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Abstract Topochemical polymerizations hold the promise of producing high molecular weight and stereoregular single crystalline polymers by first aligning monomers before polymerization. However, monomer modifications often alter the crystal packing and result in non‐reactive polymorphs. Here, we report a systematic study on the side chain functionalization of the bis(indandione) derivative system that can be polymerized under visible light. Precisely engineered side chains help organize the monomer crystals in a one‐dimensional fashion to maintain the topochemical reactivity. By optimizing the side chain length and end group of monomers, the elastic modulus of the resulting polymer single crystals can also be greatly enhanced. Lastly, using ultrasonication, insoluble polymer single crystals can be processed into free‐standing and robust polymer thin films. This work provides new insights on the molecular design of topochemical reactions and paves the way for future applications of this fascinating family of materials. 

We have built the first transformers trained on the property-to-molecular-graph task, which we dub “large property models”. A key ingredient is supplementing these models during training with relatively basic but abundant chemical property data. 

Abstract Cooperativity is used by living systems to circumvent energetic and entropic barriers to yield highly efficient molecular processes. Cooperative structural transitions involve the concerted displacement of molecules in a crystalline material, as opposed to typical molecule-by-molecule nucleation and growth mechanisms which often break single crystallinity. Cooperative transitions have acquired much attention for low transition barriers, ultrafast kinetics, and structural reversibility. However, cooperative transitions are rare in molecular crystals and their origin is poorly understood. Crystals of 2-dimensional quinoidal terthiophene (2DQTT-o-B), a high-performance n-type organic semiconductor, demonstrate two distinct thermally activated phase transitions following these mechanisms. Here we show reorientation of the alkyl side chains triggers cooperative behavior, tilting the molecules like dominos. Whereas, nucleation and growth transition is coincident with increasing alkyl chain disorder and driven by forming a biradical state. We establish alkyl chain engineering as integral to rationally controlling these polymorphic behaviors for novel electronic applications. 

Coarse-grained molecular dynamics (CGMD) simulations address lengthscales and timescales that are critical to many chemical and material applications. Nevertheless, contemporary CGMD modeling is relatively bespoke and there are no black-box CGMD methodologies available that could play a comparable role in discovery applications that density functional theory plays for electronic structure. This gap might be filled by machine learning (ML)-based CGMD potentials that simplify model development, but these methods are still in their early stages and have yet to demonstrate a significant advantage over existing physics-based CGMD methods. Here, we explore the potential of Δ-learning models to leverage the advantages of these two approaches. This is implemented by using ML-based potentials to learn the difference between the target CGMD variable and the predictions of physics-based potentials. The Δ-models are benchmarked against the baseline models in reproducing on-target and off-target atomistic properties as a function of CG resolution, mapping operator, and system topology. The Δ-models outperform the reference ML-only CGMD models in nearly all scenarios. In several cases, the ML-only models manage to minimize training errors while still producing qualitatively incorrect dynamics, which is corrected by the Δ-models. Given their negligible added cost, Δ-models provide essentially free gains over their ML-only counterparts. Nevertheless, an unexpected finding is that neither the Δ-learning models nor the ML-only models significantly outperform the elementary pairwise models in reproducing atomistic properties. This fundamental failure is attributed to the relatively large irreducible force errors associated with coarse-graining that produces little benefit from using more complex potentials. 

High energy density lithium–sulfur batteries (LSBs) are a potential replacement for lithium-ion batteries (LIBs). However, practical lifetimes are inhibited by lithium polysulfide (LiPS) shuttling. Concurrently, plastic waste accumulation worldwide threatens our ecosystems. Herein, a fast and facile strategy to upcycle polyethylene terephthalate (PET) waste into useful materials is investigated. Dilithium terephthalate (Li2TP) and dipotassium terephthalate (K2TP) salts were synthesized from waste soda bottles via microwave depolymerization and solution coated onto glass fiber paper (GFP) separators. Salt-functionalized separators with Li2TP@GFP and K2TP@GFP mitigated LiPS shuttling and improved electrochemical performance in cells. Pore analysis and density functional theory (DFT) calculations indicate the action mechanism is synergistic physical blocking of bulky LiPS anions in nanopores and diffusion inhibition via electrostatic interactions with abundant carboxylate groups. LSBs with K2TP@GFP separator showing highest LiPS affinity and smallest pore size demonstrated enhanced initial capacity as compared to non-modified GFP by 5.4% to 648 mAh g−1, and increased cycle 100 capacity by 23% to 551 mAh g−1. Overall, K2TP@GFP retained 85% of initial capacity after 100 cycles with an average capacity fading of 0.15% per cycle. By comparison, GFP retained only 73% of initial capacity after 100 cycles with 0.27% average capacity loss, demonstrating effective LiPS retention.