## 1 Introduction  
Viscosity is of great significance for the processing of glasses or glass-ceramics due to its decisive role in the steps of melting, pressing, forming, and annealing [1]. However, the temperature-dependent viscosity changes cannot be measured in glass with a single experimental technique, since the viscosity varies during melting to formation [2, 3]. Moreover, the high cost of measuring glass viscosity and the difficulty of measuring the range of low viscosity, restrict its real practice. To accurately fit the viscosity-temperature curve, researchers have taken great efforts to manage glass viscosity, through controlling each correlated contributor such as temperature [4, 5], compositions [6, 7], structure [8, 9], thermal history [10, 11], etc. Over the past few years, the analysis of experimental data has contributed to the modeling of temperature-dependent viscosity. The classical Vogel-Fulcher-Tammann (VFT) equation [12; 13], a three-parameter model that works well for glasses with variable compositions, is suitable to predict viscosity across more than 10 orders of magnitude. The VFT equation was proposed mathematically based on the analysis of viscosity and widely applied in the glass company. Following the VFT equation, other three-parameter models were later developed, such as the Adam-Gibbs equation (AG) [14], the Avramov-Milchev (AM) equation [15], and the Mauro-Yue-Ellison-Gupta-Allan (MYEGA) equation [16]. The AM model was developed on the assumption of random probability distribution of activation energies for molecular transport due to structural disorder. MYGEA was derived from the analysis of energy landscape and the temperature-dependent constraint theory for configuration entropy. Generally speaking, if the viscosity of glass-forming liquids is low enough, it would result in a linear relationship between ln\(\eta\) and 1/_T_ so that the modeling is relatively simple. However, it remains a great challenge for the phenomenon of overfitting when it comes to the high-viscosity region [17]. Therefore, it is highly desirable to predict the viscosity more accurately by constructing an improved model using different mathematical expressions. Liquid viscosity is also one of the most important properties of chemical transportation, thus many viscosity models of molecular and polymer liquids have been developed in this area. Among them, glass-forming liquids belong to the Newtonian fluids, which are in category of many other similar organic or inorganic liquids [2; 18; 19] and have been extensively studied. The Arrhenius equation was firstly used for the viscosity calculation of fluids many years ago, i.e., In \(\eta=A+B/T\), where \(A\) and \(B\) are dependent of composition, with \(T\) being the temperature. However, the Arrhenius equation is habitually suitable for the low-viscosity range [20], which means non-Arrhenius behavior would occur when the temperature drops because the changes of network structures become the main factors that influence the viscosity [20]. The Eyring viscosity equation as a conventional method was derived from [PERSON]'s absolute rate theory, which is used to define the viscous flow of a liquid as the activation process [21]. Thus far, many modified models have been established by improving the calculation accuracy of activation energy in the Eyring equation. Among these studies, a model with connectivity of the activation volume to the activation energy was used for fitting the pressure-dependent viscosity of liquids at a constant temperature, and the calculated values were in good agreement with the measured results [22; 23; 24; 25]. However, the properties of glass in the forming process is hardly influenced by pressure, so the impact of pressure can be neglected [26]. Through this theory, denoting the temperature-dependent parameters in the model as specific expressions is a feasible way to study the viscosity-temperature relationship of the glass-forming liquids.