Machine learning-based structure–property predictions in silica aerogels R Abdusalamov, P Pandit, B Milow, M Itskov, A Rege Soft Matter 17 (31), 7350-7358, 2021 | 17 | 2021 |
On the origin of power-scaling exponents in silica aerogels S Aney, P Pandit, L Ratke, B Milow, A Rege Journal of Sol-Gel Science and Technology, 1-8, 2023 | 2 | 2023 |
Deep reinforcement learning for microstructural optimisation of silica aerogels P Pandit, R Abdusalamov, M Itskov, A Rege Scientific Reports 14 (1), 1511, 2024 | 1 | 2024 |
Data‐driven inverse design and optimisation of silica aerogel model networks P Pandit, R Abdusalamov, M Itskov, B Milow, A Rege PAMM 23 (1), e202200329, 2023 | 1 | 2023 |
Reinforcement Learning For Inverse Design Of Porous Materials P Pandit, R Abdusalamov, AG Rege | | 2023 |
Scaling the Elastic Properties of Silica Aerogels: A Modelling Insight P Pandit, S Aney, AG Rege | | 2023 |
How accurately can silica aerogels be computationally modelled? N Borzecka, P Pandit, AG Rege | | 2023 |
A New Type Of Hybrid Aggregation Model And The Application Towards Silica (Aero) gels N Borzecka, P Pandit, AG Rege | | 2023 |
Reinforcement Learning for Tailored Development of Aerogels P Pandit, AG Rege | | 2023 |
Intelligent Computational Micro-architectured Design of Aerogels for Battery Development P Pandit, AG Rege | | 2023 |
Pore size estimation using image segmentation in silica aerogels P Pandit, M Schwan, M Heyer, B Milow, AG Rege | | 2022 |
Effect of diffusive and ballistic aggregation on properties of gels P Pandit, B Milow, AG Rege | | 2022 |
On the impact of aggregation mechanism in modelling fractal materials AG Rege, P Pandit, B Milow | | 2022 |
Predictive modeling and simulation of silica aerogels by using aggregation algorithms R Abdusalamov, P Pandit, M Itskov, B Milow, A Rege PAMM 21 (1), e202100165, 2021 | | 2021 |
An artificial Intelligence approach in the mechanical and morphological analysis of silica aerogels P Pandit RWTH Aachen University, 2021 | | 2021 |