Manu Suvarna

发表

Predicting biodiesel properties and its optimal fatty acid profile via explainable machine learning

M. E. Günay, R. Yıldırım, M. Jahirul, 2022, Renewable Energy.

Machine learning aided supercritical water gasification for H2-rich syngas production with process optimization and catalyst screening

Xiaonan Wang, Lan-jia Pan, Manu Suvarna, 2021 .

Process modelling and simulation of bitumen mining and recovery from oil sands

E. Nduagu, Manu Suvarna, M. Divakaran, 2019, Minerals Engineering.

Applied Machine Learning for Prediction of CO2 Adsorption on Biomass Waste-Derived Porous Carbons.

Y. Ok, Sean Low, K. Lee, 2021, Environmental science & technology.

A hybrid data-driven and mechanistic modelling approach for hydrothermal gasification

Yingru Zhao, Xiaonan Wang, Lan-jia Pan, 2021, Applied Energy.

Prediction of Soil Heavy Metal Immobilization by Biochar Using Machine Learning

Daniel C W Tsang, Y. Ok, P. D. Dissanayake, 2022, Environmental science & technology.

A review of computational modeling techniques for wet waste valorization: Research trends and future perspectives

Y. Ok, J. Pérez‐Ramírez, Lan-jia Pan, 2022, Journal of Cleaner Production.

Fuel properties of hydrochar and pyrochar: Prediction and exploration with machine learning

Y. Tong, Xiaonan Wang, Lan-jia Pan, 2020, Applied Energy.

A generalized machine learning framework to predict the space-time yield of methanol from thermocatalytic CO2 hydrogenation

Manu Suvarna, T. P. Araújo, J. Pérez–Ramírez, 2022, Applied Catalysis B: Environmental.

Wet wastes to bioenergy and biochar: A critical review with future perspectives

M. Tabatabaei, Y. Ok, Lan-jia Pan, 2022, Science of The Total Environment.

Recent advancements in sustainable upcycling of solid waste into porous carbons for carbon dioxide capture

Y. Ok, A. Park, Junyao Wang, 2022, Renewable and Sustainable Energy Reviews.

Online prediction of mechanical properties of hot rolled steel plate using machine learning

Jiajia Cai, Xiaonan Wang, Xinzhe Zhu, 2021 .

Cyber–Physical Production Systems for Data-Driven, Decentralized, and Secure Manufacturing—A Perspective

Xiaonan Wang, Y. Ng, Manu Suvarna, 2021, Engineering.

A machine learning framework to quantify and assess the impact of COVID-19 on the power sector: An Indian context

Xiaonan Wang, Manu Suvarna, Qianyu Chen, 2021, Advances in Applied Energy.

Identifying Descriptors for Promoted Rhodium-Based Catalysts for Higher Alcohol Synthesis via Machine Learning.

Manu Suvarna, Phil Preikschas, J. Pérez–Ramírez, 2022, ACS catalysis.

Predicting Biodiesel Properties and its Optimal Fatty Acid Profile Via Explainable Machine Learning

M. E. Günay, R. Yıldırım, M. Jahirul, 2022, SSRN Electronic Journal.

A three-step machine learning framework for energy profiling, activity state prediction and production estimation in smart process manufacturing

Yee Shee Tan, Jie Li, Manu Suvarna, 2021 .

Smart Manufacturing for Smart Cities—Overview, Insights, and Future Directions

Jie Li, Xiaonan Wang, Christoph Herrmann, 2020, Adv. Intell. Syst..

Embracing data science in catalysis research

Manu Suvarna, J. Pérez-Ramírez, 2024, Nature Catalysis.

Active learning streamlines development of high performance catalysts for higher alcohol synthesis

Manu Suvarna, Tangsheng Zou, Antonio J. Martín, 2024, Nature communications.