Kinetic isotope effect | EPFL Graph Search

In physical organic chemistry, a kinetic isotope effect (KIE) is the change in the reaction rate of a chemical reaction when one of the atoms in the reactants is replaced by one of its isotopes. Formally, it is the ratio of rate constants for the reactions involving the light (kL) and the heavy (kH) isotopically substituted reactants (isotopologues): :\text{KIE}=\frac{k_L}{k_H} This change in reaction rate is a quantum mechanical effect that primarily results from heavier isotopologues having lower vibrational frequencies compared to their lighter counterparts. In most cases, this implies a greater energetic input needed for heavier isotopologues to reach the transition state (or, in rare cases, the dissociation limit), and consequently, a slower reaction rate. The study of kinetic isotope effects can help the elucidation of the reaction mechanism of certain chemical reactions and is occasionally exploited in drug development to improve unfavorable p

Kinks in the angle resolved photoemission and inelastic x-ray spectra of high temperature superconductors

Jeff Graf

Though the high superconducting transition temperature (Tc) is the most interesting technological aspect of high temperature superconductors, the complex way in which the spin, lattice and electronic degrees of freedom interplay, makes them of the highest scientific interest. This is illustrated by their rich phase diagram characterized by a variety of exotic groundstate including; Mott insulating, pseudogap and high temperature superconductivity. One of the most serious barriers that has prevented our understanding of the mechanism of high temperature superconductors thus far is the lack of information on how low energy Landau quasiparticles result from an organization of real particles. This organization, often colloquially referred to as "dressing", is a fundamental general concept in physics that explains a variety of physical phenomena, such as exotic particle formations and phase transitions. The role of the lattice in this dressing is particularly controversial. Phonons are quanta of lattice vibration energy, and play a crucial role in conventional superconductivity. They provide an attractive interaction allowing the electrons to condensate in superconducting Cooper pairs. However, high temperature superconductivity in the cuprates in achieved through hole doping in an antiferromagnetic Mott insulator. In this case, the antiferromagnetic background, the strong coulomb repulsion and the anisotropic superconducting gap all suggest a marginal role of the phonons. In order to assess experimentally the exact role of the phonon, angle resolved photoemission spectroscopy (ARPES) is the weapon of choice given its unique ability to probe the electronic structure of solids in an energy- and momentum-resolved manner. In this thesis, I will use ARPES to characterize the various form of dressing of the quasiparticles in the high temperature superconductor from the Fermi level all the way to the valence band complex. I'll show that when combined with isotope substitution and inelastic x-rays scattering, the strong electron-phonon interaction can be probed in vivid details. This thesis presents three fundamental results. 1) Using the isotope effect, the important and unusual role of the phonon is demonstrated, as well as the strong interplay between the magnetic and phonic degrees of freedom. 2) Using inelastic scattering, the intriguing interplay between the Fermi surface and the bond stretching phonon is exposed. And 3) By exploring the ARPES data up to high energy, two new energy scales at high binding energy as well as the spectral waterfalls phenomenon are revealed. When all these new elements are considered together, they clearly show the need to consider simultaneously the spin, lattice, Fermi surface topology and electronic degrees of freedom. The spectacular progress in ARPES techniques over the past two decades was critical for these results, and I will present in this thesis our current effort in pushing the techniques even further. In particular I'll present my efforts in building a laser based ARPES setup with a hemispherical analyzer and a spin resolved time of flight analyzer.

EPFL2008

Sheath collapse at critical shallow angle due to kinetic effects

Alessandro Geraldini

The Debye sheath is known to vanish completely in magnetised plasmas for a sufficiently small electron gyroradius and small angle between the magnetic field and the wall. This angle depends on the current onto the wall. When the Debye sheath vanishes, there is still a potential drop between the wall and the plasma across the magnetic presheath. The magnetic field angle corresponding to the predicted sheath collapse is shown to be much smaller than previous estimates, scaling with the electron-ion mass ratio and not with the square root of the mass ratio. This is shown to be a consequence of the kinetic electron and finite ion orbit width effects, which are not captured by fluid models. The wall potential with respect to the bulk plasma at which the Debye sheath vanishes is calculated. Above this wall potential, it is possible that the Debye sheath will invert.

IOP Publishing Ltd2022

Integrating Rate Based Models into a Multi-Objective Process Design & Optimisation Framework using Surrogate Models

Levent Sinan Teske

In the development of energy and chemical processes, the process engineers extensively apply computer aided methods to design & optimise these processes and corresponding process units. Such applications are multi-scale modelling and multi-objective optimisation methods. Multi-objective optimisation of super-structured process designs are expensive in CPU-time due to the high number of potential configurations and operation conditions to be calculated. Thus single process units are generally represented by simple models like equilibrium based (chemical or phase equilibrium) or specific short cut models. In the development of new processes, kinetic effects or mass transport limitations in certain process units may play an important role, especially in multiphase chemical reactors. Therefore, it is desirable to represent such process units by experimentally derived rate based models (i.e. reaction rates and mass transport rates) in the process flowsheet simulators used for the extensive multi-objective optimisation. This increases the trust engineers have in the results and allows enriching the process simulations with newest experimental findings. As most rate based models are iteratively solved, a direct incorporation would cause higher CPU-time that penalises the use of multi-objective optimisation. A global surrogate model (SUMO) of a rate based model was successfully generated to allow its incorporation into a process design & optimisation tool which makes use of an evolutionary multi-objective optimisation. The methodology was applied to a fluidised bed methanation reactor in the process chain from wood to Synthetic Natural Gas (SNG). Two types of surrogate model, an ordinary Kriging interpolation and an artificial neural network, were generated and compared to its underlying rate based model and the chemical equilibrium model. The analysis showed that kinetic limitations have significant influence on the result already for standard bulk gas chemical components. A case study applying the previous version of the process design model and the revised version (with rate based model introduced as a set of five surrogate models) will demonstrate that the prediction uncertainties of the process design & optimisation methodology are reduced due to the integration of the rate based model of the fluidised bed methanation reactor. It will be shown that the different process design models predict considerably different optimal operating conditions of the Wood-to-SNG process. This emphasises the importance of the integration of rate based models into the process design models. The presented approach has been developed for the fluidised bed methanation reactor, however, it is a generic approach which can be applied to other process unit technologies as well. Future investigations will target other technologies to further improve the process design & optimisation predictions and support project development.

EPFL2014