Crystalline Particles Research Articles

Structural, physicochemical, prebiotic properties of guava pulp insoluble dietary fiber and its quality enhancement ability on cow/goat yogurt: Impacts of ultrasound-assisted enzyme treatment

This study explores the effect of ultrasound-assisted cellulase (UE) processing on the structure, functional performance, and prebiotic properties of guava insoluble dietary fiber (RIDF). As the ultrasound exposure time increased (0–40 min), the particle size (from 126.3 μm to 38.7 μm) and crystallinity (from 30.72% to 14.42%) of RIDF significantly decreased, while its soluble carbohydrate content (from 1.40% to 6.17%) and water solubility (from 8.6% to 16.4%) notably increased. These crucial changes suggested the degradation and disorganization of RIDF. Meanwhile, UE-RIDF (modified RIDF) demonstrated a honeycomb network microstructure with a larger surface area, indicating distinct structural and morphological properties compared to RIDF. Consequently, UE-RIDF showed stronger retention/adsorption capacity and improved in vitro prebiotic activity. Interestingly, UE treatment increased RIDF fermentability, leading to additional shifts in its modulation of human fecal microbiota, including a higher abundance of Proteobacteria and Phascolarctobacterium. Furthermore, compared to pure cow/goat yogurt, yogurt fermented with UE-RIDF displayed a lower pH, better stability, and improved texture and rheological properties during a 21-day refrigeration period. These findings highlight the potential application of RIDF as a novel prebiotic active ingredient in fermented foods for the first time, underscoring the critical role of UE treatment in enhancing its performance.

Properties and antibacterial activity of MnFe2O4 nanoparticles obtained by pulsed laser ablation in liquid

In this study, MnFe2O4 nanoparticles (NPs) were fabricated via pulsed laser ablation in liquid. Chemical and structural composition, microstructure, magnetic and antibacterial properties were characterized. Spinel was found as the main crystalline phase, while Fe2O3 and Mn2O3 were observed as the major secondary phases, all identified by X-ray diffractometry (XRD). Observation by Transmission Electron Microscopy (TEM) indicated that most of the nanoparticles were spherical in shape and found in agglomerates, most likely because of their magnetic nature. Moreover, Fast Fourier Transform of selective area electron diffraction patterns pointed at the existence of crystalline particles. The coercive field (Hc) and saturation magnetization (Ms) values determined for these NPs were found to increase with decreasing temperature. Their antibacterial properties were evaluated using the viable bacteria counting technique (colony) for MnFe2O4 concentrations of 100 and 300 μg/mL with Bacillus subtilis, Salmonella typhimurium, Pseudomonas aeruginosa, Klebsiella pneumoniae and Escherichia coli strains.

The role of NLRP3 inflammasome pathway in silicosis-induced pulmonary fibrosis and its prospect as a therapeutic target

Inhalation of crystalline silicon dioxide particles can induce silicosis, and the development of silicosis is closely related to the occurrence and development of pulmonary inflammation and pulmonary fibrosis. NOD-like receptor thermal protein domain associated protein 3 (NLRP3) inflammasome has been established as a major proinflammatory receptor for sensing environmental danger signals. Activation of NLRP3 inflammasomes after phagocytosis of silicon dioxide particles by pulmonary macrophages may be an important mechanism to induce oxidative stress and sustained inflammatory response in the lung. This article summarizes the role of NLRP3 inflammasome in the inflammatory response and pulmonary fibrosis in silicosis, and analyzes it as a potential target for silicosis treatment.

A General Materials Data Science Framework for Quantitative 2D Analysis of Particle Growth from Image Sequences

Phase transformations are a challenging problem in materials science, which lead to changes in properties and may impact performance of material systems in various applications. We introduce a general framework for the analysis of particle growth kinetics by utilizing concepts from machine learning and graph theory. As a model system, we use image sequences of atomic force microscopy showing the crystallization of an amorphous fluoroelastomer film. To identify crystalline particles in an amorphous matrix and track the temporal evolution of the particle dispersion, we have developed quantitative methods of 2D analysis. 700 image sequences were analyzed using a neural network architecture, achieving 0.97 pixel-wise classification accuracy as a measure of the correctly classified pixels. The growth kinetics of isolated and impinged particles were tracked throughout time using these image sequences. The relationship between image sequences and spatiotemporal graph representations was explored to identify the proximity of crystallites from each other. The framework enables the analysis of all image sequences without the requirement of sampling for specific particles or timesteps for various materials systems.

Crystalline-Amorphous Interfaces Engineering of CoO-InOx for Highly Efficient CO2 Electroreduction to CO.

As a fundamental product of CO2 conversion through two-electron transfer, CO is used to produce numerous chemicals and fuels with high efficiency, which has broad application prospects. In this work, it has successfully optimized catalytic activity by fabricating an electrocatalyst featuring crystalline-amorphous CoO-InOx interfaces, thereby significantly expediting CO production. The 1.21%CoO-InOx consists of randomly dispersed CoO crystalline particles among amorphous InOx nanoribbons. In contrast to the same-phase structure, the unique CoO-InOx heterostructure provides plentiful reactive crystalline-amorphous interfacial sites. The Faradaic efficiency of CO (FECO) can reach up to 95.67% with a current density of 61.72mA cm-2 in a typical H-cell using MeCN containing 0.5M 1-Butyl-3-methylimidazolium hexafluorophosphate ([Bmim]PF6) as the electrolyte. Comprehensive experiments indicate that CoO-InOx interfaces with optimization of charge transfer enhance the double-layer capacitance and CO2 adsorption capacity. Theoretical calculations further reveal that the regulating of the electronic structure at interfacial sites not only optimizes the Gibbs free energy of *COOH intermediate formation but also inhibits HER, resulting in high selectivity toward CO.

The Influence of Titanium Dioxide (TiO2) Particle Size and Crystalline Form on the Microstructure and UV Protection Factor of Polyester Substrates.

The inclusion of particles in a polymeric substrate to achieve certain properties is a well-known practice. In the case of textile substrates, this practice may deeply affect the structure of the produced yarns, as even a filament with no textile applications can be obtained. In this manuscript, titanium dioxide (TiO2) particles were incorporated into polyester (PET) chips and the influence of these fillers on the properties of yarn and fabric, and the ultraviolet protection factor (UPF) was assessed. For this purpose, rutile and anatase crystalline forms of TiO2, as well as the size of the particles, were evaluated. Moreover, parameters such as mechanical properties, orientation of the macromolecules and thermal behavior were analyzed to ensure that the textile grade is maintained throughout the production process. The results showed that the inclusion of micro- and nanoparticles of TiO2 decreases the molecular weight and tenacity of PET. Also, although orientation and crystallinity varied during the textile process, the resulting heatset fabrics did not present important differences in those parameters. Finally, the attainment of textile-grade PET-TiO2 fabrics with UPF indexes of 50+ with both rutile and anatase and micro- and nano-sized TiO2 forms was demonstrated.

Divergence among Local Structure, Dynamics, and Nucleation Outcome in Heterogeneous Nucleation of Close-Packed Crystals.

Heterogeneous crystal nucleation is the dominant mechanism of crystallization in most systems, yet its underlying physics remains an enigma. While emergent interfacial crystalline order precedes heterogeneous nucleation, its importance in the nucleation mechanism is unclear. Here, we use path sampling simulations of two model systems to demonstrate that crystalline order in its traditional sense is not predictive of the outcome of the heterogeneous nucleation of close-packed crystals. Consequently, structure-based collective variables (CVs) that reliably describe homogeneous nucleation can be poor descriptors of heterogeneous nucleation. This divergence between structure and nucleation outcome is accompanied by an intriguing dynamical anomaly, wherein low-coordinated crystalline particles outpace their liquid-like counterparts. We use committor analysis, high-throughput screening, and machine learning to devise CV optimization strategies and present suitable structural heuristics within the metastable fluid for CV prescreening. Employing such optimized CVs is pivotal for properly characterizing the mechanism of heterogeneous nucleation in metallic and colloidal systems.

Parallel Processing of Image Databases for Accelerated Morphological Analysis

Nuclear forensics relies on different signatures to identify the source of nuclear material. Such signatures include crystalline structure, chemical composition, and particle morphology. One way to quantify morphology in electron microscope imagery is through image segmentation, where pixels are assigned to several partitions (or groups) that correspond to particles, grains, and other objects of interest within the image. Once pixels are assigned to segments, it is relatively straightforward to quantify other quantities of interest, such as grain size, circularity, etc. However, the range and diversity of microscope images make it difficult to obtain an accurate segmentation automatically. The accuracy of segmentation can be improved through supervised learning, but this requires many images to be manually segmented. Another way to improve the accuracy is to use interactive segmentation. Interactive segmentation requires a human to provide image-specific user input to improve performance. However, the amount of user input (effort) is generally far less than is required for supervised learning. In this paper, we investigate several parallelization strategies to automatically explore the user input parameter space of interactive segmentation algorithms across a large number of images. Specifically, we investigate four different parallelization mechanisms in a high-performance computing (HPC) environment and use the Amdahl fraction to evaluate efficiency on multiple processor cores across multiple nodes. Ultimately, the parallelization strategy that was most efficient utilized the message passing interface integrated with the segmentation and quantification code. This strategy had an Amdahl fraction of 0.985 and a performance of about 0.251 s/image. These results indicate that the parameter space of interactive segmentation algorithms can be efficiently explored using HPC. This opens the door to future work where user input is reduced and where interactive image segmentation algorithms are automatically applied to large image sets.

High-Performance Lithium-Ion Batteries with High Stability Derived from Titanium-Oxide- and Sulfur-Loaded Carbon Spherogels.

This study presents a novel approach to developing high-performance lithium-ion battery electrodes by loading titania-carbon hybrid spherogels with sulfur. The resulting hybrid materials combine high charge storage capacity, electrical conductivity, and core-shell morphology, enabling the development of next-generation battery electrodes. We obtained homogeneous carbon spheres caging crystalline titania particles and sulfur using a template-assisted sol-gel route and carefully treated the titania-loaded carbon spherogels with hydrogen sulfide. The carbon shells maintain their microporous hollow sphere morphology, allowing for efficient sulfur deposition while protecting the titania crystals. By adjusting the sulfur impregnation of the carbon sphere and varying the titania loading, we achieved excellent lithium storage properties by successfully cycling encapsulated sulfur in the sphere while benefiting from the lithiation of titania particles. Without adding a conductive component, the optimized material provided after 150 cycles at a specific current of 250 mA g-1 a specific capacity of 825 mAh g-1 with a Coulombic efficiency of 98%.

Investigating the antibacterial activity of Thyme Oil/TiO2 modified resins against oral pathogenic bacteria

Dental composites lack inherent antimicrobial activity, leading to secondary caries and restoration failure. This study developed a novel thyme oil/TiO2 nanoparticle filler to impart sustainable antibacterial functions to dental resins. TiO2 nanoparticles were synthesized via a sol-gel method and characterized as 20–30 nm crystalline anatase particles. Functionalization with thyme oil was confirmed by FTIR, with 5.8% thyme oil content measured by TGA. Resin disks containing 0.5–2 wt% thyme-TiO2 exhibited significant inhibition zones against S. mutans, L. acidophilus and C. albicans (8–12 mm) compared to thyme oil-free controls (0 mm) (p < 0.05). Thyme-TiO2 at 1–2 wt% showed sustained release of thyme oil over 15 days with bacterial viability reduction of 68–99% compared to unmodified resin (p < 0.05). Resin-dentin microtensile bond strengths were 45–50 MPa for 0.5–2 wt% thyme-TiO2 and not significantly different from control (p > 0.05). Likewise, flexural strength, elastic modulus and surface microhardness values were unchanged with thyme-TiO2 incorporation ≤ 2 wt% (p > 0.05). DPSC viability was > 90% for all resins, indicating good cytocompatibility. Overall, the thyme-TiO2 nanocomposite successfully endowed the dental resin with potent, long-lasting antibacterial effects without compromising key mechanical properties.

Synthesis of phytogenically deposed Ag nanospheres on ZnO nanosheets for photocatalytic and catalytic applications

Current study presents the phytogenic deposition of metallic Ag nanospheres on ZnO nanosheets to produce Ag/ZnO nanostructures using Jacobaea Maritima (Silver Ragwort) plant extract and the prepared materials were tested for the photo-mineralization of methylene blue (MB) dye and catalytic reduction of nitroaromatics i.e. 4-nitroaniline (4-NA) and 4-nitrophenol (4-NP) in the presence of NaBH4 solution. The mean grain size and crystallinity of ZnO particles in Ag/ZnO nanostructures were found to be increased while the particle strain and dislocation density decreased with the elevation of Ag level in ZnO, and band gap energy value was reduced that has improved the photodegradation efficiency for MB dye from 45% to 98.60%, however, an excess amount of Ag has suppressed the photo-activity of Ag/ZnO nanostructures due to increase of band gap value and coverage of ZnO nanocrystals by Ag clusters. The catalytic reduction process indicated that the 4-NA and 4-NP were almost decolorized within 8 and 10 min, respectively. The degradation reaction rate of MB dye was enhanced by ∼7 times for Ag/ZnO nanostructures in comparison to pure ZnO nanosheets. The trapping experiments established that the •O2− and •OH radicals were the key active entities engaged in the deprivation of MB dye.

Enhanced high-rate performance in Zn/Al dual-doped LiMn2O4 with submicron truncated structure

The Jahn-Teller effect and Mn dissolution always restrict the practical electrochemical properties of spinel LiMn2O4 cathode material. Herein, a low-temperature solid-state combustion method is employed to synthesize various truncated octahedral LiZn0.03AlxMn1.97-xO4 (x ≤ 0.08) with submicron structure. The Zn/Al dual-doping is conducive to forming {110} and {100} planes, and is also beneficial to the crystal development of LiMn2O4. It is found that as the amount of Al doping increases, the average particle size gradually decreases from 188 nm to 113 nm. In addition, the Zn/Al co-doping integrated with small particles can improve the high-rate performance. The optimal LiZn0.03Al0.03Mn1.94O4 exhibits submicron truncated octahedral morphology, high crystallinity, and good particles dispersibility. Benefiting from these structure merits, the LiZn0.03Al0.03Mn1.94O4 delivers the first discharge capacity of 113.1 mAh⋅g−1 and low capacity fade of 9.9 % after 300 cycles at 1C. It also shows the high first discharge capacity of 86.6 mAh⋅g−1 at 10C and the high capacity retention of 72.1 % after 2000 cycles. Even at ultrahigh current density of 15C and 20C, the ultralong cycling lifespans over 2000 cycles are also achieved in LiZn0.03Al0.03Mn1.94O4 cathode material. The excellent electrochemical properties are ascribed to its relatively high Li+ diffusion coefficient (1.60 × 10−11 cm2⋅s−1) and low apparent activation energy (25.45 kJ⋅mol−1) during the de-intercalation process. The Zn/Al dual-doping and submicron truncated octahedron designs of the LiMn2O4 provide a scientific reference to prepare high-performance cathode materials.

Redistribution of dopants between amorphous and crystalline phases in ZrO2–SiO2 nanoceramics

AbstractExtensive efforts have been devoted to investigate the distribution of dopants in ceramics. However, one critical question remained barely explored, which is the redistribution of dopants between amorphous and crystalline phases during fast sintering of ceramics. Here we address this gap by observing the redistribution of five selected dopants (Y, Ce, Yb, Hf, and Ta) in ZrO2–SiO2 nanoceramics during sintering. We designed two groups of experiments: In group one, dual‐phase amorphous particles were sintered with multicomponent crystalline ones. The former particles were ZrO2–SiO2 glass, whereas the latter ones consisted of ZrO2 solid‐solution nanocrystallites (SSNCs) embedded in an oxide glass containing Zr, Si, Y, Ce, Hf, Yb, and Ta. In group two, dual‐phase crystalline particles were sintered with multicomponent amorphous ones. The former particles were composed of ZrO2 nanocrystallites (NCs) embedded in an amorphous SiO2 matrix, whereas the latter ones were oxide glass containing Zr, Si, Y, Ce, Hf, Yb, and Ta. Redistribution of the dopants from the glass to ZrO2 NCs occurred in the two groups, that is, the five dopants migrated from the glass matrix into the ZrO2 NCs, forming ZrO2 SSNCs. The redistribution of the dopants not only increased the configuration entropy of the ZrO2 NCs but also benefited the network structure integrity of SiO2 glass. The dopant redistribution process was driven by the minimization of the studied material's free energy. The reported results are important for understanding the redistribution behaviors of dopants and are expected to provide new insights to design new ceramics via the multielement co‐doping strategy.

Investigating the effect of process variables for ball milling of wood chips: energy demand and particle size

AbstractEnergy demand is the major drawback to using mechanical treatments within the biorefinery context. These treatments use energy to reduce particle size and crystallinity and, as a result, increase the accessibility of cellulose. However, the study of energy demand in milling needs to be more noticed. Therefore, this study aims to study how operational variables affect particle size and energy demand on one of the most used milling technologies: ball milling. The variables considered were mass of biomass, mass of balls and time. It was found that time is the most affecting variable for particle size and energy demand. Additionally, it was possible to optimise milling regarding energy demand and particle size. Furthermore, it was found that from the three traditional laws of comminution Bond was the one that gave the best results in terms of accuracy.

A synergistic approach to improving antifouling and antibacterial properties of Ag/DBR/PES membrane

In this study, a novel approach was employed to address the persistent challenge of biofouling in membrane-based separation processes. The method involved enhancing the antifouling and antibacterial properties of polyethersulfone (PES) membranes through the incorporation of dragon's blood resin (DBR) and silver nanoparticles (AgNPs). Four types of membranes with different compositions were prepared and subjected to various characterization including antibacterial test. The introduction of silver coating (M-DB/Fe/Ag) led to an increase in hydrophilicity of the membrane, which changed to higher permeability and very good humic acid rejection (R: 98.32 %) and flux recovery ratio (FRR: 95.87 %). SEM analysis revealed the presence of crystalline particles, indicating a successful Ag coating, followed by a stable negative charge on the membrane surface. Among the prepared membranes, only M-DB/Fe/Ag exhibited antibacterial activity against E. coli with an inhibition zone diameter of 9.46 mm. Based on its anti-biofouling properties, the results have significant potential for various applications.

Compatibility and interaction between C6F12O[sbnd]N2 gas mixture and sealing rubber materials

The C6F12O gas mixture has good insulating properties and can replace the strong greenhouse gas sulfur hexafluoride (SF6) in power equipment. To ensure the safe operation of the equipment, the compatibility between the C6F12O/N2 gas mixture and commonly sealing rubber materials Ethylene-Propylene-Diene Monomer (EPDM), Nitrile Butadiene Rubber (NBR), and Fluororubber (FKM)) is an important factor. In this paper, the compatibility between the C6F12O/N2 gas mixture and rubber materials at different temperatures is studied. Moreover, the free volume fraction, diffusion coefficient, and radial distribution function are calculated. It is found that there exists a chemical reaction between the C6F12O/N2 gas mixture and rubbers, which leads to the appearance of folds or crystalline particles and the accumulation of a large number of F elements on the surface of NBR and EPDM. The simulation results show that the diffusion of the C6F12O/N2 gas mixture in the rubber is enhanced with the increase of temperature, and the diffusion coefficient of C6F12O in NBR is the largest, reaching 33.439 × 10−11m2/s. The experimental and theoretical results show that compatibility between the C6F12O/N2 gas mixture and FKM is better. FKM will have a better application prospect in C6F12O/N2-containing power equipment.

Statistical approach to design Zn particle size, shape, and crystallinity for alkaline batteries

Statistical approach to design Zn particle size, shape, and crystallinity for alkaline batteries

Green and shape-tunable synthesis of ellagic acid crystalline particles by tannic acid for neuroprotection against oxidative stress.

Oxidative stress (OS) plays an important role in the emergence and prevention of neurodegenerative diseases, such as Alzheimer's disease (AD). Excess reactive oxygen species (ROS) accumulated in a neuronal cell can lead to OS, producing cell injury and death. Seeking nanoantioxidants against AD-related oxidative stress has attracted a lot of attention, especially those potential antioxidant agents derived from natural polyphenols. However, the transformation of abundant plant polyphenols to antioxidative biomaterials against OS is still challenging. In this work, we report a new method to transform amorphous tannic acid (TA) into tailorable shaped ellagic acid (EA) crystalline particles without using an organic solvent. EA crystalline particles were generated from TA, which underwent a chemical transformation, in situ metal phenolic coordination and acid-induced assembly process, and the size and shape could be controlled by varying the amount of acid. As-prepared EA crystalline particles showed excellent stability in water and lysosomal mimicking fluid and possess unique fluorescence properties and a strong response in mass spectrometry, which is beneficial for their imaging analysis in cells and tissues. More importantly, EA particles have shown significant H2O2-related ROS scavenging ability, a high cellular uptake capacity, an excellent neuroprotective effect in PC12 cells, a high drug loading capacity and BBB permeability to enter the brain. Our study suggested that the EA crystalline particles show great potential for OS-mediated AD treatment.

Effect of CeO2 support structure on the catalytic performance of ammonia synthesis in an electric field at low temperatures.

Ammonia is an extremely important storage and transport medium for renewable energy, and technology is expected to produce it on demand and onsite using renewable energy. Applying a DC (direct current) to a solid catalyst layer with semiconducting properties makes ammonia synthesis highly efficient, even at low temperatures (approximately 400 K). In this process, oxide supports with semiconducting properties play important roles as metal supports and conduction fields for electrons and protons. The influence of the degree of particle aggregation on the support properties and ammonia synthesis using an electric field was evaluated for CeO2, which is the best material for this purpose because of its semiconducting properties. The results showed that controlling the aggregation structure of the crystalline particles could significantly influence the surface conductivity of protons and electrons; thus, the activity could be largely controlled. The Ru-CeO2 interaction could also be controlled by changing the crystallinity, which suppressed the aggregation of the supported Ru and significantly improved the ammonia synthesis activity using an electric field at low temperatures.

Optimum pyrolysis conditions to prepare the most crystalline boron carbide powder from boric acid-mannitol complex ester.

A weak acidic complex ester (CE) in solid form was prepared by a condensation reaction between very weak boric acid (BA: H3BO3) and (D)-mannitol (MA: C6H14O6) by the molar ratio of BA/MA = 2. A boron carbide (B4C) precursor was obtained from heating of the CE at 400 °C for 4 h. The precursor was pyrolyzed under argon flow in the interval of 1300-1550 °C for 4 h and at 1400 °C for 1-4 h, respectively. The materials were examined using several techniques such as X-ray diffraction analysis, thermal analysis, scanning electron microscopy, particle size distribution, and nitrogen adsorption/desorption. The optimum pyrolysis temperature and duration were 1400 °C and 4 h, respectively. The most crystalline B4C particles were distributed between 1 and 100 μm with a mean particle size of 20 μm. The specific surface area and specific pore volume were 13.5 m2 g-1 and 0.09 cm3 g-1, respectively. The size of the pores was between 2 and 36 nm with a mean size of 14 nm.