Application of Boltzmann’s integration method under non-ideal conditions

Boltzmann’s integration method may prove to be a very powerful tool to study the transport diffusion of guest molecules in nanoporous host systems. In many cases, however, the prerequisites for applying this method are not completely fulfilled. In the following, the consequences of these deviations on the accuracy of the obtained results are discussed. It is found that the results of Boltzmann’s integration method can be corrected by different considerations. The discussion is focussed on the concentration profiles observed during the adsorption and desorption of methanol in ferrierite-type crystals as observable by interference microscopy

Assessing one-dimensional diffusion in nanoporous materials from transient concentration profiles

The use of interference microscopy has enabled the direct observation of transient concentration profiles generated by intracrystalline transport diffusion in nanoporous materials. The thus accessible intracrystalline concentration profiles contain a wealth of information which cannot be deduced by any macroscopic method. In this paper, we illustrate five different ways for determining the concentration-dependent diffusivity in one-dimensional systems and two for the surface permeability. These methods are discussed by application to concentration profiles evolving during the uptake of methanol by the zeolite ferrierite and of methanol by the metal organic framework (MOF) manganese(II) formate. We show that the diffusivity can be calculated most precisely by means of Fick’s 1st law. As the circumstances permit, Boltzmann’s integration method also yields very precise results. Furthermore, we present a simple procedure that enables the estimation of the influence of the surface barrier on the overal

Significance of concentration-dependent intracrystalline diffusion and surface permeation for overall mass transfer

The intracrystalline concentration profiles evolving during molecular uptake and release by nanoporous materials as accessible by interference microscopy contain a lot of hidden information. For concentration-independent transport parameter, the influence of surface resistances to overall mass transfer can be calculated by correlating the actual surface concentration with the overall uptake. By using a numerical solution of Fick’s 2nd law and considering a large variety of concentration dependencies of the transport diffusivity and the surface permeability, we show that the factor by which the transport process is retarded by the surface resistance may reasonably well be estimated by the type of correlation between the actual boundary concentration and the total uptake at a given time. In this way, a novel technique of uptake analysis which may analytically be shown to hold for constant diffusivities and surface permeabilities, is shown to be quite generally applicable

Insights in the Ionic Conduction inside Nanoporous Metal-Organic Frameworks by Using an Appropriate Equivalent Circuit

The conduction of protons and other ions in nanoporous materials, such as metal-organic frameworks (MOFs), is intensively explored with the aim of enhancing the performance of energy-related electrochemical systems. The ionic conductivity, as a key property of the material, is typically determined by using electrochemical impedance spectroscopy (EIS) in connection with a suitable equivalent circuit. Often, equivalent circuits are used where the physical meaning of each component is debatable. Here, we present an equivalent circuit for the ionic conduction of electrolytes in nanoporous, nonconducting materials between inert and impermeable electrodes without faradaic electrode reactions. We show the equivalent circuit perfectly describes the impedance spectra measured for the ion conduction in MOFs in the form of powders pressed into pellets as well as for MOF thin films. This is demonstrated for the ionic conduction of an aprotic ionic liquid, and of various protic solvents in different MOF structures. Due to the clear physical meaning of each element of the equivalent circuit, further insights into the electrical double layer forming at the MOF-electrode interface can be obtained. As a result, EIS combined with the appropriate reference circuit allows us to make statements of the quality of the MOF-substrate interface of different MOF-film samples

Optical sensor array of chiral MOF-based Fabry–Pérot films for enantioselective odor sensing

An optical sensor array based on photonic Fabry–Pérot films of surface-mounted metal–organic-frameworks (SURMOFs) with different homochiral structures is presented. It is used to detect and enantioselectively discriminant 3 pairs of chiral odor molecules, either pure or in binary mixtures

Metal‐Organic Framework Thin Films Grown on Functionalized Graphene as Solid‐State Ion‐Gated FETs

The unique properties of 2D-materials like graphene are exploited in various electronic devices. In sensor applications, graphene shows a very high sensitivity, but only a low specificity. This shortcoming can be mastered by using heterostructures, where graphene is combined with materials exhibiting high analyte selectivities. Herein, this study demonstrates the precise deposition of nanoporous metal-organic frameworks (MOFs) on graphene, yielding bilayers with excellent specificity while the sensitivity remains large. The key for the successful layer-by-layer deposition of the MOF films (SURMOFs) is the use of planar polyaromatic anchors. Then, the MOF pores are loaded with ionic liquid (IL). For functioning sensor devices, the IL@MOF films are grown on graphene field-effect transistors (GFETs). Adding a top-gate electrode yields an ion-gated GFET. Analysis of the transistor characteristics reveals a clear Dirac point at low gate voltages, good on-off ratios, and decent charge mobilities and densities in the graphene channel. The GFET-sensor reveals a strong and selective response. Compared to other ion-gated-FET devices, the IL@MOF material is relatively hard, allowing the manufacturing of ultrathin devices. The new MOF-anchoring strategy offers a novel approach generally applicable for the functionalization of 2D-materials, where MOF/2D-material hetero-bilayers carry a huge potential for a wide variety of applications

EVALUATION OF PASSIVELY INDUCED SHOULDER STRETCH REFLEX USING AN ISOKINETIC DYNAMOMETER IN MEN

The purpose of the current study was to determine shoulder internal rotator muscles\u27 reflex latencies (SLR) under variable conditions in 20 healthy, specifically trained male participants. Sets of different external shoulder rotation stretches were applied via an isokinetic dynamometer. SLR latencies were determined from sEMG readings as the time from external shoulder rotation stretches application to onset of muscle activity. The amount of muscular response to the perturbation was evaluated via a peak-to-peak analysis. SLR latencies and amplitudes of the pectoral muscle and the anterior deltoid were affected by the investigated muscle and the level of pre-innervation torque. Our results indicated faster muscular stretch response than reported in previous studies which can be attributed to training induced adaptions of the shoulder muscles and capsule

A MOF-based electronic nose for carbon dioxide sensing with enhanced affinity and selectivity by ionic-liquid embedment

The unequivocal detection of CO$_2$ is important in many situations, like in the living environment, plant cultivation and the conservation of cultural relics and archives. Due to their large specific surface areas and highly ordered and tunable structures, metal–organic frameworks (MOFs) have the potential to improve CO$_2$ sensing, however, they often suffer from low CO$_2$ affinity and selectivity. Ionic liquids (ILs) have high CO$_2$ affinity, but their performance in sensors is hampered by their nonporous, liquid form. Here, we present a low-cost and portable CO$_2$ sensor system based on an array of gravimetric sensors made of MOF films with embedded ILs in the pores. The array is composed of MOF films of two different structures, which are HKUST-1 and UiO-66, filled with 3 different types of ILs and 2 different pore-filling levels, resulting in an array of up to 14 different sensors. We show that the different combinations of IL and MOF result in different affinities for CO$_2$ and other analytes. With the help of machine learning using a neural network, the sensor array was used to quantify the CO$_2$ concentration as well as to distinguish CO$_2$ from other gases and vapors, like nitrogen, ethanol, methanol and water, and to distinguish certain binary mixtures. While the MOF-sensor array without IL achieves only a small accuracy for determining the CO$_2$ concentration, the IL@MOF sensor array can accurately classify the gas types (98% accuracy) in mixed gas atmospheres of unknown composition and concentration as well as can determine the CO$_2$ gas concentration with an average error of only 2.7%. Using only MOFs with a pronounced chemical stability (like UiO-66) in the sensor array also allows the detection and identification of CO$_2$ in a humid atmosphere. Moreover, the presented sensor system has very high sensitivity with a CO$_2$ limit of detection below 100 ppm, which is four times smaller than the CO$_2$ concentration in air. This work shows the unprecedented performance of the sensor arrays of MOFs with embedded ILs, referred to as IL@MOF-electronic nose (IL@MOF-e-nose), for sensing the composition and concentration of CO$_2$ gas mixtures