More than 400 million years of natural selection acting throughout the arthropoda has resulted in highly specialized and energetically efficient processes to produce protein-based fibers with properties that are a source of inspiration for all. As a result, for over 80 years researchers have been inspired by natural silk production in their attempts to spin artificial silks. While significant progress has been made, with fibers now regularly outperforming silkworm silks, surpassing the properties of superior silks, such as spider dragline, is still an area of considerable effort. This review provides an overview of the different approaches for artificial silk fiber spinning and compares all published fiber properties to date which has identified future trends and challenges on the road towards replicating high performance silks.

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The extensional flow behaviour and spinnability of native silk proteins at rates comparable to natural spinning are investigated.

Synthetic silk production has undergone significant technological and commercial advances over the past 5 years, with fibers from most labs and companies now regularly matching the properties of natural silk by one metric or another. Yet the fundamental links between silk protein processing and performance remain largely unresolved and fiber optimization is commonly achieved through non-natural methods. In an effort to address this challenge, data that closes this loop of processing and performance is presented by spinning a native silk feedstock ex vivo into a near-native fiber using just two naturally occurring parameters; pH activation and extensional flow (i.e., spinning rate). This allows us to link previous experimental and modelling hypothesis surrounding silk's pH responsiveness directly to multiscale hierarchical structure development during spinning. Finally, fibers that match, and then exceed, natural silk's mechanical properties are spun and understood by rate of work input. This approach not only provides energetic insights into natural silk spinning and controlled protein denaturation, but is believed will help interpret and improve synthetic silk processing. Ultimately, it is hoped that these results will contribute towards novel bioinspired energy-efficient processing strategies that are driven by work input optimization and where excellent mechanical properties are self-emergent.