Polymer networks are complex systems consisting of molecular components. Whereas the
properties of the individual components are typically well understood by most chemists …

Decades of nanotoxicology research have generated extensive and diverse data sets.
However, data is not equal to information. The question is how to extract critical information …

Synthetic polymers are versatile and widely used materials. Similar to small organic
molecules, a large chemical space of such materials is hypothetically accessible …

Polymer–protein hybrids are intriguing materials that can bolster protein stability in non‐
native environments, thereby enhancing their utility in diverse medicinal, commercial, and …

The design rules for materials are clear for applications with a single objective. For most
applications, however, there are often multiple, sometimes competing objectives where …

Accurate and efficient prediction of polymer properties is of great significance in polymer
design. Conventionally, expensive and time-consuming experiments or simulations are …

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 …

The design of new functional polymers depends on the successful navigation of their
structure-function landscapes. Advances in combinatorial polymer chemistry and machine …

Recent breakthroughs in computing power have made it feasible to use machine learning
and deep learning to advance scientific computing in many fields, including fluid mechanics …

The complexity and diversity of polymer topologies, or chain architectures, present
substantial challenges in predicting and engineering polymer properties. Although machine …