In this study a total of 186 complex halide systems were collected; the formabilities of ABX3 (X = F, Cl, Br and I) halide perovskites were investigated using the empirical structure map, which was constructed by Goldschmidt's tolerance factor and the octahedral factor. A model for halide perovskite formability was built up. In this model obtained, for all 186 complex halides systems, only one system (CsF–MnF2) without perovskite structure and six systems (RbF–PbF2, CsF–BeF2, KCl–FeCl2, TlI–MnI2, RbI–SnI2, TlI–PbI2) with perovskite structure were wrongly classified, so its predicting accuracy reaches 96%. It is also indicated that both the tolerance factor and the octahedral factor are a necessary but not sufficient condition for ABX3 halide perovskite formability, and a lowest limit of the octahedral factor exists for halide perovskite formation. This result is consistent with our previous report for ABO3 oxide perovskite, and may be helpful to design novel halide materials with the perovskite structure.

Formability of ABX3 (X = F, Cl, Br, I) halide perovskites

Meeting the growing global energy demand is one of the important challenges of the 21st century. Currently over 80% of the world's energy requirements are supplied by the combustion of fossil fuels, which promotes global warming and has deleterious effects on our environment. Moreover, fossil fuels are non-renewable energy and will eventually be exhausted due to the high consumption rate. A new type of alternative energy that is clean, renewable and inexpensive is urgently needed. Several candidates are currently available such as hydraulic power, wind force and nuclear power. Solar energy is particularly attractive because it is essentially clean and inexhaustible. A year's worth of sunlight would provide more than 100 times the energy of the world's entire known fossil fuel reserves. Photocatalysis and photovoltaics are two of the most important routes for the utilization of solar energy. However, environmental protection is also critical to realize a sustainable future, and water pollution is a serious problem of current society. Photocatalysis is also an essential route for the degradation of organic dyes in wastewater. A type of compound with the defined structure of perovskite (ABX3) was observed to play important roles in photocatalysis and photovoltaics. These materials can be used as photocatalysts for water splitting reaction for hydrogen production and photo-degradation of organic dyes in wastewater as well as for photoanodes in dye-sensitized solar cells and light absorbers in perovskite-based solar cells for electricity generation. In this review paper, the recent progress of perovskites for applications in these fields is comprehensively summarized. A description of the basic principles of the water splitting reaction, photo-degradation of organic dyes and solar cells as well as the requirements for efficient photocatalysts is first provided. Then, emphasis is placed on the designation and strategies for perovskite catalysts to improve their photocatalytic activity and/or light adsorption capability. Comments on current and future challenges are also provided. The main purpose of this review paper is to provide a current summary of recent progress in perovskite materials for use in these important areas and to provide some useful guidelines for future development in these hot research areas.

Research progress of perovskite materials in photocatalysis- and photovoltaics-related energy conversion and environmental treatment.

The tolerance factor is a widely used predictor of perovskite stability. The recent interest in hybrid perovskites for use as solar cell absorbers has lead to application of the tolerance factor to these materials as a way to explain and predict structure. Here we critically assess the suitability of the tolerance factor for halide perovskites. We show that the tolerance factor fails to accurately predict the stability of the 32 known inorganic iodide perovskites, and propose an alternative method. We introduce a revised set of ionic radii for cations that is anion dependent, this revision is necessary due to increased covalency in metal–halide bonds for heavier halides compared with the metal-oxide and fluoride bonds used to calculate Shannon radii. We also employ a 2D structural map to account for the size requirements of the halide anions. Together these measures yield a simple system which may assist in the search for new hybrid and inorganic perovskites.

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On the application of the tolerance factor to inorganic and hybrid halide perovskites: a revised system

Organolead-halide-perovskite-based solar cells have recently received significant attention due to their excellent photovoltaic performance and low cost. The general formula of this perovskite light harvester is RPbX3, where R and X stand for a monovalent organic cation and halide anion, respectively. Structures of the perovskite solar cell are designed based on the function of the perovskite. Organolead halide perovskites can be used either as sensitizers or n- or p-type light harvesters. Rapid progress has been made over the past year since the first report on long-term, durable, 9.7% efficiency perovskite solar cells based on CH3NH3PbI3-sensitized TiO2 in 2012. As a result, power conversion efficiencies as high as 16% have been achieved. Further improvement is expected from this material in terms of understanding charge accumulation and transport properties. Organolead halide perovskite is now regarded as a promising solar cell material, opening new horizons in solar cell research.

Organolead Halide Perovskite: New Horizons in Solar Cell Research

DOI: 10.1002/aenm.201903242 materials in silico,[19–22] high computational costs and poor scaling still limit their effectiveness in exploring unconstrained chemical spaces and/or complex real-world materials. For instance, highthroughput DFT screening works typically limit the search space to hundreds or, at best, thousands of materials, while DFT simulations of materials are mostly limited to typically less than 1000 atoms, i.e., bulk crystals and isolated molecules. ML therefore offers a solution to the materials exploration problem, making predictions of new materials or properties from existing data, which in turn can drive the generation of more data that can be used to further refine the ML models. Here, we will provide an in-depth, critical review of MLguided design and discovery of energy materials, a field where a novel material with superior performance (e.g., higher energy density, higher energy conversion efficiency, etc.) can have a transformative impact on the urgent global problem of climate change. This review is structured along the steps in a typical workflow for materials ML model building, as shown in Figure 1. The next four sections will provide a concise overview of ML concepts designed to give the reader an appreciation of state-of-the-art techniques as well as resources for building ML models for materials. Section 6 reviews the actual application of ML techniques to the discovery and design of various classes of energy materials, from energy storage (e.g., batteries, fuel cells, etc.) to energy conversion (e.g., thermoelectrics, catalysis, etc.). The final section outlines our perspectives on various challenges and opportunities in ML for energy materials design.

A Critical Review of Machine Learning of Energy Materials

Prediction of lattice constant in cubic perovskites

Formability of ABO3 cubic perovskites

The invention relates to a preparing method for a SiC particle reinforced foam aluminum based composite, which comprises the following procedures: taking by mass among the total alloy amount 1-3% Mg, 6-8% Si and remainder Al, heating 10-20% SiC particles to melt into molten aluminum alloy, carrying out electromagnetic agitating evenly; adding 1-3% foaming agent by mass, after agitating evenly the foaming agent, keeping temperature and foaming 3-5 minutes; cooling after the molten aluminum grows steadily so as to cool and solidify the molten aluminum alloy foam, then getting SiC particle reinforced foam aluminum based composite with even hole structure and high porosity. The method adds molten aluminum alloy SiCp, which on one hand increases the viscosity of the molten alloy so as to prevent the bubbles dissolved from the foaming agent from floating upward and prolong the lives of the bubbles, on another hand, SiCp can also improve the strength of the foam aluminum. These bubbles take SiCp as a core and grow, then are cooled concurrently in all directions, this can overcome any shortcoming in solidifying and get foam aluminum of high porosity and even hole structure. By using electromagnetic agitating, the burning loss in the agitating blade can be avoided, this is useful for controlling the chemical components of the alloy.

Method for preparing SiC particle reinforced foamed aluminium radical composite material

The present invention is composite boron nitride paint for precise invested mold casting of titanium and titanium alloy, and belongs to the field of non-ferrous metal casting technology. The composite paint consists of boron nitride 29-65 wt%, Yt sol or zirconium diacetate 33-70 wt%, surfactant 0.1-5 wt% and defoaming agent 0.1-5 wt%. The boron nitride is boron nitride 200 mesh below grains of pyrolytic boron nitride, crushed cold pressed boron nitride block, high purity boron nitride or boron nitride with small amount of flux. The composite boron nitride paint has the features of high floatability, easy maintenance and simple preparation process.

Hongbao Liu

Papers

Prediction of lattice constant in cubic perovskites

Formability of ABO3 cubic perovskites

Method for preparing SiC particle reinforced foamed aluminium radical composite material

Boron nitride composite paint for precise invested mold casting of titanium and titanium alloy

Reaction between Ti and boron nitride based investment shell molds used for casting titanium alloys