Microstructure Optimization via Grain-Boundary Segregation to Enhance DC Bias Dielectric Performance of BaTiO3 Multilayer Ceramic Capacitors.
Sign Up to like & getrecommendations! Published in 2025 at "Advanced materials"
DOI: 10.1002/adma.202507233
Abstract: BaTiO₃‐based multilayer ceramic capacitors (MLCCs) are essential components in modern electronics. To enhance overall capacitance, achieving thinner ceramic layers has become a primary issue. However, this introduces two major challenges: controlling grain size during processing… read more here.
Keywords: multilayer ceramic; ceramic capacitors; optimization via; microstructure optimization ... See more keywords
Foresight planning: Radiotherapy plan optimization via self‐supervised model predictive control
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DOI: 10.1002/mp.70132
Abstract: Treatment planning for intensity‐modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) relies on meticulous operation of the inverse optimization, a complex and iterative process of adjusting dose‐volume objectives to achieve an optimal dose… read more here.
Keywords: planning radiotherapy; via self; foresight planning; optimization via ... See more keywords
Optimization via multimodel simulation
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DOI: 10.1007/s00158-018-1934-2
Abstract: Increasing computational power and the availability of 3D printers provide new tools for the combination of modeling and experimentation. Several simulation tools can be run independently and in parallel, e.g., long running computational fluid dynamics… read more here.
Keywords: via multimodel; multimodel simulation; optimization via; optimization ... See more keywords
Distributed Bilevel Constrained Optimization via Multiagent System Approaches
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DOI: 10.1109/tcyb.2025.3531393
Abstract: In this article, two types of multiagent systems (MASs) are developed for distributed bilevel constrained optimization. Within the framework of the distributed bilevel optimization modeling, the objective function is in a summation manner of local… read more here.
Keywords: constrained optimization; bilevel constrained; distributed bilevel; optimization via ... See more keywords
Dynamical Hyperparameter Optimization via Deep Reinforcement Learning in Tracking
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DOI: 10.1109/tpami.2019.2956703
Abstract: Hyperparameters are numerical pre-sets whose values are assigned prior to the commencement of a learning process. Selecting appropriate hyperparameters is often critical for achieving satisfactory performance in many vision problems, such as deep learning-based visual… read more here.
Keywords: optimization via; hyperparameter optimization; dynamical hyperparameter; hyperparameter ... See more keywords