| AQUAMI: An open source Python package and GUI for the automatic quantitative analysis of morphologically complex multiphase materials J Stuckner, K Frei, I McCue, MJ Demkowicz, M Murayama Computational Materials Science 139, 320-329, 2017 | 85 | 2017 |
| Microstructure segmentation with deep learning encoders pre-trained on a large microscopy dataset J Stuckner, B Harder, TM Smith npj Computational Materials 8 (200), 2022 | 74 | 2022 |
| Real-time video imaging of mechanical motions of a single molecular shuttle with sub-millisecond sub-angstrom precision T Shimizu, D Lungerich, J Stuckner, M Murayama, K Harano, E Nakamura Bulletin of the Chemical Society of Japan 93 (9), 1079-1085, 2020 | 60 | 2020 |
| Gaining new insights into nanoporous gold by mining and analysis of published images I McCue, J Stuckner, M Murayama, MJ Demkowicz Scientific reports 8 (1), 6761, 2018 | 50 | 2018 |
| Utilizing local phase transformation strengthening for nickel-base superalloys TM Smith, NA Zarkevich, AJ Egan, J Stuckner, TP Gabb, JW Lawson, ... Communications Materials 2 (1), 106, 2021 | 41 | 2021 |
| Fracture in nanoporous gold: An integrated computational and experimental study N Beets, J Stuckner, M Murayama, D Farkas Acta Materialia 185, 257-270, 2020 | 34 | 2020 |
| Enhancing the creep strength of next-generation disk superalloys via local phase transformation strengthening TM Smith, TP Gabb, KN Wertz, J Stuckner, LJ Evans, AJ Egan, MJ Mills Superalloys 2020: Proceedings of the 14th International Symposium on …, 2020 | 25 | 2020 |
| Tractable Multiscale Modeling with an Embedded Microscale Surrogate, AIAA SciTech 2021 Forum, Jan. 19-21, 2021 J Stuckner, S Graeber, B Weborg, T Ricks, SM Arnold DOI 10, 6.2021-1963, 0 | 24 | |
| Indentation response of nanoporous gold from atomistic simulations D Farkas, J Stuckner, R Umbel, B Kuhr, MJ Demkowicz Journal of Materials Research 33 (10), 1382-1390, 2018 | 20 | 2018 |
| Steam oxidation performance of Yb2Si2O7 environmental barrier coatings exposed to CMAS BJ Harder, JL Stokes, BA Kowalski, J Stuckner, JA Setlock Journal of the European Ceramic Society 44 (4), 2486-2498, 2024 | 18 | 2024 |
| Multiscale analysis of composites using surrogate modeling and information optimal designs SM Arnold, M Piekenbrock, TM Ricks, J Stuckner AIAA Scitech 2020 Forum, 1863, 2020 | 16 | 2020 |
| Optimal experimental design with fast neural network surrogate models J Stuckner, M Piekenbrock, SM Arnold, TM Ricks Computational Materials Science 200, 110747, 2021 | 15 | 2021 |
| Ultra-fast electron microscopic imaging of single molecules with a direct electron detection camera and noise reduction J Stuckner, T Shimizu, K Harano, E Nakamura, M Murayama Microscopy and Microanalysis 26 (4), 667-675, 2020 | 14 | 2020 |
| Tractable multiscale modeling with an embedded microscale surrogate J Stuckner, S Graeber, B Weborg, TM Ricks, SM Arnold AIAA Scitech 2021 Forum, 1963, 2021 | 13 | 2021 |
| Mechanical properties of nanoporous gold subjected to tensile stresses in real-time, sub-microscopic scale J Stuckner, M Murayama Journal of Materials Science 54 (18), 12106-12115, 2019 | 13 | 2019 |
| A convolutional neural network for multiscale modeling of composite materials A Sorini, EJ Pineda, J Stuckner, PA Gustafson AIAA Scitech 2021 Forum, 0310, 2021 | 12 | 2021 |
| The influence of processing conditions on the 3-D interconnected structure of nanosilver paste JA Stuckner, GQ Lu, M Mitsuhara, WT Reynolds, M Murayama IEEE Transactions on Electron Devices 64 (2), 494-499, 2017 | 10 | 2017 |
| A data-driven framework to select a cost-efficient subset of parameters to qualify sourced materials NM Senanayake, JLW Carter, CL Bowman, DL Ellis, J Stuckner Integrating Materials and Manufacturing Innovation 11 (3), 339-351, 2022 | 6 | 2022 |
| Predicting Unreinforced Fabric Mechanical Behavior with Recurrent Neural Networks B Hearley, J Stuckner, E Pineda, S Murman | 6 | 2022 |
| A Robust Machine Learning Schema for Developing, Maintaining, and Disseminating Machine Learning Models BL Hearley, SM Arnold, J Stuckner | 5 | 2022 |
Mitsuhiro MurayamaProfessor of Materials Science and Engineering, Virginia TechZweryfikowany adres z vt.edu