particles. On the contrary, other metaheuristic algorithms rely on the social or swarming behavior of the organisms, requiring a large population of search particles. We evaluated the performance of the proposed algorithm on LeNet-5 and ResNet architecture using the CIFAR-10 dataset. The results show a high success rate for the proposed algorithms. The proposed strategy raises a concern about the robustness and security aspects of artificially intelligent learning systems.

Modification of the magneto-hydrodynamic equilibrium by the lower-hybrid wave driven fast electrons on the TST-2 spherical tokamak

Presence of a large population of fast particles may qualitatively modify the tokamak equilibrium from the one that can be described by standard magneto-hydrodynamics (MHD). The kinetic modification of the MHD equilibrium was studied for a lower-hybrid (LH) wave driven plasma on the TST-2 spherical tokamak. The analysis was performed using an equilibrium reconstruction method based on an extended MHD model that considers a two-component plasma of bulk MHD fluid and kinetic fast electrons. Scrape-off-layer current appeared naturally in the extended MHD analysis because of the finite electron orbit excursion from the flux surfaces. This reduced the bulk pressure contribution to the toroidal current substantially. The resulting poloidal flux profile was more consistent with that inferred from the Thomson scattering measurement.

Laser synthesis of uncapped palladium nanocatalysts

We report the synthesis of uncapped ‘naked’ palladium nanoparticles (PdNPs) through the facile and green route of femtosecond laser reduction in liquid using two different precursors: potassium tetrachloropalladate (K2PdCl4) and palladium nitrate (Pd(NO3)2). Stabilization of the Pd precursor by lowering the pH enabled the synthesis of PdNPs in the sub-5 nm range. Laser synthesis using both precursors generated ultrasmall spherical NPs with average diameters of 1.2 nm and 3.1 nm for the nitrate and chloride precursors, respectively. An additional population of anisotropic large particles with nanopopcorn and nanoflower morphologies observed in electron microscopy images appears to result from the aggregation of the ultrasmall PdNPs. The PdNPs are efficient catalysts for Suzuki cross-coupling reactions and for the reduction of para-nitrophenol by sodium borohydride in water. The excellent catalytic activity of our laser-generated PdNPs is attributed to the ligand-free structure and small particle sizes generated through laser reduction in liquid.

Drift kinetic theory of alpha transport by tokamak perturbations

Upcoming tokamak experiments fuelled with deuterium and tritium are expected to have large alpha particle populations. Such experiments motivate new attention to the theory of alpha particle confinement and transport. A key topic is the interaction of alpha particles with perturbations to the tokamak fields, including those from ripple and magnetohydrodynamic modes like Alfvén eigenmodes. These perturbations can transport alphas, leading to changed localization of alpha heating, loss of alpha power and damage to device walls. Alpha interaction with these perturbations is often studied with single-particle theory. In contrast, we derive a drift kinetic theory to calculate the alpha heat flux resulting from arbitrary perturbation frequency and periodicity (provided these can be studied drift kinetically). Novel features of the theory include the retention of a large effective collision frequency resulting from the resonant alpha collisional boundary layer, correlated interactions over many poloidal transits and finite orbit effects. Heat fluxes are considered for the example cases of ripple and the toroidal Alfvén eigenmode (TAE). The ripple heat flux is small. The TAE heat flux is significant and scales with the square of the perturbation amplitude, allowing the derivation of constraints on mode amplitude for avoidance of significant alpha depletion. A simple saturation condition suggests that TAEs in one upcoming experiment will not cause significant alpha transport via the mechanisms in this theory. However, saturation above the level suggested by the simple condition, but within numerical and experimental experience, which could be accompanied by the onset of stochasticity, could cause significant transport.

Backward waves in the nonlinear regime of the Buneman instability

Observation of low- and high-frequency backward waves in the nonlinear regime of the Buneman instability is reported. Intense low-frequency backward waves propagating in the direction opposite to the electron drift (with respect to the ion population) of ions and electrons are found. The excitation of these waves is explained based on the linear theory for the stability of the electron velocity distribution function that is modified by nonlinear effects. In the nonlinear regime, the electron distribution exhibits a wide plateau formed by electron hole trapping and extends into the negative velocity region. It is shown that within the linear approach, the backward waves correspond to the weakly unstable or marginally stable modes generated by the large population of particles with negative velocities.

A semi dynamic in vitro digestion study of milk protein concentrate dispersions structured with different polysaccharides

Hydrocolloids are often added as functional ingredients in foods, to better design the structure of the matrix and ensure food quality and optimal sensory properties. However, much less is known about their influence on the physical and chemical changes during gastric digestion. In this study, semi-continuous in vitro gastric digestion was applied on a model food system, prepared with milk protein concentrate (MPC) (3% w/v) and 1% alginate, pectin, guar gum, as well as a 1:1 mixture of alginate and pectin. The dynamics during simulated gastric digestion were observed by measuring particle size distributions, structuring at various length scales, as well as by evaluating differences in protein breakdown. Immediately after contact with the simulated gastric fluids, all samples showed extensive aggregation and formation of different structures. MPC control dispersions (no polysaccharide) and MPC containing alginate formed large inhomogeneous aggregates. The lack of structural homogeneity affected the simulated gastric emptying: there were marked differences in the type of aggregates present at various times of emptying depending on the hydrocolloid present in the mixture. MPC containing pectin or guar gum formed macroscopically homogeneous dispersion, with rather small protein aggregates showing a large population of particles between 60 and 100 ​μm of diameter, with marked differences in microstructure. Pectin created large coacervates, while guar microscopic phase separated systems. These dispersions showed a higher extent of protein digestion, due to the larger surface area created for enzyme activity compared to the macroscopically phase separated matrices. In all cases, there was a large undigested fraction at the end point of 140 ​min. SDS PAGE demonstrated differences in the casein peptides distribution depending on the type of polysaccharide present during simulated gastric emptying. This in spite of similarities in cumulative protein emptied. It was concluded that in this semi-continuous in vitro gastric digestion model, structuring with polysaccharides has a significant impact on gastric emptying and protein digestion kinetics.

Automated Single-Particle Reconstruction of Heterogeneous Inorganic Nanoparticles

Single-particle reconstruction can be used to perform three-dimensional (3D) imaging of homogeneous populations of nano-sized objects, in particular viruses and proteins. Here, it is demonstrated that it can also be used to obtain 3D reconstructions of heterogeneous populations of inorganic nanoparticles. An automated acquisition scheme in a scanning transmission electron microscope is used to collect images of thousands of nanoparticles. Particle images are subsequently semi-automatically clustered in terms of their properties and separate 3D reconstructions are performed from selected particle image clusters. The result is a 3D dataset that is representative of the full population. The study demonstrates a methodology that allows 3D imaging and analysis of inorganic nanoparticles in a fully automated manner that is truly representative of large particle populations.

Smart Development of Big Data App for Determining the Modelling of Covid-19 Medicinal Compounds Using Deep AI Core Engine System

Smart Big Data App Using Deep Artificial Intelligence (AI) Core Engine System focuses on solving problems related to the difficulty in building a prototyping model computer simulation like in silico as a model initiation of the complex Covid-19 medicinal compound involving Big Data ecosystems such as Hadoop and Spark. The difficulty is for example, currently, it is still very arduous to measure the rate of mixture of a compound when combined with many other compounds, which can consider the trade-off in minimizing the negative effects but optimizing the positive effects. In addition, the computation time becomes very long when using a system that is not in the Big Data ecosystem since this is proportional to the large number of compounds that vary widely and also the number of different situations of Covid-19 patients with other congenital diseases (comorbid) or without congenital disease; thus, it can be considered to be included in a condition that requires a very complex computational process which is very difficult to model using a conventional mathematical approach because the calculations are certainly very complex when compared to approaches using meta-heuristics algorithms such as Particle Swarm Optimization (PSO) which is much easier but requires a very large particle population space and iterative process to achieve global convergence. As a consequence, it requires fast computation processes based on distributed computing such as using the Big Data ecosystem. From the review of these problems, the system was created based on the Computational Intelligence; hence, the end-users, especially the developers, can build an application easier in spite of the complex computations, one of the which is in the meta-heuristic technique to minimize the negative effects and optimize the positive effects of the medicinal compounds by including a lot of data to get a better modeling. Therefore, the prototyping modeling project can be quick and robust, and achieve high performance measurements.

Acoustic attenuation spectroscopy and helium ion microscopy study of rehydration of dairy powder

Complete hydration is essential for the production of structured dairy products from powders. It is essential that the ingredients used hydrate completely. Determination of an end point of rehydration is non-trivial, but ultrasound-based methodologies have demonstrated potential in this area and are well suited to measuring bulk samples in situ. Here, acoustic attenuation spectroscopy (AAS) is used to monitor rehydration of skim milk powder, and recombined systems of micellar casein isolate with lactose and whey protein isolate. Dynamic light scattering, zeta-potential measurements and AAS as a function of pH characterise each component around its isoelectric point to assess its functionality. Scanning helium ion microscopy was used to image the dry powders, without any conductive coating, producing resolution equivalent to scanning electron microscopy, but with much larger focal lengths and fewer imaging artefacts. Imaging the powders provides information on particle size and morphology which can affect dissolution behaviour. Reconstituted skim milk powder and recombined samples were monitored showing there are changes occurring over several hours. Attenuation coefficients are shown to predict the end point of hydration. Model fitting is used to extract volume fractions and average particle sizes of large and small particle populations in recombined samples over time. AAS is demonstrated to be capable of tracking the dynamics in rehydrating dispersions over time. Physical parameters such as the volume fraction and particle size of the dispersed phase can be determined.

Interaction between casein and rice glutelin: Binding mechanisms and molecular assembly behaviours

The present study investigated the interaction between acid casein and rice glutelin (RG) under neutral conditions. Large particle populations contain casein-RG complex which consisted of β-casein, αs1-casein, and RG was formed. The results of multispectral studies indicated that the peptide chain and secondary structure of casein did not change during the binding process. Besides, the binding behaviours seemed to be closely related to the surface hydrophobic region of RG. Thermodynamic parameter calculations showed that the main driving forces behind this structure formation were the hydrogen bonds and van der Waals forces. On the other hand, the addition of RG caused the generation of small particle populations (~20 nm) which mainly composed of κ-casein and αs2-casein, and such small particle populations maintained aggregation through residual calcium. Moreover, it is noting that these two particle populations can coexist stably, this finding will provide an avenue to produce, by design, casein nanoparticles.

Vortex‐Wide Detection of Large Aspherical NAT Particles in the Arctic Winter 2011/12 Stratosphere

AbstractMicron‐sized HNO3‐containing particles in polar stratospheric clouds are known to denitrify the polar winter stratosphere and support chemical ozone loss. We show that populations of nitric acid trihydrate (NAT) particles with volume‐equivalent median radii of 3–7 μm can be detected vortex‐wide by means of infrared limb sounding. Key for detection are the applied optical characteristics of highly aspherical particles consisting of the β‐NAT phase. Spectroscopic signatures and ambient conditions of detected populations show that these particles play a key role in denitrification of the Arctic winter stratosphere. Complementary gas‐phase HNO3 observations indicate collocated highly efficient HNO3 sequestration within days and are consistent with measured spectral signals of populations of large NAT particles. High amounts of condensed gas‐phase equivalent HNO3 exceeding 10 ppbv and long persistence of detected populations, despite expected gravitational settling, imply that our understanding of the particles is incomplete.

Obtaining Reliable Kinetics from Nanosized Battery Materials

One of the many frontiers of energy storage is high power, both on charge and on discharge. Consequently, development of materials that can support high current densities are in vogue. This challenge is here that the mass transport in structures that support ion insertion/dis-insertion is known to be slow. Approaches to address this challenge includes increasing the operational temperature and nanosizing the electroactive active materials. Nanosizing, however leads to severe problems related to obtaining good electronic contact as well as questions regarding the uniformity of the performing across a large population of particles. In this talk we will discuss our recent development of techniques to overcome this these challenges, including techniques that rely on electrochemistry as well as purely chemical ones. Special focus will be given our hyphenated technique providing structural information while providing full charge (disinsertion) in seconds.

Effect of rice glutelin-resveratrol interactions on the formation and stability of emulsions: A multiphotonic spectroscopy and molecular docking study

An understanding of the molecular mechanisms underpinning protein-polyphenol interactions is critical for incorporating bioactive polyphenols into functional foods and beverages. This study characterized the interaction between rice glutelin (RG) and resveratrol (RES) using a combination of spectroscopic and molecular simulation techniques. Resveratrol quenched the intrinsic fluorescence of rice glutelin, which is indicative of a binding interaction between the two molecules. Resveratrol addition caused a decrease in surface hydrophobicity, alteration in protein microenvironment, and change in conformation of the rice glutelin. Thermodynamic analysis suggested that the binding of resveratrol to the protein was spontaneous and mainly driven by hydrophobic interactions. A RG-RES complex with a molar ratio of 1:1 was formed, suggesting that rice glutelin may be a suitable carrier for resveratrol. More detailed insights into the nature of the binding site and the forces involved were obtained using molecular simulation studies. Finally, we examined the impact of resveratrol on the formation and stability of oil-in-water emulsions stabilized by rice glutelin. Emulsions containing small highly anionic oil droplets could be formed in the presence of resveratrol, but a population of large particles was observed during storage. These particles appeared to consist of oil droplets with water droplets trapped inside. We hypothesize that water diffused into the oil droplets and formed small water droplets that were stabilized by amphiphilic resveratrol. Our results have important implications for the development of effective delivery systems for resveratrol.