Glass transition in supercooled liquids with medium-range crystalline order I Tah, S Sengupta, S Sastry, C Dasgupta, S Karmakar Physical review letters 121 (8), 085703, 2018 | 42 | 2018 |
Non-Gaussianity of the van Hove function and dynamic-heterogeneity length scale BP Bhowmik, I Tah, S Karmakar Physical Review E 98 (2), 022122, 2018 | 39 | 2018 |
Block analysis for the calculation of dynamic and static length scales in glass-forming liquids S Chakrabarty, I Tah, S Karmakar, C Dasgupta Physical Review Letters 119 (20), 205502, 2017 | 29 | 2017 |
Fragility in glassy liquids: A structural approach based on machine learning I Tah, SA Ridout, AJ Liu The Journal of Chemical Physics 157 (12), 2022 | 26 | 2022 |
Understanding slow and heterogeneous dynamics in model supercooled glass-forming liquids I Tah, A Mutneja, S Karmakar ACS omega 6 (11), 7229-7239, 2021 | 19 | 2021 |
Quantifying the link between local structure and cellular rearrangements using information in models of biological tissues I Tah, TA Sharp, AJ Liu, DM Sussman Soft Matter 17 (45), 10242-10253, 2021 | 18 | 2021 |
How does a hydrophobic macromolecule respond to a mixed osmolyte environment? I Tah, J Mondal The Journal of Physical Chemistry B 120 (42), 10969-10978, 2016 | 17 | 2016 |
Signature of dynamical heterogeneity in spatial correlations of particle displacement and its temporal evolution in supercooled liquids I Tah, S Karmakar Physical Review Research 2 (2), 022067, 2020 | 16 | 2020 |
Possible universal relation between short time β-relaxation and long time α-relaxation in glass-forming liquids R Das, I Tah, S Karmakar The Journal of chemical physics 149 (2), 2018 | 14 | 2018 |
Soft matter roadmap JL Barrat, E Del Gado, SU Egelhaaf, X Mao, M Dijkstra, DJ Pine, ... Journal of Physics: Materials 7 (1), 012501, 2023 | 8 | 2023 |
Kinetic fragility directly correlates with the many-body static amorphous order in glass-forming liquids I Tah, S Karmakar Physical Review Materials 6 (3), 035601, 2022 | 8 | 2022 |
Tuning for fluidity using fluctuations in biological tissue models S Arzash, I Tah, AJ Liu, ML Manning arXiv preprint arXiv:2312.11683, 2023 | 4 | 2023 |
Building a “trap model” of glassy dynamics from a local structural predictor of rearrangements SA Ridout, I Tah, AJ Liu Europhysics Letters 144 (4), 47001, 2023 | 4 | 2023 |
Minimal vertex model explains how the amnioserosa avoids fluidization during Drosophila dorsal closure I Tah, D Haertter, JM Crawford, DP Kiehart, CF Schmidt, AJ Liu ArXiv, 2023 | 2 | 2023 |
A minimal model predicts cell shapes and tissue mechanics in the amnioserosa during dorsal closure I Tah, D Haertter, J Crawford, DP Kiehart, C Schmidt, AJW Liu Biophysical Journal 121 (3), 263a, 2022 | 1 | 2022 |
Biological tissues can fluidize by tuning their internal degrees of freedom S Arzash, I Tah, A Liu, ML Manning Bulletin of the American Physical Society, 2024 | | 2024 |
Adding learning degrees of freedom in biological tissues S Arzash, I Tah, A Liu, ML Manning APS March Meeting Abstracts 2023, K10. 002, 2023 | | 2023 |
Assessing the connection between cellular rearrangements and local structure using information in models of biological tissues. I Tah, T Sharp, A Liu, D Sussman APS March Meeting Abstracts 2021, R16. 002, 2021 | | 2021 |
Section 4.5–Machine learning for soft matter learning SA Ridout, M Stern, I Tah, G Zhang, AJ Liu Soft Matter Roadmap 22, 23, 0 | | |
Role of Static and Dynamic Length Scales in Glass Transition I Tah Mumbai, 0 | | |