Segura, T., Miller, A. W., & Anderson, A. (2024). Data from: Wound healing splinting devices with improved wound access and application speed. Duke Research Data Repository. https://doi.org/10.7924/r4s75kg76
Kastenholz, H. V., Topper, M. I. , Warren, W. S. , Fischer, M. C., & Grass, D. (2024). Noninvasive identification of carbon-based black pigments with pump-probe microscopy. Duke Research Data Repository. https://doi.org/10.7924/r43j3nx2k
Cossette, B. J., Shetty, S., Issah, L. A., & Collier, J. H. (2024). Data from: Self-assembling allergen vaccine platform raises therapeutic allergen-specific IgG responses without induction of systemic allergic responses. Duke Research Data Repository. https://doi.org/10.7924/r4v40xs2n
Peña, E., Pelot, N., & Grill, W. M. (2024). Data from: Computational models of compound nerve action potentials: Efficient filter-based methods to quantify effects of tissue conductivities, conduction distance, and nerve fiber parameters. Duke Research Data Repository. https://doi.org/10.7924/r4fx7gq46
Peña, E., Pelot, N. A., Grill, W. M. (2023). Data from: Spatiotemporal Parameters for Energy Efficient Kilohertz-Frequency Nerve Block with Low Onset Response. Duke Research Data Repository. https://doi.org/10.7924/r4w37z317
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
Yousef, A., Rizzi, S., Insley, J., Mateevitsi, V., Randles, A. (2023). Data from: Enabling in situ visualization of large-scale cell simulations. Duke Research Data Repository. https://doi.org/10.7924/r49g5tm50
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
Zhou, K., Harfouche, M., Cooke, C. L., Park, J., Konda, P. C., Kreiss, L., Doman, J., Reamey, P., Saliu, V., Cook, C., Zheng, M., Bechtel, J. P., McCarroll, M., Bagwell, J., Horstmeyer, G., Bagnat, M. & Horstmeyer, R. (2023). Data from: Parallelized computational 3D video microscopy of freely moving organisms at multiple gigapixels per second. Duke Research Data Repository. https://doi.org/10.7924/r4db86b1q
