publications

2025

1. Piezoelectric truss metamaterials: data-driven design and additive manufacturing

   Saurav Sharma, Satya K Ammu, Prakash Thakolkaran, Jovana Jovanova, Kunal Masania, and Siddhant Kumar

   npj Metamaterials, 2025

   Bib

   @article{sharma2025piezoelectric,
     title = {Piezoelectric truss metamaterials: data-driven design and additive manufacturing},
     author = {Sharma, Saurav and Ammu, Satya K and Thakolkaran, Prakash and Jovanova, Jovana and Masania, Kunal and Kumar, Siddhant},
     journal = {npj Metamaterials},
     volume = {1},
     number = {1},
     pages = {9},
     year = {2025},
     publisher = {Nature Publishing Group UK London}
   }

2. Can kan cans? input-convex kolmogorov-arnold networks (kans) as hyperelastic constitutive artificial neural networks (cans)

   Prakash Thakolkaran, Yaqi Guo, Shivam Saini, Mathias Peirlinck, Benjamin Alheit, and Siddhant Kumar

   Computer Methods in Applied Mechanics and Engineering, 2025

   Bib

   @article{thakolkaran2025can,
     title = {Can kan cans? input-convex kolmogorov-arnold networks (kans) as hyperelastic constitutive artificial neural networks (cans)},
     author = {Thakolkaran, Prakash and Guo, Yaqi and Saini, Shivam and Peirlinck, Mathias and Alheit, Benjamin and Kumar, Siddhant},
     journal = {Computer Methods in Applied Mechanics and Engineering},
     volume = {443},
     pages = {118089},
     year = {2025},
     publisher = {Elsevier}
   }

3. Toward Sustainable Polymer Design: A Molecular Dynamics-Informed Machine Learning Approach for Vitrimers

   Yiwen Zheng, Agni K Biswal, Yaqi Guo, Prakash Thakolkaran, Yash Kokane, Vikas Varshney, Siddhant Kumar, and Aniruddh Vashisth

   arXiv preprint arXiv:2503.20956, 2025

   Bib

   @article{zheng2025toward,
     title = {Toward Sustainable Polymer Design: A Molecular Dynamics-Informed Machine Learning Approach for Vitrimers},
     author = {Zheng, Yiwen and Biswal, Agni K and Guo, Yaqi and Thakolkaran, Prakash and Kokane, Yash and Varshney, Vikas and Kumar, Siddhant and Vashisth, Aniruddh},
     journal = {arXiv preprint arXiv:2503.20956},
     year = {2025}
   }

4. AI-Guided Inverse Design and Discovery of Recyclable Vitrimeric Polymers

   Yiwen Zheng, Prakash Thakolkaran, Agni K Biswal, Jake A Smith, Ziheng Lu, Shuxin Zheng, Bichlien H Nguyen, Siddhant Kumar, and Aniruddh Vashisth

   Advanced Science, 2025

   Bib

   @article{zheng2025ai,
     title = {AI-Guided Inverse Design and Discovery of Recyclable Vitrimeric Polymers},
     author = {Zheng, Yiwen and Thakolkaran, Prakash and Biswal, Agni K and Smith, Jake A and Lu, Ziheng and Zheng, Shuxin and Nguyen, Bichlien H and Kumar, Siddhant and Vashisth, Aniruddh},
     journal = {Advanced Science},
     volume = {12},
     number = {6},
     pages = {2411385},
     year = {2025},
     publisher = {Wiley Online Library}
   }

5. Deep learning reveals key predictors of thermal conductivity in covalent organic frameworks

   Prakash Thakolkaran, Yiwen Zheng, Yaqi Guo, Aniruddh Vashisth, and Siddhant Kumar

   Digital Discovery, 2025

   Bib

   @article{thakolkaran2025deep,
     title = {Deep learning reveals key predictors of thermal conductivity in covalent organic frameworks},
     author = {Thakolkaran, Prakash and Zheng, Yiwen and Guo, Yaqi and Vashisth, Aniruddh and Kumar, Siddhant},
     journal = {Digital Discovery},
     volume = {4},
     number = {11},
     pages = {3351--3362},
     year = {2025},
     publisher = {Royal Society of Chemistry}
   }

6. Experiment-informed finite-strain inverse design of spinodal metamaterials

   Prakash Thakolkaran, Michael Espinal, Somayajulu Dhulipala, Siddhant Kumar, and Carlos M Portela

   Extreme Mechanics Letters, 2025

   Bib

   @article{thakolkaran2025experiment,
     title = {Experiment-informed finite-strain inverse design of spinodal metamaterials},
     author = {Thakolkaran, Prakash and Espinal, Michael and Dhulipala, Somayajulu and Kumar, Siddhant and Portela, Carlos M},
     journal = {Extreme Mechanics Letters},
     volume = {74},
     pages = {102274},
     year = {2025},
     publisher = {Elsevier}
   }

2023

1. Inverse-designed growth-based cellular metamaterials

   Sikko Van’t Sant, Prakash Thakolkaran, Jonàs Martı́nez, and Siddhant Kumar

   Mechanics of Materials, 2023

   Bib

   @article{van2023inverse,
     title = {Inverse-designed growth-based cellular metamaterials},
     author = {Van’t Sant, Sikko and Thakolkaran, Prakash and Mart{\'\i}nez, Jon{\`a}s and Kumar, Siddhant},
     journal = {Mechanics of Materials},
     volume = {182},
     pages = {104668},
     year = {2023},
     publisher = {Elsevier}
   }

2. Artificial neural network supported design of a lattice-based artificial spinal disc for restoring patient-specific anisotropic behaviors

   Zhiyang Yu, Prakash Thakolkaran, Kristina Shea, and Tino Stanković

   Computers in Biology and Medicine, 2023

   Bib

   @article{yu2023artificial,
     title = {Artificial neural network supported design of a lattice-based artificial spinal disc for restoring patient-specific anisotropic behaviors},
     author = {Yu, Zhiyang and Thakolkaran, Prakash and Shea, Kristina and Stankovi{\'c}, Tino},
     journal = {Computers in Biology and Medicine},
     volume = {152},
     pages = {106475},
     year = {2023},
     publisher = {Elsevier}
   }

2022

1. Bayesian-EUCLID: Discovering hyperelastic material laws with uncertainties

   Akshay Joshi, Prakash Thakolkaran, Yiwen Zheng, Maxime Escande, Moritz Flaschel, Laura De Lorenzis, and Siddhant Kumar

   Computer Methods in Applied Mechanics and Engineering, 2022

   Bib

   @article{joshi2022bayesian,
     title = {Bayesian-EUCLID: Discovering hyperelastic material laws with uncertainties},
     author = {Joshi, Akshay and Thakolkaran, Prakash and Zheng, Yiwen and Escande, Maxime and Flaschel, Moritz and De Lorenzis, Laura and Kumar, Siddhant},
     journal = {Computer Methods in Applied Mechanics and Engineering},
     volume = {398},
     pages = {115225},
     year = {2022},
     publisher = {Elsevier}
   }

2. NN-EUCLID: Deep-learning hyperelasticity without stress data

   Prakash Thakolkaran, Akshay Joshi, Yiwen Zheng, Moritz Flaschel, Laura De Lorenzis, and Siddhant Kumar

   Journal of the Mechanics and Physics of Solids, 2022

   Bib

   @article{thakolkaran2022nn,
     title = {NN-EUCLID: Deep-learning hyperelasticity without stress data},
     author = {Thakolkaran, Prakash and Joshi, Akshay and Zheng, Yiwen and Flaschel, Moritz and De Lorenzis, Laura and Kumar, Siddhant},
     journal = {Journal of the Mechanics and Physics of Solids},
     volume = {169},
     pages = {105076},
     year = {2022},
     publisher = {Elsevier}
   }

2019

1. 3D fabrication of fully iron magnetic microrobots

   Carlos CJ Alcântara, Sangwon Kim, Sunkey Lee, Bumjin Jang, Prakash Thakolkaran, Jin-Young Kim, Hongsoo Choi, Bradley J Nelson, and Salvador Pané

   Small, 2019

   Bib

   @article{alcantara20193d,
     title = {3D fabrication of fully iron magnetic microrobots},
     author = {Alc{\a}ntara, Carlos CJ and Kim, Sangwon and Lee, Sunkey and Jang, Bumjin and Thakolkaran, Prakash and Kim, Jin-Young and Choi, Hongsoo and Nelson, Bradley J and Pan{\'e}, Salvador},
     journal = {Small},
     volume = {15},
     number = {16},
     pages = {1805006},
     year = {2019},
     publisher = {Wiley Online Library}
   }