Zhuohong has successfully defended his thesis, "Optimizing Stability of Plant Virus-Based Nanoparticles for Applications in Agriculture and Material Advances". Congratulations Dr. Wu!

Abe has successfully defended his thesis, "Junctions and Strands: Breaking Property Tradeoffs in Polymer Networks and Composite Polymer Electrolytes". Congratulations Dr. Herzog-Arbeitman!

Craig and Rubinstein discuss how reducing the crosslink density in highly entangled natural rubber increases its crack resistance and prolongs its useful life. Article Link

The MONET team traveled to Durham, NC for the Year 4 Annual meeting and sponsor review. Over three days we presented the work accomplished so far and discussed ideas for the future. These are invaluable opportunities for face to face interactions and lead to great new collaborations!

This award recognizes outstanding early career investigators conducting research in any area of fundamental polymer or biopolymer science. Professor Kalow will be honored during an award symposium at ACS Fall 2025 in Washington, D.C. from August 17-21. Congratulations Julia!

A team from the Gong and Rubinstein labs report demonstrate how weak bonds can be leveraged to achieve self-strengthening in polymer network materials. These weak sacrificial bonds trigger mechanochemical reactions, forming new networks rapidly enough to reinforce the material during deformation and significantly improve crack resistance. Article Link

A team from the Klausen , Nelson , Kulik , and Craig labs report a novel chemical design for accelerated mechanochemical bond scission based on replacing a single carbon atom in a crosslinker with a silicon atom. They show seamless incorporation of these scissile carbosilanes to toughen 3D-printed networks, which demonstrates their suitability for additive manufacturing processes. Article Link

A team from the Craig , Olsen , and Rubinstein labs, in collaboration with others at MIT, systematically study the fracture mechanics of polymer-like networks with hybrid bond strengths to reveal that varying the ratio of strong and weak strands within otherwise identical networks gives a non-monotonic relationship between intrinsic fracture energy and strong strand fraction.   The interplay between concentration and clustering of strand types in networks with hybrid bond strengths, combined with crack growth phenomena and nonlocal energy release, provides insights into unusual fracture characteristics in polymer networks and percolated lattices. Article Link

A team from the Kulik and Craig labs leverage density functional theory (DFT) and external force explicitly included (EFEI) modeling to study a set of 395 feasible Fe2+ and Co2+ candidates to discover potential transition metal mechanophores exhibiting force-activated spin-crossover. The set of spin-crossover mechanophores, the design principles, and the computational approach will be useful in guiding the high-throughput discovery of transition metal mechanophores with diverse functionalities and broad applications, including mechanically activated catalysis. Article Link

A team from the Olsen lab utilize a custom-built rheo-fluoresence setup to quantify bond dissociation in model end-linked associative polymers in real time with nonlinear shear deformation based on a fluorescence quench transition when phenanthroline ligands bind with Ni 2+ . Article Link

A team from the Moore lab introduce the restoring force triangle (RFT) to facilitate understanding of the selective responsiveness of mechanophores as specific molecular units within the macromolecular backbone that are particularly sensitive to tension. The RFT helps chemists intuitively understand how tensile force contributes to the activation of a putative mechanophore, facilitating the development of mechanochemical reactions and mechano-responsive materials. Article Link

A team from the Nelson and Olvera de la Cruz labs establish a strain learning mechanical metamaterial that can not only recover after plastic deformation but also become stronger and stiffer in response to the applied loads. These protein–polymer strain learning metamaterials offer a unique platform for materials that can autonomously remodel after being deformed, mimicking the remodeling processes that occur in natural materials. Article Link