The Hydrology of Coalbed Methane Reservoirs and the Interplay of Gas, Water, and Coal in CBM Production

7 pages (includes color illustrations and map)

The Hydrology of Coalbed Methane Reservoirs and the Interplay of Gas, Water, and Coal in CBM Production

7 pages (includes color illustrations and map)

Automatic Construction of Predictive Neuron Models through Large Scale Assimilation of Electrophysiological Data.

We report on the construction of neuron models by assimilating electrophysiological data with large-scale constrained nonlinear optimization. The method implements interior point line parameter search to determine parameters from the responses to intracellular current injections of zebra finch HVC neurons. We incorporated these parameters into a nine ionic channel conductance model to obtain completed models which we then use to predict the state of the neuron under arbitrary current stimulation. Each model was validated by successfully predicting the dynamics of the membrane potential induced by 20-50 different current protocols. The dispersion of parameters extracted from different assimilation windows was studied. Differences in constraints from current protocols, stochastic variability in neuron output, and noise behave as a residual temperature which broadens the global minimum of the objective function to an ellipsoid domain whose principal axes follow an exponentially decaying distribution. The maximum likelihood expectation of extracted parameters was found to provide an excellent approximation of the global minimum and yields highly consistent kinetics for both neurons studied. Large scale assimilation absorbs the intrinsic variability of electrophysiological data over wide assimilation windows. It builds models in an automatic manner treating all data as equal quantities and requiring minimal additional insight

Graphite-polydimethylsiloxane strain sensors for embedded structural health monitoring

Here we describe the synthesis and testing of miniature sensors for structural health monitoring. The sensors were incorporated into building materials to detect strain relaxation events within the region of elastic deformation prior to the onset of plastic deformation. Our sensors consisted of thin composite films of polydimethylsiloxane and graphite nanoparticles that conduct via tunnelling percolation. Tunnelling-percolation through elastomers with low Young's modulus is highly sensitive to deformation and gives a large piezoresistance which we use to infer the local strain. The response of sensors embedded in calcium aluminate mortar, Portland cement mortar, and very fine sand columns was compared under stress. We show that the sensors can detect micro-events where strain is redistributed locally from one direction to another and may thus be used to monitor structural integrity and provide early warning of material disaggregation.</p

Atomic-scale plasticity in presence of Frank loops

International audienceThe different reactions between edge or screw dislocations and interstitial Frank loops were studied by means of Molecular Dynamics simulations. The calculations were performed at 600K using an EAM potential describing a model FCC material with a low Stacking Fault Energy. An interaction matrix that provides the corresponding interaction strength was determined. In an attempt to investigate the role of pile-ups, simulations with either one or two dislocations in the cell were performed. We find that screw and edge dislocations behave very differently. Edge dislocations shear Frank loops in two out of three cases, while screw dislocations systematically unfault Frank loops by mechanisms that involve cross-slip. After unfaulting, they are strongly pinned by the formation of extended helical turns. The simulations show an original unpinning effect that leads to clear band broadening. This process involves the junction of two screw dislocations around an helical turn (arm-exchange) and the transfer of a dislocation from its initial glide plane to an upper glide plane (elevator effect)

Cu/Ag EAM Potential Optimized for Heteroepitaxial Diffusion from ab initio Data

A binary embedded-atom method (EAM) potential is optimized for Cu on Ag(111) by fitting to ab initio data. The fitting database consists of DFT calculations of Cu monomers and dimers on Ag(111), specifically their relative energies, adatom heights, and dimer separations. We start from the Mishin Cu-Ag EAM potential and first modify the Cu-Ag pair potential to match the FCC/HCP site energy difference then include Cu-Cu pair potential optimization for the entire database. The optimized EAM potential reproduce DFT monomer and dimer relative energies and geometries correctly. In trimer calculations, the potential produces the DFT relative energy between FCC and HCP trimers, though a different ground state is predicted. We use the optimized potential to calculate diffusion barriers for Cu monomers, dimers, and trimers. The predicted monomer barrier is the same as DFT, while experimental barriers for monomers and dimers are both lower than predicted here. We attribute the difference with experiment to the overestimation of surface adsorption energies by DFT and a simple correction is presented. Our results show that the optimized Cu-Ag EAM can be applied in the study of larger Cu islands on Ag(111).Comment: 15 pages, 7 figure

Politique et cultures sous l’Ancien Régime

Guy Chaussinand-Nogaret, directeur d’études Nous sommes partis du constat, que le XXe siècle a largement confirmé, que certaines individualités jouent un rôle, positif ou négatif, bienfaisant ou pervers, mais toujours déterminant dans l’histoire. La biographie est donc une des clés qui servent à l’intelligibilité du passé comme du présent, du passé-présent et du présent-passé. Il s’agissait donc d’évoquer des figures qui, si elles ne font pas l’histoire à elles seules, déterminent en partie l..