| Diverse property-spectrum of flavors of polyolefins: A data analysis study A Rajan, O Hvidsten, C Kim, R Ramprasad APS March Meeting Abstracts 2022, W16. 006, 2022 | | 2022 |
| Design of polymers for energy storage capacitors using machine learning and evolutionary algorithms J Kern, L Chen, C Kim, R Ramprasad Journal of Materials Science 56, 19623-19635, 2021 | 11 | 2021 |
| Electronic device that uses virtual field to reserve transmission and reception time of radar signal and control method thereof C Junsu, KIM Chiho, J Lee US Patent 11,184,076, 2021 | | 2021 |
| An informatics approach for designing conducting polymers H Sahu, H Li, L Chen, AC Rajan, C Kim, N Stingelin, R Ramprasad ACS Applied Materials & Interfaces 13 (45), 53314-53322, 2021 | 14 | 2021 |
| Interpretable machine learning-based predictions of methane uptake isotherms in metal–organic frameworks R Gurnani, Z Yu, C Kim, DS Sholl, R Ramprasad Chemistry of Materials 33 (10), 3543-3552, 2021 | 41 | 2021 |
| Novel high voltage polymer insulators using computational and data-driven techniques D Kamal, H Tran, C Kim, Y Wang, L Chen, Y Cao, VR Joseph, ... The Journal of Chemical Physics 154 (17), 2021 | 15 | 2021 |
| Polymer informatics with multi-task learning C Kuenneth, AC Rajan, H Tran, L Chen, C Kim, R Ramprasad Patterns 2 (4), 2021 | 60 | 2021 |
| Polymer informatics: Current status and critical next steps L Chen, G Pilania, R Batra, TD Huan, C Kim, C Kuenneth, R Ramprasad Materials Science and Engineering: R: Reports 144, 100595, 2021 | 163 | 2021 |
| A Machine Learning Approach to the Design of Polymer Electrolyte Membranes KH Shen, H Tran, C Kim, R Ramprasad APS March Meeting Abstracts 2021, E03. 003, 2021 | | 2021 |
| A massive dataset of synthesis-friendly hypothetical polymers A Rajan, C Kim, C Kuenneth, D Kamal, R Gurnani, R Batra, R Ramprasad APS March Meeting Abstracts 2021, E60. 011, 2021 | | 2021 |
| Polymer design using genetic algorithm and machine learning C Kim, R Batra, L Chen, H Tran, R Ramprasad Computational Materials Science 186, 110067, 2021 | 147 | 2021 |
| Polymers for extreme conditions designed using syntax-directed variational autoencoders R Batra, H Dai, TD Huan, L Chen, C Kim, WR Gutekunst, L Song, ... Chemistry of Materials 32 (24), 10489-10500, 2020 | 56 | 2020 |
| An Autonomous Computational Workflow for Efficient Generation of Polymer Data H Tran, H Sahu, BG Del Rio, D Kamal, C Kim, R Ramprasad 2020 Virtual AIChE Annual Meeting, 2020 | | 2020 |
| Machine-learning predictions of polymer properties with Polymer Genome H Doan Tran, C Kim, L Chen, A Chandrasekaran, R Batra, S Venkatram, ... Journal of Applied Physics 128 (17), 2020 | 147 | 2020 |
| Polymer genome–based prediction of gas permeabilities in polymers G Zhu, C Kim, A Chandrasekarn, JD Everett, R Ramprasad, RP Lively Journal of Polymer Engineering 40 (6), 451-457, 2020 | 42 | 2020 |
| Predicting crystallization tendency of polymers using multifidelity information fusion and machine learning S Venkatram, R Batra, L Chen, C Kim, M Shelton, R Ramprasad The Journal of Physical Chemistry B 124 (28), 6046-6054, 2020 | 37 | 2020 |
| A deep learning solvent-selection paradigm powered by a massive solvent/nonsolvent database for polymers A Chandrasekaran, C Kim, S Venkatram, R Ramprasad Macromolecules 53 (12), 4764-4769, 2020 | 52 | 2020 |
| Refractive index prediction models for polymers using machine learning JP Lightstone, L Chen, C Kim, R Batra, R Ramprasad Journal of Applied Physics 127 (21), 2020 | 29 | 2020 |
| Frequency-dependent dielectric constant prediction of polymers using machine learning L Chen, C Kim, R Batra, JP Lightstone, C Wu, Z Li, AA Deshmukh, ... npj Computational Materials 6 (1), 61, 2020 | 75 | 2020 |
| A multi-fidelity information-fusion approach to machine learn and predict polymer bandgap A Patra, R Batra, A Chandrasekaran, C Kim, TD Huan, R Ramprasad Computational Materials Science 172, 109286, 2020 | 64 | 2020 |
Huan TranGeorgia Institute of Technology在 mse.gatech.edu 的电子邮件经过验证
