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Prakash Thakolkaran
Prakash Thakolkaran
PhD Candidate, TU Delft
Verified email at tudelft.nl - Homepage
Title
Cited by
Cited by
Year
3D fabrication of fully iron magnetic microrobots
CCJ Alcântara, S Kim, S Lee, B Jang, P Thakolkaran, JY Kim, H Choi, ...
Small 15 (16), 1805006, 2019
1202019
NN-EUCLID: Deep-learning hyperelasticity without stress data
P Thakolkaran, A Joshi, Y Zheng, M Flaschel, L De Lorenzis, S Kumar
Journal of Mechanics and Physics of Solids 169, 105076, 2022
1162022
Bayesian-EUCLID: Discovering hyperelastic material laws with uncertainties
A Joshi, P Thakolkaran, Y Zheng, M Escande, M Flaschel, L De Lorenzis, ...
Computer Methods in Applied Mechanics and Engineering 398, 115225, 2022
572022
Inverse-designed growth-based cellular metamaterials
S Van’t Sant, P Thakolkaran, J Martínez, S Kumar
Mechanics of Materials 182, 104668, 2023
262023
Artificial neural network supported design of a lattice-based artificial spinal disc for restoring patient-specific anisotropic behaviors
Z Yu, P Thakolkaran, K Shea, T Stanković
Computers in Biology and Medicine 152, 106475, 2023
92023
Experiment-informed finite-strain inverse design of spinodal metamaterials
P Thakolkaran, M Espinal, S Dhulipala, S Kumar, CM Portela
Extreme Mechanics Letters 74, 102274, 2025
72025
AI‐Guided Inverse Design and Discovery of Recyclable Vitrimeric Polymers
Y Zheng, P Thakolkaran, AK Biswal, JA Smith, Z Lu, S Zheng, BH Nguyen, ...
Advanced Science 12 (6), 2411385, 2025
2*2025
Can KAN CANs? Input-convex Kolmogorov-Arnold Networks (KANs) as hyperelastic constitutive artificial neural networks (CANs)
P Thakolkaran, Y Guo, S Saini, M Peirlinck, B Alheit, S Kumar
arXiv preprint arXiv:2503.05617, 2025
2025
Deep learning reveals key predictors of thermal conductivity in covalent organic frameworks
P Thakolkaran, Y Zheng, Y Guo, A Vashisth, S Kumar
arXiv preprint arXiv:2409.06457, 2024
2024
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