We investigate the difference between hadron resonance gas (HRG) calculations for chemical freeze-out parameters at fully and partly chemical equilibria. To this end, the results are compared with the particle ratios measured in central Au-Au collisions at a wide range of nucleon-nucleon center-of-mass energies, √ s N N = 7.7 − 200 GeV as offered by the STAR experiment. We restrict the discussion to STAR, because of large statistics and overall homogeneity of STAR measurements (one detector) against previous experiments. We find that the matter produced at these energies is likely in fully chemical equilibrium, which is consistent with recent lattice QCD results. The possible improvements by partial chemical equilibrium (γ S = 1) are very limited. We also discuss these results with the ones deduced from φ/π − and Ω − /π − ratios. These hadron ratios are sensitive to the degree of chemical equilibrium. Accordingly, the conclusion that the matter produced reaches fully chemical equilibrium in central Au-Au at RHIC energies is confirmed.

At thermal equilibrium, different chemical freezeout conditions have been proposed so far. They have an ultimate aim of proposing a universal description for the chemical freezeout parameters (T ch and µ b ), which are to be extracted from the statistical fitting of different particle ratios measured at various collision energies with calculations from thermal models. A systematic comparison between these conditions is presented. The physical meaning of each of them and their sensitivity to the hadron mass cuts are discussed. Based on availability, some of them are compared with recent lattice calculations. We found that most of these conditions are thermodynamically equivalent, especially at small baryon chemical potential. We propose that further crucial consistency tests should be performed at low energies. The fireball thermodynamics is another way of guessing conditions describing the chemical freezeout parameters extracted from high-energy experiments. We endorse the possibility that the various chemical freezeout conditions should be interpreted as different aspects of one universal condition.

The impedance spectroscopy, electrical conductivity and electric modulus of bulk phenol red were measured, as a function of both frequency and temperature. Artificial neural networks (ANNs) were used for modeling its electrical properties. The two parts (real and imaginary) of its complex impedance (Z*) were analyzed and the activation energy related to the electrical relaxation process was evaluated. Nyquist curves were plotted showing semicircles for the different temperatures. The AC electrical conductivity follows a power law σac(ω) α ωη. The maximum barrier height Bm was derived for specific temperatures. A plausible mechanism for the AC conduction of bulk phenol red was deduced from the temperature reliance of the frequency exponent. The dielectric data was analyzed using electric modulus as a tool. In addition, ANNs were used to model the impedance parts and the total electrical conductivity. Numerous runs were tried, to obtain the best performance. The training and prediction results were compared to the equivalent experimental results, with a good match obtained. An equation describing the experimental results was obtained mathematically, based on the use of ANNs. The outputs demonstrated that ANNs are an admirable tool for modeling experimental results.

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