TiO2 -Based Surfaces with Special Wettability – From Nature to Biomimetic Application

Super-wetting/antiwetting surfaces with extremely high contrast of surface energy and liquid adhesion have attracted a lot of interest in both fundamental research and industry. Various types of special wetting surfaces can be constructed by adjusting the topographical structure and chemical composition. In this chapter, recent advance of the super-wetting/antiwetting surfaces with special solid/liquid adhesion has been reviewed, with a focus on the biomimetic fabrication and applications of TiO2-based surfaces. Special super-wettability examples include lotus-leaf-inspired surfaces with low adhesion, rose-petal-inspired surfaces with high adhesion, spider silk bio-inspired surfaces with directional adhesion, fish-scale-inspired underwater superoleophobic surface, and artificial surfaces with controllable or stimuli-responsive liquid adhesion. In addition, we will review some potential applications related to artificial antiwetting surface with controllable adhesion, e.g., self-cleaning, antifogging/anti-icing, micro-droplet manipulation, fog/water collection, water/oil separation, anti-bioadhesion, micro-template for patterning, and friction reduction. Finally, the difficulty and prospects of this renascent and rapidly developing field are also briefly proposed and discussed

Learning to reconstruct and understand indoor scenes from sparse views

This paper proposes a new method for simultaneous 3D reconstruction and semantic segmentation for indoor scenes. Unlike existing methods that require recording a video using a color camera and/or a depth camera, our method only needs a small number of (e.g., 3~5) color images from uncalibrated sparse views, which significantly simplifies data acquisition and broadens applicable scenarios. To achieve promising 3D reconstruction from sparse views with limited overlap, our method first recovers the depth map and semantic information for each view, and then fuses the depth maps into a 3D scene. To this end, we design an iterative deep architecture, named IterNet, to estimate the depth map and semantic segmentation alternately. To obtain accurate alignment between views with limited overlap, we further propose a joint global and local registration method to reconstruct a 3D scene with semantic information. We also make available a new indoor synthetic dataset, containing photorealistic high-resolution RGB images, accurate depth maps and pixel-level semantic labels for thousands of complex layouts. Experimental results on public datasets and our dataset demonstrate that our method achieves more accurate depth estimation, smaller semantic segmentation errors, and better 3D reconstruction results over state-of-the-art methods

Human Motion Transfer with 3D Constraints and Detail Enhancement

We propose a new method for realistic human motion transfer using a generative adversarial network (GAN), which generates a motion video of a target character imitating actions of a source character, while maintaining high authenticity of the generated results. We tackle the problem by decoupling and recombining the posture information and appearance information of both the source and target characters. The innovation of our approach lies in the use of the projection of a reconstructed 3D human model as the condition of GAN to better maintain the structural integrity of transfer results in different poses. We further introduce a detail enhancement net to enhance the details of transfer results by exploiting the details in real source frames. Extensive experiments show that our approach yields better results both qualitatively and quantitatively than the state-of-the-art methods

Deep edge map guided depth super resolution

Accurate edge reconstruction is critical for depth map super resolution (SR). Therefore, many traditional SR methods utilize edge maps to guide depth SR. However, it is difficult to predict accurate edge maps from low resolution (LR) depth maps. In this paper, we propose a deep edge map guided depth SR method, which includes an edge prediction subnetwork and an SR subnetwork. The edge prediction subnetwork takes advantage of the hierarchical representation of color and depth images to produce accurate edge maps, which promote the performance of SR subnetwork. The SR subnetwork is a disentangling cascaded network to progressively upsample SR result, where every level is made up of a weight sharing module and an adaptive module. The weight sharing module extracts the general features in different levels, while the adaptive module transfers the general features to the specific features to adapt to different degraded inputs. Quantitative and qualitative evaluations on various datasets with different magnification factors demonstrate the effectiveness and promising performance of the proposed method. In addition, we construct a benchmark dataset captured by Kinect-v2 to facilitate research on real-world depth map SR

Progress on fabrication, modification and applications of titania nanotube Arrays

Titania nanotube arrays as a novel nano-material has unique highly ordered array structure, good mechanical and chemical stability, as well as excellent corrosion resistance. It has been fabricated by electrochemical anodization of pure Ti sheet in electrolytes containing small amounts of fluoric ions. This paper reviews the new research achievements of TiO2 nanotube arrays on the preparation processes, forming mechanism, modification and the applications in the photocatalytic degradation of pollutants, solar cells, gas sensor materials, photolysis water. The existing problems and further prospects in this field are also discussed

Electrical transport properties of individual TiO2 nanowire in one dimension

The anatase TiO2 nanowire arrays with 60 ran diameter and 20 nm diameter were prepared within the nanochannels of anodic aluminum oxide (AAO) template by an electrochemically induced sol-gel method. Atomic force microscopy (AFM) technique was applied to map topographic image at half-contact mode and to measure current-voltage characteristics of individual TiO2 nanowire at contact mode. The I-V characteristics of individual TiO2 nanowire by AFM revealed semiconductor characteristics. The bias voltage resulting in a measurable current on individual TiO2 nanowire was much lower than that on the bulk TiO2 materials, and its value increased with the diameter of individual nanowire decreasing

Fabrication of highly ordered titanium dioxide nanotube array and investigation of its photocatalytic activity

A highly ordered titanium dioxide (TiO2) nanotube array film on titanium substrate was fabricated by using an electrochemical anodic oxidation method, and some preparation parameters of the TiO2 nanotube arrays were investigated as well. The SEM and XRD experiments were performed to characterize the morphology and crystalline phase of the TiO2 nanotube arrays. It was found that the morphology of the TiO2 nanotube arrays was greatly associated with the anodization voltage. The photocatalytic activity of the TiO2 nanotube array film was evaluated by the decolorization of methyl orange under the illumination of a high-pressure mercury lamp. The results showed that the TiO2 nanotube arrays prepared at 20 V and annealed at 500 degrees C exhibited the best photocatalytic activity to the degradation of methyl orange. And the photocatalytic activity of the TiO2 nanotube array film was much higher than that of the regular TiO2 nanoparticle film

Investment Case for a Comprehensive Package of Interventions Against Hepatitis B in China: Applied Modeling to Help National Strategy Planning.

BACKGROUND content: In 2016, the first global viral hepatitis elimination targets were endorsed. An estimated one-third of the world's population of individuals with chronic hepatitis B virus (HBV) infection live in China and liver cancer is the sixth leading cause of mortality, but coverage of first-line antiviral treatment was low. In 2015, China was one of the first countries to initiate a consultative process for a renewed approach to viral hepatitis. We present the investment case for the scale-up of a comprehensive package of HBV interventions. METHODS content: A dynamic simulation model of HBV was developed and used to simulate the Chinese HBV epidemic. We evaluated the impact, costs, and return on investment of a comprehensive package of prevention and treatment interventions from a societal perspective, incorporating costs of management of end-stage liver disease and lost productivity costs. RESULTS content: Despite the successes of historical vaccination scale-up since 1992, there will be a projected 60 million people still living with HBV in 2030 and 10 million HBV-related deaths, including 5.7 million HBV-related cancer deaths between 2015 and 2030. This could be reduced by 2.1 million by highly active case-finding and optimal antiviral treatment regimens. The package of interventions is likely to have a positive return on investment to society of US$1.57 per US dollar invested. CONCLUSIONS content: Increases in HBV-related deaths for the next few decades pose a major public health threat in China. Active case-finding and access to optimal antiviral treatment are required to mitigate this risk. This investment case approach provides a real-world example of how applied modeling can support national dialog and inform policy planning