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Engineering topics

Liu, Hongwei

Publications and source records attributed to Liu, Hongwei.

Graphene-supported single atom catalysts for high performance lithium-oxygen batteries

The optimal choice of d-block metals in single atom catalysts (SACs) is crucial for designing efficient electrocatalysts for activating the Oxygen reduction reaction (ORR)/ Oxygen evolution reaction (OER) in lithiumoxygen batteries (LOBs). Herein, we used the Quantum Mechanics methods to understand the origin of reactivity for a series of 16 d-block metals supported on nitrogen-doped graphene as SACs for ORR and OER in LOBs. Based on the Gibbs free energy calculations, we found that among the 16 SACs investigated, Zn-SAC exhibits the highest electrochemical activity with the lowest overpotential of 0.17 V. Here we then used machine learning (ML) to develop an intrinsic descriptor, phi, that correlates the catalytic activity with electronic and chemical properties of the catalytic centers at the M-N 4 active site on graphene surface. We established a linear relationship between phi and the catalytic activity that provides guidance for designing efficient SACs for electrocatalysis in LOBs. To validate these predictions, we report electrochemical measurements showing that Zn-SAC exhibits an ultra-stable cyclability with reduced overpotentials over Mo-SAC and nitrogen-doped graphene (NG), confirming our theoretical prediction. This fundamental work provides a deep understanding on the rational design of efficient SACs for OER/ ORR in LOBs.

25 ENERGY STORAGE↗

Revealing Variable Dependences in Hexagonal Boron Nitride Synthesis via Machine Learning

Wafer-scale monolayer two-dimensional (2D) materials have been realized by epitaxial chemical vapor deposition (CVD) in recent years. To scale up the synthesis of 2D materials, a systematic analysis of how the growth dynamics depend on the growth parameters is essential to unravel its mechanisms. However, the studies of CVD-grown 2D materials mostly adopted the control variate method and considered each parameter as an independent variable, which is not comprehensive for 2D materials growth optimization. Herein, we synthesized a representative 2D material, monolayer hexagonal boron nitride (hBN), on single-crystalline Cu (111) by epitaxial chemical vapor deposition and varied the growth parameters to regulate the hBN domain sizes. Furthermore, we explored the correlation between two growth parameters and provided the growth windows for large flake sizes by the Gaussian process. Here, this new analysis approach based on machine learning provides a more comprehensive understanding of the growth mechanism for 2D materials.

36 MATERIALS SCIENCE↗

Growth of Large‐Sized 2D Ultrathin SnSe Crystals with In‐Plane Ferroelectricity

Abstract Tin (II) selenide (SnSe) is an emerging 2D material with many intriguing properties, such as record‐high thermoelectric figure of merit (ZT), purely in‐plane ferroelectricity, and excellent nonlinear optical properties. To explore these functional properties and related applications, a crucial step is to develop controllable routes to synthesize large‐area, ultrathin, and high‐quality SnSe crystals. Physical vapor deposition (PVD) constitutes a reliable method to synthesize 2D SnSe, however, effects of various growth parameters have not yet been systematically investigated, and current PVD‐synthesized flakes are often thick (>10 nm) with small lateral sizes (<10 µm). In this work, high‐quality 2D SnSe crystals are synthesized via low‐pressure PVD, which display in‐plane ferroelectric domains observed by piezoresponse force microscopy and polarization‐dependent reflection spectroscopy. Detailed studies regarding the roles of various parameters are further carried out, including substrate pre‐annealing, growth duration, temperature, and pressure, which enable to rationally optimize the growth and obtain 2D SnSe crystals with lateral sizes up to ≈23.0 µm and thicknesses down to ≈2.0 nm (3–4 layers). This work paves the way for the controlled growth of large‐area 2D SnSe, facilitating the future exploration of many interesting multiferroic properties and applications with atomic thickness.

2D materials↗