Related papers: Nuclear liquid-gas phase transition with machine l…
We apply the chiral SU(3) quark mean field model to study the properties of strange hadronic matter at finite temperature. The liquid-gas phase transition is studied as a function of the strangeness fraction. The pressure of the system…
Around a glass transition, the dynamics of a supercooled liquid dramatically slow down, exhibited by caging of particles, while the structural changes remain subtle. In alternative to recent machine learning studies searching for structural…
We present results and discuss methods for computing the melting temperature of dense molecular hydrogen using a machine learned model trained on quantum Monte Carlo data. In this newly trained model, we emphasize the importance of accurate…
We discuss the dependence of the phase diagram of a hypothetical isotope of helium with nuclear mass less than 4 atomic mass units. We argue that with decreasing nucleus mass, the temperature of the superfluid phase transition (about 2.2 K…
Infrared thermography is a powerful tool for studying liquid-to-vapor phase change processes. However, its application has been limited in the study of vapor-to-liquid phase transitions due to the presence of complex liquid dynamics,…
By relating the charge multiplicity distribution and the temperature of a de-exciting nucleus through a deep neural network, we propose that the charge multiplicity distribution can be used as a thermometer of heavy-ion collisions. Based on…
Machine learning algorithms have been available since the 1990s, but it is much more recently that they have come into use also in the physical sciences. While these algorithms have already proven to be useful in uncovering new properties…
The thermodynamic properties of nuclei are studied in a mean field model using a Skryme interaction. Properties of two component systems are investigated over the complete range of proton fraction from a system of pure neutrons to a system…
Progress on nuclear liquid gas phase transition (LGPT) or critical behavior has been simply reviewed and some signals of LGPT in heavy ion collisions, especially in NIMROD data, are focused. These signals include the power-law charge…
We numerically analyze recent high energy heavy-ion collision experiments based on a hydrodynamical model with phase transition and discuss a systematic change of initial state of QGP-fluid depending on colliding-nuclei's mass. In a…
Background: The advent of new dedicated experimental programs on hyperon physics is rapidly boosting the field, and the possibility of synthetizing multiple strange hypernuclei requires the addition of the strangeness degree of freedom to…
Obtaining the atomistic structure and dynamics of disordered condensed phase systems from first principles remains one of the forefront challenges of chemical theory. Here we exploit recent advances in periodic electronic structure to show…
We estimate the nuclear saturation density and the binding energy in a nuclear liquid from precision data on the coupling of the four-quark scattering vertex in the vector channel, computed within functional QCD. We show that this coupling…
Identifying phase transitions and classifying phases of matter is central to understanding the properties and behavior of a broad range of material systems. In recent years, machine-learning (ML) techniques have been successfully applied to…
Temperature is a fundamental regulator of chemical and biochemical kinetics, yet capturing nonlinear thermal effects directly from experimental data remains a major challenge due to limited throughput and model flexibility. Recent advances…
The phenomenon of nuclear liquid-gas phase transition is a topic of contemporary interest. In heavy-ion collisions, there is no direct way of accessing the thermodynamic variables like pressure, density, free energy, entropy etc., and…
We develop a transferable machine learning model which predicts structural relaxation from amorphous supercooled liquid structures. The trained networks are able to predict dynamic heterogeneity across a broad range of temperatures and time…
Critical heat flux is a key quantity in boiling system modeling due to its impact on heat transfer and component temperature and performance. This study investigates the development and validation of an uncertainty-aware hybrid modeling…
Power transformers are an important component of a nuclear power plant (NPP). Currently, the NPP operates a lot of power transformers with extended service life, which exceeds the designated 25 years. Due to the extension of the service…
The liquid-gas phase transition in hot neutron-rich nuclear matter is investigated within a self-consistent thermal model using different interactions with or without isospin and/or momentum dependence. The boundary of the phase-coexistence…