Dispersed Clusters Research Articles

Interactions between nanoscale zero valent iron and extracellular polymeric substances of anaerobic sludge

The effects on the activity of anaerobic digestion (AD) of interactions between extracellular polymeric substances (EPS), a protective barrier of microorganisms towards toxic compounds, and nanoscale zero valent iron (nZVI) remain incompletely understood. In this work, EPS induced a dosage-dependent dispersion of nZVI clusters due to their effective accumulation on the nZVI surface. The small size of nZVI clusters and the formation of stable Fe-EPS complex promoted the dissolution of nZVI with a final increase of 15–20% H2 yield. Further characterizations of EPS demonstrated the presence of some semiquinones, like riboflavin, which may work as a sink to accept electrons from nZVI. This likely explains the EPS dosage-related reduction of H2 release rate in the initial stage and the possible decrease in nZVI reducibility responsible for disrupting cell integrity. Interactions between nZVI and EPS could improve the electrochemical activity of EPS, favoring microbial extracellular electron transfer. Therefore, the presence of EPS at relatively higher concentrations may 1) reduce the inhibition of nZVI to AD process by avoiding the fast accumulation of H2 and restricting damage to cell integrity; 2) benefit the methanogenesis process by providing more exogenous H2 from complete nZVI dissolution with higher electrochemical activity of EPS. This study provides insight into the interactions between EPS and nanoparticles with strong reducibility in biological wastewater treatment systems.

Heterogeneity-Induced Mesoscale Toughening in Polymer Nanocomposites

We report a mesoscale toughening mechanism in polymer nanocomposites that is distinct from previously reported ones. Fractography analysis of epoxy composites with nano-silica additives reveals a stochastic dispersion of nanofiller clusters which creates mesoscale stiffness heterogeneity as confirmed by nanoindentation testing. To analyze the effect of heterogeneity, a finite element model where a crack grows through heterogeneous material was created. Simulations and experimental results indicate that inducing stiffness heterogeneity increases toughness by modification of the crack tip fields. Our results indicate that mesoscale toughening (induced by the nanoparticle additives) plays a significant role in influencing fracture toughness in nanocomposite materials.

Synthesis of cobalt ferrite colloidal nanoparticle clusters by ultrasonic-assisted solvothermal process

In the present work, cobalt ferrite colloidal nanoparticle clusters were synthesized via solvothermal method using cobalt and iron chlorides, sodium acetate, and ethylene glycol as starting materials. The effects of ultrasonication process of the primary solution on the structure, microstructure, specific surface area, and molecular and magnetic characteristics of the synthesized powders were investigated. Results showed that solvothermal method with/without ultrasonication resulted in nanoscale cobalt ferrite clusters. Field emission scanning electron microscopy micrographs revealed that the synthesized powders were consisted of well-dispersed raspberry-like clusters. Applied ultrasonic waves decreased the mean cluster size while increased the cluster dispersion. The synthesized cobalt ferrite powders had high specific surface area of about 127 m2g−1 which slightly decreased to about 122 m2g−1 after ultrasonication. Generally, the powders showed superparamagnetic properties with a minimum saturation magnetization of 55 emu/g. Ultrasonication for 60 min reduced the coercivity and the effective magneto-crystalline anisotropy of the cobalt ferrite powders.

3D Dstorm Imaging Reveals Camkii-Dependent Dispersal of Ryanodine Receptor Clusters in Failing Rat Cardiomyocytes

Excitation-contraction coupling in the heart crucially depends on the function of ryanodine receptors (RyRs). Recent advances in single-molecule localization microscopy have enabled nanoscale visualization of RyR organization, yet the precise geometric arrangement of RyRs in both health and disease has yet to be characterized. Here, we employed our recently developed 3D dSTORM method to quantify the subcellular, nanoscale organization of RyRs in normal and failing (post-infarction) rat cardiomyocytes, proposing that disassembly of RyR clusters promotes impaired Ca2+ homeostasis in this condition. We specifically investigated the nanoscale organization of interior RyRs which are associated with the transverse tubule network; a subpopulation of RyRs that can only be quantitatively characterized in 3D. We observed a significant reduction in RyR cluster size in failing cardiomyocytes when compared to sham-operated controls (5.0±0.3 vs. 7.8±0.4 RyRs/cluster, p<0.05). RyR cluster groupings localized within 100 nm of their neighbours comprise Ca2+ release units (CRUs), which are thought to cooperatively generate Ca2+ sparks. 3D imaging revealed an average of 21±0.9 RyRs/CRU in sham cells, but only 15.1±1.3 RyRs/CRU in failing cells (p<0.05). Failing cardiomyocytes also contained more RyR clusters / CRU than sham cells (2.7±0.1 vs 2.9±0.1, p<0.05), associated with slower Ca2+ spark kinetics (time to peak = 7.7±0.5 vs 10.5±0.4, p<0.05). When failing cardiomyocytes were treated with a CaMKII blocker (Autocamtide-1-related Inhibitory Peptide, AIP), Ca2+ spark characteristics were restored to sham levels. AIP administration also reversed the RyR dispersal observed at both the cluster and CRU level. Importantly, stimulation of CaMKII by the EPAC activator 8-CPT reproduced RyR dispersion in healthy cardiomyocytes. Together, our results suggest that RyR cluster disassembly in failing cardiomyocytes is driven by CaMKII phosphorylation, and promotes impaired cardiomyocyte Ca2+ homeostasis in this disease.

Kinematics of disk galaxies in (proto-)clusters atz= 1.5

Aims.While many aspects of the impact of dense environments on late-type galaxies at redshifts below unity have been scrutinized in the past few decades, observational studies of the interplay between environment and disk galaxy evolution atz &gt; 1 are still scarce. We observed star-forming galaxies atz ≈ 1.5 selected from the HyperSuprimeCam Subaru Strategic Program. The galaxies are part of two significant overdensities of [O II] emitters identified via narrowband imaging and photometric redshifts fromgrizyphotometry.Methods.We used theK-band Multi-Object Spectrograph (KMOS) to carry out Hαintegral field spectroscopy of 46 galaxies in total. Ionized gas maps, star formation rates, and velocity fields were derived from the Hαemission line. We quantified morphological and kinematical asymmetries in order to look for potential gravitational (e.g., galaxy-galaxy) or hydrodynamical (e.g., ram-pressure) interactions.Results.Hαemission was detected in 36 of our targets. Of these galaxies, 34 are members of two (proto-)clusters atz = 1.47, confirming our selection strategy to be highly efficient. By fitting model velocity fields to the observed ones, we determined the intrinsic maximum rotation velocityVmaxof 14 galaxies. Utilizing the luminosity–velocity (Tully–Fisher) relation, we find that these galaxies are more luminous than their local counterparts of similar mass by up to ∼4 mag in the rest-frameB-band. In contrast to field galaxies atz &lt; 1, the offsets of thez ≈ 1.5 (proto-)cluster galaxies from the local Tully–Fisher relation are not correlated with their star formation rates but with the ratio betweenVmaxand gas velocity dispersionσg. This probably reflects that fewer disks have settled to purely rotational kinematics and highVmax/σgratios, as is observed in the field at similar redshifts. Tests with degraded low-redshift cluster galaxy data show that we cannot identify purely hydrodynamical interactions with the imaging currently at hand. Due to relatively low galaxy velocity dispersions (σv &lt; 400 km s−1) of the (proto-)clusters, gravitational interactions are likely more efficient, resulting in higher kinematical asymmetries than in present-days clusters.

A Sustainable Biomineralization Approach for the Synthesis of Highly Fluorescent Ultra-Small Pt Nanoclusters.

Herein we report the first example of a facile biomineralization process to produce ultra-small-sized highly fluorescent aqueous dispersions of platinum noble metal quantum clusters (Pt-NMQCs) using a multi-stimulus responsive, biomimetic intrinsically disordered protein (IDP), Rec1-resilin. We demonstrate that Rec1-resilin acts concurrently as the host, reducing agent, and stabilizer of the blue-green fluorescent Pt-NMQCs once they are being formed. The photophysical properties, quantum yield, and fluorescence lifetime measurements of the synthesized Pt-NMQCs were examined using UV-Vis and fluorescence spectroscopy. The oxidation state of the Pt-NMQCs was quantitatively analyzed using X-ray photoelectron spectroscopy. Both a small angle X-ray scattering technique and a modeling approach have been attempted to present a detailed understanding of the structure and conformational dynamics of Rec1-resilin as an IDP during the formation of the Pt-NMQCs. It has been demonstrated that the green fluorescent Pt-NMQCs exhibit a high quantum yield of ~7.0% and a lifetime of ~9.5 ns in aqueous media. The change in photoluminescence properties due to the inter-dot interactions between proximal dots and aggregation of the Pt-NMQCs by evaporation was also measured spectroscopically and discussed.

The Young Massive Star Cluster Westerlund 2 Observed with MUSE. II. MUSEpack—A Python Package to Analyze the Kinematics of Young Star Clusters

Abstract We mapped the Galactic young massive star cluster Westerlund 2 with the integral field spectrograph MUSE (spatial resolution: 0.2 arcsec px−1, spectral resolution: Δλ = 1.25 Å, wavelength range: 4600–9350 Å) mounted on the Very Large Telescope. We present the fully reduced data set and introduce our new Python package “MUSEpack,” which we developed to measure stellar radial velocities (RVs) with an absolute precision of 1–2 km s−1 without the necessity of a spectral template library. This novel method uses the two-dimensional spectra and an atomic transition line library to create templates around strong absorption lines for each individual star. Automatic, multi-core processing makes it possible to efficiently determine stellar RVs of a large number of stars with the necessary precision to measure the velocity dispersion of young star clusters. MUSEpack also provides an enhanced method for removing telluric lines in crowded fields without sky exposures, and a Python wrapper for ESO’s data reduction pipeline. We observed Westerlund 2 with a total of 11 short and 5 long exposures (survey area: ∼11 arcmin2 or 15.8 pc2) to cover the bright nebular emission and OB stars, as well as the fainter pre-main-sequence stars (≥1 M ⊙). We extracted 1725 stellar spectra with a mean signal-to-noise ratio of S/N &gt; 5 per pixel. Typical RV uncertainties of 4.78 km s−1, 2.92 km s−1, and 1.1 km s−1 are reached for stars with a mean S/N &gt; 10, S/N &gt; 20, and S/N &gt; 50 per pixel, respectively. It is possible to reach RV accuracies of 0.9 km s−1, 1.3 km s−1, and 2.2 km s−1 with ≥5, 3–4, and 1–2 spectral lines used to measure the RVs, respectively. The combined statistical uncertainty on the RV measurements is 1.10 km s−1.

Microalloying effects of Mo versus Cr in HSLA steels with ultrafine-grained ferrite microstructures

Thermo-mechanical processing with warm-deformation in the ferrite is a promising pathway towards manufacturing of large volumes of steels with ultrafine grain sizes. We apply this processing to HSLA steels to invoke grain refinement coupled with strengthening arising from microalloying. The aim is to systematically unravel the strengthening via the addition of ‘modern’ microalloying elements Mo versus Cr besides Nb. These elements have been proposed to provide significant additional strengthening during such processing but the mechanisms yet remain unknown. Therefore, three model Fe-1.6Mn-0.04C-0.1Nb+0.5Mo/Cr steels were warm-rolled at ∼600 °C with an overall reduction of 50% followed by ageing. It was found that Mo leads to an increase in hardness of ∼20% compared to the base alloy, whereas Cr provides only a minor hardening increment. SEM, EBSD, TEM and atom probe were used to reveal the beneficial effect of Mo versus Cr. It was found that Mo is more effective delaying dislocation recovery. We also report that Mo partitions into nanoscale Nb–C solute clusters and precipitates of NbC and Fe3C during ageing, retarding the coarsening of these phases. However, Cr was found to partition into Fe3C only, and does not contribute to the nature of the dispersion of clusters and NbC.

Investigating New Routes for Biomass Upgrading: “H2-Free” Hydrodeoxygenation Using Ni-Based Catalysts

This work showcases an innovative route for biocompound upgrading via hydrodeoxygenation (HDO) reactions, eliminating the need for external high-pressure hydrogen supply. We propose the use of water as reaction media and the utilization of multifunctional catalysts that are able to conduct multiple steps such as water activation and HDO. In this study, we validate our hypothesis in a high-pressure batch reactor process using guaiacol as a model compound and multicomponent Ni-based catalysts. In particular, a comparison between ceria-supported and carbon/ceria-supported samples is established, the carbon-based materials being the suitable choice for this reaction. The physicochemical study by X-ray photoelectron spectroscopy, transmission electron microscopy, X-ray diffraction, and temperature-programmed reduction reveals the greater dispersion of Ni clusters and the strong metal-support interaction in the carbon/ceria-based samples accounting for the enhanced performance. In addition, the characterization of the spent samples points out the resistance of our catalysts toward sintering and coking. Overall, the novel catalytic approach proposed in this paper opens new research possibilities to achieve low-cost bio-oil upgrading processes.

Analysis of Primary Care Computerized Medical Records (CMR) Data With Deep Autoencoders (DAE)

The use of deep learning is becoming increasingly important in the analysis of medical data such as pattern recognition for classification. The use of primary healthcare computational medical records (CMR) data is vital in prediction of infection prevalence across a population, and decision making at a national scale. To date, the application of machine learning algorithms to CMR data remains under-utilized despite the potential impact for use in diagnostics or prevention of epidemics such as outbreaks of influenza. A particular challenge in epidemiology is how to differentiate incident cases from those that are follow-ups for the same condition. Furthermore, the CMR data are typically heterogeneous, noisy, high dimensional and incomplete, making automated analysis difficult. We introduce a methodology for converting heterogeneous data such that it is compatible with a deep autoencoder for reduction of CMR data. This approach provides a tool for real time visualization of these high dimensional data, revealing previously unknown dependencies and clusters. Our unsupervised nonlinear reduction method can be used to identify the features driving the formation of these clusters that can aid decision making in healthcare applications. The results in this work demonstrate that our methods can cluster more than 97.84% of the data (clusters >5 points) each of which is uniquely described by three attributes in the data: Clinical System (CMR system), Read Code (as recorded) and Read Term (standardized coding). Further, we propose the use of Shannon Entropy as a means to analyse the dispersion of clusters and the contribution from the underlying attributes to gain further insight from the data. Our results demonstrate that Shannon Entropy is a useful metric for analysing both the low dimensional clusters of CMR data, and also the features in the original heterogeneous data. Finally, we find that the entropy of the low dimensional clusters are directly representative of the entropy of the input data (Pearson Correlation = 0.99, R2 = 0.98) and therefore the reduced data from the deep autoencoder is reflective of the original CMR data variability.

Semi-solid stirring of modified ceramic nanoparticles using iron and nickel in an aluminum A356 melt

Suitable dispersion of ceramic nanoparticles in a melt of aluminum alloys is a very hard task due to their severe tendency for agglomeration. In this study, a solid-state process including the mixing of as-received alumina and silicon carbide nanoparticles with iron and nickel powders was applied to disperse ceramic nanoparticles from their agglomerated form before a semi-solid vortex casting. After casting and solidification, the hot-rolling was utilized and as-cast and rolled samples were exposed to microstructural characterizations. It was obtained that the initial process led to the dispersion of single nanoparticles and sub-micron clusters in a matrix of nickel and iron. Also, it was found that nickel improved the dispersion of silicon carbide nanoparticles in the primary a-Al matrix and a promising dispersion was obtained after solidification and rolling, while the results for the other samples were not promising.

Easy Formation of Functional Liposomes in Water Using a pH‐Responsive Microbial Glycolipid: Encapsulation of Magnetic and Upconverting Nanoparticles

AbstractThe compartmentalization of colloids into topologically closed, vesicular, microphases offers an attractive mean to concentrate a functional cargo in aqueous solutions for a range of biomedical, cosmetic, and biotechnological applications. In this paper, we develop a simple, phospholipid‐free, phase change method employing a pH‐responsive glycolipid. The method is applied to the encapsulation of a sonicated, metastable, aqueous dispersion of functional colloids in the lumen of lipid vesicles: uncoated magnetic maghemite γ‐Fe2O3 and oleic‐acid coated upconverting NaYF4 : Yb/Ln (Ln=Er or Tm) nanoparticles (NPs). We find a stable liposomal dispersion containing a sub‐population of crowded liposomes with high concentrations of NPs. The encapsulated NPs, formed at nearly neutral pH and room temperature, are stable over time and towards extrusion. The vesicular microphase is entirely composed of pH‐responsive glycolipids, which undergo a pH‐mediated mesoscopic structural transition from an open lamellar (2&lt;pH&lt;4) to topologically closed vesicular state (pH&gt;4). We also show that encapsulation successfully works with a stable colloidal aqueous dispersion of iron clusters stabilized in ferritin cages. This compartmentalization approach combining self‐assembly with an orthogonal nonequilibrium dispersion of nanoparticles shows untapped potential for synthesizing unusual classes of mixed matter.

α−Calcitonin gene-related peptide inhibits autophagy and calpain systems and maintains the stability of neuromuscular junction in denervated muscles

ObjectiveAlthough it is well established that a-calcitonin gene-related peptide (CGRP) stabilizes muscle-type cholinergic receptors nicotinic subunits (AChR), the underlying mechanism by which this neuropeptide regulates muscle protein metabolism and neuromuscular junction (NMJ) morphology is unclear. MethodsTo elucidate the mechanisms how CGRP controls NMJ stability in denervated mice skeletal muscles, we carried out physiological, pharmacological, and molecular analyses of atrophic muscles induced by sciatic nerve transection. ResultsHere, we report that CGRP treatment in vivo abrogated the deleterious effects on NMJ upon denervation (DEN), an effect that was associated with suppression of skeletal muscle proteolysis, but not stimulation of protein synthesis. CGRP also blocked the DEN-induced increase in endocytic AChR vesicles and the elevation of autophagosomes per NMJ area. The treatment of denervated animals with rapamycin blocked the stimulatory effects of CGRP on mTORC1 and its inhibitory actions on autophagic flux and NMJ degeneration. Furthermore, CGRP inhibited the DEN-induced hyperactivation of Ca2+-dependent proteolysis, a degradative system that has been shown to destabilize NMJ. Consistently, calpain was found to be activated by cholinergic stimulation in myotubes leading to the dispersal of AChR clusters, an effect that was abolished by CGRP. ConclusionTaken together, these data suggest that the inhibitory effect of CGRP on autophagy and calpain may represent an important mechanism for the preservation of synapse morphology when degradative machinery is exacerbated upon denervation conditions.

Remote and reversible control of in vivo bacteria clustering by NIR-driven multivalent upconverting nanosystems

Achieving remote and reversible control of bacterial cell-cell interactions associated with interference with pathological processes in living systems remains a challenge owing to the complexity of the in vivo microenvironment and the lack of regulation systems. We present, for the first time, the development of a versatile platform to achieve NIR-driven reversible bacterial clustering both in vitro and in vivo. This platform consisted of β-CD modified UCNP (UCNP-CD) and photochromic azobenzene glycoconjugates (azo-man), which could dynamically display d-mannose bioactive ligands. Specifically, by virtue of the noncovalent yet strong multivalent interactions between bacteria and nanosystems, robust bacterial clusters could be formed even in vivo within 1 h. Upon NIR stimulation, the upconverted emissions from UCNPs triggered the continuous isomerization of azo-man, leading to dissociation of the nanosystems and dispersion of bacterial clusters. Moreover, in vivo pathogenic infection process could be interfered with the NIR-switched bacterial agglutination. Most importantly, the noninvasive and deep-tissue-penetrating nature of NIR made it possible for dynamically regulation of cellular interactions with minimized influence to both normal cells and nature bacteria flora. This strategy would bring new perspectives for anti-virulence therapeutics and in-depth investigations of specific physiological phenomena.

The Permutable k-means for the Bi-Partial Criterion

The here applied objective function for clustering consists of two parts, where the first one takes into account intra-cluster relations, and the second – inter-cluster ones. In the case of k -means algorithm, such bi-partial objective function combines cluster dispersions with inter-cluster similarity, to be jointly minimized. The first part only of such objective function provides the “standard” quality of clustering based on distances between objects (the well-known classical k -means). To improve the clustering quality based on the bi-partial objective function, we need to develop the permutable version of k -means algorithm. This paper shows the permutable k -means that appears to be a new type of clustering procedure.

Development of new-generation low-carbon steel: Part II-wear behaviour

ABSTRACTA new-generation unalloyed low-carbon steel (containing 0.1 wt.% C) has been recently developed by the research group of the present corresponding author through incomplete austenitisation-based cyclic ice-brine quenching possessing an exceptionally high strength (UTS = 1.7 GPa) along with elimination of a yield point phenomenon. This is attributed to the evolution of a novel microstructure that consists of fine plate martensite crystals with a dispersion of nano-sized cementite particles and clusters. The present research work is conceived as the Part II of this investigation to establish this new-generation ultrahigh strength low-carbon steel as a unique wear-resistant steel substituting the conventional dual-phase steel along with the readily awaited in-depth correlation between wear mechanism and structural evolution. The wear behaviour of heat-treated steels is investigated against an alumina disc using a pin-on-disc tribometer. The steel subjected to incomplete austenitisation-based cyclic ice-brine quenching exhibits much better wear resistance than conventional dual-phase steel. Dominant microcutting and microploughing abrasion aggravate wear loss, especially at higher load, in dual-phase steel that inherently possesses lower matrix hardness. But, very high-surface hardness is attained in the incomplete austenitisation-based cyclic ice-brine quenched steel by virtue of a significant strain hardening of martensite matrix in between hard nano-sized cementite particles. Besides, the wear rate is not allowed to shoot up even at the highest load through the generation of hard abrasion-resistant tribo-oxide layer of Al2FeO4. This envisages an advent of novel wear-resistant steel as a better substitution for the dual-phase steel.

DG2CEP: a near real-time on-line algorithm for detecting spatial clusters large data streams through complex event processing

Spatial concentrations (or spatial clusters) of moving objects, such as vehicles and humans, is a mobility pattern that is relevant to many applications. Fast detection of this pattern and its evolution, e.g., if the cluster is shrinking or growing, is useful in numerous scenarios, such as detecting the formation of traffic jams or detecting a fast dispersion of people in a music concert. On-Line detection of this pattern is a challenging task because it requires algorithms that are capable of continuously and efficiently processing the high volume of position updates in a timely manner. Currently, the majority of approaches for spatial cluster detection operate in batch mode, where moving objects location updates are recorded during time periods of a certain length and then batch-processed by an external routine, thus delaying the result of the cluster detection until the end of the time period. Further, they extensively use spatial data structures and operators, which can be troublesome to maintain or parallelize in on-line scenarios. To address these issues, in this paper we propose DG2CEP, a parallel algorithm that combines the well-known density-based clustering algorithm DBSCAN with the data stream processing paradigm Complex Event Processing (CEP) to achieve continuous and timely detection of spatial clusters. Our experiments with real-world data streams indicate that DG2CEP is able to detect the formation and dispersion of clusters with small latency while having higher similarity to DBSCAN than batch-based approaches.

Smart elastomeric hydrogel of polyacrylamide containing nanosized barium ferrite and graphene oxide

Smart elastomeric hydrogels based on polyacrylamide containing ferrimagnetic nanoparticles of BaFe12O19 alone or a combination of BaFe12O19 and graphene oxide were synthesized. An improvised sample preparation technique was evolved to design actuators, where the hydrogel samples in rolls form were inserted into cut pieces of hard plastic sleeve in order to fabricate a lab-level actuator. The magneto-responsive actuation behaviour was measured by applying an external magnetic field with the help of a hand-held square type of NdFeB magnet. While the sample containing only 20 wt% BaFe12O19 exhibited only 15 mm deflection at threshold magnetic field of 28 mT, the deflection was significantly enhanced up to 23 mm for the sample containing 1 wt% GO and 20 wt% BaFe12O19 at a threshold magnetic field of 36.7 mT. Up to 20 wt% BaFe12O19, the hydrogels showed a heterogeneous dispersion of large-sized BaFe12O19 clusters and addition of a small percentage, e.g. 1% of GO resulted in significant improvement in the homogeneity of dispersion as well as reduction of the scale of the BaFe12O19 clusters. The saturation magnetization value of the hydrogels was also improved by 50–75% due to the addition of 1 wt% GO with 20 wt% BaFe12O19.

Immobilizing Pd nanoclusters into electronically conductive metal-organic frameworks as bi-functional electrocatalysts for hydrogen evolution and oxygen reduction reactions

Although noble metals, especially Pt and Pt-based materials, are the most efficient catalysts for electrocatalysis, their high cost, low abundance and the strong tendency to aggregate of nanoparticles hinder their further commercial applications. In recent years, metal-organic frameworks (MOFs) have been found to be promising templates for immobilizing nanoclusters (NCs) as advanced catalysts. However, their poor electrical conductivities largely limit their applications in the field of electrochemistry and electrocatalysis. In this study, electrically conductive MOF-74 is chose as template to immobilize tiny Pd NCs in the pores (Pd@MOF-74). Unlike the usually reported MOF-based electrocatalysts, without the post calcination process, the Pd@MOF-74 exhibited excellent electrocatalytic performances for both hydrogen evolution reaction (HER) and oxygen reduction reaction (ORR). Moreover, due to the tiny size and the high dispersion of Pd clusters confined in the MOFs, the loading of noble Pd metal can be largely reduced for the catalysis. Meanwhile, the Pd clusters immobilized in the MOF-74 showed higher long-term durability in both acid and alkaline electrolytes than commercial Pt/C.

Investigation of the magnetic hyperthermia effect in an aqueous dispersion of colloidosomal nanoparticle clusters

The article describes the effect of magnetic hyperthermia under the influence of an oscillating magnetic field acting on the colloidosomal iron oxide nanoparticle clusters with dimensions of <dC> ≅ 100 nm containing magnetite nanoparticles <dP> ≅ 11.8 nm.The experiment was carried out at the magnetic field frequency f = 355 kHz at various amplitude values up to H = 20 kA·m−1. The nature of the heating curves shows that the main mechanism of heating is the effect of magnetic relaxation.The general construction of apparatus generating an oscillating magnetic field is described.The specific loss power (SLP) value was determined in the experiment.