Personal statement

Serene is currently a lecturer in Chemical Engineering discipline, Monash University Malaysia. She has been actively involved in the area of multiscale simulation of membrane material, whereby it involves integration of designed materials from atomistic structures adapting molecular simulation tool and evaluation of performance in process design using chemical engineering software. She was a chemical engineering graduate from University of Toronto (Canada), whereby she received the Professor Ronald W. Missen Prize and Sustainable Energy Plant Design Award. Subsequently, she pursued her Master and Doctoral degree in Chemical Engineering in Universiti Teknologi PETRONAS (Malaysia). In addition to academic recognitions, her simulation works have been integrated in software that has won several awards in international and national exhibitions, as well as been successfully commercialized to industrial players.

Academic degrees

• Doctor of Philosophy in Chemical Engineering, Universiti Teknologi PETRONAS, Malaysia, 2019
• Master in Chemical Engineering, Universiti Teknologi PETRONAS, Malaysia, 2014
• Degree in Applied Science (Hons) in Chemical Engineering, University of Toronto, Canada, 2012

Professional affiliations

Member of National Professional Bodies

• Board of Engineers Malaysia (BEM), Graduate Engineer
• Society of Engineering Education Malaysia (SEEM), Member

Member of International Professional Bodies

• Institution of Chemical Engineers (IChemE), Associate Member
• International Association of Engineers (IAENG), Member

Research Interests

• Multiscale simulation
• Process modelling
• Process simulation
• Process design & optimization
• Molecular simulation

Research Projects

Title: Multiscale Simulation of Novel Mixed Matrix Membrane Applied in co2/ch4 Separation for Industrial Scale Application

This research aims to establish multiscale simulation framework for mixed matrix membrane to be applied in industrial application. Computational approach has been generally subdivided into nanoscale (atomic properties), mesoscale (interaction between two groups that constitute to gas transport properties), macroscale (performance of a single unit) and process design (process economics and optimization) dimensions. The nanoscale and mesoscale dimensions have been devoted to employment of molecular modelling simulation tools to predict intrinsic material properties. On the other hand, simulation from the aspect of macroscale and process design has been dedicated to studying external effects towards process performance. Both material and operating parameters are closely related to evaluate material’s techno-economic feasibility at an industrial scale. The motivation in mixed matrix membrane (MMM), which has incorporated a combination of polymer and inorganic fillers, has been driven to the recent advancement in its transport properties that have provided promising results towards improving the separation performance of conventional pristine material. Nonetheless, it remains a big challenge to commercialize MMM due to the lack of knowledge pertaining to finding the essentials of materials at the molecular level, such as compatibility and interaction between polymer and inorganic fillers, as well as incorporation in process simulations for prediction of properties and process economics at different operating conditions. The multiscale simulation framework will be able to assist in improving the extrapolation of material properties applied to existing applications and new operation windows by minimizing the technical risks and requirement of pilot plants or experimental studies that are often cumbersome.

No content

No content

No content

Local Award/Recognition/Exhibition/Stewardship

• Special Award: Overall Best Product, Best Information, Communication & Technology Cluster
  Gold Award - InTEX 2019, Hollow Fiber Membrane Prediction Program (HFMPP), 2019
• Silver Award - MTE 2016, Hollow Fiber Membrane Prediction Program (HFMPP), MTE, 2016
• Silver Award - Eureka Innovation Exhibition, Hollow Fiber Membrane Prediction Program (HFMPP), 2014