Materials informatics employs techniques, tools, and theories drawn from the emerging fields of data science, internet, computer science and engineering, and digital technologies to the materials science and engineering to accelerate materials, products and manufacturing innovations. Manufacturing is transforming into shorter design cycles, mass customization, ondemand production, and sustainable products. Additive manufacturing or 3D printing is a popular example of such a trend. However, the success of this manufacturing transformation is critically dependent on the availability of suitable materials and of data on invertible processing-structure-property-performance life cycle linkages of materials. Experience suggests that the material development cycle, i.e. the time to develop and deploy new material, generally exceeds the product design and development cycle. Hence, there is a need to accelerate materials innovation in order to keep up with product and manufacturing innovations. This is a major challenge considering the hundreds of thousands of materials and processes, and the huge amount of data on microstructure, composition, properties, and functional, environmental, and economic performance of materials. Moreover, the data sharing culture among the materials community is sparse. Materials informatics is key to the necessary transformation in product design and manufacturing. Through the association of material and information sciences, the emerging field of materials informatics proposes to computationally mine and analyze large ensembles of experimental and modeling datasets efficiently and cost effectively and to deliver core materials knowledge in user-friendly ways to the designers of materials and products, and to the manufacturers. This paper reviews the various developments in materials informatics and how it facilitates materials innovation by way of specific examples. KeywordsMaterials informatics • Materials data analytics • Materials modelling • Materials data mining • Materials selection • Materials web platform • Materials 4.0 B Seeram Ramakrishna

A binder-free titania paste was prepared by chemical modification of an acidic TiO2 sol with ammonia. By varying the ammonia concentration, the viscosity of the acidic TiO2 suspension increased, thereby allowing uniform films to be cast. The photoelectrochemical performance of TiO2 electrodes, cast as single layers, was dependent on the thermal treatment cycle. Fourier transform infrared spectroscopy was used to characterize the extent of residual organics and found that acetates from the TiO2 precursor preparation were retained within the electrode structure after thermal treatment at 150 °C. Electrodes of nominal thickness 4 lm produced an energy conversion efficiency as high as 5.4% using this simple thermal treatment. A binder-free titania paste was prepared by chemical modification of an acidic TiO 2 sol with ammonia. By varying the ammonia concentration, the viscosity of the acidic TiO 2 suspension increased, thereby allowing uniform films to be cast. The photoelectrochemical performance of TiO 2 electrodes, cast as single layers, was dependent on the thermal treatment cycle. Fourier transform infrared spectroscopy was used to characterize the extent of residual organics and found that acetates from the TiO 2 precursor preparation were retained within the electrode structure after thermal treatment at 150°C. Electrodes of nominal thickness 4 lm produced an energy conversion efficiency as high as 5.4% using this simple thermal treatment.

Fine-tuning surface energies of coatings through experimental trial and error can be very tedious and time-consuming. The use of a reliable theoretical model can provide useful guidelines for experimental and formulation design for surface hydrophobicity. In this work, we perform multiscale modeling with molecular dynamics (MD) simulations, theoretical models, and computational fluid dynamics (CFD) simulations to investigate the wetting and sliding behavior of a water droplet on experimentally fabricated coatings. The wetting behavior of a water droplet on untreated polydimethylsiloxane (PDMS) surface and PDMS surface functionalized with hydroxyl and fluoride groups is studied by MD simulations. MD simulation results show that water contact angle (WCA) increases with increasing length of fluorocarbon chains, and this is in good agreement with experimental measurement of PDMS surface functionalized with C8F17. A theoretical model using the results from the MD simulation and inputs from experimental measurements of surface morphology is further proposed to predict the WCA of functionalized microstructured PDMS surface. The validated theoretical model shows that, though increasing the filler concentration aids in enhancing surface hydrophobicity, the separation distance between neighboring features decreases, weakening the hydrophobicity property and indicating there is an optimal filler concentration for the most hydrophobic surface. To perform multiscale modeling to predict the hydrophobicity of coating, the CFD model is constructed to predict droplet sliding and bouncing on an inclined surface in the macroscopic scale by using the WCA from MD simulations and theoretical model as input. The sliding and bouncing behaviors in CFD simulations are well-matched with the experimental observations on different hydrophobic surfaces. This multiscale model presented here is useful in the formulation design for controlled surface hydrophobicity of PDMS surfaces, and it facilitates the applications of PDMS in various aqueous systems.