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Abstract The brick-and-mortar structure inspired by nature, such as in nacre, is considered one of the most optimal designs for structural composites. Given the large number of design possibilities, extensive computational work is required to guide their manufacturing. Here, we propose a computational framework that combines statistical analysis and machine learning with finite element analysis to establish structure–property design strategies for brick-and-mortar composites. Approximately 20,000 models with different geometrical designs were categorized into good and bad based on their failure modes, with statistical analysis of the results used to find the importance of each feature. Aspect ratio of the bricks and horizontal mortar thickness were identified as the main influencing features. A decision tree machine learning model was then established to draw the boundaries of good design space. This approach might be used for the design of brick-and-mortar composites with improved mechanical properties. 

Abstract Printing functional devices on flexible substrates requires printing of high conductivity metallic patterns. To prevent deformation and damage of the polymeric substrate, the processing (printing) and post-processing (annealing) temperature of the metal patterns must be lower than the glass transition temperature of the substrate. Here, a hybrid process including deposition of a sacrificial blanket thin film, followed by room environment nozzle-based electrodeposition, and subsequent etching of the blanket film is demonstrated to print pure and nanocrystalline metallic (Ni and Cu) patterns on flexible substrates (PI and PET). Microscopy and spectroscopy showed that the printed metal is nanocrystalline, solid with no porosity and with low impurities. Electrical resistivity close to the bulk (~2-time) was obtained without any thermal annealing. Mechanical characterization confirmed excellent cyclic strength of the deposited metal, with limited degradation under high cyclic flexure. Several devices including radio frequency identification (RFID) tag, heater, strain gauge, and temperature sensor are demonstrated.