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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, synthesi ...
Aim: There is a necessity for new drugs to be more efficient than today's standard due to the emergence of drug-resistant strains of Mycobacterium tuberculosis (Mtb) Results/methodology: 12 new isoniazid-based adamantane derivatives were synthesized and te ...
Recent advances in material science and digital fabrication provide promising opportunities for product design, mechanical and biomedical engineering, robotics, architecture, art, and science. Engineered materials and personalized fabrication are revolutio ...
Computational nanophotonics has already made a disruptive impact on the photonic and optoelectronic industries and has dramatically influenced the ways today's optical engineers create, optimize, and use innovative materials and computer-aided services. Th ...
Novel computational methods such as artificial neural networks, adaptive neuro-fuzzy inference systems and genetic programming are used in this chapter for the modeling of the nonlinear behavior of composite laminates subjected to constant amplitude loadin ...
This paper deals with a main limitation of Markovian traffic assignment (MTA) models: when the network includes cyclic structures and the link costs are small enough, the fact that the MTA models assign traffic flows to all feasible paths causes computatio ...
We introduce a novel approach to reduce the computational effort of solving convex chance constrained programs through the scenario approach. Instead of reducing the number of required scenarios, we directly minimize the computational cost of the scenario ...
In homogeneous catalysis, the turnover frequency (TOF) and turnover number (TON) are the most commonly used quantities that experimentally describe catalytic activity. Computational studies, on the other hand, generally yield the ubiquitous free energy pro ...
Computational methods are crucial for the analysis of diffusion magnetic resonance imaging (MRI) of the brain. Computational diffusion MRI can provide rich information at many size scales, including local microstructure measures such as diffusion anisotrop ...
While Physics-Based Simulation (PBS) can accurately drape a 3D garment on a 3D body, it remains too costly for real-time applications, such as virtual try-on. By contrast, inference in a deep network, requiring a single forward pass, is much faster. Taking ...
