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Machine learning (ML) is increasingly central to chemical discovery, yet most efforts remain confined to distributed and isolated research groups, limiting external validation and community engagement. Here, we introduce a generalizable mode of scientific outreach that couples a published study to a community-engaged test set, enabling post-publication evaluation by the broader ML community. This approach is demonstrated using a prior study on AI-guided discovery of photostable light-harvesting small molecules. After publishing an experimental dataset and in-house ML models, we leveraged automated block chemistry to synthesize nine additional light-harvesting molecules to serve as a blinded community test set. We then hosted an open Kaggle competition where we challenged the world community to outperform our best in-house predictive photostability model. In only one month, this competition received >700 submissions, including several innovative strategies that improved upon our previously published results. Given the success of this competition, we propose community-engaged test sets as a blueprint for post-publication benchmarking that democratizes access to high-quality experimental data, encourages innovative scientific engagement, and strengthens cross-disciplinary collaboration in the chemical sciences. 

Abstract Mechanoresponsive polymeric materials that respond to mechanical deformation are highly valued for their potential in sensors, degradation studies, and optoelectronics. However, direct visualization and detection of these responses remain significant obstacles. In this study, novel mechanoresponsive polybiidenedionediyl (PBIT) derivative topochemical polymers are developed that depolymerize under mechanical forces, exhibiting a distinct and irreversible color change in response to grinding, milling, and compression. This color change is attributed to the alteration of polymer backbone conjugation during elongated Carbon‐Carbon (C─C) single bond cleavage. Quantum chemical pulling simulations on PBIT polymers reveals a force range of 4.3–5.0 nN associated with the selective cleavage of elongated C─C single bonds. This force range is comparable to that observed for typical homolytic mechanophores, supporting the mechanistic interpretation of homolytic bond scission under mechanical stress. C─C bond cleavage kinetic studies of PBIT under compression indicates that strong interchain interactions significantly increase the pressure needed to cleave the elongated C─C bonds. Additionally, PBIT polymer thin films are composited with polydimethylsiloxane to create free‐standing and robust thin films, which can serve as ink‐free and rewritable paper for writing and stress visualization applications. This advancement opens new possibilities for utilizing crystalline and brittle topochemical polymers in practical applications. 

We report a reversible photo-induced doping effect in two-dimensional (2D) tungsten diselenide (WSe 2 ) field effect transistors on hexagonal boron nitride (h-BN) substrates under low-intensity visible light illumination (∼10 nW μm −2 ). Our experimental results have shown that this reversible doping process is mainly attributed to two types of defects in h-BN substrates. Moreover, the photo-doped WSe 2 transistors can be stable for more than one week in a dark environment and maintain the high on/off ratio (10 8 ) and carrier mobility, since there are no additional impurities involved during the photo-induced doping process to increase the columbic scattering in the conducting channel. These fundamental studies not only provide an accessible strategy to control the charge doping level and then to achieve a writing/erasing process in 2D transistors, but also shed light on the defect states and interfaces in 2D materials.