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
Charbonneau, P., Hu, Y., & Morse, P. (2024). Data from: Dynamics and fluctuations of minimally-structured glass formers. Duke Research Data Repository. https://doi.org/10.7924/r4tt4tq52
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
Moreno-Hernandez, I. A., & Vigil, S. A. (2023). Data from: Dissolution heterogeneity observed in anisotropic ruthenium dioxide nanocrystals via liquid-phase transmission electron microscopy. Duke Research Data Repository. https://doi.org/10.7924/r47h1sc26
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
Chen, Z., & Yang, W. (2023). Data and scripts from: Development of a machine-learning finite-range nonlocal density functional. Duke Research Data Repository. https://doi.org/10.7924/r4fj2p230
Yu, Y., O'Neill, R. T., Boulatov, R., Widenhoefer, R. A., Craig, S. L.(2023). Data from: Allosteric control of olefin isomerization kinetics via remote metal binding and its mechano-chemical analysis. Duke Research Data Repository. https://doi.org/10.7924/r4474k10q
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
Li, J., Yu, J., Zehua, C., & Yang, W. (2023). Data from: Linear scaling calculations of excitation energies with active-space particle-particle random phase approximation. Duke Research Data Repository. https://doi.org/10.7924/r4wm1g15c
Qin, X., Blum, V. (2023). Phonon and Raman caculation data from: Coherent Phonon‐Induced Modulation of Charge Transfer in 2D Hybrid Perovskites. Duke Research Data Repository. https://doi.org/10.7924/r4mc93m7j
Song, R., Cao, Q., Chan, C. Wang, Z., Wong, P. Y., Wong, K. S., Blum, V. & Lu, H. (2023). Data from: Chiral perovskite nanoplatelets with tunable circularly polarized luminescence in the strong confinement regime. Duke Research Data Repository. https://doi.org/10.7924/r4v40x41n
Hou, S., Zhang, C., Niver, A. & Welsher, K. (2022). Data from: Mapping nanoscale forces and potentials in live cells with microsecond 3D single-particle tracking. Duke Research Data Repository. https://doi.org/10.7924/r4dv1q87f
Wang, L., Zheng, X., Kouznetsova, T. B. , Yen, T., Ouchi, T., Brown, C. L., Craig, S. L. (2022). Data from: Mechanochemistry of cubane. Duke Research Data Repository. https://doi.org/10.7924/r47h1r86c
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
Johnson, C., Exell, J., Lin, Y., Aguilar, J., Welsher, K. D. (2022). Data from: Capturing the start point of the virus-cell interaction with high-speed 3D single-particle tracking. Duke Research Data Repository. https://doi.org/10.7924/r4bp07h15.
Folena, G., Biroli, G., Charbonneau, P., Hu, Y., Zamponi, F. (2022). Data from: Equilibrium fluctuations in mean-field disordered models. Duke Research Data Repository. https://doi.org/10.7924/r42f7w487
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., Folena, G., Hu, Y., & Zamponi, F. (2022). Data and scripts from: Local dynamical heterogeneity in simple glass formers. Duke Research Data Repository. https://doi.org/10.7924/r4542tw29
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
Hu, Y. & Charbonneau, P. (2021). Data and scripts from: Numerical transfer matrix study of frustrated next-nearest-neighbor Ising models on square lattices. Duke Research Data Repository. https://doi.org/10.7924/r4v40tw6p
Charbonneau, P. & Hu, Yi. (2021). Data and scripts accompanying comment on: "Kosterlitz-Thouless-type caging-uncaging transition in a quasi-one-dimensional hard disk system". Duke Research Data Repository. https://doi.org/10.7924/r4g16258z
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, B., Charbonneau, P., Hu, Y., & Yang, Z. (2021). Data and scripts from: High-dimensional percolation criticality and hints of mean-field-like caging of the random Lorentz gas. Duke Research Data Repository. https://doi.org/10.7924/r4s46r07b
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
Hu, Y., & Charbonneau, P. (2021). Data and scripts from: Percolation thresholds on high-dimensional D_n and E_8-related lattices. Duke Research Data Repository. https://doi.org/10.7924/r4fx7bk95
Biroli, G., Charbonneau, P., Hu, Y., Ikeda, H., Szamel, G., & Zamponi, F. (2021). Data from: Mean-field caging in a random Lorentz gas. Duke Research Data Repository. https://doi.org/10.7924/r4sb44m3b
Morse, P. K., Roy, S., Agoritsas, E., Stanifer, E., Corwin, E. I., & Manning, M. L. (2021). Data from: A direct link between active matter and sheared granular systems. Duke Research Data Repository. https://doi.org/10.7924/r4cv4kb23
Charbonneau, P. & Hu, Y. (2021). Data and scripts from: Resolving the two-dimensional ANNNI model using transfer matrices. Duke Research Data Repository. https://doi.org/10.7924/r4k074j0t
Biroli, G., Charbonneau, P., Corwin, E. I., Hu, Y., Ikeda, H., Szamel, G., & Zamponi, F. (2021). Data and Scripts from: Interplay between percolation and glassiness in the random Lorentz gas. Duke Research Data Repository. https://doi.org/10.7924/r4qz29054
Charbonneau, P. & Morse, P. (2021). Data From: Memory formation in jammed hard spheres. Duke Research Data Repository. https://doi.org/10.7924/r41r6vf5t
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
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
Kundu, J., & Charbonneau, P. (2020). Data From: Postponing the dynamical transition density using competing interactions. Duke Research Data Repository. https://doi.org/10.7924/r4xd0wb95
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.
Flenner, E., Berthier, L., Charbonneau, P., & Fullerton, C. (2019). Data from: Front-mediated melting of isotropic ultrastable glasses. Duke Digital Repository. https://doi.org/10.7924/r4542pd2c
Altan, I., James, S., Khan, A., Quinn, M., Charbonneau, P., & McManus, J. (2019). Data and scripts from: Using Schematic Models to Understand the Microscopic Basis for Inverted Solubility in gammaD-crystallin. Duke Digital Repository. https://doi.org/10.7924/r4fq9v942
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
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
Berthier, L., Charbonneau, P., Ninarello, A., Ozawa, M., & Yaida, S. (2019). Data and scripts from: Zero-temperature glass transition in two dimensions. Duke Digital Repository. https://doi.org/10.7924/r46w9b248
Berthier, L., Charbonneau, P., Kundu, J. (2019). Data and scripts from: Bypassing sluggishness: SWAP algorithm and glassiness in high dimensions. Duke Digital Repository. https://doi.org/10.7924/r49w0dr6j
Charbonneau, P., Hu, Y., Raju, A., Sethna, J., & Yaida, S. (2019). Data and scripts from: Morphology of renormalization-group flow for the de Almeida–Thouless–Gardner universality class. Duke Digital Repository. https://doi.org/10.7924/r4zc7wm7d
Charbonneau, P., Corwin, E. I., Fu, L., Tsekenis, G., & van der Naald, M. (2019). Data and scripts from: Glassy, Gardner-like phenomenology in minimally polydisperse crystalline systems. Duke Digital Repository. https://doi.org/10.7924/r4k93500n
Birolo, G., Charbonneau, P., & Hu, Y. (2019). Data and scripts from: Dynamics around the Site Percolation Threshold on High-Dimensional Hypercubic Lattices. Duke Digital Repository. https://doi.org/10.7924/r4571cf37
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
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
