Enzyme-induced mineralization (EIM) has been shown to greatly enhance the mechanical properties of hydrogels by precipitation of calcium salts. Another feature of such hydrogels is their high toughness even when containing finely nanostructured mineral content of ≈75 wt%. This might be useful for bendable materials with high content of functional inorganic nanostructures. The present study demonstrates that EIM can form homogeneous nanostructures of water-insoluble iron salts within hydrogels. Crystalline iron(II) carbonate precipitates urease-induced within polyacrylate-based hydrogels and forms platelet structures that have the potential of forming self-organized nacre-like architectures. The platelet structure can be influenced by chemical composition of the hydrogel. Further, amorphous iron(II) phosphate precipitates within hydrogels with alkaline phosphatase, forming a nanostructured porous inorganic phase, homogeneously distributed within the double network hydrogel. The high amount of iron phosphate (more than 80 wt%) affords a stiffness of ≈100 MPa. The composite is still bendable with considerable toughness of 400 J m −2 and strength of 1 MPa. The high water content (>50%) may allow fast diffusion processes within the material. This makes the iron phosphate-based composite an interesting candidate for flexible electrodes and demonstrates that EIM can be used to deliberately soften ceramic materials, rendering them bendable.

The increasing digitalization and standardization within the process industry lead to a high availability of digital, machine-readable processes and plant descriptions. In particular, the publication of the DEXPI standard provides a digital representation of plant topologies including a complete description of all specifications. In early planning phases, this can be used as the basis for an automated safety assessment since digital availability significantly simplifies accessibility for smart search algorithms. This paper presents the preHAZOP search algorithm, which was developed to analyze P&IDs in DEXPI format and to detect safety-critical deviations regarding their risk according to a classical HAZOP analysis. The preHAZOP is of particular interest in early process development stages and can be easily integrated into modern, digital engineering workflows.

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