The Henry constant and isosteric heat at zero loading for adsorption on energetically heterogeneous solids absolute versus excess

AbstractHydrogen cyanide polymers – heterogeneous solids ranging in color from yellow to orange to brown to black – may be among the organic macromolecules most readily formed within the Solar System. The non-volatile black crust of comet Halley, for example, as well as the extensive orangebrown streaks in the atmosphere of Jupiter, might consist largely of such polymers synthesized from HCN formed by photolysis of methane and ammonia, the color observed depending on the concentration of HCN involved. Laboratory studies of these ubiquitous compounds point to the presence of polyamidine structures synthesized directly from hydrogen cyanide. These would be converted by water to polypeptides which can be further hydrolyzed to α-amino acids. Black polymers and multimers with conjugated ladder structures derived from HCN could also be formed and might well be the source of the many nitrogen heterocycles, adenine included, observed after pyrolysis. The dark brown color arising from the impacts of comet P/Shoemaker-Levy 9 on Jupiter might therefore be mainly caused by the presence of HCN polymers, whether originally present, deposited by the impactor or synthesized directly from HCN. Spectroscopic detection of these predicted macromolecules and their hydrolytic and pyrolytic by-products would strengthen significantly the hypothesis that cyanide polymerization is a preferred pathway for prebiotic and extraterrestrial chemistry.

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STUDY ON THE VARIATION LAW OF ISOSTERIC HEAT OF ADSORPTION OF CH4 ON THE DIFFERENT TYPES OF KEROGEN

Special Topics & Reviews in Porous Media An International Journal ◽

10.1615/specialtopicsrevporousmedia.v7.i1.50 ◽

2016 ◽

Vol 7 (1) ◽

pp. 57-65

Author(s):

Jian Xiong ◽

Danxu Luo ◽

Xiangjun Liu ◽

Lixi Liang

Keyword(s):

Isosteric Heat ◽

Heat Of Adsorption ◽

Isosteric Heat Of Adsorption ◽

Different Types

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Green Synthesis and Enhanced CO2 Capture Performance of Perfluorinated Cerium-Based Metal-Organic Frameworks with UiO-66 and MIL-140 Topology

10.26434/chemrxiv.6876749.v1 ◽

2018 ◽

Cited By ~ 1

Author(s):

Roberto D’Amato ◽

Anna Donnadio ◽

Mariolino Carta ◽

Claudio Sangregorio ◽

Riccardo Vivani ◽

...

Keyword(s):

Photoelectron Spectroscopy ◽

Metal Organic Frameworks ◽

Isosteric Heat ◽

Experimental Conditions ◽

Cerium Ammonium Nitrate ◽

Ideal Adsorbed Solution Theory ◽

Metal Organic ◽

Adsorbed Solution ◽

Better Than ◽

The Ideal

Reaction of cerium ammonium nitrate and tetrafluoroterephthalic acid in water afforded two new metal-organic frameworks with UiO-66 [F4_UiO-66(Ce)] and MIL-140 [F4_MIL-140A(Ce)] topologies. The two compounds can be obtained in the same experimental conditions, just by varying the amount of acetic acid used as crystallization modulator in the synthesis. Both F4_UiO-66(Ce) and F4_MIL-140A(Ce) feature pores with size < 8 Å, which classifies them as ultramicroporous. Combination of X-ray photoelectron spectroscopy and magnetic susceptibility measurements revealed that both compounds contain a small amount of Ce(III), which is preferentially accumulated near the surface of the crystallites. The CO2 sorption properties of F4_UiO-66(Ce) and F4_MIL-140A(Ce) were investigated, finding that they perform better than their Zr-based analogues. F4_MIL-140A(Ce) displays an unusual S-shaped isotherm with steep uptake increase at pressure < 0.2 bar at 298 K. This makes F4_MIL-140A(Ce) exceptionally selective for CO2 over N2: the calculated selectivity, according to the ideal adsorbed solution theory for a 0.15:0.85 mixture at 1 bar and 293 K, is higher than 1900, amongst the highest ever reported for metal-organic frameworks. The calculated isosteric heat of CO2 adsorption is in the range of 38-40 kJ mol-1, indicating a strong physisorptive character.

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pyGAPS: A Python-Based Framework for Adsorption Isotherm Processing and Material Characterisation

10.26434/chemrxiv.7970402.v1 ◽

2019 ◽

Author(s):

Paul Iacomi ◽

Philip L. Llewellyn

Keyword(s):

Pore Size Distribution ◽

Pore Size ◽

Size Distribution ◽

Surface Area ◽

Isosteric Heat ◽

Material Characterisation ◽

Mixture Adsorption ◽

Surface Energetics ◽

Adsorption Processing ◽

User Friendly

Material characterisation through adsorption is a widely-used laboratory technique. The isotherms obtained through volumetric or gravimetric experiments impart insight through their features but can also be analysed to determine material characteristics such as specific surface area, pore size distribution, surface energetics, or used for predicting mixture adsorption. The pyGAPS (python General Adsorption Processing Suite) framework was developed to address the need for high-throughput processing of such adsorption data, independent of the origin, while also being capable of presenting individual results in a user-friendly manner. It contains many common characterisation methods such as: BET and Langmuir surface area, t and α plots, pore size distribution calculations (BJH, Dollimore-Heal, Horvath-Kawazoe, DFT/NLDFT kernel fitting), isosteric heat calculations, IAST calculations, isotherm modelling and more, as well as the ability to import and store data from Excel, CSV, JSON and sqlite databases. In this work, a description of the capabilities of pyGAPS is presented. The code is then be used in two case studies: a routine characterisation of a UiO-66(Zr) sample and in the processing of an adsorption dataset of a commercial carbon (Takeda 5A) for applications in gas separation.

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A computational framework to establish data-driven constitutive models for time- or path-dependent heterogeneous solids

Scientific Reports ◽

10.1038/s41598-021-94957-0 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Weijian Ge ◽

Vito L. Tagarielli

Keyword(s):

Constitutive Models ◽

Computational Procedure ◽

Data Driven ◽

Dissipated Energy ◽

Computational Framework ◽

Heterogeneous Solids ◽

Non Linear ◽

Recorded Data ◽

Path Dependent ◽

Computational Homogenisation

AbstractWe propose and implement a computational procedure to establish data-driven surrogate constitutive models for heterogeneous materials. We study the multiaxial response of non-linear n-phase composites via Finite Element (FE) simulations and computational homogenisation. Pseudo-random, multiaxial, non-proportional histories of macroscopic strain are imposed on volume elements of n-phase composites, subject to periodic boundary conditions, and the corresponding histories of macroscopic stresses and plastically dissipated energy are recorded. The recorded data is used to train surrogate, phenomenological constitutive models based on neural networks (NNs), and the accuracy of these models is assessed and discussed. We analyse heterogeneous composites with hyperelastic, viscoelastic or elastic–plastic local constitutive descriptions. In each of these three cases, we propose and assess optimal choices of inputs and outputs for the surrogate models and strategies for their training. We find that the proposed computational procedure can capture accurately and effectively the response of non-linear n-phase composites subject to arbitrary mechanical loading.

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