Robust and Corrosion-Resistant Overall Water Splitting Electrode Enabled by Additive Manufacturing.

Electrolysis of water has emerged as a prominent area of research in recent years. As a promising catalyst support, copper foam is widely investigated for electrolytic water, yet the insufficient mechanical strength and corrosion resistance render it less suitable for harsh working conditions. To exploit high-performance catalyst supports, various metal supports are comprehensively evaluated, and Ti6 Al4 V (Ti64) support exhibited outstanding compression and corrosion resistance. With this in mind, a 3D porous Ti64 catalyst support is fabricated using the selective laser sintering (SLM) 3D printing technology, and a conductive layer of nickel (Ni) is coated to increase the electrical conductivity and facilitate the deposition of catalysts. Subsequently, Co0.8 Ni0.2 (CO3 )0.5 (OH)·0.11H2 O (CoNiCH) nanoneedles are deposited. The resulting porous Ti64/Ni/CoNiCH electrode displayed an impressive performance in the oxygen evolution reaction (OER) and reached 30 mA cm-2 at an overpotential of only 200 mV. Remarkably, even after being compressed at 15.04 MPa, no obvious structural deformation is observed, and the attenuation of its catalytic efficiency is negligible. Based on the computational analysis, the CoNiCH catalyst demonstrated superior catalytic activity at the Ni site in comparison to the Co site. Furthermore, the electrode reached 30 mA cm-2 at 1.75 V in full water splitting conditions and showed no significant performance degradation even after 60 h of continuous operation. This study presents an innovative approach to robust and corrosion-resistant catalyst design.

Manageable Bubble Release Through 3D Printed Microcapillary for Highly Efficient Overall Water Splitting.

Porous metal foams (e.g., Ni/Cu/Ti) are applied as catalyst supports extensively for water splitting due to their large specific area and excellent conductivity, however, intrinsic bubble congestion is unavoidable because of the irregular three-dimensional (3D) networks, resulting in high polarization and degraded electrocatalytic performances. To boost the H2 O decomposition kinetics, the immediate bubble removal and water supply sequential in the gas-liquid-solid interface is essential. Inspired by the high efficiency of water/nutrient transport in the capillaries plants, this work designs a graphene-based capillary array with side holes as catalyst support to manage the bubble release and water supply via a Z-axis controllable digital light processing (DLP) 3D printing technology. Like planting rice, a low-cost, high-active CoNi carbonate hydroxide (CoNiCH) is planted on support. A homemade cell can reach 10 mA cm-2 in 1.51 V, and be kept at 30 mA cm-2 for 60 h without noticeable degradation, surpassing most of the known cells. This research provides a promising avenue to design and prepare advanced catalysts in various fields, including energy applications, pollutant treatment, and chemical synthesis.

Vein pattern recognition based on RGB images using Monte Carlo simulation and ridge tracking.

In forensic investigations, images of evidence can often be obtained from crimes such as child pornography and masked violent riots. However, identifying criminals is usually very difficult and sometimes impossible because these images usually contain skin of body parts, while their faces and other commonly used biometrics are unavailable. Vein patterns are a potential biometric to solve this problem. Traditional systems use near-infrared (NIR) imaging technologies to obtain vein patterns, which cannot be applied to forensic analysis since only RGB images are available. However, veins are unobservable in RGB images. In this paper, a comprehensive scheme including a vein uncovering algorithm, a vein extraction algorithm, and a vein pattern matching algorithm is presented. Based on the Monte Carlo (MC) simulation of light transmission in a skin optical model, physical parameters corresponding to different skin colors are obtained, and vein patterns are uncovered from the parameter distribution images. After preprocessing with cubic convolution and Gabor filtering, vein lines are extracted based on ridge tracking. Local gradient orientation and the geometric direction of veins are utilized to guarantee the correct tracking direction. Hessian-based Frangi filters are adopted to locate potential veins. In the matching step, effective minutiae are extracted to represent the topology of vein patterns. A modified coherent point drift (CPD) algorithm is proposed utilizing coordinates, Gabor energy values, and curvatures of minutiae to match vein patterns. Comprehensive experiments were carried out to evaluate the proposed three algorithms. Experimental results show the superiority of the proposed algorithms to various state-of-the-art methods.