Abstract
Adsorption heat transformation (AHT) systems can play a major role in protecting our environment by decreasing the usage of fossil fuels and utilizing natural and alternative working fluids. The adsorption isotherm is the most important feature in characterizing an AHT system. There are eight types of International Union of Pure and Applied Chemistry (IUPAC) classified adsorption isotherms for different “adsorbent-adsorbate” pairs with numerous empirical or semi-empirical mathematical models to fit them. Researchers face difficulties in choosing the best isotherm model to describe their experimental findings as there are several models for a single type of adsorption isotherm. This study presents the optimal models for all eight types of isotherms employing several useful statistical approaches such as average error; confidence interval (CI), information criterion (ICs), and proportion tests using bootstrap sampling. Isotherm data of 13 working pairs (which include all eight types of IUPAC isotherms) for AHT applications are extracted from literature and fitted with appropriate models using two error functions. It was found that modified Brunauer–Emmet–Teller (BET) for Type-I(a) and Type-II; Tóth for Type-I(b); GAB for Type-III; Ng et al. model for Type-IV(a) and Type-IV(b); Sun and Chakraborty model for Type-V; and Yahia et al. model for Type-VI are the most appropriate as they ensure less information loss compared to other models. Moreover; the findings are affirmed using selection probability; overall; and pairwise proportion tests. The present findings are important in the rigorous analysis of isotherm data.
Highlights
To reduce global electricity demand, scientists are paying considerable attention to adsorption heat transformation (AHT) technologies such as cooling and heating as they can be driven by renewable energy or waste heat having a temperature of as low as 60 ◦ C [1]
The main aim of the current study is to find out optimal models for all the eight types of isotherms employing several statistical tools such as average error, confidence interval (CI), information criterion (IC’s), and proportion tests using bootstrap sampling
Relevant adsorption pairs for all the International Union of Pure and Applied Chemistry (IUPAC)-classified adsorption isotherms are first selected for analysis
Summary
To reduce global electricity demand, scientists are paying considerable attention to adsorption heat transformation (AHT) technologies such as cooling and heating as they can be driven by renewable energy or waste heat having a temperature of as low as 60 ◦ C [1]. It is found that different pairs exhibit different types of adsorption isotherms, and numerous authors had tried to get the best-fitted model for those [17]. Parameter effect adjustment and information loss are considered in this investigation to find the optimal isotherm model for a particular type, which makes it significant from the statistical analysis of the best-fitting model. 13 relevant isotherm data of “adsorbent-adsorbate” pairs are extracted from the literature for identifying optimal models for IUPAC classified eight types of isotherms. Statistical information criteria using a bootstrap sample have been used to select the optimal isotherm model for all IUPAC classified adsorption isotherms. Overall and pairwise proportion tests are conducted, for the equality of minimum information criterion, to identify the statistically significant optimal models for all types of IUPAC classified isotherms
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