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Advances in renewable and sustainable energy technologies critically depend on our ability to design and realize materials with optimal properties. Materials discovery and design efforts ideally involve close coupling between materials prediction, synthesis and characterization. The increased use of computational tools, the generation of materials databases, and advances in experimental methods have substantially accelerated these activities. It is therefore an opportune time to consider future prospects for materials by design approaches. The purpose of this Roadmap is to present an overview of the current state of computational materials prediction, synthesis and characterization approaches, materials design needs for various technologies, and future challenges and opportunities that must be addressed. The various perspectives cover topics on computational techniques, validation, materials databases, materials informatics, high-throughput combinatorial methods, advanced characterization approaches, and materials design issues in thermoelectrics, photovoltaics, solid state lighting, catalysts, batteries, metal alloys, complex oxides and transparent conducting materials. It is our hope that this Roadmap will guide researchers and funding agencies in identifying new prospects for materials design.

Several critical technologies are currently materials-limited, awaiting novel materials solutions for advancement, e.g., transportation (light-weight, high-strength alloys, and corrosion resistant coatings), sustainable energy (earth-abundant catalysts for solar fuel production), and nanoelectronics (low-energy/operation integrated circuit devices). The main goal of the Materials Genome Initiative (MGI), launched in 2011, is the discovery, process optimization, and commercial deployment of novel materials twice as fast as current practice (5-10 vs. 10-20 years), and at reduced cost. The MGI has resulted in significant progress in computational simulation and modeling to enable predictions of materials properties. More recently, an experimental component, based on high-throughput experimental (also known as combinatorial) materials science has been added. [ABSTRACT FROM AUTHOR]

Using near-edge X-ray absorption fine structure (NEXAFS) spectroscopy, we shed light on the nature of the interaction between CO2 and the amine moieties in a hyperbranched aminosilica (HAS) material, a porous aminosilica composite with great potential for postcombustion carbon capture applications. We show that after dosing a pristine (annealed) HAS sample with CO2, the C K-edge NEXAFS spectrum presents a new π* resonance at 289.9 eV, which can be attributed to the formation of a C═O (carbonyl) bond. Additional analyses of the O K-edge using model samples containing carbamate, carbonate, and bicarbonate functional groups as reference demonstrate a carbamate bonding mechanism for the chemical adsorption of CO2 by the HAS material under the conditions employed. These findings show the capability of the C and O K-edge NEXAFS technique to identify CO2-adsorbate species despite the high concentration of C and O atoms inherently present in the sample (prior to CO2 dosing) and the significant similarities between the possible adsorbates.