• Energy Research

Abstract To properly address the threat of global warming, there is an urgent need to reduce CO2 from the atmosphere through the development of environment-friendly technologies. Therefore, capturing/storage and utilization of CO2 as a refrigerant for adsorption cooling/heating technologies have been gaining momentum in the last decades. This study focuses on the development of novel activated carbons (ACs) with extremely large pore volume and high surface area from environment-friendly and abundantly available biomass precursor seeking higher CO2 adsorption capacity. Four AC samples are synthesized from the two biomass precursor’s namely waste palm trunk (WPT) and mangrove (M) employing potassium hydroxide as an activating agent. The porous properties of the synthesized ACs are investigated from the N2 adsorption/desorption data. It is praiseworthy to elucidate that the highest surface area and pore volume for biomass-derived ACs (BACs) are obtained 2927 m2 g−1 and 2.87 cm3 g−1, respectively. CO2 adsorption characteristics are investigated using a high precision magnetic suspension balance unit at five different temperatures ranging from 25 to 70 °C with various pressures. The WPT-AC (C500)/CO2 pair shows the highest adsorption uptake as high as 1.791 g g−1 (excess adsorption) and 2.172 g g−1 (absolute adsorption) at 25 °C and 5.04 MPa, which is superior to any other ACs reported to date. To the best of our knowledge, porous properties and adsorption uptake of CO2 reported in this study are the up-to-date benchmarks. The results show that novel BACs/CO2 pairs possess remarkably high adsorption performance, which will contribute towards the advancement of various adsorption-based technologies.

Abstract Adsorption cooling systems powered by low-grade thermal or renewable energy are considered as a potential alternative to the vapor compression systems. To improve the performance and compactness of the system, this study focuses on the synthesis and characterization of activated carbon (AC) composite employing graphene nanoplatelets (GNPs) namely H-grade and C-grade, and polyvinyl alcohol. The influence of GNPs on the porous properties, thermal conductivity, and ethanol adsorption characteristics of composites have been experimentally investigated. Porous properties results show that the studied composites possess high surface area and pore volume with microporous nature. The C-grade contained composite shows the higher porous properties compared to H-grade, however, thermal conductivity for the later one is the highest. The highest thermal conductivity is found to be 1.55 W m−1 K−1 for H-grade (40 wt%) contained composite which is 23.5 times higher than that of powder AC. Ethanol adsorption characteristics on studied composites are conducted gravimetrically at adsorption temperatures 30–70 °C. Experimental data are also fitted with Toth and Dubinin-Astakhov (D-A) isotherm models within ±5% RMSD and found 23% improvement of effective volumetric uptake for H25 (20 wt%) composite compared to parent AC. The instantaneous ethanol adsorption uptake onto composites has also been presented for adsorption temperature 30 °C and evaporator pressure at 1.8 kPa.

Adsorption cooling technologies driven by low-grade thermal or solar power are used as an energy-efficient alternative to conventional refrigeration and air conditioning systems. Explicit understanding of the adsorption cycles requires precise determination of the performance parameters, replication of the experimental data, and the rigorous study of the adsorption heat transformation method. Hence, the optimum adsorption isotherms model must be identified. Scientists often face difficulties in selecting the suitable isotherm model as there are many models for a particular form of adsorption isotherm. The present study introduces a novel approach for choosing the optimal models for each type of International Union of Pure and Applied Chemistry (IUPAC) classified adsorption isotherm using robust statistical methods. First, the box-and-whisker plots of error identification are employed. Tóth for Type-I(a) and Type-I(b), modified BET for Type-II, GAB for Type-III, Universal for Type-IV(a), and Type-IV(b), Sun Chakrabarty for Type-V, and Yahia et al. for Type-VI were found lower than the other candidate models in box-and-whisker plot. The optimality of our selected models was further verified using analysis of variance (ANOVA), pairwise Tukey honest significant difference (HSD) test, Kruskal–Wallis rank-sum test, and pairwise Wilcoxon rank-sum test. In short, rigorous statistical analysis was performed to identify the best model for each type of isotherm by minimizing error. Moreover, specific cooling effect (SCE) of Maxsorb III/ethanol and silica gel/water pairs were determined. Results showed that Tóth is the optimal isotherm model for the studied pairs, and the SCE values obtained from the model agree well with experimental data. The optimum isotherm model is indispensable for the precise designing of the next generation adsorption cooling cycles.

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.