Beam network model for fracture of materials with hierarchical microstructure

We introduce a beam network model for hierarchically patterned materials. In these materials, load-parallel gaps intercept stress transmission in the load perpendicular direction in such a manner that damage is confined within hierarchically nested, load-carrying ‘modules’. We describe the morphological characteristics of such materials in terms of deterministically constructed, hierarchical beam network (DHBN) models and randomized variants thereof. We then use these models to analyse the process of damage accumulation (characterized by the locations and timings of beam breakages prior to global failures, and the concomitant avalanche statistics) and of global failure. We demonstrate that, irrespective of the degree of local disorder, failure of hierarchically (micro)structured materials is characterized by diffuse local damage nucleation which ultimately percolates on the network, but never by stress-driven propagation of a critical crack. Failure of non hierarchical reference networks, on the other hand, is characterized by the sequence of damage nucleation, crack formation and crack propagation. These differences are apparent at low and intermediate degrees of material disorder but disappear in very strongly disordered materials where the local failure strengths exhibit extreme scatter. We furthermore demonstrate that, independent of material disorder, the different modes of failure lead to significant differences in fracture surface morphology.

A universal method for depositing patterned materials in situ

Current techniques of patterned material deposition require separate steps for patterning and material deposition. The complexity and harsh working conditions post serious limitations for fabrication. Here, we introduce a single-step and easy-to-adapt method that can deposit materials in-situ. Its methodology is based on the semiconductor nanoparticle assisted photon-induced chemical reduction and optical trapping. This universal mechanism can be used for depositing a large selection of materials including metals, insulators and magnets, with quality on par with current technologies. Patterning with several materials together with optical-diffraction-limited resolution and accuracy can be achieved from macroscopic to microscopic scale. Furthermore, the setup is naturally compatible with optical microscopy based measurements, thus sample characterisation and material deposition can be realised in-situ. Various devices fabricated with this method in 2D or 3D show it is ready for deployment in practical applications. This method will provide a distinct tool in material technology.

Image Analysis of Structured Surfaces for Quantitative Topographical Characterization

<p>In the fields of functional materials, interfacial chemistry, and microscale devices, surface structuring provides an opportunity to engineer materials with unique tunable properties such as wettability, anti-fouling, crack propagation, and specific surface area. Often, the resulting properties are related to the feature sizes of the structured surfaces and therefore, it is necessary to accurately quantify these topographies. This work presents a step-by-step description of a method for the quantification of the size of periodic structures using 2D discrete Fourier Transform analysis coupled with data filtering techniques to optimize feature size extraction and reduce user bias and error. The method is validated using artificial images of periodic patterns as well as scanning electron microscopy images of gold films that are structured on different substrates. While image Fourier Transform has been used previously and is a built-in feature in some commercial and open-source image analysis software, this work details image pre-processing and feature extraction steps, and how to best apply them, which has not been described in detail elsewhere. This method can analyze engineered or natural periodic topographies (e.g., wrinkles) to enable the design of patterned materials for applications including photovoltaics, biosensors, tissue engineering, flexible electronics, and thin film metrology.</p>

Image Analysis of Structured Surfaces for Quantitative Topographical Characterization

<p>In the fields of functional materials, interfacial chemistry, and microscale devices, surface structuring provides an opportunity to engineer materials with unique tunable properties such as wettability, anti-fouling, crack propagation, and specific surface area. Often, the resulting properties are related to the feature sizes of the structured surfaces and therefore, it is necessary to accurately quantify these topographies. This work presents a step-by-step description of a method for the quantification of the size of periodic structures using 2D discrete Fourier Transform analysis coupled with data filtering techniques to optimize feature size extraction and reduce user bias and error. The method is validated using artificial images of periodic patterns as well as scanning electron microscopy images of gold films that are structured on different substrates. While image Fourier Transform has been used previously and is a built-in feature in some commercial and open-source image analysis software, this work details image pre-processing and feature extraction steps, and how to best apply them, which has not been described in detail elsewhere. This method can analyze engineered or natural periodic topographies (e.g., wrinkles) to enable the design of patterned materials for applications including photovoltaics, biosensors, tissue engineering, flexible electronics, and thin film metrology.</p>

Controlled deprotection and release of a small molecule from a compartmented synthetic tissue module

Synthetic tissues built from communicating aqueous droplets offer potential applications in biotechnology, however, controlled release of their contents has not been achieved. Here we construct two-droplet synthetic tissue modules that function in an aqueous environment. One droplet contains a cell-free protein synthesis system and a prodrug-activating enzyme and the other a small-molecule prodrug analog. When a Zn2+-sensitive protein pore is made in the first droplet, it allows the prodrug to migrate from the second droplet and become activated by the enzyme. With Zn2+ in the external medium, the activated molecule is retained in the module until it is released on-demand by a divalent cation chelator. The module is constructed in such a manner that one or more, potentially with different properties, might be incorporated into extended synthetic tissues, including patterned materials generated by 3D-printing. Such modules will thereby increase the sophistication of synthetic tissues for applications including controlled multidrug delivery.

Material patterning on substrates by manipulation of fluidic behavior

ABSTRACT Patterned materials on substrates are of great importance for a wide variety of applications. In solution-based approaches to material patterning, fluidic flow is inevitable. Here we demonstrate not only the importance of fluidic behavior but also the methodology of engineering the flow pattern to guide the material crystallization and assembly. We show by both experiment and simulation that substrate heating, which is generally used to accelerate evaporation, produces irregular complex vortexes. Instead, a top-heating–bottom-cooling (THBC) set-up offers an inverse temperature gradient and results in a single Marangoni vortex, which is desired for ordered nanomaterial patterning near the contact line. We then realize the fabrication of large-scale patterns of iodide perovskite crystals on different substrates under THBC conditions. We further demonstrate that harnessing the flow behavior is a general strategy with great feasibility to pattern various functional materials ranging from inorganic, organic, hybrid to biological categories on different substrates, presenting great potential for practical applications.