Reverse electrodialysis in bilayer nanochannels: salinity gradient-driven power generation.

To evaluate the possibility of nano-fluidic reverse electrodialysis (RED) for salinity gradient energy harvesting, we consider the behavior of ion transportation in a bilayer cylindrical nanochannel consisting of different sized nanopores connecting two large reservoirs at different NaCl concentrations. Numerical simulations to illustrate the electrokinetic behavior at asymmetric sub-pore length and surface charge density are conducted, the impacts of which on transference number, osmotic current, diffusive voltage, maximum power and maximum power efficiency are systematically investigated. The results reveal that the transference number in Config. I (where high NaCl concentration is applied at the larger nanopore) is always larger than that in the opposite configuration (Config. II). At low concentration ratios, the osmotic current and maximum power have maximum values, while the maximum power efficiency decreases consistently. For Config. II, the ion transportation is impacted by the surface charge density at both sub-nanopores, while for Config. I, it is determined by the surface charge density at the downstream small nanopore. When large surface charge density is applied at the downstream small nanopore in contact with a very low concentration reservoir, there exists an interesting phenomenon: the larger surface charge density at the large nanopore induces a slight performance drop due to the impact of upstream EDL overlap.

High-Quality Textured 3D Shape Reconstruction with Cascaded Fully Convolutional Networks.

We present a learning-based approach to reconstructing high-resolution three-dimensional (3D) shapes with detailed geometry and high-fidelity textures. Albeit extensively studied, algorithms for 3D reconstruction from multi-view depth-and-color (RGB-D) scans are still prone to measurement noise and occlusions; limited scanning or capturing angles also often lead to incomplete reconstructions. Propelled by recent advances in 3D deep learning techniques, in this paper, we introduce a novel computation- and memory-efficient cascaded 3D convolutional network architecture, which learns to reconstruct implicit surface representations as well as the corresponding color information from noisy and imperfect RGB-D maps. The proposed 3D neural network performs reconstruction in a progressive and coarse-to-fine manner, achieving unprecedented output resolution and fidelity. Meanwhile, an algorithm for end-to-end training of the proposed cascaded structure is developed. We further introduce Human10, a newly created dataset containing both detailed and textured full-body reconstructions as well as corresponding raw RGB-D scans of 10 subjects. Qualitative and quantitative experimental results on both synthetic and real-world datasets demonstrate that the presented approach outperforms existing state-of-the-art work regarding visual quality and accuracy of reconstructed models.

Ionic thermal up-diffusion in nanofluidic salinity-gradient energy harvesting.

Advances in nanofabrication and materials science give a boost to the research in nanofluidic energy harvesting. Contrary to previous efforts on isothermal conditions, here a study on asymmetric temperature dependence in nanofluidic power generation is conducted. Results are somewhat counterintuitive. A negative temperature difference can significantly improve the membrane potential due to the impact of ionic thermal up-diffusion that promotes the selectivity and suppresses the ion-concentration polarization, especially at the low-concentration side, which results in dramatically enhanced electric power. A positive temperature difference lowers the membrane potential due to the impact of ionic thermal down-diffusion, although it promotes the diffusion current induced by decreased electrical resistance. Originating from the compromise of the temperature-impacted membrane potential and diffusion current, a positive temperature difference enhances the power at low transmembrane-concentration intensities and hinders the power for high transmembrane-concentration intensities. Based on the system's temperature response, we have proposed a simple and efficient way to fabricate tunable ionic voltage sources and enhance salinity-gradient energy conversion based on small nanoscale biochannels and mimetic nanochannels. These findings reveal the importance of a long-overlooked element-temperature-in nanofluidic energy harvesting and provide insights for the optimization and fabrication of high-performance nanofluidic power devices.