Adsorption dynamics of gases and vapors on the nanoporous metal organic framework material Ni2(4,4'-bipyridine)3(NO3)4: guest modification of host sorption behavior.

Desolvation of Ni(2)(4,4'-bipyridine)(3)(NO(3))(4).2CH(3)OH and Ni(2)(4,4'-bipyridine)(3)(NO(3))(4).2C(2)H(5)OH give flexible metal-organic porous structures M and E, respectively, which have the same stoichiometry, but subtly different structures. This study combines measurements of the thermodynamics and kinetics of carbon dioxide, methanol, and ethanol sorption on adsorbents M and E over a range of temperatures with adsorbent structural characterization at different adsorbate (guest) loadings. The adsorption kinetics for methanol and ethanol adsorption on porous structure E obey a linear driving force (LDF) mass transfer model for adsorption at low surface coverage. The corresponding adsorption kinetics for porous structure M follow a double exponential (DE) model, which is consistent with two different barriers for diffusion through the windows and along the pores in the structure. The former is a high-energy barrier due to the opening of the windows in the structure, required to allow adsorption to occur, while the latter is a lower-energy barrier for diffusion in the pore cavities. X-ray diffraction studies at various methanol and ethanol loadings showed that the host porous structures E and M underwent different scissoring motions, leading to an increase in unit cell volume with the space group remaining unchanged during adsorption. The results are discussed in terms of reversible adsorbate/adsorbent (host/guest) structural changes and the adsorption mechanism involving hydrogen-bonding interactions with specific surface sites for methanol and ethanol adsorption in relation to pore size and extent of filling. This paper contains the first evidence for individual kinetic barriers to diffusion through windows and pore cavities in flexible porous coordination polymer frameworks.

The linear driving force (LDF) model is applied to predict the service life of activated carbon cartridges. It is compared with the currently used Wheeler-Jonas equation, which results from a model of chemical reaction kinetics. The LDF model is based on a mass transfer model of adsorbate into the particle. The two models are studied in constant-pattern conditions. The properties of the two models are first clarified and then compared. It is shown that the Wheeler-Jonas equation leads to symmetrical breakthrough curves, whereas the constant-pattern LDF equation results in asymmetrical curves. Thus, the curvature of the isotherm has no influence on the shape of the Wheeler-Jonas curve. For the LDF breakthrough curve, it is shown that the asymmetry increases with the curvature of the isotherm. Wheeler-Jonas can be used with a Dubinin-Raduskevitch isotherm, whereas the LDF model analytical solution is valid for a Langmuir isotherm only. The LDF model can be used with the DR isotherm, but a numerical solution is required. At very low concentrations where the isotherm is linear, the constant pattern no longer exists and both models fail. The Dubinin-Raduskevitch isotherm must be fitted with a Langmuir isotherm to use the analytical solution of the LDF model.

On the linear driving force approximation for adsorption cooling applications

Adsorptive storage of natural gas provides an alternative to the compression storage technology. Activated carbons can provide good storage capacity at relatively low cost. The volumetric storage capacity can be increased (two to three times) on carbon monoliths/pellets compared with the powdered form. The uptake rate and the effect of adsorption heat are important factors as the storage capacity must be realized rapidly for charging cycles.Methane adsorption kinetics was investigated on an activated carbon and its pellet in a batch adsorber at 298 K. The carbon was prepared by templated synthesis whereas the pellet was fabricated using a binderless method. Linear driving force (LDF) and Fickian diffusion (FD) models were utilized to study the kinetics. Both LDF and FD models can adequately describe the observed methane kinetics on the carbon samples when the dosing pressure > 5 bar. The heat of methane adsorption was found as high as 22 kJ/mol, and it plays an important role in the observed kinetic rates on both carbon powder and the pellet. The adsorption kinetics on the pellet appears to be slightly faster than that on the powder due to the quicker dissipation of the sorption heat. The LDF model is recommended for the study of methane uptake kinetics onto both carbon samples because of its simplicity and flexibility, and ability to model the data at both low and high sorption pressures. The effects of isotherm nonlinearity and surface heterogeneity were also discussed. Copyright © 2010 Curtin University of Technology and John Wiley & Sons, Ltd.

The interaction of methanol with clean and oxidized films of Ni, Pd and Al has been investigated in the temperature range 223–450 K. Dissociative adsorption of methanol on the clean films occurred even at 223 K. A substantial fraction of the adsorption on oxidized Al film at 223 K was reversible. Further extensive adsorption of the alcohol took place on all surfaces, excluding oxidized Al, in the temperature range 290–450 K. Oxidation of Ni and Al films occurred through the reaction of the resulting surface methoxide and hydrogen adatoms in which gaseous methane was produced. The surface methoxide on Pd underwent a series of reactions by which CH2O, CO and H2 were formed. Carbon dioxide and water vapour were also detected in the gas phase subsequent to the methanol adsorption on oxidized Ni and Pd films at temperatures < 290 K. The rate of methanol adsorption on any film directly depended on the methanol pressure. The activation energy (Ea) of methanol adsorption as well as the pre-exponential factor (A) in the rate equation remained independent of the variation in the extent of adsorption. A linear relationship was found between the values of log A and those of Ea for the various surfaces, with the exception of Al, suggesting the operation of a compensation effect in the methanol adsorption and decomposition on such surfaces. Adsorption of monodeuterated methanol on the films over a similar temperature range was also carried out with the aim of examining the reactivity of the oxygen–hydrogen bond and to obtain information regarding the mode of alcohol adsorption and its subsequent decomposition on the surface.

Alcohols are important high volatility industrial chemicals, and when present in low concentrations require highly selective separation techniques. This paper investigates the kinetics of the adsorption of water, methanol, and butanol vapors on natural clinoptilolite based on experimental data obtained from laboratory‐scale equipment under constant saturated vapor pressure conditions at ambient temperature. In order to determine the corresponding mass transfer and diffusion coefficients of the adsorbed components in the zeolite particles, the kinetic curves have been investigated using two simple models—the linear driving force model (LDFM) as well as the particle diffusion model. The equilibrium and the kinetic parameters can also be determined from the experimental values of the statistical moments of the kinetic curves. Two main results have been obtained from this study. At the experimental conditions, the overall rates of adsorption of both methanol and water vapors are nearly equal, and they are of the same order of magnitude to the macro‐(meso)‐pore and intracrystalline diffusion rates predicted for the biporous clinoptilolite structure. In contrast, the diffusion of butanol vapors is much slower in the zeolite particles and particle crystals, where the intracrystalline mass transfer resistance plays a dominant role, even for the largest particles studied. The simple LDFM predictions exhibit very good correlation to the experimental data for all adsorptive components and particle sizes, despite the biporous zeolite structure. This model can be used to provide an acceptable and quick interpretation of adsorption rate curves, even at nonlinear equilibrium conditions. Copyright © 2009 Curtin University of Technology and John Wiley &amp; Sons, Ltd.

In this work, experimental data of CO2 capture by adsorption was determined gravimetrically, at 30 °C and pressures up to 40 bar, and in a fixed bed unit at 20 bar, using NaY as adsorbent. Langmuir, Sips and Tóth isotherm models were used to correlate the equilibrium data. Sips and Tóth models were best fitted allowing estimate the maximum CO2 adsorbed amount. The breakthrough curve was modeled using Linear Driving Force (LDF) and Thomas models. The LDF model represented better the CO2 breakthrough curve than Thomas model. The mass transfer resistance in NaY micropores can be assumed as the limiting step for CO2 adsorption in fixed bed, since the intraparticle mass transfer coefficient of LDF model was smaller than the experimental overall volumetric mass transfer coefficient, although external film resistance is not negligible.

The so-called (first-order) linear driving force (LDF) model for gas adsorption kinetics is frequently and successfully used for analysis and design of adsorptive processes because it is simple, analytical, and physically consistent. Yet, for certain operating conditions, such as cyclic adsorption and desorption, significant differences between the LDF model and the rigorous Fickian diffusion (FD) model can be found. In principle, increasing the order of the approximate LDF model can yield predictions closer to the FD model. As in the classical first-order LDF model, generalized LDF must be consistent with the physics of the FD model. This paper provides a minimal set of properties that generalized LDF models should meet in order to be physically consistent. This is done by showing that the FD model describes positive real dynamics, which are closely related to the thermodynamics of the adsorption−diffusion process. In this form, a generalized LDF model should inherit this property in order to guarantee that the main thermodynamic characteristics of the adsorption−diffusion dynamics will be retained to some extent.

Adsorbate mass transfer into porous adsorbents – A practical viewpoint

Improved ODE integrator and mass transfer approach for simulating a cyclic adsorption process

This issue contains a Perspective article by Dr. Richard Cramer, who is known by all as the inventor of the popular 3D QSAR method CoMFA. A December 2010 search of Google Scholar identified approximately 3,000 articles that discuss or use CoMFA. Hence, it is of great interest to read Dr. Cramer’s perspective of QSAR as he reflects on the results from the 22 years since the original publication of the method and his more than 30 years experience with QSAR. Although the Perspective focuses on propriety software, the results have implications beyond that software, indeed beyond QSAR and CoMFA. The most important lesson is the realization that there is a distinction between a predictive QSAR model and molecular modeling to investigate physical reality. Any QSAR model must emphasize the differences in the ligand structure that lead to differences in biological potency. If these differences are correctly encoded, the QSAR will be predictive. Because traditional QSAR meets the criterion of focusing on differences in ligand structures, this may explain its continued success. Its problem can be to generate accurate descriptions of the molecules. Dr. Cramer shows that considering the 3D properties of the ligand structures is a two-edged sword. Traditional CoMFA and related methodologies base their fits and predictions on the 3D locations of hydrogen bonding and steric occupancy. This improvement over traditional 2D QSAR is complicated by the necessity to choose a conformation for each molecule and how to align the molecules. Whereas these 3D properties may be more realistic, one may be tempted to generate a realistic model of the binding. It often happens that there are subtle differences in the low-energy 3D structures of molecules that are similar in 2D. Because these differences are the direct result of changes in the structures of the ligands, using these changes to suggest the potency of untested molecules adds noise to the relationship between changes in the ligand structures and changes in their bioactivity. The Perspective starts with a summary of unpublished results: specifically, the accuracy of Topomer CoMFA potency forecasts. In the four known cases in which the method was applied, the potency of the 140 newly synthesized molecules was predicted within 0.5 log units. In every series the accuracy of the predictions was greater than that from leave-one-out cross-validation. To understand the significance of these results, it is important to recognize that Topomer CoMFA discards the idea of generating molecular descriptors from low energy conformations of whole molecules as superimposed: Instead, the molecules are decomposed into molecular fragments, one fragment per position on the common ‘‘core’’, and aligned on the bond that attaches the fragment to the core. Importantly, the 3D conformation of each fragment is not chosen to be a low-energy one, but rather to follow a predefined heuristic. The QSAR analysis uses these fragments in the traditional CoMFA paradigm of calculating electrostatic and steric fields and analyzing the results with PLS. Dr. Cramer emphasizes the relentless focus of Topomer CoMFA on changes in the structure of the small molecule as the sole reason for their change in biological potency: it is changes in the structure of the small molecule that is responsible for changes in the observed potency, whether or not the changes in the 2D structure of the small molecule leads to changes in the 3D structure of the target biomolecule or even in the small molecule as compared to other Y. C. Martin (&) Waukegan, IL, USA e-mail: yvonnecmartin@comcast.net

Adsorption of methanol, ethanol and water on well-characterized PtSn surface alloys

Selecting an optimum kinetic model for gas–solid adsorption based on statistical approaches and a model selection criterion

Water vapor sorption kinetics of polymer based sorbents: Theory and experiments

Structural change tests aim to identify evidence of a structural break or change in the underlying generating process of a time series. The BDS test has its origins in chaos theory and seeks to test, using the correlation integral, the hypothesis that a time series is generated by an identically and independently distributed (IID) stochastic process over time. The BDS test is already widely used as a powerful tool for testing the hypothesis of white noise in the residuals of time series models. In this paper, we illustrate how the BDS test can be implemented also in a recursive manner to evaluate the hypothesis of structural change in a time series, taking advantage of its ability to test the IID hypothesis. We apply the BDS test repeatedly, starting with a sub-sample of the original time series and incrementally increasing the number of observations until it is applied to the full sample time series. A structural change in the unknown underlying generator model is detected when a change in the trend shown by this recursively computed BDS statistic is detected. The strength of this recursive BDS test lies in the fact that it does not require making any assumptions about the underlying time series generator model. We ilustrate the power and potential of this recursive BDS test through an application to real economic data. In this sense, we apply the test to assess the structural changes caused by the COVID-19 pandemic in international financial markets. Using daily data from the world’s top stock indices, we have detected strong and statistically significant evidence of two major structural changes during the period from June 2018 to June 2022. The first occurred in March 2020, coinciding with the onset of economic restrictions in the main Western countries as a result of the pandemic. The second occurred towards the end of August 2020, with the end of the main economic restrictions and the beginning of a new post-pandemic economic scenario. This methodology to test for structural changes in a time series is easy to implement and can detect changes in any system or process behind the time series even when this generating system is not known, and without the need to specify or estimate any a priori generating model. In this sense, the recursive BDS test could be incorporated as an initial preliminary step to any exercise of time series modeling. If a structural change is detected in a time series, rather than estimating a single predictive model for the full-sample time series, efforts should be made to estimate different predictive models, one for the time before and one for the time after the detected structural change.