137 research outputs found

    Looking for Design in Materials Design

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    Despite great advances in computation, materials design is still science fiction. The construction of structure-property relations on the quantum scale will turn computational empiricism into true design.Comment: 3 pages, 1 figur

    Molecular Dynamics Simulation of Polymer-Metal Bonds

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    Molecular simulation is becoming a very powerful tool for studying dynamic phenomena in materials. The simulation yields information about interaction at length and time scales unattainable by experimental measurements and unpredictable by continuum theories. This is especially meaningful when referring to bonding between a polymer and a metal substrate. A very important characteristic of polymers is that their physical properties do not rely on the detailed chemical structure of the molecular chains but only on their flexibility, and accordingly they will be able to adopt different conformations. In this paper, a molecular simulation of the bonding between vinyl ester polymer and steel is presented. Four different polymers with increasing chain lengths have been studied. Atomic co-ordinates are adjusted in order to reduce the molecular energy. Conformational changes in the macromolecules have been followed to obtain the polymer pair correlation function. Radius of gyration and end-to-end distance distributions of the individual chains have been used as a quantitative measurement of their flexibility. There exists a correlation between flexibility of the molecular chains and the energy of adhesion between the polymer and the metal substrate. Close contacts between the two materials are established at certain points but every atom up to a certain distance from the interface contributes to the total value of the adhesion energy of the system

    Life Cycle Costs and Life Cycle Assessment for the Harvesting, Conversion, and the Use of Switchgrass to Produce Electricity

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    This paper considers both LCA and LCC of the pyrolysis of switchgrass to use as an energy source in a conventional power plant. The process consists of cultivation, harvesting, transportation, storage, pyrolysis, transportation, and power generation. Here pyrolysis oil is converted to electric power through cocombustion in conventional fossil fuel power plants. Several scenarios are conducted to determine the effect of selected design variables on the production of pyrolysis oil and type of conventional power plants. The set of design variables consist of land fraction, land shape, the distance needed to transport switchgrass to the pyrolysis plant, the distance needed to transport pyrolysis oil to electric generation plant, and the pyrolysis plant capacity. Using an average agriculture land fraction of the United States at 0.4, the estimated cost of electricity from pyrolysis of 5000 tons of switchgrass is the lowest at $0.12 per kwh. Using natural gas turbine power plant for electricity generation, the price of electricity can go as low as 7.70 cent/kwh. The main advantage in using a pyrolysis plant is the negative GHG emission from the process which can define that the process is environmentally friendly

    Microchannel Reactor System for Catalytic Hydrogenation

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    We successfully demonstrated a novel process intensification concept enabled by the development of microchannel reactors, for energy efficient catalytic hydrogenation reactions at moderate temperature, and pressure, and low solvent levels. We designed, fabricated, evaluated, and optimized a laboratory-scale microchannel reactor system for hydrogenation of onitroanisole and a proprietary BMS molecule. In the second phase of the program, as a prelude to full-scale commercialization, we designed and developed a fully-automated skid-mounted multichannel microreactor pilot plant system for multiphase reactions. The system is capable of processing 1 – 10 kg/h of liquid substrate, and an industrially relevant immiscible liquid-liquid was successfully demonstrated on the system. Our microreactor-based pilot plant is one-of-akind. We anticipate that this process intensification concept, if successfully demonstrated, will provide a paradigm-changing basis for replacing existing energy inefficient, cost ineffective, environmentally detrimental slurry semi-batch reactor-based manufacturing practiced in the pharmaceutical and fine chemicals industries

    Large Scale Benchmark of Materials Design Methods

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    Lack of rigorous reproducibility and validation are major hurdles for scientific development across many fields. Materials science in particular encompasses a variety of experimental and theoretical approaches that require careful benchmarking. Leaderboard efforts have been developed previously to mitigate these issues. However, a comprehensive comparison and benchmarking on an integrated platform with multiple data modalities with both perfect and defect materials data is still lacking. This work introduces JARVIS-Leaderboard, an open-source and community-driven platform that facilitates benchmarking and enhances reproducibility. The platform allows users to set up benchmarks with custom tasks and enables contributions in the form of dataset, code, and meta-data submissions. We cover the following materials design categories: Artificial Intelligence (AI), Electronic Structure (ES), Force-fields (FF), Quantum Computation (QC) and Experiments (EXP). For AI, we cover several types of input data, including atomic structures, atomistic images, spectra, and text. For ES, we consider multiple ES approaches, software packages, pseudopotentials, materials, and properties, comparing results to experiment. For FF, we compare multiple approaches for material property predictions. For QC, we benchmark Hamiltonian simulations using various quantum algorithms and circuits. Finally, for experiments, we use the inter-laboratory approach to establish benchmarks. There are 1281 contributions to 274 benchmarks using 152 methods with more than 8 million data-points, and the leaderboard is continuously expanding. The JARVIS-Leaderboard is available at the website: https://pages.nist.gov/jarvis_leaderboar
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