A general-purpose material property data extraction pipeline from large polymer corpora using natural language processing

The ever-increasing number of materials science articles makes it hard to infer chemistry-structure-property relations from literature. We used natural language processing methods to automatically extract material property data from the abstracts of polymer literature. As a component of our pipeline, we trained MaterialsBERT, a language model, using 2.4 million materials science abstracts, which outperforms other baseline models in three out of five named entity recognition datasets. Using this pipeline, we obtained ~300,000 material property records from ~130,000 abstracts in 60 hours. The extracted data was analyzed for a diverse range of applications such as fuel cells, supercapacitors, and polymer solar cells to recover non-trivial insights. The data extracted through our pipeline is made available at polymerscholar.org which can be used to locate material property data recorded in abstracts. This work demonstrates the feasibility of an automatic pipeline that starts from published literature and ends with extracted material property information.

Polyurethane elastomers with amphiphilic ABA tri-block co-polymers as the soft segments showing record-high tensile strength and simultaneously increased ductility

Polyurethane elastomers with amphiphilic ABA tri-block co-polymers as the soft segments robustly show record-high tensile strength and simultaneously increased ductility via producing small and uniform hard domains.

Simultaneously improving the ductility and strength of aromatic thermoset films

Aromatic thermoset materials have shown great potential applications in various fields owing to their excellent mechanical strengths. However, their poor ductility is still hinders their large-scale applications. In this study, a new class of aromatic thermosets consisting of two types of crosslinks was successfully developed by incorporating the special group imidazole into a type of crosslinked thermoset. One crosslink is constituted of reversible multiple noncovalent interactions containing “face-face” π–π stacking, “point-point” hydrogen bonds, and ion-pair electrostatic interactions, whereas the other is composed of permanent covalent bonds. Most importantly, the synergetic interplay among these reversible multiple noncovalent interactions enables them to evade the restrictions from the aromatic polymer skeletons to proceed with their dynamic dissociating-rebuilding processes, which can timely and effectively dissipate the internal stress. Finally, owing to the coefficient of these two types of crosslinks, a significantly enhanced ductility was successfully obtained on these aromatic thermosets and their tensile strengths were also improved. Such thermosets having simultaneously enhanced strengths and ductility are predicted to be eventually used in a wide range of applications.