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When two objects slide against each other, wear and friction occur at their interface. The accumulation of wear forms what is commonly referred to as a ``third-body''. Understanding third-body evolution has significant applications in industry, where contr ...
Interface stress is a fundamental descriptor for interphase boundaries and is defined in strict relation to the interface energy. In nanomultilayers with their intrinsically high interface density, the functional properties are dictated by the interface st ...
Convolutional neural networks (CNNs) are powerful tools in Deep Learning mainly due to their ability to exploit the translational symmetry present in images, as they are equivariant to translations. Other datasets present different types of symmetries (e.g ...
Metal-Organic Frameworks (MOFs) are a class of porous materials that are applicable in many energy and environmentally relevant areas, due to their unique features including unprecedented internal surface areas and easy chemical tunability. Gas separation ...
Three methods based on the three-dimensional shallow ice approximation of glacier flow are devised that infer a glacier's subglacial topography from the observation of its time-evolving surface and mass balance. The quasi-stationary inverse method relying ...
Springer2014
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Contact of rough surfaces is of prime importance in the study of friction and wear. Numerical simulations are well suited for this non-linear problem, but natural surfaces being fractal [1], they have high discretization requirements. There is therefore a ...
2018
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We present a shape optimization algorithm to estimate the ice thickness distribution within a two-dimensional, non-sliding mountain glacier, given a transient surface geometry and a mass-balance distribution. The approach is based on the minimization of th ...
De Gruyter2014
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The columnar self-assembly resulting from units of N, N', N"-trihexylbenzene-1,3,5-tricarboxamide is investigated in solution and the solid state by means of NMR spectroscopy. A parallel computational study utilizing both semiempirical and DFT methods allo ...
Royal Soc Chemistry2017
Radicals play an important role in many areas of chemistry, such as atmospheric, aquatic, polymer, and biological, to name a few. Radicals are often highly reactive species which are short-lived and therefore harder to study by experimental techniques. In ...
EPFL2013
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Convolutional Neural Networks (CNNs) are a cornerstone of the Deep Learning toolbox and have led to many breakthroughs in Artificial Intelligence. So far, these neural networks (NNs) have mostly been developed for regular Euclidean domains such as those su ...
