Although known since the late 19th century, organic–inorganic perovskites have recently received extraordinary research community attention because of their unique physical properties, which make them promising candidates for application in photovoltaic (PV) and related optoelectronic devices. This review will explore beyond the current focus on three-dimensional (3-D) lead(II) halide perovskites, to highlight the great chemical flexibility and outstanding potential of the broader class of 3-D and lower dimensional organic-based perovskite family for electronic, optical, and energy-based applications as well as fundamental research. The concept of a multifunctional organic–inorganic hybrid, in which the organic and inorganic structural components provide intentional, unique, and hopefully synergistic features to the compound, represents an important contemporary target.

Organic–Inorganic Perovskites: Structural Versatility for Functional Materials Design

Next-generation displays require efficient light sources that combine high brightness, color purity, stability, compatibility with flexible substrates, and transparency. Metal halide perovskites are a promising platform for these applications, especially in light of their excellent charge transport and bandgap tunability. Low-dimensional perovskites, which possess perovskite domains spatially confined at the nanoscale, have further extended the degree of tunability and functionality of this materials platform. Herein, the advances in perovskite materials for light-emission applications are reviewed. Connections among materials properties, photophysical and electrooptic spectroscopic properties, and device performance are established. It is discussed how incompletely solved problems in these materials can be tackled, including the need for increased stability, efficient blue emission, and efficient infrared emission. In conclusion, an outlook on the technologies that can be realized using this material platform is presented.

Perovskites for Light Emission.

Perovskite lead halides (CH3NH3PbI3) have recently taken a promising position in photovoltaics and optoelectronics because of remarkable semiconducting properties and possible ferroelectricity. However, the potential toxicity of lead arouses great environmental concern for widespread application. A new chemically tailored lead-free semiconducting hybrid ferroelectric is reported, N-methylpyrrolidinium)3Sb2Br9 (1), which consists of a zero-dimensional (0-D) perovskite-like anionic framework connected by corner- sharing SbBr6 coordinated octahedra. It presents a large ferroelectric spontaneous polarization of approximately 7.6 μC cm−2, as well as notable semiconducting properties, including positive temperature-dependent conductivity and ultraviolet-sensitive photoconductivity. Theoretical analysis of electronic structure and energy gap discloses a dominant contribution of the 0-D perovskite-like structure to the semiconducting properties of the material. This finding throws light on the rational design of new perovskite-like hybrids, especially lead-free semiconducting ferroelectrics.

Exploring a Lead-free Semiconducting Hybrid Ferroelectric with a Zero-Dimensional Perovskite-like Structure

Corrosion rate prediction of 3C steel under different seawater environment by using support vector regression

Triple ionic–electronic conductors (TIECs) are materials that can simultaneously transport electronic species alongside two ionic species. The recent emergence of TIECs provides intriguing opportunities to maximize performance in a variety of electrochemical devices, including fuel cells, membrane reactors and electrolysis cells. However, the potential application of these nascent materials is limited by lack of fundamental knowledge of their transport properties and electrocatalytic activity. The goal of this Review is to summarize and analyse the current understanding of TIEC transport and electrochemistry in single-phase materials, including defect formation and conduction mechanisms. We particularly focus on the discovery criteria (for example, crystal structure and ion electronegativity), design principles (for example, cation and anion substitution chemistry) and operating conditions (for example, atmosphere) of materials that enable deliberate tuning of the conductivity of each charge carrier. Lastly, we identify important areas for further advances, including higher chemical stability, lower operating temperatures and discovery of n-type TIEC materials. Triple ionic–electronic conductors can be used in electrochemical devices, including fuel cells, membrane reactors and electrolysis cells. Current understanding in single-phase conductors including defect formation and conduction mechanisms are now discussed.

Triple ionic-electronic conducting oxides for next-generation electrochemical devices.

Support vector regression applied to materials optimization of sialon ceramics

On the criteria of formation and lattice distortion of perovskite-type complex halides

The progress in the studies and practical applications of plase change materials(PCMs)have been widely reviewed,and the classification,the performance,the energy storage mechanism and the characteristics of PCMs have been studied in this paper.The applications of PCMs in solar energy application,architectural energy economy,concentrated air conditioning and other fields have also been introduced here.And the prospective developments in PCMs have been anticipated.

Studies and Applications of Phase Change Materials

Data mining (DM) or knowledge discovery in databases (KDD), a multi-disciplinary research area, has been recognized by many researchers as a key research topic in database and machine learning, arousing wide interest of industrial circle for its large potential application. This article briefly introduces the basic concept of data mining and its present situation, summarizing its tasks and techniques, and then focusing on its applications in chemical industry optimization for which some challenges and development have also been revealed.

Application of Data Mining Techniques in Chemical Industry Optimization

The support vector classification (SVC) was employed to make a model for classification of antifungal activities of 1-(1H-1,2,4-triazole-1-yl)-2-(2,4-difluorophenyl)-3-substituted-2-propanols triazole derivatives. The compounds with high antifungal activities and those with low antifungal activities were compared on the basis of the following molecular descriptors: net atomic charge on the atom N connecting with R, dipole moment and heat of formation. By using the SVC, a mathematical model was constructed, which can predict the antifungal activities of the triazole derivatives, with an accuracy of 91% on the basis of the leave-one-out cross-validation (LOOCV) test. The results indicate that the performance of the SVC model can exceed that of the principal component analysis (PCA) and K-Nearest Neighbor (KNN) models for this real world data set.

Chen Nian-yi

Papers

Support vector regression applied to materials optimization of sialon ceramics

On the criteria of formation and lattice distortion of perovskite-type complex halides

Studies and Applications of Phase Change Materials

Application of Data Mining Techniques in Chemical Industry Optimization

Support vector classification for structure-activity-relationship of 1-(1H-1,2,4-triazole-1-yl)-2-(2,4-difluorophenyl)-3-substituted-2-propanols