Beyond Janus Geometry: Characterization of Flow Fields Around Nonspherical Photocatalytic Microswimmers

Catalytic microswimmers that move by a phoretic mechanism in response to a self-induced chemical gradient are often obtained by the design of spherical janus microparticles, which suffer from multi-step fabrication and low yields. Approaches such as irregular particle shapes, local excitation or intrinsic asymmetry are on the rise to facilitate manufacturing, but the effects on the generation of motion remain poorly understood. In this work, single crystalline BiVO4 microswimmers are presented that rely on a strict inherent asymmetry of charge-carrier distribution under illumination. The origin of the asymmetrical flow pattern is elucidated becauseof the high spatial resolution of measured flow fields around pinned BiVO4 colloids. As a result the flow from oxidative to reductive particle sides was confirmed. Distribution of oxidation and reduction reactions suggests a dominant self-electrophoretic motion mechanism with a source quadrupole as the origin of the induced flows. It is shown that the symmetry of the flow fields is broken by self-shadowing of the particles and synthetic surface defects that impact the photocatalytic activity of the microswimmers. The results demonstrate the complexity of symmetry breaking in nonspherical microswimmers and are leading the way towards understanding ofpropulsion mechanisms of phoretic colloids of various shapes.

Influence of Pyrolysis Parameters Using Microwave toward Structural Properties of ZnO/CNS Intermediate and Application of ZnCr2O4/CNS Final Product for Dark Degradation of Pesticide in Wet Paddy Soil

Pesticide is a pollution problem in agriculture. The usage of ZnCr2O4/CNS and H2O2 as additive in liquid fertilizer has potency for catalytic pesticide degradation. Colloid condition is needed for easy spraying. Rice husk and sawdust were used as carbon precursor and ZnCl2 as activator. The biomass–ZnCl2 mixtures were pyrolyzed using microwave (400–800 W, 50 min). The products were dispersed in water by blending then evaporated to obtain ZnO/CNS. The composites were reacted with KOH, CrCl3·6H2O, more ZnCl2, and little water by microwave (600 W, 5 min). The ZnCr2O4/CNS and H2O2 were used for degradation of buthylphenylmethyl carbamate (BPMC) in wet deactivated paddy soil. TOC was measured using TOC meter. The FTIR spectra of the ZnO/CNS composites indicated the completed carbonization except at 800 W without ZnCl2. The X-ray diffractograms of the composites confirmed ZnO/CNS structure. SEM images showed irregular particle shapes for using both biomass. ZnCr2O4/CNS structure was confirmed by XRD as the final product with crystallite size of 74.99 nm. The sawdust produced more stable colloids of CNS and ZnO/CNS composite than the rice husk. The pyrolysis without ZnCl2 formed more stable colloid than with ZnCl2. The ZnCr2O4/CNS from sawdust gave better dark catalytic degradation of BPMC than from rice husk, i.e., 2.5 and 1.6 times larger for 400 and 800 W pyrolysis, respectively.

Drag Coefficients of Irregularly Shaped Particles in Newtonian Fluids

An accurate prediction of the settling velocities of drill cuttings is essential in effectively designing, running, and optimizing drilling operations. If there is no reliable process for modelling the drag coefficient, the settling velocity cannot be obtained. In most current literature, particles are assumed to be spherical, which can be easily modelled. However, this assumption may lead to inaccurate results for other irregular particle shapes. This paper studies the transport behavior of irregular particles by modelling these shapes as variants of a bow shape, with a numerical simulation approach for their drag coefficients. The drilling fluid around the particle is water (Newtonian). The drag coefficients of the non-spherical particle (grouped into three sub-shapes) were modelled. In addition, the inlet velocity of the fluid is varied to show the effects on the shape drag coefficients. The results of the simulations were compared to experimental results carried out by other researchers. It was observed that as the particles became less streamlined, their drag coefficient increased. A sensitivity analysis was carried out to investigate the effects of fluid properties on the drag coefficient. The results were consistent and logical. The results showed that Computational Fluid Dynamics analysis provided a reliable estimation of the drag coefficient, which can help optimize the transport of drill cuttings during drilling operations.

Flattening of ring particles and self-gravity wakes in Saturn’s rings

<p>The varying geometry of Cassini star occultations by Saturn’s rings constrains both the size and shape of structures that block starlight. Statistics of UVIS star occultations measure structures as small as meters, on times scales of minutes to decades. We calculate the excess variance, skewness and kurtosis including the effects of irregular particle shadows, along with a <em><strong>granola bar</strong></em> model of gaps, ghosts and clumps. The widths <strong>W</strong> and separation <strong>S</strong> of rectangular clumps play an analogous role to the relative size of the particle shadows, <strong>δ.</strong> In the first model considered, our calculations are based on the moments of the transparency <strong>T</strong> in that part of the ring <strong>A </strong>sampled by the occultation, thus extending the work of  Showalter and Nicholson (1990) to larger <strong>τ</strong>  and <strong>δ</strong>, and to higher central moments, without their simplifying assumptions. We also calculate these statistics using an approach based on the <em><strong>autocovariance, autocoskewness and autocokurtosis</strong></em>.</p><p>These new approaches compare well to the formula for excess variance from Showalter and Nicholson in the region where all are accurate, <strong>δτ</strong><strong>≪</strong><strong>1</strong>. Skewness for small <strong>τ </strong>has a different sign for transparent and opaque structures, distinguishing gaps from clumps. The higher order central moments are more sensitive to the extremes of the size distribution and opacity.</p><p>We explain the upward curvature of the dependence of normalized excess variance for Saturn’s background C ring by the observation of Jerousek etal (2018) that the measured optical depth is correlated with particle size. For a linear dependence <strong>R<sub>eff</sub> = 12 * (τ – 0.08) + 1.8m</strong> from Jerousek’s results, we match the curvature of normalized excess variance, the skewness and the kurtosis in the region between 78,000 and 84,600km from Saturn.</p><p>Statistics calculated from the granola bar model give different predictions from individual particles. The different <strong>τ dependence </strong>suggests that the wave crests compress the gaps more than the wakes, and produce more regularity among the clumps; and larger and more opaque self-gravity wakes in the wave crests, with transparent ghosts. The UVIS observations fall between the most regular and the most irregular granola bar models.</p><p>We compare selected occultations (Eckert etal 2020) at different values of the elevation <strong>B</strong> to estimate the flattening and axial ratio of ring particles and clumps. In Ring C, we find spheres: The statistical measures from multiple occultations follow the expected dependence on <strong>sin B</strong>, e.g. Showalter & Nicholson (1990). However, in the Janus 2:1 and Mimas 5:3 density waves, the excess variance for stars β Cen, λ Sco and σ Sgr shows no <strong>B</strong> dependence. This is exactly the expectation for completely flat (<strong>H/W =0</strong>) self-gravity wakes that we have derived from the autocovariance of the wake shadows. A closer analysis of this particular case gives <strong>H/W < 0.04</strong>, different from Colwell etal (2007), suggesting wakes are more like<em><strong> linguine</strong></em> than <em><strong>granola bars</strong></em>.</p>

Penggunaan Metode Taguchi untuk Menentukan Kondisi Parameter Optimum Pada Pembuatan CaO dari Batu Kapur (CaCO-3)

Research has been carried out to determine the optimum conditions for making quicklime (CaO) using the Taguchi Method. CaO is the burning result of limestone (CaCO_3) in calcination process by releasing of CO_2 gas until CaO solids occur. The limestone was calcined at 950^o c. The Taguchi Method is a quality improvement technique with the selection of the most influential parameters of the making of process CaO. The parameters are particle size, CaO mass, heating temperature and stirring time. The XRF results show that the levels of CaO after the Taguchi Method design has increased from 98.779% to 98.814%. The XRD results show that the CaO phase is amorphous. The phase which were formed by calcination are Lime (CaO), Quartz (SiO_2) and Hematite (〖Fe〗_2 O_3). Based on the SEM results, the morphology of CaCO_3 has an irregular particle size and tends to be a granular solid due to the presence of impurity. Meanwhile, the results of the EDS analysis show that the content of Calcium (Ca) is quite high. From the design results of the Taguchi Method, the optimum conditions is obtained at a particle size of 140 mesh, 75 gr CaO mass, heating temperature 70^o c and stirring time 0,5 hour.

Effect of synthesis and activation methods on the character of CoMo/ultrastable Y-zeolite catalysts

The properties of three types of CoMo/USY catalysts with different synthesized methods have been studied. The sequential and co-impregnation methods followed by activation using calcination and reduction process have been conducted. The properties of the catalysts were examined using Fourier-transform-infrared (FTIR) spectroscopy, X-ray diffraction (XRD) with refinement, and surface area analyzer (SAA). The FTIR spectrum study revealed the enhanced intensity of its Bronsted acid site, and the XRD diffractogram pattern verified the composition of pure metals, oxides, and alloys in the catalyst. The SAA demonstrated the mesoporous features of the catalyst. Scanning electron microscopy showed an irregular particle morphology. Additional analysis using the transmission electron microscopy indicated that the metal has successfully impregnated without damaging the USY structure.

Simulation of Nonlinear Heat Conduction in Perforated Material by Improved Moving Particle Semi-Implicit Method

An improved moving particle semi-implicit (MPS) method is presented to simulate heat conduction with temperature-dependent thermal conductivity. Based on Taylor expansion, a modified Laplacian operator is proposed, and its accuracy in irregular particle distributions is verified. Two problems are considered: (1) heat conduction in a one-dimensional (1D) slab and (2) heat conduction in a perforated sector with different boundary conditions. Consistent results with a mesh-based method are obtained, and the feasibility of the proposed method for heat conduction simulation with temperature-dependent conductivity is demonstrated.

A Super-Clustering Approach for Fully Automated Single Particle Picking in Cryo-EM

Structure determination of proteins and macromolecular complexes by single-particle cryo-electron microscopy (cryo-EM) is poised to revolutionize structural biology. An early challenging step in the cryo-EM pipeline is the detection and selection of particles from two-dimensional micrographs (particle picking). Most existing particle-picking methods require human intervention to deal with complex (irregular) particle shapes and extremely low signal-to-noise ratio (SNR) in cryo-EM images. Here, we design a fully automated super-clustering approach for single particle picking (SuperCryoEMPicker) in cryo-EM micrographs, which focuses on identifying, detecting, and picking particles of the complex and irregular shapes in micrographs with extremely low signal-to-noise ratio (SNR). Our method first applies advanced image processing procedures to improve the quality of the cryo-EM images. The binary mask image-highlighting protein particles are then generated from each individual cryo-EM image using the super-clustering (SP) method, which improves upon base clustering methods (i.e., k-means, fuzzy c-means (FCM), and intensity-based cluster (IBC) algorithm) via a super-pixel algorithm. SuperCryoEMPicker is tested and evaluated on micrographs of β-galactosidase and 80S ribosomes, which are examples of cryo-EM data exhibiting complex and irregular particle shapes. The results show that the super-particle clustering method provides a more robust detection of particles than the base clustering methods, such as k-means, FCM, and IBC. SuperCryoEMPicker automatically and effectively identifies very complex particles from cryo-EM images of extremely low SNR. As a fully automated particle detection method, it has the potential to relieve researchers from laborious, manual particle-labeling work and therefore is a useful tool for cryo-EM protein structure determination.