ABSTRACT
Fibrous nanomaterials such as electrospun materials have many uses ranging from tissue engineering to biosensors. High-resolution imaging is an important component in the characterization of these materials. Important parameters required to predict and study the properties of fibre rich materials include diameter and orientation distribution as well as fibre spacing. The orientations and the relative dimensions of the fibres can be measured via specially designed imaging software. Difficulties in this measurement process can arise if fibres are distributed in close proximity to each other in relation to the resolution of the imaging modality. For example, if some automation is required in the measurement process and, particularly, if the automated processes are not designed for situations where the fibres are in close proximity to each other. This work is therefore concerned with the development of automated measurement techniques to provide estimates of the diameters of fibres and also the orientation distribution. The software automatically detects special points in the fibrous materials where fibres can be considered to have some delineation from surrounding fibres. These sparse points are considered to be points at which estimates of the fibres' properties can be quantified. Aligned and randomly distributed electrospun poly(caprolactone) nanofibres were prepared. Imaging of these materials was performed with an X-ray Computer Tomography system with an image voxel size of 0.15 × 0.15 × 0.15 µm3 . Scanning Electron Microscopy images were also obtained. Fibre diameters estimated using images from both modalities using the developed techniques were found to be in agreement. Orientation distribution was summarized with multiscale entropy and found to be consistent with visual observation across different scales. LAY DESCRIPTION: Fibres are present in many types of materials which can include, for some materials, very small fibres e.g. a few nanometres in diameter. Very small fibres are present in collagen and elastin which are common tissues of many organs in many types of living things. The sizes of these very small fibres and how they are arranged are important information that can help in the understanding of the overall properties of these materials. Materials with very small fibres can also be synthesized using specialised techniques. The properties of these synthesized fibrous materials are also important to help in understanding how the materials will perform in various different applications. Applications are many and can range from tissue engineering to drug delivery. Some properties of these materials can be shown, visually, with the aid of 3D imaging techniques such as X-ray Computer Tomography (XCT) or in 2D, with Scanning Electron Microscopy (SEM) but at a higher magnification. The work described here is centred around the development of computer algorithms to automatically determine material properties from 3D XCT images. Tests are performed with material samples, where the fibres are aligned (in semi-parallel fashion) and another where the fibres are randomly oriented (criss-crossing). The tests show that the developed algorithms are able to successfully and relatively accurately determine the diameters of the fibres. The tests also show that it is possible to quantify the relative randomness of the orientations of the fibres.
