Charbonneau, P., Corwin, E., Parisi, G., Poncet, A., Zamponi, F. (2016). Data and scripts from: Universal non-Debye scaling in the density of states of amorphous solids. https://doi.org/doi:10.7924/G8KW5CX3
Zhuang, Y. and Charbonneau, P. (2016). Data and scripts from: Equilibrium phase behavior of the square-well linear microphase-forming model. Duke Digital Repository. https://doi.org/doi:10.7924/G8057CVF
Hu, Y., Charbonneau, P. (2018). Data and Scripts from: Clustering and assembly dynamics of a one-dimensional microphase former. Duke Digital Repository. https://doi.org/10.7924/r41n81s8j
Hu, Y., Fu, L., Charbonneau, P. (2018). Data, generating scripts and figures from: Correlation lengths in quasi-one-dimensional systems via transfer matrices. Duke Digital Repository. https://doi.org/10.7924/r4mk68m43
Pham, A. T., Zhuang, Y., Detwiler, P., Socolar, J.E.S., Charbonneau, P., Yellen, B. (2017). Data and scripts from: Phase diagram and aggregation dynamics of a monolayer of paramagnetic colloids. Duke Digital Repository. https://doi.org/doi:10.7924/G86H4FBQ
Zhuang, Y. and Charbonneau, P. (2017). Data and scripts from: Microphase equilibrium and assembly dynamics. Duke Digital Repository. https://doi.org/10.7924/G8JH3J7B
Charbonneau, P., Altan, I., Fusco, D., Afonine, P.V. (2018). Data and scripts from: Learning about biomolecular solvation from water in protein crystals. Duke Digital Repository. https://doi:10.7924/r4bg2mc23
Zhuang, Y. and Charbonneau, P. (2018). Data and scripts from: Equilibrium phase behavior of the square-well linear microphase-forming model. Duke Digital Repository. V2 https://doi.org/10.7924/r42z16837
Altan, I., & Charbonneau, P. (2019). Data and scripts from: Obtaining soft matter models of proteins and their phase behavior. Duke Digital Repository. https://doi.org/10.7924/r4ww7bs1p
Fu, L., Steinhardt, W., Zhao, Y., Socolar, J.E.S., and Charbonneau, P. (2017). Data and scripts from: Hard sphere packings within cylinders. Duke Digital Repository. https://doi.org/10.7924/G8SF2T3Z
Fu, L., Bian, C., Shields, W., Cruz, D., Lopez, G., Charbonneau, P. (2017). Data and scripts from: Assembly of hard spheres in a cylinder: a computational and experimental study. Duke Digital Repository. https://doi.org/doi:10.7924/G82Z13F1
Jin, Y., Ru, X., Su, N., Beratan, D., Zhang, P., & Yang, W. (2020). Data from: Revisiting the Hole Size in Double Helical DNA with Localized Orbital Scaling Corrections. Duke Research Data Repository. https://doi.org/10.7924/r4k072k9s
Lin, Y., Kouznetsova, T., Chang, C., Craig, S. (2020). Data from: Enhanced polymer mechanical degradation through mechanochemically unveiled lactonization. Duke Research Data Repository. https://doi.org/10.7924/r49s1r065
Zhang, Y., Wang, Z., Kouznetsova, T., Sha, Y., Xu, E., Shannahan, L., Fermen-Coker, M., Lin., Y., Craig, S. (2020). Data from: Distal conformational locks on ferrocene mechanophores guide reaction pathways for enhanced mechanochemistry. V2 Duke Research Data Repository. https://doi.org/10.7924/r4125x84n
How can an amorphous material be rigid? Glass – the prototypical and ubiquitous amorphous solid – inhabits an incredibly ramified and complex energy landscape, which presumably underlies its rigidity. But how? Dealing with so many relevant energy minima and the ensuing far-from-equilibrium dynamics has emerged as one of the central problems in statistical physics. Tackling it requires new tools and concepts. The Simons Collaboration on Cracking the Glass Problem, addressing such fundamental issues as disorder, nonlinear response and far-from-equilibrium dynamics, builds upon three powerful approaches: the study of marginal stability at jamming, the mean-field theory of glasses in infinite dimension, and the dynamics of systems in complex landscapes. The convergence of recent breakthroughs in these areas generates a unique opportunity to come to grips with these three outstanding and intimately related challenges. This collection of datasets is associated with publications from the Charbonneau group and their collaborators as part of the Simons collaboration.
Khan, A., James, S., Quinn, M., Altan, I., Charbonneau, P., & McManus, J. (2019). Data and scripts from: temperature-dependent interactions explain normal and inverted solubility in a γD-crystallin mutant. Duke Digital Repository. https://doi.org/10.7924/r49w0dx6s
Zhang, Y., Wang, Z., Kouznetsova, T., Sha, Y., Xu, E., Shannahan, L., Fermen-Coker, M., Lin., Y. (2020). Data from: Distal conformational locks on ferrocene mechanophores guide reaction pathways for increased mechanochemical reactivity. V3 Duke Research Data Repository. https://doi.org/10.7924/r4gq6z428
Lin, Y., Kouznetsova, T., Chang, C., & Craig, S. (2020). Data from: Enhanced polymer mechanical degradation through mechanochemically unveiled lactonization. Duke Research Data Repository. V2 https://doi.org/10.7924/r4fq9x365
Wilson, J. W., Degan, S., Gainey, C. S., Mitropoulos, T., Simpson, M. J., Zhang, J. Y., & Warren, W. S. (2019). Data from: In vivo pump-probe and multiphoton fluorescence microscopy of melanoma and pigmented lesions in a mouse model. Duke Digital Repository. https://doi.org/10.7924/r4cc0zp95
