Area of Interest
The excellence of ISL's research has been proven by the quality of research articles published and their number of citations (Google Scholar). Two main research pillars of ISL are sustainable system design & analysis and Big Data Analytics.
The research is facilitated by process simulation and mathematical & statistical computing softwares such as aspenONE (AspenTech) and analytical instruments such as the FT-IR/NIR (660-IR, Agilent) spectrometer, and UV-Vis (8453 UV/Vis, Agilent) spectrometer, as well as a custom-made machine vision system.
1. Sustainable system design and analysis
Process design and analysis, the most traditional area in Chemical Engineering discipline, is gaining much attention due to soaring needs in production of new and renewable energy such as biofuels, green hydrogen, and fuel cells. Beginning with research on process design and analysis of biofuels production from seaweeds biomass in 2009, ISL has focused on optimal design and operation of new & renewable energy systems such as biorefinery, hydrogen production, storage & transportation, and fuel cells.
Research on energy production from biomass initially was focused on the first-generation crop biomass including sugar cane or corn, and second-generation lignocellulosic biomass. However, increasing demand for biomass feedstock resulted in increasing grain prices and faced problems such as limitation of arable land for lignocellulosic biomass that has very low growth rate. As a fundamental solution to these problems, research on energy production from various aquatic plant resources, i.e. third-generation algal biomass has been amplified in recent years.
Among the third-generation biomass resources, macroalgae or seaweeds are even more suitable alternative biomass resources because they are mostly non-food biomass and grow at a relatively fast pace. Furthermore, simple pretreatment processing due to the absence of recalcitrant substances like lignin is another advantage.
The energy conversion routes of seaweeds biomass can be divided into thermochemical routes and biochemical routes, and the final product varies accordingly. Thermochemical conversion routes include gasification producing syngas and pyrolysis producing bio-oil, and biochemical conversion routes are aerobic and anaerobic fermentation producing ethanol, volatile fatty acids, and biogas.
ISL’s research was focused on biochemical conversion routes primarily yielded many achievements, and began to study for the thermochemical conversion routes.
Process candidates of mixed alcohol dehydration
In addition, ISL has performed research on the design and operation of a natural gas liquefaction process and fuel cell systems.
MCFC system including fuel(diesel) preprocessor
2. Big Data Analytics & Machine Learning
Referring data themselves in the beginning, Big Data now embraces collection, storage, processing, analysis, application, and management of mega data. Features of Big Data are often referred as 4V of Volume (high capacity), Variety (different types), Velocity (fast generation/processing), and Value (new value). A noticeable difference compared to multivariate data analysis, a branch of PSE, is “Variety”. In Big Data, data formats include not only numbers in a table form, but also includes documents, videos, images, audio, text messages, etc.
Big Data can be applied widely for many companies in the manufacturing sector currently experiencing growth limits, and has the potential to affect the whole industry from the viewpoint of servitization of manufacturing as well as enhanced productivity.
Professor Jay Liu, the principal investigator of ISL, received his Ph.D degree under the supervision of Professor John MacGregor @McMaster University, who is a world-renowned authority on multivariate data analysis. During his Ph.D study, he worked on extending multivariate data analysis by including image data. In particular, Professor Liu collaborated with leading transnational companies and research institutes in manufacturing industry such as DuPont, General Electric, LG Chem, SK Chemicals, ArcelorMittal Dofasco, COREM. Therefore, he can be referred as a pioneer of Big Data research for manufacturing competitiveness.
Since the launch in 2009, ISL has worked on Big Data applications research with Korean companies for manufacturing competitiveness and yielded outstanding achievements.
Feature extraction method developed for defect detection
In addition, ISL is currently collaborating with international research groups in Process Analytical Technology (PAT) & Quality by Design (QbD) and Quantitative Structure-Activity Relationships (QSAR) & Quantitative Structure-Retention Time Relationships (QSRR) in pharmaceutical and proteomics fields.
Variable selection methodology for QSRR modeling in proteomics