Composition Fluctuations Research Articles

A co-doping strategy to achieve high energy storage performance in BiFeO3-based ceramics

In this work, (Bi0.65-0.65xBa0.35-0.35xNdx)(Fe0.65-0.65xTi0.35-0.35xNbx)O3+x (abbreviated as: BFBT-xNN, x = 0, 0.04, 0.08 and 0.12) ceramics were fabricated through a solid-state reaction method, aiming to obtain high-performance capacitor materials. BFBT ceramics have attracted increasing attention as potential energy storage materials because of their excellent dielectric and ferroelectric properties. However, two handicaps limit the large improvement of their energy storage performance (ESP). One is the large hysteresis of their polarization (P)-electric field (E) loops; the other is the low dielectric breakdown strength (Eb), which has a close correlation with the inevitable defects present in BF-based ceramics. Herein, we designed a co-doping strategy to overcome the two handicaps in order to achieve high ESP in BFBT ceramics. In this strategy, the trivalent rare earth Nd3+ ions and high valence Nb5+ ions are simultaneously introduced at the perovskite A- and B-sites of BFBT ceramics, which is called NN co-doping. The NN co-doping enhances the relaxor properties of BFBT ceramics due to the enhanced composition and charge fluctuations and promotes the formation of the Bi-rich phases, which contribute to the appearance of a slim P-E loop. Meanwhile, the Eb of BFBT ceramics is enhanced, which is ascribed to the significantly decreased oxygen vacancy concentration, the reduced grain size and the Bi-rich phases. Benefitting from these factors, a high recoverable energy storage density (Wrec) of 3.64 J/cm3 and energy storage efficiency (η) of 88% are simultaneously obtained under an enhanced Eb of 330 kV/cm in BFBT-0.08NN ceramics. Moreover, the ESP of BFBT-0.08NN ceramics shows good thermal stability (30–150 °C) and charge-discharge properties. These results indicate that BFBT-0.08NN ceramics could be a promising capacitor material.

Valorisation of bakery waste via the bioethanol pathway

Bakery waste is a stream that is generated in enormous quantities globally and thus poses a significant environmental problem. Furthermore, the increasing use of fossil fuels necessitates the development of alternate energy sources. In an effort to meet the EU circularity goals, in this study, a holistic method to address these issues is proposed; producing bioethanol from bakery waste. Bakery waste that was collected from local bakeries and cafeterias was utilized as feedstock. Two fermentation modes were studied in laboratory scale by applying factorial design; separate hydrolysis and fermentation and simultaneous saccharification and fermentation. For the separate hydrolysis and fermentation trials, the ethanol yield reached was almost 100% for 20 μLgstarch−1 enzyme loading and 20% solid loading at 35°C, whereas the highest ethanol yield for simultaneous saccharification and fermentation was 95% for 20 μLgstarch−1 enzyme loading and 20% solid loading. Even though a small difference in the yield was observed between the two fermentation modes, simultaneous saccharification and fermentation is beneficial in terms of technoeconomics. Furthermore, it was established that the valorisation of bakery waste for the production of bioethanol is technically viable, even at the pilot scale, as 100 gL−1 of ethanol after 31 h in a 200 L bioreactor under the optimum conditions was observed. Nevertheless, to evaluate the process feasibility, other techno-economical factors of the entire value chain must also be taken into account. These include fluctuations in the bakery waste composition, collection of bread residues as well as recovery and purification of ethanol.

Plasticity in irradiated FeCrAl nanopillars investigated using discrete dislocation dynamics

In this paper, we investigate plasticity in irradiated FeCrAl nanopillars using discrete dislocation dynamics simulations (DDD), with comparisons to transmission electron microscopic (TEM) in situ tensile tests of ion- and neutron-irradiated commercial C35M FeCrAl alloy. The effects of irradiation-induced defects, such as a/2<111> and a<100> type loops and composition fluctuations representative of phase separation in irradiated FeCrAl alloys, are investigated separately as well as superposed together in simulations. We explore the effects of defects on the stress-strain behavior, specifically yield strength and hardening response, of FeCrAl nanopillars. Our simulations confirm the widely accepted fact that irradiated alloys exhibit a stress-strain response with higher yield strength as compared to unirradiated alloys. However, our DDD calculations reveal an atypical superposition of the hardening contributions due to composition inhomogeneity and irradiation loops wherein composition inhomogeneity annihilates the hardening due to irradiation loops at small scales. As a result, we observe that the yield strength in irradiated alloys, after taking into consideration the effects of both composition inhomogeneity and irradiation loops, is smaller than the yield strength of the alloys with only irradiation loops and is approximately same for the alloy with composition inhomogeneity alone. This is referred to as “destructive interference” between the hardening contributions due to composition fluctuations and irradiation loops in the paper. We also identify this destructive interference in the superposition in our parallel TEM in situ tensile tests on unirradiated, ion-irradiated, and neutron-irradiated C35M FeCrAl alloy. This destructive interference in the hardening contributions contrasts with the dispersed barrier hardening (DBH) models widely utilized by the experimental community to model the hardening contributions due to different irradiation induced defects. The effects of the loading orientations on the yield strength and hardening are investigated and the mechanisms for the hardening in irradiated FeCrAl alloys are also reported.

Integrated Computing Accelerates Design and Performance Control of New Maraging Steels.

This paper mainly used database technology, machine learning, thermodynamic calculation, experimental verification, etc., on integrated computational materials engineering. The interaction between different alloying elements and the strengthening effect of precipitated phases were investigated mainly for martensitic ageing steels. Modelling and parameter optimization were performed by machine learning, and the highest prediction accuracy was 98.58%. We investigated the influence of composition fluctuation on performance and correlation tests to analyze the influence of elements from multiple perspectives. Furthermore, we screened out the three-component composition process parameters with composition and performance with high contrast. Thermodynamic calculations studied the effect of alloying element content on the nano-precipitation phase, Laves phase, and austenite in the material. The heat treatment process parameters of the new steel grade were also developed based on the phase diagram. A new type of martensitic ageing steel was prepared by selected vacuum arc melting. The sample with the highest overall mechanical properties had a yield strength of 1887 MPa, a tensile strength of 1907 MPa, and a hardness of 58 HRC. The sample with the highest plasticity had an elongation of 7.8%. The machine learning process for the accelerated design of new ultra-high tensile steels was found to be generalizable and reliable.

The diurnal fluctuation of colonic antibiotic resistome is correlated with nutrient substrates in a pig model

The increasing prevalence of antimicrobial resistance (AMR) poses a significant threat to public health, and the gut microbiota of livestock (e.g., pigs) are considered a crucial reservoir of antibiotic resistance genes (ARGs), contributing to the long-term persistence of AMR. However, there is still a lack of relevant research on the composition and diurnal fluctuation of ARGs, and their correlation with nutrient substrates in the gut of pigs. To address this knowledge gap, we characterized the antibiotic resistome structure, and circadian oscillations in 45 colonic metagenomically sequenced samples, covering 9-time points within 24 h, from growing pigs. We identified 227 unique types of ARGs, which belonged to 35 drug resistance classes. Tetracycline resistance and antibiotic target protection were the most enriched class and mechanism of drug resistance in colon samples, respectively. The relative abundance of ARGs fluctuated over time within 24 h, with the total abundance peaking at T21 (sampling time at 21:00 p.m.) and the total numbers reaching the peak at T15. A total of 70 core ARGs were identified, which contributed to 99 % of all ARGs. Rhythmicity analysis revealed that 50 out of 227 ARGs and 15 of 49 mobile genetic elements (MGEs) exhibited rhythmic patterns. TetW was the most abundant ARG with circadian rhythm frequently found in Limosilactobacillus reuteri. The concentration of ammonia nitrogen in the colon was significantly correlated with the host genera of rhythmic ARGs. Partial least squares path modeling (PLS-PM) analysis indicated that rhythmic ARGs were significantly correlated with bacterial community, MGEs, and colonic ammonia nitrogen. This study provides new insight into the diurnal fluctuation of ARG profiles in the colon of growing pigs, which was likely driven by the dynamic change of the availability of colonic nutrients substrates.

Fluctuations in Gut Microbiome Composition During Immune Checkpoint Inhibitor Therapy.

Immune checkpoint inhibitors (ICIs) such as programmed cell death protein-1 (PD-1) inhibitors or PD-1 ligand-1 (PD-L1) inhibitors have led to remarkable improvement in outcomes of non-small cell lung cancer (NSCLC). Unfortunately, the significant benefits of ICI therapy are frequently limited by resistance to treatment and adverse effects, and the predictive value of pre-treatment tumor tissue PD-L1 expression is limited. Development of less invasive biomarkers that could identify responders and non-responders in early on-treatment could markedly improve the treatment regimen. Accumulating evidence suggests that baseline gut microbiota profile is associated with response to PD-1/PD-L1 blockade therapy. However, change in the gut microbiome composition during PD-1/PD-L1 blockade therapy and its relation to response remain unclear. Here, we analyzed pre- and on-treatment fecal samples from five NSCLC patients receiving anti-PD-1 immunotherapy, alone or in tandem with chemotherapy, and performed 16S rRNA sequencing. The overall alpha diversity of the baseline gut microbiome was similar between three responders and two non-responders. While the gut microbiome composition remained stable overall during treatment (R2 = 0.145), responders showed significant changes in microbiome diversity between pre- and on-treatment samples during anti-PD-1 therapy compared to non-responders (P = 0.0274). Within the diverse microbiota, responders showed decreases in the abundance of genera Odoribacter, Gordonibacter, Candidatus Stoquefichus, Escherichia-Shigella, and Collinsella, and increase in abundance of Clostridium sensu stricto 1. In contrast, non-responders demonstrated on-treatment increases in genera Prevotella, Porphyromonas, Streptococcus, and Escherichia-Shigella, and decrease in abundance of Akkermansia. This pilot study identified a substantial change in gut microbiome diversity between pre- and on-treatment samples in NSCLC patients responding to anti-PD-1 therapy compared to non-responders. Our findings highlight the potential utility of gut microbiota dynamics as a noninvasive biomarker to predict response to PD-1/PD-L1 blockade therapy for a wide variety of malignancies, which sets a path for future investigation in larger prospective studies.

Quantification of metabolic niche occupancy dynamics in a Baltic Sea bacterial community.

Progress in molecular methods has enabled the monitoring of bacterial populations in time. Nevertheless, understanding community dynamics and its links with ecosystem functioning remains challenging due to the tremendous diversity of microorganisms. Conceptual frameworks that make sense of time series of taxonomically rich bacterial communities, regarding their potential ecological function, are needed. A key concept for organizing ecological functions is the niche, the set of strategies that enable a population to persist and define its impacts on the surroundings. Here we present a framework based on manifold learning to organize genomic information into potentially occupied bacterial metabolic niches over time. Manifold learning tries to uncover low-dimensional data structures in high-dimensional data sets that can be used to describe the data in reduced dimensions. We apply the method to re-construct the dynamics of putatively occupied metabolic niches using a long-term bacterial time series from the Baltic Sea, the Linnaeus Microbial Observatory (LMO). The results reveal a relatively low-dimensional space of occupied metabolic niches comprising groups of taxa with similar functional capabilities. Time patterns of occupied niches were strongly driven by seasonality. Some metabolic niches were dominated by one bacterial taxon, whereas others were occupied by multiple taxa, depending on the season. These results illustrate the power of manifold learning approaches to advance our understanding of the links between community composition and functioning in microbial systems. IMPORTANCE The increase in data availability of bacterial communities highlights the need for conceptual frameworks to advance our understanding of these complex and diverse communities alongside the production of such data. To understand the dynamics of these tremendously diverse communities, we need tools to identify overarching strategies and describe their role and function in the ecosystem in a comprehensive way. Here, we show that a manifold learning approach can coarse grain bacterial communities in terms of their metabolic strategies and that we can thereby quantitatively organize genomic information in terms of potentially occupied niches over time. This approach, therefore, advances our understanding of how fluctuations in bacterial abundances and species composition can relate to ecosystem functions and it can facilitate the analysis, monitoring, and future predictions of the development of microbial communities.

Multi-scale investigation of short-range order and dislocation glide in MoNbTi and TaNbTi multi-principal element alloys

Refractory multi-principal element alloys (RMPEAs) are promising materials for high-temperature structural applications. Here, we investigate the role of short-range ordering (SRO) on dislocation glide in the MoNbTi and TaNbTi RMPEAs using a multi-scale modeling approach. Monte carlo/molecular dynamics simulations with a moment tensor potential show that MoNbTi exhibits a much greater degree of SRO than TaNbTi and the local composition has a direct effect on the unstable stacking fault energies (USFEs). From mesoscale phase-field dislocation dynamics simulations, we find that increasing SRO leads to higher mean USFEs and stress required for dislocation glide. The gliding dislocations experience significant hardening due to pinning and depinning caused by random compositional fluctuations, with higher SRO decreasing the degree of USFE dispersion and hence, amount of hardening. Finally, we show how the morphology of an expanding dislocation loop is affected by the applied stress.

Effects of aluminum and oxygen additions on quenched-in compositional fluctuations, dynamic atomic shuffling, and their resultant diffusionless isothermal [formula omitted] transformation in ternary Ti–V-based alloys with bcc structure

Diffusionless isothermal ω transformation is a recently discovered ω transformation that occurs isothermally during aging near room temperature in Ti alloys with a bcc (β-phase) structure. Unlike conventional displacive phase transitions, the diffusionless isothermal ω transformation occurs in locally unstable nanoscale β-phase regions formed by quenched-in statistical compositional fluctuations. In the present study, the effects of Al and oxygen additions in ternary β-phase Ti–V-based alloys on the diffusionless isothermal ω transformation and its attempt process, called dynamic atomic shuffling, were studied. Elastic constant and internal friction measurements for Ti–16.6V–2.1Al and Ti–17.5V–2.5O (at.%) alloy single crystals and analysis of quenched-in compositional fluctuations using the thermodynamic theory of fluctuations indicated that the oxygen addition increases the β-phase stability, and it selectively increases the activation energy of dynamic atomic shuffling in locally unstable Ti-rich regions, which is caused by the strong attractive interaction between Ti and oxygen elements. As a result, oxygen addition suppresses the diffusionless isothermal ω transformation that occurs during aging at 298 K. In contrast, low β-phase stability, which promotes ω-phase nucleation, is retained by Al addition. Furthermore, dynamic atomic shuffling with a low activation energy is retained even though the average activation energy is enhanced by the Al addition, originating from the relatively weak atomic interaction between Ti and Al. Therefore, the diffusionless isothermal ω transformation cannot be suppressed by Al addition.

Chemical Diversity and Redox Values Change as a Function of Temporal Variations of the Essential Oil of a Tropical Forest Shrub

This study investigated the chemical phenotypical variability of Piper lhotzkyanum Kunth (Piperaceae), a shrub found in Brazilian tropical forests, over time (different periods of the day and seasons) and under natural conditions. For this, essential oils (EOs) from the leaves were collected in different seasons and times of the day and analyzed by gas chromatography coupled with mass spectrometry, and gas chromatography coupled with a flame ionization detector. The indices were applied to evaluate the chemical diversity as well as the dynamics of redox of the mixtures. The results showed that the EOs were dominated by non-oxygenated sesquiterpenes, with β-elemene, E-caryophyllene, and α-zingiberene being the main compounds identified in all collections. Temporal and seasonal analyses revealed important fluctuations in the chemical composition, redox, and chemical diversity indices of the species. A correlation between climatic factors and the variation in redox and chemical diversity was observed, highlighting the chemical phenotypic plasticity P. lhotzkyanum. This study resolves a previously unanswered question by confirming that natural light does not produce interconversion of major compounds. The adaptation capacity of this species to the environmental changes suggests new cultivation strategies to maximize the quality of EO and promote a more sustainable future in partnership with nature.

Prediction Of Combustion Driven Oscillation In A Residential Ultra-Low NOx Gas Furnace Product Using A Positive Feedback Stability Model

Combustion oscillation is a very common phenomena in many unsteady or transient HVAC applications (e.g., start-up operation). Combustion driven oscillations can occur once the sound (thermo-acoustically driven) is reflected from the combustion chamber back into the mixture supply region (and propagate even further upstream). The reflected sound causes a fluctuation in inlet mixture composition or mixture flow. In either cases, the equivalence ratio is changed and consequently the amount of heat release changes. This phenomenon could easily trap the combustion process in a loop that can easily result in combustion oscillations with higher amplitude. It can also produce unwanted transient noise tones and can raise NOx emission levels. The current work is aimed at providing a simulation model for diagnosing and preventing combustion driven oscillation using a modified positive feedback loop. This feedback loop is developed using upstream/downstream impedances (obtained from low-order acoustic simulations), and a flame transfer function. The value-add of this study (model-based approach) is that it can help design engineers to reduce the number of test iterations and optimize the design.

Kinetics and mechanism of light-induced phase separation in a mixed-halide perovskite

•Utilized in situ cryoelectron-microscopy-cathodoluminescence spectroscopy •Observed the morphological and band-gap evolution of iodide-rich clusters in situ •Performed quantitative studies of the characteristic length scale of phase separation •Phase field modeling prediction is consistent with spinodal decomposition Halide ion phase separation is a barrier to the application of mixed-halide perovskites whereby the presence of large populations of photogenerated or injected carriers causes undesirable changes in the local band gap. We investigate the mechanism of phase separation in CsPbIxBr3-x perovskite single crystals driven by light. The phase separation process and its dynamics are visualized at the nanometer scale at cryogenic temperatures using in situ scanning transmission electron microscopy and cathodoluminescence. Combined with phase field modeling, which accounts for the coupling between electronic and chemical driving forces, our observations point to a spinodal decomposition mechanism in which both the amplitude of composition fluctuation and the characteristic length scale grow non-linearly with time. Our findings provide microscopic insights that can assist in further engineering mixed-halide perovskites either for stability or for intentional programming of the local halide ion composition, opening pathways to a wide range of applications. Halide ion phase separation is a barrier to the application of mixed-halide perovskites whereby the presence of large populations of photogenerated or injected carriers causes undesirable changes in the local band gap. We investigate the mechanism of phase separation in CsPbIxBr3-x perovskite single crystals driven by light. The phase separation process and its dynamics are visualized at the nanometer scale at cryogenic temperatures using in situ scanning transmission electron microscopy and cathodoluminescence. Combined with phase field modeling, which accounts for the coupling between electronic and chemical driving forces, our observations point to a spinodal decomposition mechanism in which both the amplitude of composition fluctuation and the characteristic length scale grow non-linearly with time. Our findings provide microscopic insights that can assist in further engineering mixed-halide perovskites either for stability or for intentional programming of the local halide ion composition, opening pathways to a wide range of applications.

Effect of Chemical Composition on Molecular Mobility and Phase Coupling in Poly(3-hydroxybutyrate-co-3-hydroxyvalerate) and Poly(3-hydroxybutyrate-co-3-hydroxyhexanoate) with Different Comonomer Contents

Two series of poly (3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBHV) and poly (3-hydroxybutyrate-co-3-hydroxyhexanoate) (PHBHHx) with different amounts of hydroxyvalerate (HV) and hydroxyhexanoate (HHx) units are compared. The influence of chemical composition on the molecular mobility in quenched samples is discussed, as well as the consequences on the aptitude to crystallize and the microstructures developed during cold-crystallization. In both quenched PHBHV and PHBHHx, $$T_g$$ decreases as the content of comonomer unit increases. The HHx units (propyl side-groups) are better molecular spacers and produce a stronger $$T_g$$ shift as compared to the HV units (ethyl side-groups). Copolymerization has no striking effect on the width of the glass transition and the cooperativity length in quenched samples, but in cold-crystallized samples the glass transition is dramatically broadened. When the fully amorphous copolymers are heated from the glassy state to room temperature, crystallization occurs but is largely disrupted, suggesting that the molecular environment in the amorphous phase is significantly changed. The HHx units, which are excluded from the host crystals, delay and slow down the crystallization kinetics in a stronger way as compared to the HV units, which can partially co-crystallize. The obtained crystalline phases are prone to reorganization and the residual amorphous phases appear to have strong differences in composition and large density fluctuations. A practical consequence is that microstructures with different coupling between phases, and thus different properties and stability over time, can be obtained by controlling the nature and content of the comonomer units.

Kinetic relaxation of giant vesicles validates diffusional softening in a binary lipid mixture.

The stiffness of biological membranes determines the work required by cellular machinery to form and dismantle vesicles and other lipidic shapes. Model membrane stiffness can be determined from the equilibrium distribution of giant unilamellar vesicle surface undulations observable by phase contrast microscopy. With two or more components, lateral fluctuations of composition will couple to surface undulations depending on the curvature sensitivity of the constituent lipids. The result is a broader distribution of undulations whose complete relaxation is partially determined by lipid diffusion. In this work, kinetic analysis of the undulations of giant unilamellar vesicles made of phosphatidylcholine-phosphatidylethanolamine mixtures validates the molecular mechanism by which the membrane is made 25% softer than a single-component one. The mechanism is relevant to biological membranes, which have diverse and curvature-sensitive lipids.

Correlation between Magnetocaloric Properties and Magnetic Exchange Interaction in Gd54Fe36B10-xSix Amorphous Alloys.

Gd54Fe36B10-xSix (x = 0, 2, 5, 8, 10) amorphous ribbons were fabricated by melt-spinning technique. Based on the molecular field theory, the magnetic exchange interaction was analyzed by constructing the two-sublattice model and deriving the exchange constants JGdGd, JGdFe and JFeFe. It was revealed that appropriate substitution content of Si for B can improve the thermal stability, maximum magnetic entropy change and widened table-like magnetocaloric effect of the alloys, while excessive Si will lead to the split of the crystallization exothermal peak, inflection-like magnetic transition and deterioration of magnetocaloric properties. These phenomena are probably correlated to the stronger atomic interaction of Fe-Si than that of Fe-B, which induced the compositional fluctuation or localized heterogeneity and then caused the different way of electron transfer and nonlinear variation in magnetic exchange constants, magnetic transition behavior and magnetocaloric performance. This work analyzes the effect of exchange interaction on magnetocaloric properties of Gd-TM amorphous alloys in detail.

A comprehensive approach to crystallization sequence in novel MgO/CaO-Al2O3-SiO2 glass-ceramics by Ostwald's step rule and composition fluctuation model

An understanding of the crystallization sequence (the formation order of crystalline phases) of glasses is crucial for the processing and composition design of novel glass-ceramics. A comprehensive approach to the crystallization sequence in novel MgO/CaO-Al2O3-SiO2 (MAS/CAS) glass-ceramics was performed from the Ostwald's step rule and the model of the distribution of nanoscale composition fluctuations (DNCF) for the first time. The stoichiometric cordierite Mg2Al4Si5O18 glass exhibits the crystallization sequence predicted by the Ostwald's step rule and a narrow DNCF model, i.e., metastable β-quartz solid solutions (β-QSSs) → high-temperature type indialite → low-temperature type α-cordierite. A broad DNCF model was proposed to present in osumilite Mg2Al4Si11O30 and pyrope Mg3Al2Si3O12 glasses, resulting in the initial formation of β-QSSs or forsterite 2MgO.SiO2 prior to α-cordierite formation. The crystallization sequence in stoichiometric anorthite CaAl2Si2O8 glass was also understood along the Ostwald's step rule and a narrow DNCF model. The importance of nanoscale composition fluctuations, in particular the formation of MgO/CaO-rich fragile regions, was emphasized in the crystallization of MAS and CAS-based glasses having strong Al-O-Si linkages between AlO4 and SiO4 tetrahedra. The present article will contribute to the comprehensive design of new innovative aluminosilicate-based glass-ceramics.

Relation between thermal quenching of photoluminescence and negative capacitance on InGaN/GaN multiple quantum wells in p-i-n structure

Temperature-dependent photoluminescence (PL) and surface photovoltage (SPV) measurements were carried out to detect radiative and non-radiative transitions on InGaN/GaN quantum well (QW) blue light-emitting device (LED). The emissions, peaking at 3.03 eV and 2.89 eV, were present in both PL and SPV spectrum and shifted with the temperature in a decrease-increase-decrease manner; the so-called S-shaped behavior between 30-150 K. Remarkably, the shift continued with an increase in energy (blue shift) and finally saturated for a temperature above 150 K. The first variation below 150 K was explained by the composition fluctuation of In atom in the InGaN MQW layer. In contrast, the second significant shift in peak energy was caused to the localization effect, around 60 meV. The degree of localized (σ) value agreed with the activation energy of thermal quenching of PL intensity. A strong localization effect was also attributed to the sub-bandgap trap level in the quantum well and originated negative capacitance in admittance spectroscopy measurement.

Intervention time modified the effect of inulin on high‐fat diet‐induced obesity and gut microbial disorders

AbstractVarious epidemiological studies support that inulin improves the intestinal environment and decreases the risk of obesity. The same as host feeding rhythms, gut microbiota itself displays daily fluctuations in composition and function. The purpose of this study was to investigate the influences of intervention time of inulin to alleviate high‐fat diet (HFD)‐induced obesity based on chrono‐nutrition. Male C57BL/6J mice were given HFD and gavaged inulin at light‐on time (HFM) or light‐off time (HFN) daily. Energy expenditure (EE), 16S rRNA sequencing in colonic contents, and short‐chain fatty acids (SCFAs) analysis were carried out after 12 weeks. Both in HFM and HFN group, the HFD‐induced weight gain was significantly reduced by 20.91% and 23.32%, and the mice in HFN group showed no significant difference in weight gain with the control group. Besides, mice in HFN group showed a tendency to increase EE and fecal SCFAs contents in addition to the relative content of colonic beneficial bacteria. As the light‐off period of mice is their active period, these results suggested that inulin intake at active period exhibited relatively stronger effects on ameliorating obesity and improving the gut microbial environment.

Flowsheet modelling of a powder continuous feeder-mixer system

In this study, an integrated flowsheet model of the continuous feeder-mixer system was calibrated, simulated and compared against experimental data. The feeding process was first investigated using two major components (ibuprofen and microcrystalline cellulose (MCC)), in a formulation comprised of: 30 wt% of ibuprofen, 67.5 wt% MCC, 2 wt% of sodium starch glycolate and 0.5 wt% of magnesium stearate. The impact of a refill on feeder performance was experimentally evaluated for different operating conditions. Results showed that it had no influence on feeder performance. While simulations with the feeder model fairly reproduced the material behaviour observed in the feeder, unintended disturbances were underpredicted due to the model’s low complexity. Experimentally, mixer’s efficiency was assessed based on ibuprofen residence time distribution. Mean residence time pointed to a higher mixer’s efficiency at lower flow rates. Blend homogeneity results showed that for the entire set of experiments, ibuprofen RSD < 5%, irrespective of process variables. A feeder-mixer flowsheet model was calibrated, after regressing the axial model coefficients. The regression curves exhibited a R2 above 0.96, whereas the RMSE varied from 1.58x10-4 to 1.06x10-3 s−1 across all fitted curves. Simulations confirmed that flowsheet model captured the powder dynamics inside the mixer and qualitatively predicted the mixer’s filtering ability against feeding composition fluctuations, as well as ibuprofen RSD in blend, in line with real experiments.

Nanoscale phase separation on an AlGaN surface characterized by scanning diffusion microscopy.

AlGaN is an important material for deep ultraviolet optoelectronic devices and electronic devices. The phase separation on the AlGaN surface means small-scale compositional fluctuations of Al, which is prone to degrade the performance of devices. In order to study the mechanism of the surface phase separation, the Al0.3Ga0.7N wafer was investigated by the scanning diffusion microscopy method based on the photo-assisted Kelvin force probe microscope. The response of the surface photovoltage near the bandgap was quite different for the edge and the center of the island on the AlGaN surface. We utilize the theoretical model of scanning diffusion microscopy to fit the local absorption coefficients from the measured surface photovoltage spectrum. During the fitting process, we introduce as and ab parameters (bandgap shift and broadening) to describe the local variation of absorption coefficients α(as, ab, λ). The local bandgap and Al composition can be calculated quantitatively from the absorption coefficients. The results show that there is lower bandgap (about 305 nm) and lower Al composition (about 0.31) at the edge of the island, compared with those at the center of the island (about 300 nm for bandgap and 0.34 for Al composition). Similar to the edge of the island, there is a lower bandgap at the V-pit defect which is about 306 nm corresponding to the Al composition of about 0.30. These results mean Ga enrichment both at the edge of the island and the V-pit defect position. It proves that scanning diffusion microscopy is an effective method to review the micro-mechanism of AlGaN phase separation.