6,332 publications from this institution
Chemical force microscopy (CFM) has been used to measure adhesion and friction forces between probe tips and substrates covalently modified with self-assembled monolayers (SAMs) that terminate in distinct functional groups. Probe tips have been modified with SAMs using a procedure that involves coating commercial Si3N4 cantilever/tip assemblies with a thin layer of polycrystalline Au followed by immersion in a solution of a functionalized thiol. This methodology provides a reproducible means for endowing the probe with different chemical functional groups. A force microscope has been used to characterize the adhesive interactions between probe tips and substrates that have been modified with SAMs which terminate with COOH and CH3 functional groups in ethanol water solvent. Force versus distance curves recorded under ethanol show that the interaction between COOH/COOH > CH3/CH3 > COOH/CH3. The measured adhesive forces were found to agree well with predictions of the Johnson, Kendall, and Roberts (JKR) theory of adhesive contact, and thus show that the observed adhesion forces correlate with the surface free energy
The growth of an isolated void is analysed for a void contained in a block of material undergoing simple shearing combined with superimposed hydrostatic tension. The evolution of the size, shape and orientation of two- and three-dimensional voids in an incompressible, linearly viscous solid is first discussed. The main problem addressed is the behaviour of a two-dimensional cylindrical void in an incompressible, nonlinearly viscous solid for which the strain rate varies as the stress to a power. The growth rate of the void and its shape evolution are strong functions of the degree of material nonlinearity. Relatively simple approximate formulas are obtained for the dilatation rate of a circular void as well as for the void potential. The constitutive relation of a block of material containing a dilute distribution of circular cylindrical voids is obtained directly using the isolated void potential. The paper concludes with a summary of available results for the dilatation rates of voids and cracks under combinations of shear and hydrostatic tension.
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The problem of a spherical cavity which is embedded in a linear, fluid-infiltrated, elastic porous medium and which is subjected to the sudden quasi-static application of a stress at the cavity boundary is solved. It is demonstrated that the deformation of the cavity is homogeneous regardless of the boundary condition imposed on the pore fluid at the cavity wall. For the case in which the pore pressure vanishes at the cavity wall, the time dependence of the cavity strain is evaluated explicitly and is shown to vary between the limits of the ordinary linear elastic response based on the short-time (undrained) and on the long-time (drained) properties of the fluid-saturated solid. The results are then used to obtain a relation between the uniform stress or strain applied at infinity and the stress and strain in a highly permeable, possibly non-linear spherical inclusion. The application of this relationship to a study of earthquake premonitory processes based on the deformation of a rock mass with a spherical weakened zone is outlined. It is argued that the fluid coupling effects serve to stabilize the weakened rock against rapid fracture, and give rise instead to a precursory period of accelerating but initially quasi-static straining which ultimately leads to dynamic instability.
The h ‐ p method for solving partial differential equations uses discretizations where the grid size h and the polynomial degree p are varied to obtain the most efficiency in the computing of approximate solutions. It has been known for many years that increasing p can dramatically improve efficiency and that the current common practice of keeping p = 1 is a particularly poor choice. For problems with singularities, good efficiency requires that the grid be refined near the points with singularities so the h ‐ p method also requires a grid refinement scheme. We compare two such schemes here which we call E‐Refinement (proposed by Babuska and colleagues recently) and Q‐Refinement (proposed by Rice in the 1960's). Both of these schemes have been shown to have asymptotically optimal order of convergence. The actual behaviours of these two schemes are quite different in practice and the mechanisms for choosing good values of h, p and the grid refinement parameters are also quite different. This paper presents the results of a systematic experimental study of these two methods and discusses the difficulty of choosing highly efficient h, p and grid refinement parameters. Our study confirms that these two refinements are of approximately equal efficiency given such good choices. The data suggest that the Q‐Refinement is more efficient but the advantage is not dramatic given the uncertainties inherent in choosing numerical methods for practical applications. We conclude that it is substantially simpler to make good choices for the Q‐Refinement than for the E‐Refinement.
Disease and behavior subtype identification is of significant interest in biomedical research. However, in many settings, subtype discovery is limited by a lack of robust statistical clustering methods appropriate for binary data. Here, we introduce LACE-UP [latent class analysis ensembled with UMAP (uniform manifold approximation and projection) and PCA (principal components analysis)], an ensemble machine-learning method for clustering multidimensional binary data that does not require prespecifying the number of clusters and is robust to realistic data settings, such as the correlation of variables observed from the same individual and the inclusion of variables unrelated to the underlying subtype. The method ensembles latent class analysis, a model-based clustering method; principal components analysis, a spectral signal processing method; and UMAP, a cutting-edge model-free dimensionality reduction algorithm. In simulations, LACE-UP outperforms gold-standard techniques across a variety of realistic scenarios, including in the presence of correlated and extraneous data. We apply LACE-UP to dietary behavior data from the UK Biobank to demonstrate its power to uncover interpretable dietary subtypes that are associated with lipids and cardiovascular risk.
