Fujishima and Honda (1972) demonstrated the potential of titanium dioxide (TiO2) semiconductor materials to split water into hydrogen and oxygen in a photo-electrochemical cell. Their work triggered the development of semiconductor photocatalysis for a wide range of environmental and energy applications. One of the most significant scientific and commercial advances to date has been the development of visible light active (VLA) TiO2 photocatalytic materials. In this review, a background on TiO2 structure, properties and electronic properties in photocatalysis is presented. The development of different strategies to modify TiO2 for the utilization of visible light, including non metal and/or metal doping, dye sensitization and coupling semiconductors are discussed. Emphasis is given to the origin of visible light absorption and the reactive oxygen species generated, deduced by physicochemical and photoelectrochemical methods. Various applications of VLA TiO2, in terms of environmental remediation and in particular water treatment, disinfection and air purification, are illustrated. Comprehensive studies on the photocatalytic degradation of contaminants of emerging concern, including endocrine disrupting compounds, pharmaceuticals, pesticides, cyanotoxins and volatile organic compounds, with VLA TiO2 are discussed and compared to conventional UV-activated TiO2 nanomaterials. Recent advances in bacterial disinfection using VLA TiO2 are also reviewed. Issues concerning test protocols for real visible light activity and photocatalytic efficiencies with different light sources have been highlighted.

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A review on the visible light active titanium dioxide photocatalysts for environmental applications

Hydrogel delivery systems can leverage therapeutically beneficial outcomes of drug delivery and have found clinical use. Hydrogels can provide spatial and temporal control over the release of various therapeutic agents, including small-molecule drugs, macromolecular drugs and cells. Owing to their tunable physical properties, controllable degradability and capability to protect labile drugs from degradation, hydrogels serve as a platform in which various physiochemical interactions with the encapsulated drugs control their release. In this Review, we cover multiscale mechanisms underlying the design of hydrogel drug delivery systems, focusing on physical and chemical properties of the hydrogel network and the hydrogel-drug interactions across the network, mesh, and molecular (or atomistic) scales. We discuss how different mechanisms interact and can be integrated to exert fine control in time and space over the drug presentation. We also collect experimental release data from the literature, review clinical translation to date of these systems, and present quantitative comparisons between different systems to provide guidelines for the rational design of hydrogel delivery systems.

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Designing hydrogels for controlled drug delivery.

Nature’s hierarchical materials

Additive manufacturing (AM) alias 3D printing translates computer-aided design (CAD) virtual 3D models into physical objects. By digital slicing of CAD, 3D scan, or tomography data, AM builds objects layer by layer without the need for molds or machining. AM enables decentralized fabrication of customized objects on demand by exploiting digital information storage and retrieval via the Internet. The ongoing transition from rapid prototyping to rapid manufacturing prompts new challenges for mechanical engineers and materials scientists alike. Because polymers are by far the most utilized class of materials for AM, this Review focuses on polymer processing and the development of polymers and advanced polymer systems specifically for AM. AM techniques covered include vat photopolymerization (stereolithography), powder bed fusion (SLS), material and binder jetting (inkjet and aerosol 3D printing), sheet lamination (LOM), extrusion (FDM, 3D dispensing, 3D fiber deposition, and 3D plotting), and 3D bioprinting....

Polymers for 3D Printing and Customized Additive Manufacturing

MUCKE aims to mine a large volume of images, to structure them conceptually and to use this conceptual structuring in order to improve large-scale image retrieval. The last decade witnessed important progress concerning low-level image representations. However, there are a number problems which need to be solved in order to unleash the full potential of image mining in applications. The central problem with low-level representations is the mismatch between them and the human interpretation of image content. This problem can be instantiated, for instance, by the incapability of existing descriptors to capture spatial relationships between the concepts represented or by their incapability to convey an explanation of why two images are similar in a content-based image retrieval framework. We start by assessing existing local descriptors for image classification and by proposing to use co-occurrence matrices to better capture spatial relationships in images. The main focus in MUCKE is on cleaning large scale Web image corpora and on proposing image representations which are closer to the human interpretation of images. Consequently, we introduce methods which tackle these two problems and compare results to state of the art methods. Note: some aspects of this deliverable are withheld at this time as they are pending review. Please contact the authors for a preview.

http://ieeexplore.ieee.org/iel2/4524/12820/00592460.pdf

Image Processing

During secondary fracture healing, various tissue types including new bone are formed. The local mechanical strains play an important role in tissue proliferation and differentiation. To further our mechanobiological understanding of fracture healing, a precise assessment of local strains is mandatory. Until now, static analyses using Finite Elements (FE) have assumed homogenous material properties. With the recent quantification of both the spatial tissue patterns (Vetter et al., 2010) and the development of elastic modulus of newly formed bone during healing (Manjubala et al., 2009 ), it is now possible to incorporate this heterogeneity. Therefore, the aim of this study is to investigate the effect of this heterogeneity on the strain patterns at six successive healing stages.

The input data of the present work stemmed from a comprehensive cross-sectional study of sheep with a tibial osteotomy (Epari et al., 2006 ). In our FE model, each element containing bone was described by a bulk elastic modulus, which depended on both the local area fraction and the local elastic modulus of the bone material. The obtained strains were compared with the results of hypothetical FE models assuming homogeneous material properties.

The differences in the spatial distributions of the strains between the heterogeneous and homogeneous FE models were interpreted using a current mechanobiological theory ( Isakson et al., 2006 ). This interpretation showed that considering the heterogeneity of the hard callus is most important at the intermediate stages of healing, when cartilage transforms to bone via endochondral ossification.

The mechanical heterogeneity of the hard callus influences local tissue strains during bone healing

While contribution of physics to model fracture of materials is significant, the “reversed” process of healing is hardly investigated. Inspired by fracture healing that occurs as a self-repair process in nature, e.g. in bone, we computationally study the conditions under which a material can repair itself. In our model the material around a fracture is assumed mechano-responsive: it processes the information of i) local stiffness and ii) local strain and responds by local stiffening. Depending on how information i) and ii) is processed, healing evolves via fundamentally different paths.

Healing of a mechano-responsive material

Influence of gender and mechanical stability on bone defect healing: Males show a stronger biological response than females

Osteochondral defects in joints require surgical intervention to relieve pain and restore function. However, no current treatment enables a complete reconstitution of the articular surface. It is known that both mechanical and biological factors play a key role on osteochondral defect healing, however the underlying principles and how they can be used in the design of treatment strategies remain largely unknown. To unravel the underlying principles of mechanobiology in osteochondral defect healing, i.e., how mechanical stimuli can guide biological tissue formation, we employed a computational approach investigating the scaffold-associated mechanical and architectural properties that would enable a guided defect healing. A previous computer model of the knee joint was further developed to simulate healing of an empty osteochondral defect. Then, scaffolds were implanted in the defect and their architectures and material properties were systematically varied to identify their relevance in osteochondral defect healing. Scaffold mechanical and architectural properties were capable of influencing osteochondral defect healing. Specifically, scaffold material elastic modulus values in the range of cancellous bone (low GPa range) and a scaffold architecture that provided stability, i.e., resistance against displacement, in both the main loading direction and perpendicular to it supported the repair process. The here presented model, despite its simplifications, is regarded as a powerful tool to screen for promising properties of novel scaffold candidates fostering osteochondral defect regeneration prior to their implementation in vivo.

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Scaffold-Dependent Mechanical and Architectural Cues Guide Osteochondral Defect Healing in silico

The present invention relates to a method for detecting information relevant for the characterization of joint movements, wherein markers mounted on both sides of a body joint are used for the analysis of joint movements and wherein the method comprises the following: Determination of a mean marker configuration and determination of time-dependent discrepancies from the mean configuration, wherein an orthogonal distance regression is carried out for the determination of a mean marker configuration and wherein markers mounted on each side of the body joint are used; carrying out of a weighted orthogonal distance regression with the use of the time-dependent discrepancies from the mean configuration for weighting, wherein markers mounted on each side of the body joint are used; and solution of a linear equalization problem with the use of information which has been determined by the carrying out of the weighted orthogonal distance regression.

Georg N. Duda

Papers

The mechanical heterogeneity of the hard callus influences local tissue strains during bone healing

Healing of a mechano-responsive material

Influence of gender and mechanical stability on bone defect healing: Males show a stronger biological response than females

Scaffold-Dependent Mechanical and Architectural Cues Guide Osteochondral Defect Healing in silico

Method for detecting information relevant for the characterization of joint movements