Saturated Phase Research Articles

Reconfigurable magnonic crystals: Spin wave propagation in Pt/Co multilayer in saturated and stripe domain phase

To control the spin wave (SW) propagation, external energy sources such as magnetic fields, electric currents, or complex nanopatterning are used, which can be challenging at the deep nanoscale level. In this work, we overcome such limitations by demonstrating SW propagation in Pt/Co multilayers at a remanent state controlled by stripe domain patterns, using Brillouin light scattering and micromagnetic simulations. We show that parallel stripes with a periodicity around 100 nm exhibit reconfigurability, as the stripes can be rotated by applying the in-plane field without damaging their shape. This allows us to study SW propagation perpendicular and parallel to the stripes. We observe multimodal SW spectra—three bands in perpendicular and five in parallel geometry. Numerical results allow us to identify all observed modes and to explain the differences between two configurations by the unequal contribution of all three magnetization components in the SW dynamics. We find that the experimentally measured non-reciprocal dispersion (for the wavevector perpendicular to the stripes) is not the breaking of time-symmetry but the asymmetry in intensity of the measured signals of two different low-frequency modes, which is due to the inhomogeneous SW amplitude distribution over the multilayer thickness and the limited light penetration depth. Our results pave the way for easy reprogrammability and high energy efficiency in nanomagnonics.

Ethyl levulinate regulates traditional sulfolane biphasic absorbent for energy-efficient CO2 capture

Traditional CO2 biphasic absorbents currently suffer from problems such as high initial phase separation loading, poor product distribution selectivity, and weak dynamic phase separation ability, which limit their potential for industrial applications. This study developed a biphasic absorbent regulated by dual physical solvents by introducing partial ethyl levulinate (EL) into a sulfolane biphasic system. The optimal composition of this system was 30 wt% 1-amino-2-propanol (MIPA), 20 wt% sulfolane and 30 wt% EL. Under dual physical solvent conditions, strong electrostatic attraction between MIPA and CO2 promoted generation of MIPA zwitterions and carbamate. Analysis of the interactions between different product components through electrostatic potentials and with an independent gradient model based on Hirshfeld's partitioning revealed only extremely weak van der Waals force-driven interactions between the reaction products and EL. These interactions substantially reduced the initial phase separation loading and offered precise control over phase transition behavior. Compared with MIPA/sulfolane system, the MIPA/sulfolane/EL system achieved a 48.9 % lower initial phase separation loading, an 11.6 % lower proportion of saturated rich phase volume, a 10.1 % higher CO2-rich phase loading, and a 6.7 % lower viscosity. The excellent dynamic phase separation performance was verified using a customized device and the energy consumption for CO2 regeneration decreased to 2.2 GJ/t CO2.

Effect of permeability anisotropy on the CO2 saturation distribution and phase change during a leakage event in a saline aquifer

Effect of permeability anisotropy on the CO2 saturation distribution and phase change during a leakage event in a saline aquifer

Fast and Optimal Extraction for Sparse Equality Graphs

Equality graphs (e-graphs) are used to compactly represent equivalence classes of terms in symbolic reasoning systems. Beyond their original roots in automated theorem proving, e-graphs have been used in a variety of applications. They have become particularly important as the key ingredient in the popular technique of equality saturation, which has notable applications in compiler optimization, program synthesis, program verification, and symbolic execution, among others. In a typical equality saturation workflow, an e-graph is used to store a large number of equalities that are generated by local rewrites during a saturation phase, after which an optimal term is extracted from the e-graph as the output of the technique. However, despite its crucial role in equality saturation, e-graph extraction has received relatively little attention in the literature, which we seek to start addressing in this paper. Extraction is a challenging problem and is notably known to be NP-hard in general, so current equality saturation tools rely either on slow optimal extraction algorithms based on integer linear programming (ILP) or on heuristics that may not always produce the optimal result. In fact, in this paper, we show that e-graph extraction is hard to approximate within any constant ratio. Thus, any such heuristic will produce wildly suboptimal results in the worst case. Fortunately, we show that the problem becomes tractable when the e-graph is sparse, which is the case in many practical applications. We present a novel parameterized algorithm for extracting optimal terms from e-graphs with low treewidth, a measure of how “tree-like” a graph is, and prove its correctness. We also present an efficient Rust implementation of our algorithm and evaluate it against ILP on a number of benchmarks extracted from the Cranelift benchmark suite, a real-world compiler optimization library based on equality saturation. Our algorithm optimally extracts e-graphs with treewidths of up to 10 in a fraction of the time taken by ILP. These results suggest that our algorithm can be a valuable tool for equality saturation users who need to extract optimal terms from sparse e-graphs.

Three dimensional time-variation simulator for water flooding reservoir based on “effective water flux”

Long-term water flooding leads to changes in pore throat structure, resulting in alterations in macroscopic reservoir petrophysical parameters. However, commercial numerical simulation software does not have this capability. Ignoring variations in physical parameters during the formulation of development plans and numerical simulations can lead to significant prediction errors, which severely impacts oil field recovery. This paper, based on an analysis of effective flow rate and waterflood intensity, proposes a new erosion degree characterization parameter: Effective water flux, to represent the time-varying patterns of physical parameters. It is embedded into a black oil model to develop a time-variation simulator, whose accuracy and stability in both black oil and time-variation models are validated through comparison with the commercial numerical simulation software CMG. The study further explores the effects of different parameter variations on the development process. It was found that increases in permeability and oil viscosity exacerbate heterogeneity and reduce displacement efficiency, while decreases in residual oil saturation and water phase permeability under residual oil saturation enhance water flooding efficiency. In complex models, the effects of variations in different parameters intertwine, collectively influencing development outcomes. This paper advances the development of time-variation numerical simulation technology.

Aqueous-organic and aqueous-vapor interfacial phenomena for three phase systems containing CO2, CH4, n-butanol, n-dodecane and H2O at saturation conditions

A fundamental understanding of the interfacial properties at elevated pressure is essential for processes in the context of the energy transition, such as the storage of CO2, H2 or CH4. Systems in such processes have traces of impurities. This work aims to systematically investigate these multi-component systems through simplified vapor-liquid-liquid systems comprising H2O, (n-butanol or n-dodecane), and (CO2 or CH4). The model systems are theoretically investigated using the density gradient theory and the PCP-SAFT. The interfacial tension and saturated phase density of the model systems are experimentally measured by the pendant drop and the oscillating tube method, respectively. Good agreement between the theoretical and experimental results is found. It was found that the pure and binary systems of these mixtures can be described well by the introduced model, delivering high quality predictions.

Dwarf galaxies as a probe of a primordially magnetized Universe

Aims. The true nature of primordial magnetic fields (PMFs) and their role in the formation of galaxies remains elusive. To shed light on these unknowns, we investigated their impact by varying two sets of properties: (i) accounting for the effect of PMFs on the initial matter power spectrum and (ii) accounting for their magneto-hydrodynamical effects on the formation of galaxies. By comparing both, we can determine the dominant agent in shaping galaxy evolution. Methods. We used the magneto-hydrodynamics code RAMSES to generate multiple new zoom-in simulations for eight different host halos of dwarf galaxies across a wide luminosity range of 103 − 106 L⊙. These halos were selected from a ΛCDM cosmological box, tracking their evolution down to redshift z = 0. We explored a variety of primordial magnetic field (comoving) strengths of Bλ ranging from 0.05 to 0.50 nG. Results. We find that magnetic fields in the interstellar medium not only modify star formation processes in dwarf spheroidal galaxies, but these fields also entirely prevent the formation of stars in less compact, ultra-faint galaxies with halo masses and stellar masses below, respectively, ∼2.5 × 109 and 3 × 106 M⊙. At high redshifts, the impact of PMFs on host halos of dwarf galaxies through the modification of the matter power spectrum is more dominant than the influence of magneto-hydrodynamics in shaping their gaseous structure. Through the amplification of small perturbations ranging in mass from 107 to 109 M⊙ in the ΛCDM+PMFs matter power spectrum, primordial fields expedite the formation of the first dark matter halos, leading to an earlier onset and a higher star formation rate at redshifts of z > 9. We investigated the evolution of various energy components and demonstrated that magnetic fields with an initial strength of Bλ ≥ 0.05 nG exhibit a strong growth of magnetic energy, accompanied by a saturation phase that begins soon after the growth phase. These trends persist consistently, regardless of the initial conditions or whether it is the classical ΛCDM model or ΛCDM modified by PMFs. Lastly, we investigated the impact of PMFs on the present-time observable properties of dwarf galaxies, namely: the half light radius, V-band luminosity, mean metallicity, and velocity dispersion profile. We find that PMFs with moderate strengths of Bλ ≤ 0.10 nG show an impressive agreement with the scaling relations of the observed Local Group dwarfs. However, stronger fields lead to larger sizes and higher velocity dispersions.

Cognitive reflection in experimental anchored guessing games

The cognitive reflection test or CRT (Frederick, 2005) has been found to be a reliable predictor of the degree of strategic sophistication of subjects in a variety of laboratory experiments. These studies have found that subjects who score higher in the CRT make choices that are closer to Nash equilibrium (i.e., Brañas-Garza et al., 2012). In an extended level-k model with free subjective beliefs, we theoretically decompose the closeness to equilibrium for the class of anchored guessing games introduced in Ballester et al. (2023) into two effects: subjects with a smaller distance to equilibrium must possess a higher reasoning level in the level-k hierarchy or their level-k iteration process must begin from a starting point (called “seed”) that is inherently more advantageously positioned, which translates into the concept of “seed distance” (or both). Our main experimental finding is that subjects with a higher CRT score play closer to equilibrium due to the fact that they iterate more often in their reasoning process (as in Brañas-Garza et al., 2012), yet we find no clear evidence that they have a smaller seed distance. We also find evidence of a learning or adaptation process, which can be characterized by a warm-up phase (in which subjects reduce their seed distance), followed by a learning phase (in which they increase their reasoning level, at a faster rate in subjects with higher CRT) and then a saturation phase in which no further improvements are made.

Stability optimization of energetic particle driven modes in nuclear fusion devices: the FAR3d gyro-fluid code

The development of reduced models provide efficient methods that can be used to perform short term experimental data analysis or narrow down the parametric range of more sophisticated numerical approaches. Reduced models are derived by simplifying the physics description with the goal of retaining only the essential ingredients required to reproduce the phenomena under study. This is the role of the gyro-fluid code FAR3d, dedicated to analyze the linear and nonlinear stability of Alfvén Eigenmodes (AE), Energetic Particle Modes (EPM) and magnetic-hydrodynamic modes as pressure gradient driven mode (PGDM) and current driven modes (CDM) in nuclear fusion devices. Such analysis is valuable for improving the plasma heating efficiency and confinement; this can enhance the overall device performance. The present review is dedicated to a description of the most important contributions of the FAR3d code in the field of energetic particles (EP) and AE/EPM stability. FAR3d is used to model and characterize the AE/EPM activity measured in fusion devices as LHD, JET, DIII-D, EAST, TJ-II and Heliotron J. In addition, the computational efficiency of FAR3d facilitates performing massive parametric studies leading to the identification of optimization trends with respect to the AE/EPM stability. This can aid in identifying operational regimes where AE/EPM activity is avoided or minimized. This technique is applied to the analysis of optimized configurations with respect to the thermal plasma parameters, magnetic field configuration, external actuators and the effect of multiple EP populations. In addition, the AE/EPM saturation phase is analyzed, taking into account both steady-state phases and bursting activity observed in LHD and DIII-D devices. The nonlinear calculations provide: the induced EP transport, the generation of zonal structures as well as the energy transfer towards the thermal plasma and between different toroidal/helical families. Finally, FAR3d is used to forecast the AE/EPM stability in operational scenarios of future devices as ITER, CFETR, JT60SA and CFQS as well as possible approaches to optimization with respect to variations in the most important plasma parameters.

Combination of two-fluid model and delayed equilibrium model for the critical flow in a slit

Accurately predicting the mass flux, pressure profile, and velocity profile of the critical flow in a slit is essential for analyzing the breaking process of the liquid phase and calculating the aerosol source term for leak-before-break (LBB) monitoring and Loss of Coolant Accident (LOCA) risk analysis. A new critical flow model combining Two-fluid Model (TFM) and Delayed Equilibrium Model (DEM) is built to get accurate profiles while avoiding the same phase velocity in DEM and the arbitrary critical flow criterion in TFM. The new model is verified using past experiments of the critical flow in a slit. It proves to be accurate in mass flux but not in critical pressure, with maximum relative errors of around 25% in mass flux and around 80% in critical pressure. The new model is optimized for higher accuracy in critical pressure. The empirical equation of saturated phase mass flow rate fraction gradient is optimized by conducting approximate pressure profile calculation and regression analysis. The maximum relative error decreases little while the ratio of critical pressure relative errors lying in the range of ±40% increases after optimization. In contrast, the difference in the average abstract relative error of pressure between original TFM-DEM and DEM is much larger, for the maximum relative error of mass flux and critical pressure are around 25% and 110%. The comparison between the original and optimized TFM-DEM proves that the new critical flow model is accurate in mass flux and can be optimized to raise pressure calculation accuracy. The comparison between the original TFM-DEM and DEM proves that the phase velocity difference is the major source of accuracy improvement in the pressure profile.

Growth Phase Contribution in Dictating Drug Transport and Subcellular Accumulation inside Escherichia coli.

Depending upon nutrient availability, bacteria transit to multiple growth phases. The transition from the active to nongrowing phase results in reduced drug efficacy and, in some cases, even multidrug resistance. However, due to multiple alterations in the cell envelope, probing the drug permeation kinetics during growth phases becomes perplexing, especially across the Gram-negative bacteria's complex dual membrane envelope. To advance the understanding of drug permeation during the life cycle of Gram-negative bacteria, we sought to address two underlying objectives: (a) how changes are occurring inside the bacterial envelope during growth and (b) how the drug permeation and accumulation vary across both the membranes and in subcellular compartments during growth. Both objectives are met with the help of nonlinear optical technique second-harmonic generation spectroscopy (SHG). Specifically, using SHG, we probed the transport kinetics and accumulation of a quaternary ammonium compound (QAC), malachite green, inside Escherichia coli in various growth phases. Further insight about another QAC molecule, propidium iodide, is accomplished using fluorescence microscopy. Results indicate that actively growing cells have faster drug transport and higher cytoplasmic accumulation than slow- or nongrowing cells. In this regard, the rpoS gene plays a crucial role in limiting drug transport across the saturation phase cultures. Moreover, within a particular growth phase, membrane permeability undergoes gradual changes much before the subsequent growth phase commences. These outcomes signify the importance of reporting the growth phase and rate in drug efficacy studies.

Exploring Electric Vehicle Patent Trends through Technology Life Cycle and Social Network Analysis

In response to environmental and energy challenges, electric vehicles (EVs) have re-emerged as a viable alternative to internal combustion engines. However, existing research lacks a comprehensive analysis of the technology life cycle of EVs in both global and South Korean contexts and offers limited strategic guidance. This study introduces a novel approach to address these gaps by integrating the S-curve model with social network analysis (SNA), time series analysis, and core applicant layouts. The study specifically utilizes the logistic curve to model technology growth. It applies SNA methods, including International Patent Classification (IPC) co-occurrence analysis and the betweenness centrality metric, to identify the stages of technological development and sustainable research directions for EVs. By analyzing patent data from 2004 to 2023, the study reveals that EV technologies have reached the saturation phase globally and in South Korea, with South Korea maintaining a two-year technological advantage. The research identifies sustainable research directions, including fast charging technology and charging infrastructure, battery monitoring and management, and artificial intelligence (AI) applications. Additionally, the study also determined the sustainability of these research directions by examining the sustainability challenges faced by EVs. These insights offer a clear view of EV technology trends and future directions, guiding stakeholders.

A simple two-phase approach to predict moisture-dependent thermal conductivity for porous materials

This study develops a generalized solution for moisture-dependent thermal conductivity (λeff) in porous media, utilizing readily available parameters. By introducing arbitrary dry and saturated phases, the tri-phase model (solid, gas, and water) is simplified into a two-phase model. Seven analytical solutions are adapted, including series-parallel, Maxwell-Eucken, Landauer's, exponential, and Somerton's relations. The proposed method requires only two parameters to predict λeff under different degrees of saturation (Sr): effective dry thermal conductivity (λdry, where Sr = 0) and effective saturated thermal conductivity (λsat, where Sr = 1). In the absence of direct λsat measurement, this λsat can be obtained using λdry and the parallel relation for highly porous media, and using Landauer's relation for medium-density materials. Validation results indicate that both Landauer's and exponential relations provide the upper bound and lower bounds, respectively, for λeff. For medium-density materials, the upper bound aligns with the parallel relation and the lower bound aligns with Landauer's relation.

Representing and assessing distributed situation awareness in multi-agency disaster response: A hypergraph-based methodology

This paper introduces a novel hypergraph-based methodology for representing and assessing distributed situation awareness (DSA) in multi-agency disaster response. The fundamental ideas and motivations of our methodology stem from the following widely acknowledged understandings and phenomenons: (a) DSA’s representation should be approached from social, information and task dimensions; (b) DSA is one of the collective behaviors that emerge from the interactions; (c) the interactions in the real world are not pairwise. Our methodology delineates the collaboration, co-activation, and co-existence interactions among social, information, and task elements as higher-order interactions. We then construct these interaction systems using hypergraph-structured data derived from disaster response scenarios. Subsequently, these systems are encoded into hypergraphs, which are validated against our dataset and proven to be practical tools for depicting higher-order interaction patterns. Analytical techniques tailored to hypergraphs are applied, yielding insights intrinsic to hypergraphs regarding DSA in emergency response. Moreover, we integrate these interaction systems into a comprehensive framework that allows for the visualization and quantitative analyses of DSA evolution dynamics. We propose several indicators of evolution, discussing their trends and implications throughout the development of the emergency response. We locate the system deficiencies by revealing a mismatch between the positions of specific elements in the network and their functions. We also identify the saturation phase in the DSA evolution process.

A discovery of nanoscale sulfide droplets in MORB glasses: implications for the immiscibility of sulfide and silicate melts

Sulfur forms an immiscible liquid upon saturation in magma, and sulfide droplets are commonly found in fresh mid-ocean ridge basalt (MORB). Scanning electron microscopy (SEM) analysis revealed that the fine-grained and weakly phyric MORB samples exhibited hypocrystalline to vitreous textures. Transmission electron microscopy (TEM) of MORB glasses exhibits nanoscale sulfide droplets (10–15 nm) with rounded shapes and smooth edges, showing crystalline and homogeneous composition. Elemental distribution included S, Fe, Cu, and Ni, while Si, Al, and O were lacking. Prior research clarified the immiscibility between sulfide and silicate melts, impacting the size distribution of sulfide droplets. This is the first report on nanoscale sulfide droplets within MORB glasses, and these results suggest that nanoscale sulfide droplets represent the initial phase of sulfide saturation. Such an insight may prove useful in understanding how siderophile and chalcophile elements behaved during sulfide crystallization. In addition, this study determines the immiscibility of sulfides and silicate melts that occur in the early nanometer stage. Therefore, it is speculated that immiscibility phenomena may occur in the nanometer stage during magma evolution.

Inhibiting insulin aggregation by chaperone-like green cholinium-based DESs as additives

Protein microenvironment is critical to study protein function and stability. In the current study, the ability of synthesized choline-based deep eutectic solvents (DESs) as additives to inhibit and disaggregate amyloid fibrils of human insulin was investigated. The DESs synthesized in this study were nontoxic and can be classified as green chemistry. Utilizing various biophysical methods indicated that choline-chloride glycine (Ch/Gly) and choline-chloride ascorbic acid (Ch/Asb) exhibited chaperone-like properties. This was attributed to their inhibitory effects on the lag phase by stabilizing insulin monomers and on the saturation phase by disaggregating mature insulin fibrils. In contrast, choline-chloride histidine (Ch/His) accelerated the aggregation of insulin. Our results suggest that antioxidant and hydrophobic properties, combined with lower surface activity and higher hydrogen bond formation ability, are the main features describing the inhibitory effect of DESs on protein aggregation.

Saturated phase change threshold of plume flow gas species under low temperature and rarefied environment

Gas species in high altitude plume flow are all exposed to low temperature, thus making possible phase change processes on those other than H2O vapor. In order to obtain saturated threshold of gas species, which is normally abundant in plume flow, this study establishes Gibbs phase calculation method for CO2, CO, H2, and N2. The non-continuum effect caused by rarefied gas environment is quantitatively calculated by ratio between molecular free path scale and characteristic length of investigated object. Validation on Gibbs method is guaranteed by comparison between calculated results and data from American National Standards Institute (ANSI), while non-continuum effect method is verified by revealing essential reason for gas-solid phase change processes resembling droplet condensation phenomenon observed in high altitude environment. According to the results, non-continuum effect only influences gas-solid boundary. Phase change for rarefied gas species can only occur under low temperature. Saturated threshold deflects toward solid phase region below specific molecules number density, thus decreasing gas to solid phase change trend. Both increasing on characteristic length and existence of other gas components contamination decreases non-continuum effect. Variation on non-continuum effect shows biggest influence on CO2 saturated phase change threshold, while shows smallest influence on that of N2.

Raman spectroscopy for the determination of hydrogen concentration in liquid organic hydrogen carrier systems

This work reports on the development of a calibration approach of Raman spectroscopy for the determination of the concentration of dissolved hydrogen (H2) in representative compounds and mixtures of liquid organic hydrogen carrier (LOHC) systems based on diphenylmethane and ortho-benzyltoluene (o-BT). Hydrogen solubility data are measured by the isochoric-saturation method at temperatures and pressures up to 473 K and 7 MPa where Raman spectra of the saturated liquid phase are recorded in parallel. By selecting an appropriate frequency range attributed to the LOHC signatures in isotropic spectra, a calibration which is independent of the LOHC system, the degree of hydrogenation of the LOHC samples, and temperature can be found. The transfer of the calibration to another setup is successfully tested up to 523 K and 6 MPa, where H2 solubilities in the fully hydrogenated o-BT can be determined with an average absolute deviation of 0.009 from theoretically calculated data.

Communication—The Development of a Stable and Practical Saturated Reference Electrode for Molten Chloride Salt Systems

A simply constructed, stable, Ni/Ni2+ saturated reference electrode (SRE) has potential to measure thermodynamic behavior of molten chloride salts more reliably. Like the Ag/Ag+ reference electrode (RE), the Ni/Ni2+ SRE is made of commercially available materials. Initial experiments in molten CaCl2 and LiCl show the Ag/Ag+ RE potential drifting two times faster than the SRE. Furthermore, experiments show the replicability of SREs by comparing two Ni/Ni2+ SREs with different compositions of NiCl2 which is supportive of saturated phase behavior.

Reduced Switch Multilevel Inverter Based Shunt Active Power Filter With ANN Controller for Power Quality Improvement

In order to improve power quality, this research investigates the use of SAPF with Seventeen Level Reduced Switch Multilevel Inverter. The electricity grid's stability is significantly influenced by various non-linear loads. To address this, SAPF is proposed and designed to monitor, manage the current movement between the power source and the load. The variance between the intended and real currents drawn from utility grid is assessed using p-q theory based hysteresis current controller. The calculated error current guides the controllers in forecasting the best-suited switching signals and modulation index for the seventeen level RSMLI-SAPF system. In this paper the traditional PI controller, Artificial Neural Network based controller are compared and the results are provided to validate the performance of SAPF. The proposed system is modelled and analysed using MATLAB/Simulink. The simulation results are provided for various modulation index using Hybrid Pulse Width Modulation in which Triangle saturated Phase disposition PWM using Unipolar Third harmonic injection as Reference is used and are subjected to non-linear loads.