Clathrate hydrates are crucial from the point of view of flow assurance and future energy resources, as well as potential innovative and sustainable applications such as gas separation, CO2 sequestration, district and data center cooling, seawater desalination, and natural gas storage. Although proof of concept has been demonstrated, significant progress is necessary in order to achieve industrial-level validation and commercialization. Most of the applications possess a common requirement of enhanced kinetics in formation and dissociation. There is a need for a broader understanding of hydrate nucleation mechanisms, cause-effect relations, and investigation techniques. The stochastic nature of hydrate nucleation, confounding cause–effect relations, and spatial-temporal scales have made it even more challenging to study nucleation. The use of hydrate promoters, novel reactor configurations such as porous media in a packed bed, and nanoparticles and hydrogels necessitates us to obtain further insights about clathrate nucleation. This review provides an in depth analysis about the characteristics of clathrate hydrate nucleation and the techniques adopted for studying nucleation from an application-oriented perspective and enables further development of clathrate technology toward future applications.

Criteria/correlations proposed in the literature to predict the performance of an adsorbent in a separation process fail in three ways for carbon dioxide (CO 2 ) capture and concentration (CCC) from flue gas: (i) they cannot confirm if the stringent purity−recovery requirements will be met, (ii) the indices rank the adsorbents for a fixed set of operating conditions and not for the best performance for each adsorbent while satisfying the purity−recovery constraints, and (iii) the performance indicator for which the adsorbents are ranked is not explicitly stated, and certainly one index cannot apply for different performance indicators. In this study, a two-step method has been developed for rapid screening of the adsorbents for postcombustion CCC as a function of five easily quantifiable equilibrium isotherm characteristics of the CO 2 isotherm, namely, its binary mixture selectivity over N 2 , equilibrium loading, local slope and nonlinearity at the feed concentration, and Henry's constant. First, a study has been conducted using a central composite design of experiments for determining the effects of these isotherm characteristics. The performance of a fourstep vacuum swing adsorption (VSA) process with light product pressurization has been optimized for each combination of the aforementioned CO 2 isotherm characteristics, representing a possible adsorbent, with the objective to minimize energy consumption and maximize productivity while satisfying the purity−recovery constraints. Among the feasible combinations of isotherm characteristics, some were unable to meet the purity−recovery constraints. Next, a neural-network-based model has been proposed to predict whether an adsorbent can deliver CO 2 at 95% purity and 90% recovery. Finally, for adsorbents that pass this first test, meta-models have been developed to predict the minimum energy consumption and maximum productivity of the process. The proposed screening method has been validated with a large number of adsorbents considered in recent published studies. In the process, we have identified several adsorbents that promise a much superior performance over that of 13X zeolite, the most studied adsorbent for postcombustion CCC.

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Assessing vacuum swing adsorption (VSA) technology for postcombustion CO 2 capture and concentration (CCC) using energy and productivity indicators are useful, but its ultimate test must be the cost of electricity from a power plant including CCC. Here, our integrated optimization platform (Khurana and Farooq, AlChE J. 2017;63:2987-2995) developed earlier to simultaneously obtain the optimum adsorbent and process conditions is extended to include a comprehensive costing framework. The framework is complete with scale-up design and column scheduling, and compliant with National Energy Technology Laboratory costing guidelines for carbon capture. This is the ultimate tool that enables integrated optimization to minimize the cost of electricity. The Shell Cansolv CO 2 capture system is used as the benchmark for evaluating the best performance of two VSA cycles for two adsorbents. The operating conditions and isotherm shapes necessary to achieve the lowest possible cost of electricity for the two VSA cycles are also presented to facilitate designing or searching the best adsorbent for CCC.Carbon capture cost can be evaluated in terms $/t CO 2 captured or $/t avoided. Cost of CO 2 captured is given by Eq. 8. 17 Figure 2. Schematic of the integrated adsorbent-process optimization algorithm for minimizing the LCOE including a comprehensive costing framework complete with scale-up design and column scheduling.[Color figure can be viewed at wileyonlinelibrary.com]