A review of automated and data-driven approaches for pathway determination and reaction monitoring in complex chemical systems A Puliyanda, K Srinivasan, K Sivaramakrishnan, V Prasad Digital Chemical Engineering 2, 100009, 2022 | 15 | 2022 |
Data fusion by joint non-negative matrix factorization for hypothesizing pseudo-chemistry using Bayesian networks A Puliyanda, K Sivaramakrishnan, Z Li, A de Klerk, V Prasad Reaction Chemistry & Engineering 5 (9), 1719-1737, 2020 | 13 | 2020 |
A perspective on the impact of process systems engineering on reaction engineering K Sivaramakrishnan, A Puliyanda, DT Tefera, A Ganesh, ... Industrial & Engineering Chemistry Research 58 (26), 11149-11163, 2019 | 13 | 2019 |
A data-driven approach to generate pseudo-reaction sequences for the thermal conversion of Athabasca bitumen K Sivaramakrishnan, A Puliyanda, A de Klerk, V Prasad Reaction Chemistry & Engineering 6 (3), 505-537, 2021 | 12 | 2021 |
Structure-preserving joint non-negative tensor factorization to identify reaction pathways using Bayesian networks A Puliyanda, K Sivaramakrishnan, Z Li, A de Klerk, V Prasad Journal of Chemical Information and Modeling 61 (12), 5747-5762, 2021 | 8 | 2021 |
Process modelling and optimization of design parameters in a falling film plate and frame evaporator A Donaldson, A Thimmaiah Proceedings of the 2016 COMSOL Conference, in Bangalore, 1-9, 2016 | 7 | 2016 |
Benchmarking chemical neural ordinary differential equations to obtain reaction network-constrained kinetic models from spectroscopic data A Puliyanda, K Srinivasan, Z Li, V Prasad Engineering Applications of Artificial Intelligence 125, 106690, 2023 | 4 | 2023 |
Real-time monitoring of reaction mechanisms from spectroscopic data using hidden semi-Markov models for mode identification A Puliyanda, Z Li, V Prasad Journal of Process Control 117, 188-205, 2022 | 3 | 2022 |
Data Fusion-Based Approach for the Investigation of Reaction Networks in Hydrous Pyrolysis of Biomass F Sattari, K Srinivasan, A Puliyanda, V Prasad Industrial & Engineering Chemistry Research 62 (10), 4422-4432, 2023 | 1 | 2023 |
Automated generation of reaction network hypotheses for complex feedstocks K Srinivasan, A Puliyanda, V Prasad 2022 IEEE International Symposium on Advanced Control of Industrial …, 2022 | 1 | 2022 |
Machine learning-based monitoring of complex reactive systems AT Puliyanda | 1 | 2022 |
Model-based catalyst screening and optimal experimental design for the oxidative coupling of methane A Puliyanda Digital Chemical Engineering, 100160, 2024 | | 2024 |
Identification of Reaction Network Hypotheses for Complex Feedstocks from Spectroscopic Measurements with Minimal Human Intervention K Srinivasan, A Puliyanda, V Prasad The Journal of Physical Chemistry A, 2024 | | 2024 |
A 3d convolutional neural network autoencoder for predicting solvent configuration changes in condensed phase biomass reactions A Puliyanda, AMD Padmanathan, SH Mushrif, V Prasad Digital Discovery 3 (6), 1130-1143, 2024 | | 2024 |
Online Monitoring Based on Reaction Network and Kinetic Model Identification from Spectroscopic Data without a Priori knowledge of Species and Reactions A Puliyanda, K Srinivasan, V Prasad 2021 AIChE Annual Meeting, 2021 | | 2021 |
Application of Chemometric Methods to Generate Reaction Pathway Hypotheses for the Thermal Cracking of Athabasca Bitumen K Sivaramakrishnan, A Puliyanda, A De Klerk, V Prasad 2019 AIChE Annual Meeting, 2019 | | 2019 |
Simultaneous Canonical Polyadic Decomposition As a Data Fusion Algorithm to Develop Pseudo-Chemistry from Spectral Data A Puliyanda, A De Klerk, Z Li, V Prasad 2019 AIChE Annual Meeting, 2019 | | 2019 |
Numerical Analysis of Flow Characterization in a Continuous Crystallizer A Thimmaiah, L Falleiro, A Naval, A Ambekar, BA Ali IJCST 33, 43, 2016 | | 2016 |