Phase Transition Point Research Articles

Dynamic mesophase transition induces anomalous suppressed and anisotropic phonon thermal transport

The physical/chemical properties undergo significant transformations in the different states arising from phase transition. However, due to the lack of a dynamic perspective, transitional mesophases are largely underexamined, constrained by the high resource burden of first principles. Here, using molecular dynamics (MD) simulations empowered by the machine-learning potential, we proffer an innovative paradigm for phase transition: regulating the thermal transport properties via the transitional mesophase triggered by a uniaxial force field. We investigate the mechanical, electrical, and thermal transport properties of the two-dimensional carbon allotrope of Janus-graphene with strain-engineered phase transition. Notably, we found that the transitional mesophase significantly suppresses the thermal conductivity and induces strong anisotropy near the phase transition point. Through machine-learning-driven MD simulations, we achieved high-precision atomic-level simulations of Janus-graphene. The results show that thermal vibration-induced intermediate amorphous or interfacial phases induce strong and anisotropic interfacial thermal resistance. The investigation not only endows us with a novel perspective on mesophases during phase transitions but also enhances our holistic comprehension of the evolution of material properties.

The studies of topological phases and energy braiding of non-Hermitian models using machine learning

Abstract Complex-energy bands in non-Hermitian systems can exhibit diverse topological braiding, yet identifying these braids remains challenging and has garnered limited attention in previous studies. In this work, we explore energy braiding in one-dimensional non-Hermitian systems through both unsupervised and supervised learning techniques. For unsupervised learning, we apply diffusion maps to effectively identify non-Bloch energy braiding without requiring prior knowledge and use k-means clustering to categorize different topological features, such as Unlink and Hopf link configurations. In the supervised learning phase, we train a Convolutional Neural Network (CNN) on Bloch energy data to predict both Bloch and non-Bloch energy braiding with nearly $100\%$ accuracy. Through an analysis of the CNN, we confirm that the model has successfully developed the capacity to recognize the braiding topology of the energy bands. Our findings reveal that unsupervised learning can rapidly detect phase transition points, while the CNN is capable of predicting braid degrees even for models not included in the training set.

Analysis on hot deformation behavior and microstructural evolution of TA10 alloy smelted with the electron beam furnace

Abstract This article uses EB furnace to prepare TA10 alloy ingots with higher purity. Studying their hot deformation behavior and microstructure evolution can provide theoretical support for practical processes.The hot deformation behavior of TA10 alloy smelted via an electron beam furnace has been studied using thermal deformation experiments, the experiments were conducted from 800 °C to 1,050 °C, from 0.01 s−1 to 1 s−1 and a reduction to 60%. According to Arrhenius and Zener-Hollomon models, the constitutive equation can be constructed. TEM and EBSD aimed at exploring the microstructures and microstructural evolution, respectively. When deformed at the temperatures below the phase transition point, grain boundaries converted to large-angle gradually. The textural strength reduced when the strain rate increased. Besides, the recrystallization rate was relatively small, mainly dynamic recovery, and there was a tendency to turn into dynamic recrystallization. At the temperature higher than the phase transition point, the textural strength increased, the recrystallization rate was small, and the dynamic recovery was partially enhanced.

Composite Shell Microcapsules With Room Temperature Phase‐Change Properties and High Thermal Storage Density

AbstractInorganic hydrated salts, noted for their high thermal storage density, excellent thermal conductivity, and non‐toxicity, are suitable candidate material for thermal management, particularly in enhancing human living environments when their phase transition points are near room temperature. Herein, we present an efficient and environmentally friendly microencapsulation method for inorganic hydrated salt through organic phase separation method. Eutectic hydrated salt (EHS) consisted of sodium carbonate decahydrate (SCD) and disodium hydrogen phosphate dodecahydrate (DHPD) was prepared as the core material while the mixture of ethyl cellulose (EC) and acrylonitrile‐butadiene‐styrene (ABS) as composite shell materials. Various characterization techniques were used to evaluate the micromorphology, chemical structure, thermal properties and thermal stability of the microcapsules. The resulting microcapsules exhibited a phase change temperature of 22.6 °C with a remarkable enthalpy of 131.4 J/g. Particularly, the enthalpy remained at 117.7 J/g even after 50 thermal cycles, indicating stable cycling thermal reliability. Furthermore, it was confirmed that the EHS was effectively encapsulated within the composite shell, and the microcapsules had a quasi‐spherical shape and core‐shell structure. More importantly, this method of microencapsulation could potentially be extended to other liquid hydrated salts at room temperature, offering a versatile approach for future applications.

Water phase transition and signal nulling in 3D dual-echo adiabatic inversion-recovery UTE (IR-UTE) imaging of myelin.

The semisolid myelin sheath has very fast transverse relaxation and is invisible to conventional MRI sequences. UTE sequences can detect signal from myelin. The major challenge is the concurrent detection of various water components. The inversion recovery (IR)-based UTE (IR-UTE) sequence employs an adiabatic inversion pulse to invert and suppress water magnetizations. TI plays a key role in water suppression, with negative water magnetizations (negative phase) before the null point and positive water magnetizations (positive phase) after the null point. A series of dual-echo IR-UTE images were acquired with different TIs to detect water phase transition. The effects of TR in phase transition and water suppression were also investigated using a relatively long TR of 500 ms and a short TR of 106 ms. The water phase transition in dual-echo IR-UTE imaging of myelin was investigated in five ex vivo and five in vivo human brains. An apparent phase transition was observed in the second echo at the water signal null point, where the myelin signal was selectively detected by the UTE data acquisition at the optimal TI. The water phase transition point varied significantly across the brain when the long TR of 500 ms was used, whereas the convergence of TIs was observed when the short TR of 106 ms was used. The results suggest that the IR-UTE sequence with a short TR allows uniform inversion and nulling of water magnetizations, thereby providing volumetric imaging of myelin.

Manifestation of super chiral exceptional points in a plasmonic metasurface

The exceptional point (EP), a degenerate point within non-Hermitian parametric space, has attracted considerable attention, especially for its chiral responses. However, achieving ideal circular dichroism (CD) remains challenging due to the existence of parallel components at the EP. Here, we delve into the theoretical condition required to attain a zero-transmission parallel component. This condition, together with the chiral EP condition, leads to a point characterized by near-unity CD, termed the super chiral EP (SCEP). To illustrate our theoretical framework, we introduce a parity-time symmetric metasurface with gain and loss. The observation of SCEP is demonstrated by tuning both the coupling strength and gain–loss ratio. Furthermore, we explore distinctive properties of SCEP, including phase flip and unidirectional invisibility. Leveraging SCEP and the topological phase transition point, we achieve polarization states across the entire Poincaré surface. This work opens avenues for potential applications in polarizing optical elements, holography, logic gates, chiral molecular detection, ultrasensitive sensing, and polarization-sensitive imaging.

Propagation of chaos in the random field Curie–Weiss model

Abstract We prove quenched propagation of chaos in the Random field mean-field Ising model, also known ad the Random field Curie–Weiss model. We show that in the paramagnetic phase, i.e. in the regime where temperature and distribution of the external field admit a unique minimizer of the expected Helmholtz free energy, quenched propagation of chaos holds. By the latter we mean that the finite-dimensional marginals of the Gibbs measure converge towards a product measure with the correct expectation as the system size goes to infinity. This holds independently of whether the system is in a high-temperature phase or at a phase transition point and alsmost surely with respect to the random external field. If the Helmholtz free energy possesses several minima, there are several possible equilibrium measures. In this case, we show that the system picks one of them at random (depending on the realization of the random external field) and propagation of chaos with respect to a product measure with the same marginals as the one randomly picked holds true. We illustrate our findings in a simple example.

Revisiting thermodynamic topology of Hawking-Page and Davies type phase transitions

In this work, we propose a common vector field to study the thermodynamic topology of the Davies type and Hawking-Page phase transitions. Existing literature has shown that studying these two types of phase transitions typically requires defining two separate vector fields. In our approach, we adopt Duan's ϕ-mapping topological current theory to define a novel vector field, denoted as ϕ, whose critical points exactly correspond to the Davies point and the Hawking-Page phase transition point. More importantly, we can differentiate between these two points by their topological charge. While, the topological charge for the critical point corresponding to the Davies-type phase transition is found to be −1, the same for the Hawking-Page phase transition point, it is +1. Although our analysis is applicable to all black hole systems where both types of phase transitions are found, we illustrate it using three simple systems as examples: the Schwarzschild AdS black hole, the Reissner-Nordström AdS black hole in the grand canonical ensemble, and finally the Kerr AdS black holes in the grand canonical ensemble. It is well-known that these black holes exhibit both Davies and Hawking-Page phase transitions. With our proposed vector ϕ, the critical points obtained for these three systems exactly match the Davies-type and Hawking-Page phase transition points, and the associated topological charges are found to be −1 for the Davies point and +1 for the Hawking-Page phase transition point.

Simultaneous enhancement of the strength and plasticity of Fe[sbnd]12Mn steel through modulating grain morphology

The relationship between grain morphology and tensile properties of Fe-12Mn steel thermo-mechanically processed by rolling annealing and re-cold rolling processes was investigated. The results indicated that the re-cold rolling deformed the mostly austenite grain morphology from equiaxed to lamellar, and the steel exhibited a yield strength of 1295 MPa, tensile strength of 1518 MPa, and elongation of 18 %. Compared to the experimental steel without re-cold rolling processes, more than 300 MPa tensile strength was improved and elongation increased from 14 % to 18 %. The steel demonstrated remarkable enhancement in mechanical properties owing to the “multistage TRIP effect”, which referred to the sequential martensitic phase transformation of austenite with varying stability as the strain increased. The change in grain morphology reduced the rate of twin formation and increased the nucleation point of the martensitic phase transition, this also stabilized the retained austenite by increasing the hard phases surrounding the retained austenite, which had multistage stability. These factors contributed to the “multistage TRIP effect”, which could be sustained to higher strains and presented regular fluctuations in work-hardening rates

Novel first-order phase transition and critical points in SU(3) Yang-Mills theory with spatial compactification

We investigate the thermodynamics and phase structure of SU(3) Yang-Mills theory on T2×R2 in Euclidean spacetime in an effective-model approach. The model incorporates two Polyakov loops along two compactified directions as dynamical variables, and is constructed to reproduce thermodynamics on T2×R2 measured on the lattice. The model analysis indicates the existence of a novel first-order phase transition on T2×R2 in the deconfined phase, which terminates at critical points that should belong to the two-dimensional Z2 universality class. We argue that the interplay of the Polyakov loops induced by their cross-term in the Polyakov-loop potential is responsible for the manifestation of the first-order transition. Published by the American Physical Society 2024

CFTD from TQFTD+1 via Holographic Tensor Network, and Precision Discretization of CFT2

We show that the path integral of conformal field theories in D dimensions (CFTD) can be constructed by solving for eigenstates of a renormalization group (RG) operator following from the Turaev-Viro formulation of a topological field theory (topological quantum field theory) (TQFT) in D+1 dimensions (TQFTD+1), explicitly realizing the holographic sandwich relation between a symmetric theory and a TQFT. Generically, exact eigenstates corresponding to symmetric TQFTD follow from Frobenius algebra in TQFTD+1. For D=2, we construct eigenstates that produce 2D rational CFT path integrals exactly, which curiously connect a continuous-field theoretic path integral with the Turaev-Viro state sum. We also devise and illustrate numerical methods for D=2, 3 to search for CFTD as phase transition points between symmetric TQFTD. Finally, since the RG operator is in fact an exact analytic holographic tensor network, we compute “bulk-boundary” correlators and compare them with the AdS/CFT dictionary at D=2. Promisingly, they are numerically compatible given our accuracy, although further works will be needed to explore the precise connection to the AdS/CFT correspondence. Published by the American Physical Society 2024

Experimental investigation on temperature distribution characteristics inside the condensing tube of the R134a two-phase natural circulation loop

Temperature distribution of two-phase flow inside the condensing tube can effectively reflect the heat transfer characteristic of the fluid, playing a pivotal role in the study of heat transfer in two-phase flow systems. In this study, we use the stainless steel capillary sealed distributed fiber Bragg grating (S-DFBGs) to measure and characterize the temperature distribution of R134a fluid inside the condensing tube under steady-state (pump-driven two-phase circulation) and unsteady-state (type I and II density wave instabilities in two-phase natural circulation loop) conditions, and the frequency and time domain characteristics of the fluid temperature distribution inside the tube has been investigated in detail. Through frequency-domain analysis, the temperature spectrum inside the condensing tube can indentify two types of the instability together with flowrate and pressure. Through time-domain analysis, temperature distribution inside the condenser can dermine the phase transition point, hence the condensation length. Moreover, two types of the instability exhibit different temperature fluctuation characteristics, providing reliable and effective information for further research on two phase natural circulation instability mechanisms.

Corrected thermodynamics and stability of magnetic charged AdS black holes surrounded by quintessence

In this study, we explore the corrected thermodynamics of non-linear magnetic charged anti-de Sitter (AdS) black holes surrounded by quintessence, incorporating thermal fluctuations and deriving the corrected thermodynamic potentials. We analyze the effects of corrections due to thermal fluctuations on various thermodynamic potentials, including enthalpy, Helmholtz free energy, and Gibbs free energy. Our results show significant impacts on smaller black holes, with first-order corrections destabilizing them, while second-order corrections enhance stability with increasing parameter values. The specific heat analysis further elucidates the stability criteria, indicating that the large black holes ensure stability against phase transitions. However, the thermal fluctuations do not affect the physical limitation points as well as the second-order phase transition points of the black hole. Our findings highlight the intricate role of thermal fluctuations in black hole thermodynamics and their influence on stability, providing deeper insights into the behaviour of black holes under corrected thermodynamic conditions.

Simulation of Dynamic Characteristics of Supercritical Boiler Based on Coupling Model of Combustion and Hydrodynamics

To accommodate the integration of renewable energy, coal-fired power plants must take on the task of peak regulation, making the low-load operation of boilers increasingly routine. Under low-load conditions, the phase transition point (PTP) of the working fluid fluctuates, leading to potential flow instability, which can compromise boiler safety. In this paper, a one-dimensional coupled dynamic model of the combustion and hydrodynamics of a supercritical boiler is developed on the Modelica/Dymola 2022 platform. The spatial distribution of key thermal parameters in the furnace and the PTP position in the water-cooled wall (WCW) are analyzed in a 660 MW supercritical boiler when parameters on the combustion side change under full-load and low-load conditions. The dynamic response characteristics of the temperature, mass flow rate, and the PTP position are investigated. The results show that the over-fire air (OFA) ratio significantly influences the flue gas temperature distribution. A lower OFA ratio increases the flue gas temperature in the burner zone but reduces it at the furnace exit. The lower OFA ratio leads to a higher fluid temperature and shortens the length of the evaporation section. The temperature difference in the WCW outlet fluid between the 20% and 60% OFA ratios is 11.7 °C under BMCR conditions and 7.4 °C under 50% THA conditions. Under the BMCR and 50% THA conditions, a 5% increase in the coal caloric value raises the flue gas outlet temperature by 32.7 °C and 35.4 °C and the fluid outlet temperature by 6.5 °C and 9.9 °C, respectively. An increase in the coal calorific value reduces the length of the evaporation section. The changes in the length of the evaporation section are −2.95 m, 2.95 m, −2.62 m, and 0.54 m when the coal feeding rate, feedwater flow rate, feedwater temperature, and air supply rate are increased by 5%, respectively.

Detecting phase transitions based on siamese neural network

Machine learning has been widely applied in physics research. Although unsupervised learning can extract the critical points of phase transitions, the percolation model remains a challenge. Unsupervised learning using the raw configurations of the percolation model fails to capture the critical points. To capture the configuration characteristics of the percolation model, this paper proposes using the maximum cluster as input to the neural network. It is well understood that the order parameter of the percolation model is not simply the particle density, but rather the probability that a given site or bond belongs to the percolating cluster. Additionally, we introduce the use of a Siamese Neural Network (SNN) to detect percolation phase transitions. Unlike unsupervised dimensionality reduction methods or supervised binary classification outputs, the SNN produces a scalar output referred to as similarity. By combining the maximum cluster and the SNN, we not only successfully extract the critical value of the percolation model, but also calculate the correlation exponent via data collapse. We believe that the SNN has great potential in handling phase transition classification problems and can serve as a reference for studying other phase transition systems.

Dynamical signatures of discontinuous phase transitions: How phase coexistence determines exponential versus power-law scaling.

There are conflicting reports in the literature regarding the finite-size scaling of the Liouvillian gap and dynamical fluctuations at discontinuous phase transitions, with various studies reporting either exponential or power-law behavior. We clarify this issue by employing large deviation theory. We distinguish two distinct classes of discontinuous phase transitions that have different dynamical properties. The first class is associated with phase coexistence, i.e., the presence of multiple stable attractors of the system dynamics (e.g., local minima of the free-energy functional) in a finite phase diagram region around the phase transition point. In that case, one observes asymptotic exponential scaling related to stochastic switching between attractors (though the onset of exponential scaling may sometimes occur for very large system sizes). In the second class, there is no phase coexistence away from the phase transition point, while at the phase transition point itself there are infinitely many attractors. In that case, one observes power-law scaling related to the diffusive nature of the system relaxation to the stationary state.

Anomalous Directed Percolation on a Dynamic Network Using Rydberg Facilitation.

The facilitation of Rydberg excitations in a gas of atoms provides an ideal model system to study epidemic evolution on (dynamic) networks and self-organization of complex systems to the critical point of a nonequilibrium phase transition. Using MonteCarlo simulations and a machine learning algorithm we show that the universality class of this phase transition can be tuned but is robust against decay inherent to the self-organization process. The classes include directed percolation (DP), the most common class in short-range spreading models, and mean-field (MF) behavior, but also different types of anomalous directed percolation (ADP), characterized by rare long-range excitation processes. In a frozen gas, ground state atoms that can facilitate each other form a static network, for which we predict DP universality. With atomic motion the network becomes dynamic by long-range (Lévy-flight type) excitations. This leads to continuously varying critical exponents, varying smoothly between DP and MF values, corresponding to the ADP universality class. These findings also explain the recently observed critical exponent of Rydberg facilitation in an ultracold gas experiment [Helmrich etal., Nature (London) 577, 481 (2020)NATUAS0028-083610.1038/s41586-019-1908-6], which was in between DP and MF values.

Molecular simulations of increased thermal energy storage in metal–organic heat carriers with R1234ze(E)/R32 mixtures combined with IRMOF-1

Metal-organic heat carrier (MOHC) nanofluids offer a promising solution to enhance the efficiency of Organic Rankine Cycle systems. In this study, we developed a computational model to assess the thermal energy storage capacity of MOHC nanofluids using a base fluid mixture of R1234ze(E) and R32 refrigerants. Through Grand Canonical Monte Carlo and molecular dynamics simulations, we examined the adsorption characteristics, desorption heat, and thermodynamic properties of MOHCs. Our findings reveal that R32 molecules are preferentially adsorbed in IRMOF-1 compared to R1234ze(E), with adsorption selectivity of R32 over R1234ze(E) increasing under higher adsorption pressures. When the temperature during the endothermic process surpasses the phase transition point of the base fluid, the latent heat of phase transition can be fully exploited to enhance energy storage. Moreover, the inclusion of IRMOF-1 nanoparticles significantly improves the energy storage properties of both R32 and R1234ze(E), as well as their mixtures. The energy storage enhancement provided by IRMOF-1 is particularly pronounced under high working pressures and low temperature differences. These insights offer valuable guidance for selecting appropriate base fluids in MOHC systems, thereby optimizing the utilization of low-grade energy sources.

Electrically charged black holes in [formula omitted]-Euler–Heisenberg theory

Drawing on the concept of the non-linear dynamics of electromagnetic fields in vacuum in terms of the Euler–Heisenberg system, a static and spherically symmetric black hole solution is derived by coupling the Euler–Heisenberg term and F(R) gravity. In applying the curvature singularity tools, the black hole solution induces a singular behaviour at the centre r=0 while exhibiting a regular shape at high distances. Using the heat capacity (CQ) and the Helmholtz free energy (F), we analyse the thermodynamic stability locally and globally. Furthermore, an investigation is conducted using class tools of Geometrothermodynamics (GTs) features such as Weinhold, Ruppeiner, Hendi–Panahiyan–Eslam–Momennia (HPEM), and Quevedo to identify phase transition points associated with heat capacity, including both physical boundary points (root of the heat capacity) and second critical phase transition points (divergent points of the heat capacity). We have even examined the relevant sparsity of Hawking radiation, showing how the black hole solution behaves as a black body at specific limits. Overall, this study enhances our knowledge of the mergers of a class of non-linear dynamics of electromagnetic fields in a vacuum within F(R) gravity by modelling black hole solutions.

Phase transitions in quantum many-body scars

We propose a type of phase transition in quantum many-body systems that occurs in highly excited quantum many-body scar states while most of the spectrum is largely unaffected. Such scar-state phase transitions can be realized by embedding a matrix product state, known to undergo a phase transition, as a scar state into the thermal spectrum of a parent Hamiltonian. We find numerically that the mechanism for the scar-state phase transition involves the formation or presence of low-entropy states at energies similar to the scar state in the vicinity of the phase transition point. Published by the American Physical Society 2024