Industrial-Si-based photoanode for highly efficient and stable water splitting.

Photoelectrochemical (PEC) water splitting is an effective and sustainable method for solar energy harvesting. However, the technology is still far away from practical application because of the high cost and low efficiency. Here, we report a low-cost, stable and high-performing industrial-Si-based photoanode (n-Indus-Si/Co) that is fabricated by simple electrodeposition.

Corrigendum: Applications and techniques for fast machine learning in science.

[This corrects the article DOI: 10.3389/fdata.2022.

n-Si/SiO /CoO -Mo Photoanode for Efficient Photoelectrochemical Water Oxidation.

Green hydrogen is considered to be the key for solving the emerging energy and environmental issues. The photoelectrochemical (PEC) process for the production of green hydrogen has been widely investigated because solar power is clean and renewable. However, mass production in this way is still far away from reality.

Microstructural Characteristics and Hardness Enhancement of Super Duplex Stainless Steel by Friction Stir Processing.

In the present study, microstructural evolution and hardness of the friction stir processed (FSPed) SAF 2507 super duplex stainless steel fabricated at a rotational speed of 650 rpm and a traverse speed of 60 mm/min were investigated. A scanning electron microscope (SEM) equipped with an electron backscatter diffraction (EBSD) detector was used to study the microstructure of the stir zone. The grain sizes of austenite and ferrite in the FSPed 2507 were found to be smaller (0.

Applications and Techniques for Fast Machine Learning in Science.

In this community review report, we discuss applications and techniques for machine learning (ML) in science-the concept of integrating powerful ML methods into the real-time experimental data processing loop to accelerate scientific discovery. The material for the report builds on two workshops held by the Fast ML for Science community and covers three main areas: applications for fast ML across a number of scientific domains; techniques for training and implementing performant and resource-efficient ML algorithms; and computing architectures, platforms, and technologies for deploying these algorithms. We also present overlapping challenges across the multiple scientific domains where common solutions can be found.

Two-Dimensional Dirac Nodal Line Carbon Nitride to Anchor Single-Atom Catalyst for Oxygen Reduction Reaction.

Two-dimensional carbon nitride (2DCN) materials have emerged as an important class of 2D materials beyond graphene. However, 2DCN materials with nodal-line semimetal characteristic are rarely reported. In this work, a new nodal-line semimetal 2DCN with the stoichiometry C N is designed by using density functional theory (DFT) calculations and its application to anchor single-atom catalysts (SACs) for the oxygen reduction reaction (ORR) is investigated.

Development of Perovskite Oxide-Based Electrocatalysts for Oxygen Evolution Reaction.

Perovskite oxides are studied as electrocatalysts for oxygen evolution reactions (OER) because of their low cost, tunable structure, high stability, and good catalytic activity. However, there are two main challenges for most perovskite oxides to be efficient in OER, namely less active sites and low electrical conductivity, leading to limited catalytic performance. To overcome these intrinsic obstacles, various strategies are developed to enhance their catalytic activities in OER.

CNSi/MXene/CNSi: Unique Structure with Specific Electronic Properties for Nanodevices.

2D materials have been interesting for applications into nanodevices due to their intriguing physical properties. In this work, four types of unique structures are designed that are composed of MXenes and C/N-Si layers (CNSi), where MXene is sandwiched by the CNSi layers with different thicknesses, for their practical applications into integrated devices. The systematic calculations on their elastic constants, phonon dispersions, and thermodynamic properties show that these structures are stable, depending on the composition of MXene.

Design of 2D materials - MSiCN (M = Cr, Mo, and W; x = 1 and 2) - with tunable electronic and magnetic properties.

Two-dimensional (2D) materials have attracted increasing interest in the past decades due to their unique physical and chemical properties for diverse applications. In this work, we present a first-principles design on a novel 2D family, MSiCN (M = Cr, Mo, and W; x = 1 and 2), based on density-functional theory (DFT). We find that all MSiCN monolayers are stable by investigating their mechanic, dynamic, and thermodynamic properties.

Multi-Phase Heterostructure of CoNiP/Co P for Enhanced Hydrogen Evolution Under Alkaline and Seawater Conditions by Promoting H O Dissociation.

Hydrogen evolution reaction (HER) is a key step for electrochemical energy conversion and storage. Developing well defined nanostructures as noble-metal-free electrocatalysts for HER is promising for the application of hydrogen technology. Herein, it is reported that 3D porous hierarchical CoNiP/Co P multi-phase heterostructure on Ni foam via an electrodeposition method followed by phosphorization exhibits ultra-highly catalytic activity for HER.

Theoretical evidence of the spin-valley coupling and valley polarization in two-dimensional MoSiX (X = N, P, and As).

Very recently, the centimeter-scale MoSi2N4 monolayer was synthesized experimentally and exhibited a semiconducting nature with high mobility (Hong et al., Science, 2020, 369, 670-674). Here, we show that MoSi2N4 and its analogues, MoSi2P4 and MoSi2As4, are potential two-dimensional (2D) materials for valleytronics based on first-principles calculations.

Magnetic and electronic properties of 2D TiX (X = F, Cl, Br and I).

Searching for two-dimensional (2D) materials with a high phase-transition temperature and magnetic anisotropy is critical to the development of spintronics. Herein, we investigate the electronic and magnetic properties of 2D TiX (X = F, Cl, Br and I) monolayers based on density-functional theory (DFT). We show that the 2D TiX monolayers are stable dynamically and thermodynamically as evidenced by phonon and molecular dynamics calculations, respectively, and show their semiconducting nature.