| A novel approach for studying crack propagation in polycrystalline graphene using machine learning algorithms MSR Elapolu, MIR Shishir, A Tabarraei Computational Materials Science 201, 110878, 2022 | 29 | 2022 |
| Fracture mechanics of multi-layer molybdenum disulfide MSR Elapolu, A Tabarraei, X Wang, DE Spearot Engineering Fracture Mechanics 212, 1-12, 2019 | 22 | 2019 |
| Phononic thermal transport properties of C3N nanotubes MSR Elapolu, A Tabarraei, A Reihani, A Ramazani Nanotechnology 31 (3), 035705, 2019 | 20 | 2019 |
| Mechanical and fracture properties of polycrystalline graphene with hydrogenated grain boundaries MSR Elapolu, A Tabarraei The Journal of Physical Chemistry C 125 (20), 11147-11158, 2021 | 14 | 2021 |
| Kapitza conductance of symmetric tilt grain boundaries of monolayer boron nitride MSR Elapolu, A Tabarraei Computational Materials Science 144, 161-169, 2018 | 14 | 2018 |
| An atomistic study of the stress corrosion cracking in graphene MSR Elapolu, A Tabarraei The Journal of Physical Chemistry A 124 (35), 7060-7070, 2020 | 11 | 2020 |
| Investigation of fracture and mechanical properties of monolayer C3N using molecular dynamic simulations MIR Shishir, MSR Elapolu, A Tabarraei Mechanics of Materials 160, 103895, 2021 | 8 | 2021 |
| Predicting corrosion damage in the human body using artificial intelligence: in vitro progress and future applications MA Kurtz, R Yang, MSR Elapolu, AC Wessinger, W Nelson, K Alaniz, ... Orthopedic Clinics 54 (2), 169-192, 2023 | 7 | 2023 |
| Atomistic Simulation-Based Cohesive Zone Law of Hydrogenated Grain Boundaries of Graphene MSR Elapolu, A Tabarraei The Journal of Physical Chemistry C 124 (31), 17308-17319, 2020 | 7 | 2020 |
| A deep learning model for predicting mechanical properties of polycrystalline graphene MIR Shishir, MSR Elapolu, A Tabarraei Computational Materials Science 218, 111924, 2023 | 3 | 2023 |
| A deep convolutional neural network-based method to predict accurate fracture strength of poly-crystalline graphene MIR Shishir, MSR Elapolu, A Tabarraei ASME International Mechanical Engineering Congress and Exposition 85680 …, 2021 | 3 | 2021 |
| Applied machine learning method to predict crack propagation path in polycrystalline graphene sheet MSR Elapolu, MIR Shishir, A Tabarraei ASME International Mechanical Engineering Congress and Exposition 85680 …, 2021 | 3 | 2021 |
| Study of Thermo-Mechanical Properties of Graphene-Like Two Dimensional Material MSR Elapolu The University of North Carolina at Charlotte, 2021 | 2 | 2021 |
| Deep Neural Network Predicts Ti‐6Al‐4V Dissolution State Using Near‐Field Impedance Spectra MA Kurtz, R Yang, D Liu, MSR Elapolu, R Rai, JL Gilbert Advanced Functional Materials 34 (4), 2308932, 2024 | 1 | 2024 |
| Impact of grain boundaries on the heat conductivity of mono-layer hexagonal boron nitride MSR Elapolu, A Tabarraei ASME International Mechanical Engineering Congress and Exposition 58431 …, 2017 | 1 | 2017 |
| Blockchain technology for requirement traceability in systems engineering MSR Elapolu, R Rai, DJ Gorsich, D Rizzo, S Rapp, MP Castanier Information Systems, 102384, 2024 | | 2024 |
| Stress Corrosion Cracking of Graphene MSR Elapolu, A Tabarraei ASME International Mechanical Engineering Congress and Exposition 84607 …, 2020 | | 2020 |
| Traction Separation Laws of Hydrogenated Grain Boundaries of Graphene MSR Elapolu, A Tabarraei ASME International Mechanical Engineering Congress and Exposition 84607 …, 2020 | | 2020 |
