A New Method of Analysing Temperature-Programmed Desorption (TPD) Profiles Using an Extended Integral Equation

Koch, K.; Hunger, B.; Klepel, Olaf; Heuchel, Matthias

doi:10.1006/jcat.1997.1843

Cited by 25 publications

(21 citation statements)

References 28 publications

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“…Although peak shape and linearization methods exist (as described in Section S.VII of the supporting information), numerical simulations may be the only practical method for fitting of CRN-TPR, and others have noted that numerical simulations [45][46] have advantages for TPR of even simple reaction networks. In the context of CRN-TPR, numerical simulations have several strengths: 1) numerical simulations enable varied functional forms for the rate equation to be adopted/tested with relative ease, 2) numerical simulations can accurately describe complex mechanisms, even with concentration dependent terms and coupled kinetic equations, 3) Fewer a priori assumptions about the chemical system need to be made for numerical simulations, relative to peak shape methods (alternative mechanisms can be tested without a new derivation).…”

Section: Motivation For Numerical Modellingmentioning

confidence: 99%

Simulation and fitting of complex reaction network TPR: The key is the objective function

Savara

2016

Surface Science

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A method has been developed for finding improved fits during simulation and fitting of data from complex reaction network temperature programmed reactions (CRN-TPR). It was found that simulation and fitting of CRN-TPR presents additional challenges relative to simulation and fitting of simpler TPR systems. The method used here can enable checking the plausibility of proposed chemical mechanisms and kinetic models. The most important finding was that when choosing an objective function, use of an objective function that is based on integrated production provides more utility in finding improved fits when compared to an objective function based on the rate of production. The response surface produced by using the integrated production is monotonic, suppresses effects from experimental noise, requires fewer points to capture the response behavior, and can be simulated numerically with smaller errors. For CRN

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Section: Motivation For Numerical Modellingmentioning

confidence: 99%

Simulation and fitting of complex reaction network TPR: The key is the objective function

Savara

2016

Surface Science

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“…Characterization of the desorption energy distribution is based on the first linear Fredholm equation, similar in structure to Eq. 15, and the desorption distribution function is calculated as a kernel by inversion of the integral equation 71) . The solution of this ill-posed problem again requires an extensive computing algorithm which has been mainly applied in the studies of catalysts [71][72][73] .…”

Section: Desorption Energy Distributionmentioning

confidence: 99%

A Review of Inverse Gas Chromatography and its Development as a Tool to Characterize Anisotropic Surface Properties of Pharmaceutical Solids

Heng

2013

KONA

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Surface properties can profoundly impact the bulk and interfacial behavior of pharmaceutical solids, and also their manufacturability, processability in drug product processes, dissolution kinetics and mechanism in drug delivery. Variation in the inter-and intra-molecular interactions gives rise to anisotropic surface properties of crystalline solids which display direction-dependent characteristics relative to the orientation of the crystal unit structure. Despite its establishment since the 1950s, inverse gas chromatography (IGC) is still an evolving technology in the field of pharmaceutical R&D. In this review, the principles behind IGC as a physicochemical technique to measure the surface properties of solids are presented. The introduction is followed by an overview of its utility in pharmaceutical R&D, spanning a variety of applications including batch-to-batch variability, solid-solid transitions, physical stability, interfacial behavior in powder processing, and more. For anisotropic materials, IGC has been utilized to characterize the heterogeneity of materials using adsorption and energy distribution functions. Recent development and applications of IGC at finite concentration (IGC-FC) to determine the surface heterogeneity distribution of solids are presented. This methodology overcomes a number of limitations associated with traditional experiments.

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“…The zerothorder regime is usually well fit by only one single desorption energy and the sub-monolayer regime needs to be described using a distribution of desorption energies. This is due to the different adsorption sites from a disordered and rough substrate, as reported recently by (Noble et al 2012;Doronin et al 2015;Collings et al 2015), using models based on work by (Tait et al 2005;Koch et al 1997;Redhead 1962). For the pre-exponential factor associated to -13 CO (solid black lines) and 15 N 2 (solid red lines) TPD curves from pure ice and H 2 O ice surface at 1 K min −1 .…”

Section: Methodsmentioning

confidence: 63%

CO and N$_2$ desorption energies from water ice

Fayolle,

Balfe,

Loomis

et al. 2015

Preprint

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The relative desorption energies of CO and N 2 are key to interpretations of observed interstellar CO and N 2 abundance patterns, including the well-documented CO and N 2 H + anti-correlations in disks, protostars and molecular cloud cores. Based on laboratory experiments on pure CO and N 2 ice desorption, the difference between CO and N 2 desorption energies is small; the N 2 -to-CO desorption energy ratio is 0.93±0.03. Interstellar ices are not pure, however, and in this study we explore the effect of water ice on the desorption energy ratio of the two molecules. We present temperature programmed desorption experiments of different coverages of 13 CO and 15 N 2 on porous and compact amorphous water ices and, for reference, of pure ices. In all experiments, 15 N 2 desorption begins a few degrees before the onset of 13 CO desorption. The 15 N 2 and 13 CO energy barriers are 770 and 866 K for the pure ices, 1034 -1143 K and 1155-1298 K for different sub-monolayer coverages on compact water ice, and 1435 and 1575 K for ∼1 ML of ice on top of porous water ice. For all equivalent experiments, the N 2 -to-CO desorption energy ratio is consistently 0.9. Whenever CO and N 2 ice reside in similar ice environments (e.g. experience a similar degree of interaction with water ice) their desorption temperatures should thus be within a few degrees of one another. A smaller N 2 -to-CO desorption energy ratio may be present in interstellar and circumstellar environments if the average CO ice molecules interacts more with water ice compared to the average N 2 molecules.

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A New Method of Analysing Temperature-Programmed Desorption (TPD) Profiles Using an Extended Integral Equation

Cited by 25 publications

References 28 publications

Simulation and fitting of complex reaction network TPR: The key is the objective function

Simulation and fitting of complex reaction network TPR: The key is the objective function

A Review of Inverse Gas Chromatography and its Development as a Tool to Characterize Anisotropic Surface Properties of Pharmaceutical Solids

CO and N$_2$ desorption energies from water ice

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