Hyper-morphology: Experimentations with bio-inspired design processes for adaptive spatial re-use

This article is a newer version of a paper originally published in the eCAADe 2013 Conference Proceedings Computation & Performance. Hyper-Morphology is an on-going research outlining a bottom-up evolutionary design process based on autonomous cellular building components. The research interfaces critical operational traits of the natural world (Evolutionary Development Biology, Embryology and Cellular Differentiation) with Evolutionary Computational techniques driven design methodologies. In the Hyper-Morphology research, genetic sequences are considered as sets of locally coded relational associations between multiple factors such as the amount of components, material based constraints, and geometric adaptation/degrees of freedom based adaptation abilities etc, which are embedded autonomously within each HyperCell component. Collective intelligence driven decision-making processes are intrinsic to the Hyper-Morphology logic for intelligently operating with autonomous componential systems (akin to swarm systems). This subsequently results in user and activity centric global morphology generation in real-time. Practically, the Hyper-Morphology research focuses on a 24/7 economy loop wherein real-time adaptive spatial usage interfaces with contemporary culture of flexible living within spatial constraints in a rapidly urbanizing world.Architecture and The Built Environmen

Hyper-Morphology: Experimentations with bio-inspired design processes for adaptive spatial re-use

Hyper-Morphology is an on-going research outlining a bottom-up evolutionary design process based on autonomous cellular building components. The research interfaces critical operational traits of the natural world (Evolutionary Development Biology, Embryology and Cellular Differentiation) with Evolutionary Computational techniques driven design methodologies. In the Hyper-Morphology research, genetic sequences are considered as sets of locally coded relational associations between multiple factors such as the amount of components, material based constraints, and geometric adaptation/degrees of freedom based adaptation abilities etc, which are embedded autonomously within each HyperCell component. Collective intelligence driven decision-making processes are intrinsic to the Hyper-Morphology logic for intelligently operating with autonomous componential systems (akin to swarm systems). This subsequently results in user and activity centric global morphology generation in real-time. Practically, the Hyper-Morphology research focuses on a 24/7 economy loop wherein real-time adaptive spatial usage interfaces with contemporary culture of flexible living within spatial constraints in a rapidly urbanizing world.Architectural Engineering +TechnologyArchitecture and The Built Environmen

Recent advances in metasurface design and quantum optics applications with machine learning, physics-informed neural networks, and topology optimization methods

As a two-dimensional planar material with low depth profile, a metasurface can generate non-classical phase distributions for the transmitted and reflected electromagnetic waves at its interface. Thus, it offers more flexibility to control the wave front. A traditional metasurface design process mainly adopts the forward prediction algorithm, such as Finite Difference Time Domain, combined with manual parameter optimization. However, such methods are time-consuming, and it is difficult to keep the practical meta-atom spectrum being consistent with the ideal one. In addition, since the periodic boundary condition is used in the meta-atom design process, while the aperiodic condition is used in the array simulation, the coupling between neighboring meta-atoms leads to inevitable inaccuracy. In this review, representative intelligent methods for metasurface design are introduced and discussed, including machine learning, physics-information neural network, and topology optimization method. We elaborate on the principle of each approach, analyze their advantages and limitations, and discuss their potential applications. We also summarize recent advances in enabled metasurfaces for quantum optics applications. In short, this paper highlights a promising direction for intelligent metasurface designs and applications for future quantum optics research and serves as an up-to-date reference for researchers in the metasurface and metamaterial fields.ImPhys/Adam groupQN/Groeblacher LabQN/Quantum NanoscienceImPhys/Urbach grou