This textbook provides a comprehensive exploration of the lattice Boltzmann method (LBM) and its applications in nanoparticle modeling. It covers both single-phase and multiphase LBM methodologies in detail, followed by a section on case studies that apply these techniques. Chapter 1 discusses the fundamental concepts and significance of LBM, along with prior research relevant to nanoparticle modeling. Chapters 2 and 3 provide in-depth explanations of LBM methodologies for single-phase and multiphase fluids, respectively. Chapter 4 introduces various approaches for modeling nanoparticles. The application section extensively addresses the use of nanoparticle multiphase flow LBM simulation models, covering topics such as double emulsions, porous structures, inkjet printing, and the coffee ring effect. Chapter 5 aids understanding of multiphase flow LBM through the analysis of interfacial behavior in surfactant-covered double emulsions. Chapter 6 simulates multiphase flow within a gas diffusion layer composed of porous structures using multi-relaxation time LBM at high density ratios. Chapter 7 discusses contact line dynamics through droplet penetration phenomena in porous structures. Chapter 8 lays the groundwork for multiphase flow simulations that incorporate particle modeling through inkjet printing simulations. Finally, Chapters 9 and 10 analyze the adhesion patterns of nanoparticles during the evaporation of sessile droplets containing nanoparticles. Chapter 9 focuses on particle interactions using magnetic particles, while Chapter 10 examines how changes in contact angle affect nanoparticle adhesion patterns. This textbook aims to provide researchers and students with a deep understanding of nanoparticle dynamics using the LBM, contributing to advancements in simulation techniques in modern physics and engineering.
Hee Min Lee received his B.S. in Mechanical Engineering from Yonsei University, Republic of Korea, in 2019 and is expected to receive his Ph.D. from the same institution in 2026. During his doctoral studies, he has actively conducted research in computational fluid dynamics and has published several papers in international journals in fluid mechanics. In 2023, he received the Best Paper Award at the International Symposium on Micro & Nano Manufacturing for his research on magnetic particle control using the lattice Boltzmann method. He was also awarded a research prize at the Korean Medical 3D Printing Conference for his work on bioprinting simulation. His research interests include lattice Boltzmann simulation, multiphase flows, inkjet printing, and nanoparticle dynamics.
Joon Sang Lee is a Professor in the Department of Mechanical Engineering at Yonsei University, Republic of Korea. He received his Ph.D. in Mechanical Engineering from Iowa State University, USA.
From 2016 to 2020, he served as Associate Dean for Research at Yonsei University’s College of Engineering, where he played a key role in strengthening institutional research capacity. From 2020 to 2023, he served as Associate Vice President for International Affairs at Yonsei University.
Prof. Lee has extensive experience bridging academia and industry. He served as a Technical Advisory Professor for Samsung Electronics (2018–2019) and as a Visiting Professor at the Korea Institute of Civil Engineering and Building Technology (2019–2021). Since 2018, he has also held a joint appointment at the Yonsei University College of Medicine, promoting interdisciplinary collaboration between engineering and medicine. From 2024 to 2025, he served as the President of the Biomedical Engineering Society for Circulation.
In 2023, he founded The M.E.N.D. BioSimulator, a company specializing in advanced biomedical diagnostic software. In 2024–2025, he serves as Director of the Yonsei Enterprise Support Foundation, where he actively supports innovation and the commercialization of advanced technologies.
He has led a research group that has produced over 100 SCI-indexed journal publications. His research is interdisciplinary, encompassing lattice Boltzmann and quantum lattice Boltzmann simulations, rheology, biofluid dynamics, and neural networks, with a strong emphasis on translational and technology-driven applications.
