In the last five years, there has been tremendous growth in machine learning and artificial
intelligence as applied to polymer science. Here, we highlight the unique challenges …

Microrheology encompasses a range of methods to measure the mechanical properties of
soft materials. By characterizing the motion of embedded microscopic particles …

Abstract 3D bioprinting, a vital tool in tissue engineering, drug testing, and disease
modeling, is increasingly integrated with machine learning (ML) and artificial intelligence …

AI and ML have emerged as transformative tools in various scientific domains, including
hydrogel design. This work explores the integration of AI and ML techniques in the realm of …

This review summarizes recent progress in investigating polymer systems by using
Differential dynamic microscopy (DDM), a rapidly emerging approach that transforms a …

Estimating parameters from data is a fundamental problem in physics, customarily done by
minimizing a loss function between a model and observed statistics. In scattering-based …

A high-throughput microrheological assay is employed to assess the gelation kinetics of a
coiled-coil protein, Q, across a compositional space with varying ionic strengths and pH …

Microrheology based on video microscopy of embedded tracer particles has the potential to
be used for high-throughput protein-based materials characterization. This potential is due …

Abstract Structure and hierarchical organization are crucial elements of biological systems
and are likely required when engineering synthetic biomaterials with life‐like behavior. In …

This review discusses three types of soft matter and liquid molecular materials, namely
hydrogels, liquid crystals and gas bubbles in liquids, which are explored with an emergent …