Smooth Phase Research Articles

Calcium-Pillar Boosting Smooth Phase Transition in Potassium Vanadate Nanobelts toward Superior Cycling Performance in Potassium-Ion Batteries.

The depletion of lithium resources has prompted exploration into alternative rechargeable energy storage systems, and potassium-ion batteries (PIBs) have emerged as promising candidates. As an active cathode material for PIBs, potassium vanadate (KxV2O5) usually suffers from structural damage during electrochemical K-ion insertion/extraction and hence leading to unsatisfactory cycling performance. Here, we introduce Ca2+ ions as pillars into the potassium vanadate to enhance its structural stability and smooth its phase transition behavior. The additional Ca2+ not only stabilizes the layered structure but also promotes the rearrangement of interlayer ions and leads to a smooth solid-solution phase transition. The optimal composition K0.36Ca0.05V2O5 (KCVO) exhibits outstanding cyclic stability, delivering a capacity of ∼90 mA h g-1 at 20 mA g-1 with negligible capacity decay even after 700 cycles at 500 mA g-1. Theoretical calculations indicate lower energy barriers for K+ diffusion, promoting rapid reaction kinetics. The excellent performances and detailed investigations offer insights into the structural regulation of layered vanadium cathodes.

Probing hadron–quark phase transition in twin stars using f-modes

ABSTRACT Although it is conjectured that a phase transitions from hadronic to deconfined quark matter in the ultrahigh-density environment of neutron stars (NS), the nature of phase transition remains an unresolved mystery. Furthermore, recent efforts reveal that the finite surface tension effects can lead to a mixed phase with different geometric shapes (so-called ‘pasta’ phases), leading to a smooth phase transition from hadronic to quark matter in the NS interior. Depending on whether there is a strong or a pasta-induced smooth first-order phase transition, one may expect a third family of stable, compact stars or ‘twin stars’ to appear, with the same mass but different radii compared to NSs. The possibility of identifying twin stars using astrophysical observations has been a subject of interest. This study investigates the potential of probing the nature of the hadron–quark phase transition through future gravitational wave (GW) detections from fundamental (f-) mode oscillations in NSs. Using a newly developed model that parametrizes the hadron–quark phase transition with ‘pasta phases’, we calculate f-mode characteristics within a full general relativistic framework. We then use universal relations in GW asteroseismology to derive stellar properties from the detected mode parameters. Our findings suggest that detecting GWs from f modes with third-generation GW detectors offers a promising scenario for the existence of twin stars. However, we also estimate various uncertainties in determining the mode parameters and conclude that these uncertainties make it more challenging to identify the nature of the hadron–quark phase transition.

Thermal degradation assessment, impact strength, and hardness of combination epoxy and polystyrene powder composite

The present study investigates the reactions of polystyrene and epoxy/polystyrene powder composites, exploring different weight percentages (8%, 12%, and 16%) of polystyrene during decomposition under highly elevated temperatures within a nitrogen atmosphere. The findings reveal that polystyrene content significantly influences the thermal behavior of pure epoxy, with a higher polystyrene content correlating with the increased thermal stability of the composites. This study observed a three-stage mass loss process by examining the reaction kinetics of thermal decomposition using the Coats-Redfern approach. Initially, weight reduction occurs due to moisture and volatile elimination, followed by a smooth mass loss phase attributed to weaker polymer chain linkages and, ultimately, char formation. Chemical kinetic parameters, such as activation energy and frequency factor, were successfully determined using the Coats-Redfern approach, with a first-order reaction observed across all data points, demonstrating a high R-square mean value of 99.8%. Differential scanning calorimetry (DSC) and thermal gravitational analysis (TGA) analyses revealed an increase in glass temperature from 86.95 to 92.85 °C and an elevation in activation energy from 75.38 to 92.85 kJ/mol with increasing polystyrene content (0–16 wt%). Furthermore, the study investigated the influence of thermodynamic parameters. In terms of mechanical properties, increasing polystyrene content reduced impact strength (from 8.5 to 4.23 Kj/m2). In contrast, hardness increased from 77.5 for pure epoxy to 80.4 at 12 wt% polystyrene content in the composite. These findings underscore the importance of thermal stability results in developing a comprehensive understanding of thermal decomposition processes, informing future research endeavors and industrial applications.

One step synthesis of FeOx magnetic nanoparticles in the microreactor with intensively swirling flows

One step method of iron oxides nanoparticles synthesis using novel type of microreactors was reported. All the data received from analysis of physical and chemical properties demonstrated that the nanoparticles obtained by means of the new method are similar to the nanopowders synthesized by wet precipitation. They are magnetite-maghemite solid solutions with unit cell parameter between 8.362 and 8.374 Å, with coherent scattering range values about 9 nm. In comparison with precipitated nanopowders they have lesser degree of agglomeration. Samples obtained in microreactor have smaller value and smaller spread in regard of the specific surface (76–86 m2/g) in comparison with precipitated ones (75–125 m2/g). All the samples from microreactor consist of spherical inhomogeneities with a diffuse surface, while sample of iron oxide nanopowder synthesized by the co-precipitation method consists of scattering cylindrical inhomogeneities with nearly smooth phase boundary. It was shown that microreactor with intensively swirling flows has demonstrated several advantages: (i) possibility to control the degree of oxidation of the product which depends on the flow rates of reagents solutions to the reactor; (ii) high productivity (up to 7 L/min for the suspension with particles, approx. 200 kg/day for the dried particles) that eases the scaling-up of the proposed synthesis method.

Impact of pre-partum nutraceutical or monensin intraruminal boluses on colostrum quality and Holstein dairy cows’ performance: exploratory field study

A smooth transition phase is the key for optimal dairy cows’ performance and reduced antibiotics use. Therefore, the objective of our Our study was to compare the effect of an antibiotic growth promoter and a nutraceutical bolus, onhealth, colostrum, milk production, and profitability in transition dairy cows. Seventy-five animals blocked by parity, previous milk yield, lactation length, and body condition score (BCS) were assigned in a randomised design to 1 of 3 groups: control (CON; N = 26) receiving no treatment; monensin (MON; N = 27) receiving, a slow-releasing intraruminal bolus of sodic monensin at −20 d relative to expected calving; nutraceutical (ECS; N = 22) receiving, at −5 d before the expected calving an intraruminal bolus of Echinacea purpurea dry extract, vitamin E, l-carnitine and Silybum marianum released within 24h. Colostrum yield and density were recorded; its composition and immunoglobulins content were analysed. Every 20 days BCS was recorded; individual milk yield was recorded daily until 70DIM and monthly thereafter until 305 DIM. Milk quality was tested monthly. An economic evaluation until 70DIM was performed. Colostrum and Δ BCS were analysed by analysis of covariance. Economics and BCS were analysed with ANOVA, and milk yield and quality with ANOVA for repeated measures. The MON and ECS had lower colostrum protein and His, Arg, Ala, Met, Val and Ile content, and in higher milk yield until 35 (ECS) and 70 (MON) DIM compared to the CON. A trend for a higher partial income was observed for MON and ECS compared to the CON group, suggesting a positive impact of the treatments.

Improvement of heat-sealing strength of chitosan-based composite films and product costs analysis in the production process

The primary objective of this study was to enhance the heat-sealing strength of composite films made from chitosan and analyze the associated product costs. The approach adopted involved formulating chitosan-based composite films by incorporating gelatin and green seaweed extract. This strategic combination resulted in a notable improvement in heat-sealing strength. The ensuing attributes underwent meticulous examination, encompassing seal strength, FTIR spectroscopy, FE-SEM surface morphology analysis, and DSC thermal properties determination. Data analysis was rigorously conducted using the SPSS program, with outcomes presented as mean values accompanied by standard deviations. Disparities were discerned at a 95% confidence level, ensuring statistical robustness. The findings unveiled that the incorporation of 10% gelatin and 1% green seaweed extract substantially enhanced the seal strength of the chitosan-based composite films. Notably, the introduction of green seaweed extracts disrupted interactions between chitosan's structure and various molecular vibrations. This disruption, coupled with increased ionic interactions and hydrogen bonding, led to improved molecular interdiffusion, ultimately resulting in modified heat sealability. The study identified the optimized conditions as 10% gelatin and 1% green seaweed extract concentrations, which produced the highest seal strength at 19.4 N/m. Further evidence from scanning electron microscopy demonstrated improved interfacial adhesion, attributed to the adjusted surface morphology. The film surface did not contain small scattered particles and presented a smooth phase. This suggests that the chitosan-based composite achieved good interfacial adhesion between the two components in these films. As an essential aspect for practical application, the total production cost of the films was determined to be 606.84 baht. This information renders the data collection from the study valuable for companies seeking to enhance production efficiency and overall profitability.

Phase smoothing for diffractive deep neural networks

Optical neural networks have shown promising advantages over its electronic counterpart due to fast computational speed, high throughput, and low energy consumption. For the deep neural networks mimicked by the cascaded phase masks, the conventional training algorithm results in abruptly varying phase profiles. In this work, we show that even two kinds of diffraction formulas give completely different results for the identical rough phase masks, which denotes that the training process harvests the inaccuracy of the used diffraction modeling, which prevents the results from being replicated when the diffraction is formularized by other numerical methods or implemented in the real world. The modeling inaccuracy of each phase mask accumulates to prevent the successful optical implementation. In this work, we propose a two-step training framework to enforce smooth phase masks, and thus reduce the mismatch between numerical modeling and practical deployment.

A predictor-corrector phase unwrapping algorithm for temporally undersampled gradient-echo MRI.

To develop a method for unwrapping temporally undersampled and nonlinear gradient recalled echo (GRE) phase. Temporal unwrapping is performed as a sequential one step prediction of the echo phase, followed by a correction to the nearest integer wrap-count. A spatio-temporal extension of the 1D predictor corrector unwrapping (PCU) algorithm improves the prediction accuracy, and thereby maintains spatial continuity. The proposed method is evaluated using numerical phantom, physical phantom, and in vivo brain data at both 3 T and 9.4 T. The unwrapping performance is compared with the state-of-the-art temporal and spatial unwrapping algorithms, and the spatio-temporal iterative virtual-echo based Nyquist sampled (iVENyS) algorithm. Simulation results showed significant reduction in unwrapping errors at higher echoes compared with the state-of-the-art algorithms. Similar to the iVENyS algorithm, the PCU algorithm was able to generate spatially smooth phase images for in vivo data acquired at 3 T and 9.4 T, bypassing the use of additional spatial unwrapping step. A key advantage over iVENyS algorithm is the superior performance of PCU algorithm at higher echoes. PCU algorithm serves as a robust phase unwrapping method for temporally undersampled and nonlinear GRE phase, particularly in the presence of high field gradients.

Unsupervised deep learning model for correcting Nyquist ghosts of single-shot spatiotemporal encoding.

To design an unsupervised deep learning (DL) model for correcting Nyquist ghosts of single-shot spatiotemporal encoding (SPEN) and evaluate the model for real MRI applications. The proposed method consists of three main components: (1) an unsupervised network that combines Residual Encoder and Restricted Subspace Mapping (RERSM-net) and is trained to generate a phase-difference map based on the even and odd SPEN images; (2) a spin physical forward model to obtain the corrected image with the learned phase difference map; and (3) cycle-consistency loss that is explored for training the RERSM-net. The proposed RERSM-net could effectively generate smooth phase difference maps and correct Nyquist ghosts of single-shot SPEN. Both simulation and real in vivo MRI experiments demonstrated that our method outperforms the state-of-the-art SPEN Nyquist ghost correction method. Furthermore, the ablation experiments of generating phase-difference maps show the advantages of the proposed unsupervised model. The proposed method can effectively correct Nyquist ghosts for the single-shot SPEN sequence.

No smooth phase transition for the nodal length of band-limited spherical random fields

In this paper, we investigate the variance of the nodal length for band-limited spherical random waves. When the frequency window includes a number of eigenfunctions that grows linearly, the variance of the nodal length is linear with respect to the frequency, while it is logarithmic when a single eigenfunction is considered. Then, it is natural to conjecture that there exists a smooth transition with respect to the number of eigenfunctions in the frequency window; however, we show here that the asymptotic variance is logarithmic whenever this number grows sublinearly, so that the window “shrinks”. The result is achieved by exploiting the Christoffel–Darboux formula to establish the covariance function of the field and its first and second derivatives. This allows us to compute the two-point correlation function at high frequency and then to derive the asymptotic behaviour of the variance.

Multisource Holography

Holographic displays promise several benefits including high quality 3D imagery, accurate accommodation cues, and compact form-factors. However, holography relies on coherent illumination which can create undesirable speckle noise in the final image. Although smooth phase holograms can be speckle-free, their non-uniform eyebox makes them impractical, and speckle mitigation with partially coherent sources also reduces resolution. Averaging sequential frames for speckle reduction requires high speed modulators and consumes temporal bandwidth that may be needed elsewhere in the system. In this work, we propose multisource holography, a novel architecture that uses an array of sources to suppress speckle in a single frame without sacrificing resolution. By using two spatial light modulators, arranged sequentially, each source in the array can be controlled almost independently to create a version of the target content with different speckle. Speckle is then suppressed when the contributions from the multiple sources are averaged at the image plane. We introduce an algorithm to calculate multisource holograms, analyze the design space, and demonstrate up to a 10 dB increase in peak signal-to-noise ratio compared to an equivalent single source system. Finally, we validate the concept with a benchtop experimental prototype by producing both 2D images and focal stacks with natural defocus cues.

Adaptive evaluation for agricultural sustainability of different fertilizer management options for a green manure-maize rotation system: Impacts on crop yield, soil biochemical properties and organic carbon fractions

Green manure planting can reduce the intensity of soil use, while improving farmland productivity in double-cropping systems. However, only few studies have focused on the impacts of green manure application under different fertilization management options on succeeding crop yield and soil organic carbon (SOC) process. A three-year field experiment was conducted with a winter smooth vetch-summer maize cropping system to evaluate the effects of green manure with different chemical fertilizers on soil physiochemical properties, SOC fraction, enzyme activities and maize yield. Total eight treatments were compared including different combinations of green manure and chemical fertilizers (i.e., nitrogen and phosphorus fertilizers) in the smooth vetch phase and maize phase. The results showed that compared to the control, green manure incorporation increased the soil moisture, total nitrogen, total phosphorus, basal respiration, SOC and its labile fractions, and enzyme activities, especially for the treatments of green manure with fertilization. However, the soil pH and bulk density decreased due to green manure application. Maize yield increased 34 %–53 % after green manure application, and was found to be significantly and positively correlated with soil carbon process (P < 0.05). Moreover, SOC and its labile fractions, and total nitrogen were observed as the main drivers of the maize yield. Variation partition analysis demonstrated that soil biochemical properties and their interaction with green manure by fertilization caused variations in SOC fractions. Further, structural equation models indicated that both balanced fertilization practices had positive effects on maize yield and soil carbon process via changes in SOC fractions and C cycling-related enzyme activities, respectively. In addition, the amount balance of chemical fertilizer positively impacted the soil carbon process by regulating SOC fractions through enzyme activities. These findings provide important guidance for applying optimal fertilization management in the green manure phase to improve succeeding crop yield and soil quality as well as to mitigate the adverse impacts of chemical fertilizers. The study will be equally illuminating for other green manure-crop rotation systems.

Baric Transformation of the Nature of Magnetic Ordering and Magnetocaloric Properties in the Mn&lt;sub&gt;1 – &lt;i&gt;x&lt;/i&gt;&lt;/sub&gt;Cr&lt;sub&gt;&lt;i&gt;x&lt;/i&gt;&lt;/sub&gt;NiGe System

Abstract—The isobaric temperature dependences of the magnetization and the magnetocaloric characteristics of alloys of the Mn1 – xCrxNiGe system are studied in a constant magnetic field up to 10 kOe in the range of hydrostatic pressures up to 12 kbar. It has been established that, with increasing pressure, the implementation of helimagnetic ordering undergoes qualitative changes from smooth hysteresis-free 2nd order phase transition to 1st order phase transitions, accompanied by the appearance of a temperature hysteresis and an increase in the magnetocaloric effect. Based on the exchange-structural model, an explanation is given for the mechanism of baric transformation of magnetic and magnetocaloric properties.

Smooth and oscillatory geometric phase corrections for driven spins

For a quantum spin driven cyclically by a slowly-rotated magnetic field, geometric phases are well understood. If the cycle takes a long time the leading-order (dynamical) phase is proportional to and the geometric phase is the contribution independent of The dynamical and geometric phases are the first two terms of a series in slowness Here it is shown with an exactly solvable example that the corrections are of two types: smooth, proportional to powers of slowness, and oscillatory: essential singularities in in the form of trigonometric functions of divided by powers of The calculations are elementary and therefore suitable for presentation in graduate quantum theory courses.

Walking-Speed-Adaptive Gait Phase Estimation for Wearable Robots.

This paper introduces a Gait Phase Estimation Module (GPEM) and its real-time algorithm designed to estimate gait phases continuously and monotonically across a range of walking speeds and accelerations/decelerations. To address the challenges of real-world applications, we propose a speed-adaptive online gait phase estimation algorithm, which enables precise estimation of gait phases during both constant speed locomotion and dynamic speed changes. Experimental verification demonstrates that the proposed method offers smooth, continuous, and repetitive gait phase estimation when compared to conventional approaches such as the phase portrait method and time-based estimation. The proposed method achieved a 48% reduction in gait phase deviation compared to time-based estimation and a 48.29% reduction compared to the phase portrait method. The proposed algorithm is integrated within the GPEM, allowing for its versatile application in controlling gait assistive robots without incurring additional computational burden. The results of this study contribute to the development of robust and efficient gait phase estimation techniques for various robotic applications.

Design of adjustable multifocal diffractive optical elements with an improved smooth phase profile by continuous variable curve with multi-subperiods method.

Multifocal diffractive optical elements (MDOEs), which produce arbitrary light distribution, are widely used in lightweight and compact optical systems. MDOEs that are combined with multiple functions tend to have complex step structures, limiting their applications. We propose a facile method named continuous variable curve with multi-subperiods (CVCMS) to design adjustable multifocal single-layer diffractive optical elements. Through the analysis, the model achieved arbitrary diffraction efficiency distribution with an improved smooth continuous phase profile in each diffractive ring while retaining the periodicity. To display the high design freedom of the method, we utilized this method to design and discuss a broadband multifocal intraocular lens (MIOL) focused on the optimization of far focal point. Finally, the method was compared with other multifocal design methods. The results show that the CVCMS method achieved adjustable multifocal design with better performance and smoother profile than other MDOE design techniques. The proposed model can be applied to multifocal ophthalmic lens designs.

Investigation of the Product of Random Matrices and Related Evolution Models

In this paper, we study the phase structure of the product of D * D order matrices. In each round, we randomly choose a matrix from a finite set of d matrices and multiply it with the product from the previous round. Initially, we derived a functional equation for the case of matrices with real eigenvalues and correlated choice of matrices, which led to the identification of several phases. Subsequently, we explored the case of uncorrelated choice of matrices and derived a simpler functional equation, again identifying multiple phases. In our investigation, we observed a phase with a smooth distribution in steady-state and phases with singularities. For the general case of D-dimensional matrices, we derived a formula for the phase transition point. Additionally, we solved a related evolution model. Moreover, we examined the relaxation dynamics of the considered models. In both the smooth phase and the phase with singularities, the relaxation is exponential. The superiority of relaxation in the smooth phase depends on the specific case.

Understanding the effects of variable permeability along the cross-section of packed beds of encapsulated phase change materials for latent heat thermal energy storage systems

This work analyzes the impact of variable porosity along packed beds of encapsulated phase change materials for Latent Heat Thermal Energy Storage (LHTES) systems on their charging performance. A novel model encompassing variable permeability along the cylindrical bed’s cross-section due to geometrical constraints and a smooth phase change that is consistent with calorimetry measurements was adopted. A Finite Volumes code is used to solve the governing equations, while unknown phase change parameters are estimated using experimental data and the Levenberg-Marquardt inverse analysis algorithm. The aggregate result of the in situ estimation of the parameters related to the non-isothermal phase change and the proposed variable porosity model is a deviation of their results of at most 10% in comparisons involving temperature measurements for both the heat transfer fluid and phase change material. The significance of accounting for the variable permeability and the associated channeling effect is shown, as a considerable portion of the packed bed does not contact an enough amount of the hot heat transfer fluid to efficiently charge the LHTES system. The constant porosity model can overpredict the duration of the full conversion of heat input into heat stored by roughly 27 min and underestimate the full charging time by more than 200 min, which may lead to an erroneous sizing of the thermal energy storage unit. The usage of smaller capsules can enforce a more uniform heating of the packed bed, which allows for the heat transfer performance to approach the limit predicted by the constant porosity case.

Characterisation and Analysis of Chitosan Extract from Artemia franciscana Using SEM, FT-IR and XRD Studies

Introduction: Artemia franciscana is one of the best animal models which is used in various fields. After the hatching of Artemia the shell wastes are used for Chitosan extraction. The extraction process consumes less time when compare with other shells because of its shell size.&#x0D; Materials and Methods: The Chitosan extract was prepared using Artemia shells. The Physico-chemical properties were analysed and characterization of Chitosan extract was done using SEM, XRD and FT-IR studies.The physicochemical properties of the extracted chitosan indicate that it has optimum values desirable for wound healing applications. Chitosan has high water and fat binding capacity that can help to maintain a moist environment on the wound surface and control inflammation, respectively. The degree of deacetylation (DD) of chitosan is critical in determining its biological activities. The DD value obtained in this study was 84.77%, indicating that the chitosan sample had a high degree of deacetylation. Outcomes: The morphology of the chitosan membrane is an important factor that influences its properties and potential applications, including wound healing.&#x0D; Results: The SEM images obtained in this study revealed that pure chitosan exhibited a nonporous, smooth membranous phase with dome-shaped orifices, microfibrils, and crystallites. The XRD analysis results suggest that the chitosan used in this study is highly crystalline, with both crystalline and amorphous regions enhancing its bioactivity and biocompatibility, making it a promising material for wide range of application in medicine. The crystalline and amorphous structure of Chitosan is analysed by the XRD, SEM and FT-IR reveals its wide range of applications in medicine.

Gamma error correction algorithm for phase shift profilometry based on polar angle average

Phase errors caused by the gamma nonlinear response of the phase shift profilometry (PSP) severely affect 3D measurement accuracy. To tackle this, a simple phase error compensation technique based on polar angle average is presented in this paper to improve the accuracy. Wrapped phase values are regarded as polar angles, and a polar axis distribution map can be obtained in the polar coordinate. Practically, the polar axis distribution (PAD) of the undistorted wrapped phase is uniform. When there are nonlinear effects in an PSP, the polar axis is unevenly distributed. The difference between adjacent polar angles is computed and then rearranged with specifically labels. After that, the even PAD diagram is generated, and the smooth phase can be further recovered. Compared with conventional nonlinearity correction methods, the proposed method corrects the error without any auxiliary conditions. Its effectiveness and robustness are verified in simulations and experiments.