Despite widespread use of silk, it remains a significant challenge to fabricate fibers with properties similar to native silk. It has recently been recognized that the key to tuning silk fiber properties lies in controlling internal structure of assembled β-sheets. We report an advance in the precise control of silk fiber formation with control of properties via microfluidic solution spinning. We use an experimental approach combined with modeling to accurately predict and independently tune fiber properties including Young’s modulus and diameter to customize fibers. This is the first reported microfluidic approach capable of fabricating functional fibers with predictable properties and provides new insight into the structural transformations responsible for the unique properties of silk. Unlike bulk processes, our method facilitates the rapid and inexpensive fabrication of fibers from small volumes (50 μL) that can be characterized to investigate sequence-structure-property relationships to optimize recombinant silk technology to match and exceed natural silk properties.

Tailored biomaterials with tunable functional properties are desirable for many applications ranging from drug delivery to regenerative medicine. To improve the predictability of biopolymer materials functionality, multiple design parameters need to be considered, along with appropriate models. In this article we review the state of the art of synthesis and processing related to the design of biopolymers, with an emphasis on the integration of bottom-up computational modeling in the design process. We consider three prominent examples of well-studied biopolymer materials – elastin, silk, and collagen – and assess their hierarchical structure, intriguing functional properties and categorize existing approaches to study these materials. We find that an integrated design approach in which both experiments and computational modeling are used has rarely been applied for these materials due to difficulties in relating insights gained on different length- and time-scales. In this context, multiscale engineering offers a powerful means to accelerate the biomaterials design process for the development of tailored materials that suit the needs posed by the various applications. The combined use of experimental and computational tools has a very broad applicability not only in the field of biopolymers, but can be exploited to tailor the properties of other polymers and composite materials in general.

The mechanical properties of spider silks drive interest as sources of new materials. However, there remains a lot to learn regarding the relationships between sequence, structure, and mechanical properties. In order to predict the types of sequence–functional relationships, synthesis–characterization–computation are integrated using recombinant spider silk‐like block copolymers. Two designs are studied, both with origins from the spider Nephila clavipes. These proteins are studied both experimentally and in silico to understand the relationships between sequence chemistry, processing, structure, and materials function. Films formed from the two proteins are thoroughly characterized. In parallel, molecular modeling is used to assess the propensity of the two sequences to form β‐sheets or crystalline structures. The results demonstrate that the modeling predicts the structural differences between the two silk‐like polymers and these features can also be related to differences in functional outcomes. With this example of relating sequence design (hydrophobic–hydrophilic domains), experiment (genetic design and synthesis), processing (film and fiber formation) and modeling (predictions of crystallinity), synergy among these methods is demonstrated for predictable material outcomes. This approach offers a robust discovery path when looking towards next generation approaches to targeted materials outcomes.

No abstract