Ultra-Fast Laser Fabrication of Alumina Micro-Sample Array and High-Throughput Characterization of Microstructure and Hardness

In the light of recent advances in material informatics, there is a great demand for high-throughput approaches of sample fabrication and property characterization. Currently, no high-throughput approach has been demonstrated for the fast sampling of the microstructure and the correlated properties. In this paper, we demonstrate the ultra-fast fabrication of an alumina sample array and the high-throughput hardness characterization of these sample units. The alumina sample array was fabricated using picosecond (PS) laser micromachining and CO2 laser sintering within a short time (i.e., less than a few minutes). After laser sintering, the hardness of these sample units was characterized using micro-indentation, and the microstructure was observed using scanning electron microscopy (SEM). In each sample unit, the microstructure was uniform for the entire top surface and within about 20 µm depth from the top surface. The relative density (RD) and corresponding micro-hardness of the sample units was found to continuously vary over a wide range from 89% RD with 600 kgf/mm2 hardness to 99% RD with 1609 kgf/mm2 hardness. For these laser-sintered samples, the correlation of hardness and relative density of the alumina matched well with the literature reports on sintered alumina obtained using conventional low-throughput furnace sintering experiments.

Functional and Material Properties in Nanocatalyst Design: A Data Handling and Sharing Problem

(1) Background: Properties and descriptors are two forms of molecular in silico representations. Properties can be further divided into functional, e.g., catalyst or drug activity, and material, e.g., X-ray crystal data. Millions of real measured functional property records are available for drugs or drug candidates in online databases. In contrast, there is not a single database that registers a real conversion, TON or TOF data for catalysts. All of the data are molecular descriptors or material properties, which are mainly of a calculation origin. (2) Results: Here, we explain the reason for this. We reviewed the data handling and sharing problems in the design and discovery of catalyst candidates particularly, material informatics and catalyst design, structural coding, data collection and validation, infrastructure for catalyst design and the online databases for catalyst design. (3) Conclusions: Material design requires a property prediction step. This can only be achieved based on the registered real property measurement. In reality, in catalyst design and discovery, we can observe either a severe functional property deficit or even property famine.

Material Informatics with PoreBlazer v4.0 and CSD MOF Database

In this article, we present an updated version of the PoreBlazer code, an open access, open source Fortran 90 programme to calculate structural properties of porous materials. The article describes the properties calculated by the code, their physical meaning and their relationship to the properties that can be measured experimentally. We reflect on the progress of the code over the years and discuss features of the most recent version. The results of these calculations, along with the PoreBlazer code, documentation, and case studies are available online from https://github.com/SarkisovGroup/PoreBlazer.

Material Informatics with PoreBlazer v4.0 and CSD MOF Database

In this article, we present an updated version of the PoreBlazer code, an open access, open source Fortran 90 programme to calculate structural properties of porous materials. The article describes the properties calculated by the code, their physical meaning and their relationship to the properties that can be measured experimentally. We reflect on the progress of the code over the years and discuss features of the most recent version. The results of these calculations, along with the PoreBlazer code, documentation, and case studies are available online from https://github.com/SarkisovGroup/PoreBlazer.