Charbonneau, P., & Pilcher, J. M. (2025). Data from: From panocha to fudge: Mexican roots of an American candy. Duke Research Data Repository. https://doi.org/10.7924/r4q81k44g
Williams, J. Z., & Yang, W. (2025). Data and scripts from: Correcting Delocalization Error in Materials with Localized Orbitals and Linear-Response Screening. Duke Research Data Repository. https://doi.org/10.7924/r4vq36h9r
Delaire, O., He, X., Gupta, M. K., Abernathy, D. L., Granroth, G. E., Ye, F., Winn, B. L., & Boatner, L. (2025). Data from: Resolving the dynamic correlated disorder in KTa1−xNbxO3. Duke Research Data Repository. https://doi.org/10.7924/r4x92f52w.
Williams J., Marszalek P., & Yang W. (2024). Data from: Computed isotope shifts of high-frequency vibrational modes exceed thermal noise in propionate bound to a human olfactory receptor. Duke Research Data Repository. https://doi.org/10.7924/r4ng4wb8d
Campos, J. A. & Brown, K. R. (2024). Data and code from: Clifford-deformed compass codes. Duke Research Data Repository. https://doi.org/10.7924/r4f47wc95
Royall, C. P., Charbonneau, P., Dijkstra, M., Russo, J., Smallenburg, F., Speck, T., & Valeriani, C. (2024). Data from: Colloidal hard spheres: Triumphs, challenges, and mysteries [nucleation]. Duke Research Data Repository. https://doi.org/10.7924/r4x35163x
Kastenholz, H. V., Topper, M. I. , Warren, W. S. , Fischer, M. C., & Grass, D. (2024). Data and scripts from: Noninvasive identification of carbon-based black pigments with pump-probe microscopy. Duke Research Data Repository. V2 https://doi.org/10.7924/r48059m9k
Bonnet, G., Charbonneau, P., & Folena, G. (2023). Data and scripts from: Glass-like caging with random planes. Duke Research Data Repository. https://doi.org/10.7924/r4gx4hm10
Jin, Y., & Charbonneau, P. (2023). Data and scripts from: Dimensional study of the dynamical arrest in a random Lorentz gas. Duke Research Data Repository. https://doi.org/10.7924/r47m0gq90
Morse, P., & Charbonneau, P. (2023). Data and scripts from: Jamming, relaxation, and memory in a minimally structured glass former. Duke Research Data Repository. https://doi.org/10.7924/r4th8qc0b
Wang, S., Hu, Y., Kouznetsova, T. B., Sapir, L., Chen, D., Herzog-Arbeitman, A., Johnson, J. A., Rubinstein, M., & Craig, S. L. (2023). Data from: Facile Mechanochemical Cycloreversion of Polymer Cross-linkers Enhances Tear Resistance. Duke Research Data Repository. https://doi.org/10.7924/r43r1215n
Zheng, M., Tarzia, M., Charbonneau, P. (2022). Data and scripts from: Weakening the critical dynamical slowing down of models with SALR interactions. Duke Research Data Repository. https://doi.org/10.7924/r4vh5q02j
Mahler, A., Williams, J.Z., Su, N.Q., Yang, W. (2022): Data and scripts from: Localized orbital scaling correction for periodic systems. Duke Research Data Repository. https://doi.org/10.7924/r4s75hv98
Charbonneau, P., Kundu, J., Morse, P.K., Hu, Y. (2022). Data from: The dimensional evolution of structure and dynamics in hard sphere liquids. Duke Research Data Repository. https://doi.org/10.7924/r4p270q6x
Charbonneau, P., Morse, P. K., Perkins, W., & Zamponi, F. (2021). Data from: Three simple scenarios for high-dimensional sphere packings. Duke Research Data Repository. https://doi.org/10.7924/r40z78x37
Charbonneau, P., Gish, C., Hoy, R. & Morse, P. (2021). Data from: thermodynamic stability of hard sphere crystals in dimensions 3 through 10. Duke Research Data Repository. https://doi.org/10.7924/r4jh3mw3w
Charbonneau, P. & Tarzia, M. (2021). Data from: Solution of disordered microphases in the Bethe approximation. Duke Research Data Repository. https://doi.org/10.7924/r42v2m409
Zheng, M., & Charbonneau, P. (2021). Data and scripts from: Characterization and efficient Monte Carlo sampling of disordered microphases. Duke Research Data Repository. https://doi.org/10.7924/r4w37th8b
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.
