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C H Arns

Publications and source records attributed to C H Arns.

3 recordsLinked to original sources

Investigation of microstructural features in regenerating bone using micro computed tomography.

We illustrate some of the uses of micro-computed tomography (micro-CT) to study tissue-engineered bone using a micro-CT facility for imaging and visualizing biomaterials in three dimensions (3-D). The micro-CT is capable of acquiring 3D X-ray CT images made up of 2000(3) voxels on specimens up to 5 cm in extent with resolutions down to 2 microm. This allows the 3-D structure of tissue-engineered materials to be imaged across orders of magnitude in resolution. This capability is used to examine an explanted, tissue-engineered bone material based on a polycaprolactone scaffold and autologous bone marrow cells. Imaging of the tissue-engineered bone at a scale of 1 cm and resolutions of 10 microm allows one to visualize the complex ingrowth of bone into the polymer scaffold. From a theoretical viewpoint the voxel data may also be used to calculate expected mechanical properties of the tissue-engineered implant. These observations illustrate the benefits of tomography over traditional techniques for the characterization of bone morphology and interconnectivity. As the method is nondestructive it can perform a complimentary role to current histomorphometric techniques.

Animals↗

Reconstructing complex materials via effective grain shapes.

We introduce a powerful method based on integral geometry and the Kac theorem for the spectrum of the Laplace operator to define the effective shape of an inclusion in a system made up of a distribution of arbitrarily shaped constituents. Reconstructing the microstructure using the effective inclusion shape leads to an excellent match to the percolation thresholds and to the mechanical and transport properties across all phase fractions. Use of the equivalent shape in effective medium formulations leads to good predictions. The method is verified for a sedimentary rock sample.

Journal Article↗

Euler-Poincaré characteristics of classes of disordered media.

We consider a family of statistical measures based on the Euler-Poincaré characteristic of n-dimensional space that are sensitive to the morphology of disordered structures. These measures embody information from every order of the correlation function but can be calculated simply by summing over local contributions. We compute the evolution of the measures with density for a range of disordered microstructural models; particle-based models, amorphous microstructures, and cellular and foamlike structures. Analytic results for the particle-based models are given and the computational algorithm verified. Computational results for the different microstructures exhibit a range of qualitative behavior. A length scale is derived based on two-point autocorrelation functions to allow qualitative comparison between the different structures. We compute the morphological parameters for the experimental microstructure of a sandstone sample and compare them to three common stochastic model systems for porous media. None of the statistical models are able to accurately reproduce the morphology of the sandstone.

Journal Article↗