Fratarcangeli, M. & Moreno-Hernandez, I. A. (2024). Data from: Direct observation of structural disorder effects on iridium dioxide nanocrystal dissolution. Duke Research Data Repository. V2 https://doi.org/10.7924/r4kd2437m
Laudicina, C. C., Charbonneau, P., Hu, Y., Janssen, L., Morse, P. K., Pihlajamaa, I., & Szamel, G. (2024). Data from: Simple fluctuations in simple glass formers. Duke Research Data Repository. https://doi.org/10.7924/r4805b31d
Green, E. & Jayasundara, N. (2024). Data from: The aquatic microbiome communicates with the Zebrafish (Danio rerio) embryo through the chorion to influence developmental trajectory. Duke Research Data Repository. https://doi.org/10.7924/r4ks6xn7m
Brinson, C., Lin, A., Sheridan, R. J., & Hu, B. (2024). Data from: ViscoNet: a lightweight FEA surrogate model for polymer nanocomposites viscoelastic response prediction. Duke Research Data Repository. https://doi.org/10.7924/r4g166t5p
White, E., Seymour, A., Dale, J., Newton, E., & Johnston, D. (2024). Mapping the Ghost Fleet: Orthomosaics and ship locations from drone-based imagery of Mallows Bay, Maryland. Duke Research Data Repository. https://doi.org/10.7924/r4p273j8w
Mooney, R., & Pearson, J. (2024). Data from: Dual neuromodulatory dynamics underlie birdsong learning. Duke Research Data Repository. https://doi.org/10.7924/r4s186852
Mello, D. F., Perez, L., Bergemann, C. M., Morton, K. S., Ryde, I. T., & Meyer, J. N. (2024). Data from: Comprehensive characterization of mitochondrial bioenergetics at different larval stages reveals novel insights about the developmental metabolism of Caenorhabditis elegans. Duke Research Data Repository. https://doi.org/10.7924/r4hm5fv5t
Kurt, E., Devlin, G., Asokan, A., & Segura, T. (2024). Data from: Gene delivery from granular scaffolds for tunable biologics manufacturing. Duke Research Data Repository. https://doi.org/10.7924/r4280h775
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
Martin, A., Liu, G., Joo, B., Wu, R., Kabir, M. S., Draeger, E., Randles, A. (2024). Data and Scripts from: Designing a GPU-accelerated communication layer for efficient fluid-structure interaction computations on heterogenous systems. Duke Research Data Repository. https://doi.org/10.7924/r43n2cd83
D’Agostino, V. W., Deutsch, R. J., Kwan, M., Sunassee, E. D., Madonna, M. C., Palmer, G. M., Crouch, B. T., & Ramanujam, N. (2024). Data from: In vivo spectroscopy to concurrently characterize five metabolic and vascular endpoints relevant to aggressive breast cancer. Duke Research Data Repository. https://doi.org/10.7924/r4vx0k33z
Hussain, M., Grill, W. M., & Pelot, N. A. (2024). Data and scripts from: Highly efficient modeling and optimization of neural fiber responses to electrical stimulation. Duke Research Data Repository. https://doi.org/10.7924/r48g8tf24
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
Parikh, N., McGovern, B., & LaBar, K. S. (2023). Data from: Spatial distancing reduces emotional arousal to reactivated memories. Duke Research Data Repository. https://doi.org/10.7924/r4z89f54g
Das, I., Le Roux, L., Mulwa, R., Ruhinduka, R., & Jeuland, M. (2023). Data and scripts from: Urban demand for cooking fuels in two major African cities and implications for policy. Duke Research Data Repository. https://doi.org/10.7924/r4qf8x909
Gu, M. (2023). Data and scripts from: The power of the family in times of pandemic: Cross-country evidence from 93 countries. Duke Research Data Repository. https://doi.org/10.7924/r49z9c395
Morton, K. S., Heffernan, N., Ryde, I. T, Hartman, J. H., Meng, L., & Meyer, J. N. (2023). Data from: Chronic high-sugar diet in adulthood protects Caenorhabditis elegans from 6-OHDA induced dopaminergic neurodegeneration. Duke Research Data Repository. https://doi.org/10.7924/r4183gr2w
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
Martin, A., Liu, G., Ladd, W., Lee, S., Gounley, J., Vetter, J., Patel, S., Rizzi, S., Mateevitsi, V., Insley, J., Randles, A. (2023). Data and scripts from: Performance evaluation of heterogenous GPU programming frameworks for hemodynamic simulations. Duke Research Data Repository. https://doi.org/10.7924/r45t3t64k
Tanade, C., Rakestraw, E., Ladd, W., Draeger, E., Randles, A. (2023). Data from: Cloud computing to enable wearable-driven longitudinal hemodynamic maps. Duke Research Data Repository. https://doi.org/10.7924/r4f76jd8n
