Critical Fluctuations Research Articles

Criticality-enhanced precision in phase thermometry

Temperature estimation of interacting quantum many-body systems is both a challenging task and topic of interest in quantum metrology, given that critical behavior at phase transitions can boost the metrological sensitivity. Here we study noninvasive quantum thermometry of a finite, two-dimensional Ising spin lattice based on measuring the dephasing dynamics of a spin probe coupled to the lattice. We demonstrate a strong critical enhancement of the achievable precision in terms of the quantum Fisher information, which depends on the coupling range and the interrogation time. Our numerical simulations are compared to instructive analytic results for the critical scaling of the sensitivity in the Curie-Weiss model of a fully connected lattice and to the mean-field description in the thermodynamic limit, both of which fail to describe the critical spin fluctuations on the lattice the spin probe is sensitive to. Phase metrology could thus help to investigate the critical behavior of finite many-body systems beyond the validity of mean-field models. Published by the American Physical Society 2024

Flexible design of renewable hydrogen production systems through identifying bottlenecks under uncertainty

Renewable hydrogen production technology within the energy sector stands as a vital avenue towards decarbonization in process industries. However, for systems characterized by high penetration of renewable energy, the challenges posed by uncertain parameters impacting stable production present significant obstacles to the large-scale application of hydrogen production from renewable energy. To address the issues, this work proposed a comprehensive four-step strategy for the bottleneck identification and optimization of the renewable hydrogen production systems (RHPS), which encompasses four models including system configuration optimization, flexibility analysis, bottleneck identification, and debottlenecking models. The effectiveness of the proposed strategy is substantiated through a case study. The results indicate that positive fluctuations on supply side and negative fluctuations on demand side contribute to bolstering the flexibility of RHPS. When the RHPS possesses sufficient flexibility, the critical fluctuation amplitude for photovoltaic power is −36 %, whereas for wind turbine power, it stands at −32 %. It highlights that when the photovoltaic power fluctuates, the ability of RHPS to maintain its own stability is stronger than when the wind turbine power fluctuates. Furthermore, when the fluctuations of supply side are positive, the rate of change in critical fluctuation amplitudes on the supply side is 4.63 times than that of the demand side. This underscores that the power decline in the supply side has a more pronounced detrimental effect on the stability of RHPS than an increase in the demand side. The proposed strategy for optimizing RHPS offers valuable theoretical insights for the system design and retrofitting under uncertainty.

Multispectral Insights into Turbidity Variations Over Time in The Derawan Island

Abstract This investigation delves into the temporal and spatial dynamics of turbidity in the Derawan Islands, Indonesia, utilizing a comprehensive approach that combines multispectral satellite imagery from Sentinel-2, in-situ measurements via AAQ Licor sensors across 165 observation stations, and continuous data collection from a Turbidity Logger. Situated within the Coral Triangle, understanding the turbidity variations in the Derawan Islands is crucial for the conservation and sustainable management of its marine ecosystems. Our research developed and validated empirically derived algorithms to accurately estimate turbidity, utilizing a strategic partition of in-situ data—70% for model development and 30% for validation. This approach resulted in robust models, demonstrating their efficacy with Root Mean Square Error (RMSE) values as low as 0.85 and R-Squared (R2) values up to 0.56, indicating a high degree of accuracy in satellite-derived turbidity measurements. The study unveiled significant spatial and temporal turbidity heterogeneity, linking these variations to both natural and anthropogenic factors. The high-resolution data from the Turbidity Logger revealed critical diurnal fluctuations and short-term turbidity events, providing insights into the dynamic marine environment of the Derawan Islands.

Divergence of Critical Fluctuations on Approaching Catastrophic Phase Inversion in Turbulent Emulsions.

Catastrophic phase inversion, the breakdown of a concentrated emulsion characterized by the most puzzling sudden feature, is crucial in numerous industrial applications. Here we combine well-controlled experiments and fully resolved numerical simulations to study the critical dynamics of catastrophic phase inversion in oil-water emulsions under turbulent flow as the phase-inversion volume fraction is approached. We reveal that the phase inversion is characterized by the critical power-law divergence of fluctuations in the global drag force. We determine the enhanced dynamical heterogeneity in the local droplet structures at approaching the phase inversion, and tightly connect it to the diverging drag fluctuations. Moreover, we show that near to the critical point the phase inversion is triggered as a stochastic process by large fluctuations at both large and small scales. Our findings pave the way to modeling the phase inversion process as an out-of-equilibrium critical-like phenomena.

Pressure-Tuned Quantum Criticality in the Locally Noncentrosymmetric Superconductor CeRh_{2}As_{2}.

The unconventional superconductor CeRh_{2}As_{2} (critical temperature T_{c}≈0.4 K) displays an exceptionally rare magnetic-field-induced transition between two distinct superconducting (SC) phases, proposed to be states of even and odd parity of the SC order parameter, which are enabled by a locally noncentrosymmetric structure. The superconductivity is preceded by a phase transition of unknown origin at T_{0}=0.5 K. Electronic low-temperature properties of CeRh_{2}As_{2} show pronounced non-Fermi-liquid behavior, indicative of a proximity to a quantum critical point (QCP). The role of quantum fluctuations and normal state orders for the superconductivity in a system with staggered Rashba interaction is currently an open question, pertinent to explaining the occurrence of the two-phase superconductivity. In this work, using measurements of resistivity and specific heat under hydrostatic pressure, we show that the T_{0} order vanishes completely at a modest pressure of P_{0}≈0.5 GPa, revealing a QCP. In line with the quantum criticality picture, the linear temperature dependence of the resistivity at P_{0} evolves into a Fermi-liquid quadratic dependence as quantum critical fluctuations are suppressed by increasing pressure. Furthermore, the domelike behavior of T_{c} around P_{0} implies that the fluctuations of the T_{0} order are involved in the SC pairing mechanism.

Experimental Investigation of the Heaving Motion Effect on Critical Heat Flux Phenomena and Wall Temperature Fluctuation Using R134a for Floating Nuclear Applications

This study experimentally investigated the flow boiling critical heat flux (CHF) under heaving conditions pertinent to floating nuclear power plants (FNPPs). Experiments were conducted using R134a to simulate the operational pressure of pressurized water reactors, extending the CHF database to a pressure range of 5 to 18 MPa. The tested heaving motion reached up to 0.6 g of maximum acceleration, with a period that varied from 3 to 5.3 s. A parametric trend involving mass flux, critical quality, and motion conditions was analyzed through extensive tests encompassing static and heaving conditions. The results showed that CHF reduction was observed due to the effect of heaving acceleration, even in the absence of oscillations in other thermal-hydraulic factors. The CHF reduction was up to 9% in the present experimental conditions. The heaving motion effect was prominent under two specific thermal-hydraulic conditions: when the critical quality was close to zero and when it exceeded the value of 0.6. Furthermore, an examination of wall temperature responses suggested that a longer period of heaving motion can lead to an earlier occurrence of CHF. This fundamental effort was conducted to enhance the understanding of the CHF mechanism under motion conditions, with the aim of contributing to the safe and efficient design of FNPPs.

Linking excess entropy and acentric factor in spherical fluids.

Introduced by Pitzer in 1955, the acentric factor (ω) has been used to evaluate a molecule's deviation from the corresponding state principle. Pitzer devised ω based on a concept called perfect liquid (or centric fluid), a hypothetical species perfectly adhering to this principle. However, its physical significance remains unclear. This work attempts to clarify the centric fluid from an excess entropy perspective. We observe that the excess entropy per particle of centric fluids approximates -kB at their critical points, akin to the communal entropy of an ideal gas in classical cell theory. We devise an excess entropy dissection and apply it to model fluids (square-well, Lennard-Jones, Mie n-6, and the two-body abinitio models) to interpret this similarity. The dissection method identifies both centricity-independent and centricity-dependent entropic features. Regardless of the acentric factor, the attractive interaction contribution to the excess entropy peaks at the density where local density is most enhanced due to the competition between the local attraction and critical fluctuations. However, only in centric fluids does the entropic contribution from the local attractive potential become comparable to that of the hard sphere exclusion, making the centric fluid more structured than acentric ones. These findings elucidate the physical significance of the centric fluid as a system of particles where the repulsive and attractive contributions to the excess entropy become equal at its gas-liquid criticality. We expect these findings to offer a way to find suitable intermolecular potentials and assess the physical adequacy of equations of state.

Optimization of crossover SRK equation of state for thermodynamic properties calculation of CO2

In recent years, the CO2 super/transcritical power cycle has gained significant attention as the most widely studied power cycle. The accurate thermodynamic properties data is very important for cycle design and performance analysis. In this study, the Kiselev's crossover method based on the renormalization group theory is used to improve the classic SRK equation of state in non-critical region and reproduce the critical fluctuation phenomenon in critical region. The nonlinear equations method and interior-point method are used in the parameter fitting of crossover SRK (CSRK) to get the optimal parameters. The replaced method avoids the problem that Newton iteration method is prone to divergence and falling into local optima. The thermodynamic properties of CO2 including the VLE properties, heat capacity and speed of sound are calculated by CSRK, respectively. The results show the calculation of the non-critical region is improved, and the critical fluctuation phenomenon in the near-critical region is described accurately, especially the second-order thermodynamic properties calculation results is improved from 3.65 % to 2.80 % compared with our previous work.

Experimental study on road deicing using circulated heating produced from geothermal fluid

In this study, a ground source heat pump was employed as an energy source to perform preheating and deicing tests on asphalt pavement using hydraulic heating.The influence of different water temperature and ambient temperature on the temperature distribution of road system, energy consumption of heat pump system, energy consumption ratio between road system and heat pump system (COPsys) in preheating test was studied, and the influence of road temperature and deicing performance (qice) in deicing test was studied. The results show that during the preheating phase, increasing the water temperature from 40 °C to 50 °C resulted in COPsys drop of 46 %, and when the ambient temperature is reduced from −5 °C to −10 °C, resulted in a COPsys increase of 26 %. In the de-icing experimental, a higher critical temperature for de-icing indicates more energy stored at the surface, and greater temperature fluctuations during the melting phase indicate better ice melting effects. Lowering the ambient temperature increases the critical de-icing temperature and reduces temperature fluctuations during the melting phase. Increasing the water temperature increases the critical de-icing temperature and temperature fluctuations during the melting phase.

Monte Carlo simulations of the blinking-checkers model for polyamorphic fluids

The blinking-checkers model [F. Caupin and M. A. Anisimov, Phys. Rev. Lett, 127,185701 (2021)] is a minimal lattice model which has demonstrated that, in the meanfield approximation, it can reproduce the phenomenon of fluid polyamorphism. This model is a binary lattice-gas, in which each site has three possible states: empty, occupied with particles of type 1, and occupied with particles of type 2. Additionally, the two types of particles may interconvert from one to another. Equilibrium interconversion imposes a constraint that makes this model thermodynamically equivalent to a single-component system. In this work, Monte-Carlo simulations of the blinking-checkers model are performed, demonstrating polyamorphic phase behaviour. The locations of the liquid-liquid and liquid-gas critical points are found to be different from the meanfield predictions for this model with the same interaction parameters, as the phase behaviour is significantly affected by critical fluctuations. Based on the computed values of the critical exponents of the order parameter, susceptibility, correlation length, and surface tension, we confirm that the blinking-checkers model, for both liquid-gas and liquid-liquid equilibria, belongs to the three-dimensional Ising class of critical-point universality.

Coordinate versus momentum cuts and effects of collective flow on critical fluctuations

We analyze particle number fluctuations in the crossover region near the critical endpoint of a first-order phase transition by utilizing molecular dynamics simulations of the classical Lennard-Jones fluid. We extend our previous study [V. A. Kuznietsov , ] by incorporating longitudinal collective flow. The scaled variance of particle number distribution inside different coordinate and momentum space acceptances is computed through ensemble averaging and found to agree with earlier results obtained using time averaging, validating the ergodic hypothesis for fluctuation observables. Presence of a sizable collective flow is found to be essential for observing large fluctuations from the critical point in momentum space acceptances. We discuss our findings in the context of heavy-ion collisions. Published by the American Physical Society 2024

Simulations of Stochastic Fluid Dynamics near a Critical Point in the Phase Diagram.

We present simulations of stochastic fluid dynamics in the vicinity of a critical endpoint belonging to the universality class of the Ising model. This study is motivated by the challenge of modeling the dynamics of critical fluctuations near a conjectured critical endpoint in the phase diagram of quantum chromodynamics (QCD). We focus on the interaction of shear modes with a conserved scalar density, which is known as model H. We show that the observed dynamical scaling behavior depends on the correlation length and the shear viscosity of the fluid. As the correlation length is increased or the viscosity is decreased we observe a crossover from the dynamical exponent of critical diffusion, z≃4, to the expected scaling exponent of model H, z≃3. We use our method to investigate the time-dependent correlation function of non-Gaussian moments M^{n}(t) of the order parameter. We find that the relaxation time depends in a nontrivial manner on the power n.

Comparative Analysis of Machine Learning Models for Predicting the Mechanical Behavior of Bio-Based Cellular Composite Sandwich Structures.

The growing demand for sustainable materials has significantly increased interest in biocomposites, which are made from renewable raw materials and have excellent mechanical properties. The use of machine learning (ML) can improve our understanding of their mechanical behavior while saving costs and time. In this study, the mechanical behavior of innovative biocomposite sandwich structures under quasi-static out-of-plane compression was investigated using ML algorithms to analyze the effects of geometric variations on load-bearing capacities. A comprehensive dataset of experimental mechanical tests focusing on compression loading was employed, evaluating three ML models-generalized regression neural networks (GRNN), extreme learning machine (ELM), and support vector regression (SVR). Performance indicators such as R-squared (R2), mean absolute error (MAE), and root mean square error (RMSE) were used to compare the models. It was shown that the GRNN model with an RMSE of 0.0301, an MAE of 0.0177, and R2 of 0.9999 in the training dataset, and an RMSE of 0.0874, MAE of 0.0489, and R2 of 0.9993 in the testing set had a higher predictive accuracy. In contrast, the ELM model showed moderate performance, while the SVR model had the lowest accuracy with RMSE, MAE, and R2 values of 0.5769, 0.3782, and 0.9700 for training, and RMSE, MAE, and R2 values of 0.5980, 0.3976 and 0.9695 for testing, suggesting that it has limited effectiveness in predicting the mechanical behavior of the biocomposite structures. The nonlinear load-displacement behavior, including critical peaks and fluctuations, was effectively captured by the GRNN model for both the training and test datasets. The progressive improvement in model performance from SVR to ELM to GRNN was illustrated, highlighting the increasing complexity and capability of machine learning models in capturing detailed nonlinear relationships. The superior performance and generalization ability of the GRNN model were confirmed by the Taylor diagram and Williams plot, with the majority of testing samples falling within the applicability domain, indicating strong generalization to new, unseen data. The results demonstrate the potential of using advanced ML models to accurately predict the mechanical behavior of biocomposites, enabling more efficient and cost-effective development and optimization processes in the field of sustainable materials.

Anatomy of critical fluctuations in hadronic matter

Critical phenomena in phase transitions of strongly interacting matter, governed by quantum chromodynamics, are inherently encoded in the fluctuations of conserved charges. In this work, we study the net-baryon number density fluctuations, including the lowest-lying nucleon and the baryonic resonance Δ(1232), based on the parity doublet model in the mean-field approximation. We focus on the qualitative features of the second-order susceptibility of the net-baryon number density in dense hadronic matter and how the inclusion of Δ(1232) affects it. We demonstrate that the fluctuations of the individual baryons do not necessarily reflect the total net-baryon number fluctuations at finite density, due to the nontrivial correlations between different particle species. Our results highlight the role of baryonic correlations in the interpretation of data from heavy ion collision experiments. Published by the American Physical Society 2024

Are Critical Fluctuations Responsible for Glass Formation?

The dynamic heterogeneities occurring just before the transition to the glassy phase have been named as the cause of amorphization in supercooled systems. Numerous studies conducted so far have confirmed this hypothesis, and based on it, a widely accepted solution to the puzzle of glass transition has been developed. This report focuses on verifying the existence of a strong pretransitional anomaly near the glass transition Tg. For this purpose, supercooled liquid-crystalline systems with a strong rod-like structure were selected. Based on the obtained experimental data, we demonstrate in this article that the previously postulated dynamic heterogeneities exhibit a critical characteristic, meaning a strong pretransitional anomaly can be observed with the described critical exponent α=0.5. Due to this property, it can be concluded that these heterogeneities are critical fluctuations, and consequently, the transition to the glassy state can be described based on the theory of critical phenomena. To measure the pretransitional anomaly near Tg in supercooled liquid-crystalline systems, broadband dielectric spectroscopy (BDS) and nonlinear dielectric effect (NDE) methods were applied. The exponent α provides insight into the nature and intensity of critical fluctuations in the system. A value of α=0.5 suggests that the fluctuations become increasingly intense as the system approaches the critical point, contributing to the divergence in specific heat. Understanding the role of critical fluctuations in the glass transition is crucial for innovating and improving a wide range of materials for energy storage, materials design, biomedical applications, food preservation, and environmental sustainability. These advancements can lead to materials with superior properties, optimized manufacturing processes, and applications that meet the demands of modern technology and sustainability challenges.

Interplay between short-range and critical long-range fluctuations in the out-of-equilibrium behavior of the particle density at quantum transitions

Interplay between short-range and critical long-range fluctuations in the out-of-equilibrium behavior of the particle density at quantum transitions

Random Field Ising Model Criticality in a Complex Binary Liquid System.

While Ising criticality in classical liquids has been firmly established both theoretically and experimentally, much less is known about criticality in liquids in which the growth of the correlation length is frustrated by finite-size effects. A theoretical approach for dealing with this issue is the random-field Ising model (RFIM). While experimental critical-exponent values have been reported for magnetic samples (here, we consider γ, ν and η), little experimental information is available for critical fluctuations in corresponding liquid systems. In this paper, we present a study on a binary liquid consisting of 3-methyl pyridine and heavy water in a very light-weight porous gel. We find that the experimental results are in agreement with the theoretical predictions from the RFIM.

Exceptionally Slow, Long-Range, and Non-Gaussian Critical Fluctuations Dominate the Charge Density Wave Transition.

(TaSe_{4})_{2}I is a well-studied quasi-one-dimensional compound long-known to have a charge-density wave (CDW) transition around 263K. We argue that the critical fluctuations of the pinned CDW order parameter near the transition can be inferred from the resistance noise on account of their coupling to the dissipative normal carriers. Remarkably, the critical fluctuations of the CDW order parameter are slow enough to survive the thermodynamic limit and dominate the low-frequency resistance noise. The noise variance and relaxation time show rapid growth (critical opalescence and critical slowing down) within a temperature window of ϵ≈±0.1, where ϵ is the reduced temperature. This is very wide but consistent with the Ginzburg criterion. We further show that this resistance noise can be quantitatively used to extract the associated critical exponents. Below |ϵ|≲0.02, we observe a crossover from mean-field to a fluctuation-dominated regime with the critical exponents taking anomalously low values. The distribution of fluctuations in the critical transition region is skewed and strongly non-Gaussian. This non-Gaussianity is interpreted as the breakdown of the validity of the central limit theorem as the diverging coherence volume becomes comparable to the macroscopic sample size. The large magnitude critical fluctuations observed over an extended temperature range, as well as the crossover from the mean-field to the fluctuation-dominated regime highlight the role of the quasi-one-dimensional character in controlling the phase transition.

Yielding Is an Absorbing Phase Transition with Vanishing Critical Fluctuations.

The yielding transition in athermal complex fluids can be interpreted as an absorbing phase transition between an elastic, absorbing state with high mesoscopic degeneracy and a flowing, active state. We characterize quantitatively this phase transition in an elastoplastic model under fixed applied shear stress, using a finite-size scaling analysis. We find vanishing critical fluctuations of the order parameter (i.e., the shear rate), and relate this property to the convex character of the phase transition (β>1). We locate yielding within a family of models akin to fixed-energy sandpile (FES) models, only with long-range redistribution kernels with zero modes that result from mechanical equilibrium. For redistribution kernels with sufficiently fast decay, this family of models belongs to a short-range universality class distinct from the conserved directed percolation class of usual FES, which is induced by zero modes.

Nuclear magnetic resonance studies in a model transverse field Ising system

The suppression of ferroquadrupolar order in TmVO4 in a magnetic field is well-described by the transverse field Ising model, enabling detailed studies of critical dynamics near the quantum phase transition. We describe nuclear magnetic resonance measurements in pure and Y-doped single crystals. The non-Kramers nature of the ground state doublet leads to a unique form of the hyperfine coupling that exclusively probes the transverse field susceptibility. Our results show that this quantity diverges at the critical field, in contrast to the mean-field prediction. Furthermore, we find evidence for quantum critical fluctuations present near Tm-rich regions in Y-doped crystals at levels beyond which long-range order is suppressed, suggesting the presence of quantum Griffiths phases.