We present a unified density-based topology-optimization framework that yields integrated photonic designs optimized for manufacturing constraints including all those of commercial semiconductor foundries. We introduce a new method to impose minimum-area and minimum-enclosed-area constraints, and simultaneously adapt previous techniques for minimum linewidth, linespacing, and curvature, all of which are implemented without any additional re-parameterizations. Furthermore, we show how differentiable morphological transforms can be used to produce devices that are robust to over/under-etching while also satisfying manufacturing constraints. We demonstrate our methodology by designing three broadband silicon-photonics devices for nine different foundry-constraint combinations.
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Sci Rep
December 2024
School of Electrical & Electronics Engineering, SASTRA Deemed University, Thanjavur, 613 401, India.
Cement ball mills in the finishing stage of the cement industries consume the highest energy in the cement manufacturing stage. Therefore, suitable controllers that result in good productivity and product quality with reduced energy consumption are required for the cement ball mill grinding process to increase the profit margins. In this study, generalised predictive controllers (GPC)have been designed for the cement ball mill grinding operation using the model obtained from the step response data taken from the industrially recognized simulator.
View Article and Find Full Text PDFBiomimetics (Basel)
December 2024
State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150001, China.
Enabling a robot to learn skills from a human and adapt to different task scenarios will enable the use of robots in manufacturing to improve efficiency. Movement Primitives (MPs) are prominent tools for encoding skills. This paper investigates how to learn MPs from a small number of human demonstrations and adapt to different task constraints, including waypoints, joint limits, virtual walls, and obstacles.
View Article and Find Full Text PDFFront Artif Intell
December 2024
School of Industrial Engineering and Management, Oklahoma State University, Stillwater, OK, United States.
The ability to accurately predict the yields of different crop genotypes in response to weather variability is crucial for developing climate resilient crop cultivars. Genotype-environment interactions introduce large variations in crop-climate responses, and are hard to factor in to breeding programs. Data-driven approaches, particularly those based on machine learning, can help guide breeding efforts by factoring in genotype-environment interactions when making yield predictions.
View Article and Find Full Text PDFJ Mech Behav Biomed Mater
December 2024
Centre for Precision Engineering Material and Manufacturing Research (PEM Research Centre), Atlantic Technological University, Ash Lane, Sligo, F91 YW50, Ireland; School of Mechanical Engineering, Technological University Dublin, Dublin, Ireland.
Chem Rev
December 2024
Department of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois 60208, United States.
Cell-free gene expression (CFE) systems empower synthetic biologists to build biological molecules and processes outside of living intact cells. The foundational principle is that precise, complex biomolecular transformations can be conducted in purified enzyme or crude cell lysate systems. This concept circumvents mechanisms that have evolved to facilitate species survival, bypasses limitations on molecular transport across the cell wall, and provides a significant departure from traditional, cell-based processes that rely on microscopic cellular "reactors.
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