The Complex Fluids and Transport Phenomena Laboratory focuses on innovative research in analyzing and understanding transport phenomena. This is achieved through experimental, theoretical, and computational approaches, with a focus on the application of complex fluids in advanced manufacturing. The laboratory develops numerical and experimental techniques to decipher microscale flow phenomena involving complex interactions at liquid/gas interfaces and among particles, which are pivotal in the production of batteries, fuel cells, and optical films. The goal is to craft novel processes that leverage the unique properties of complex fluids, enhancing the efficiency and effectiveness of high-performance film production and redefining manufacturing processes for key energy storage and generation devices. The laboratory aims to pave the way for next-generation manufacturing techniques at the forefront of innovation in the use of complex fluids, setting new standards for the production of batteries, fuel cells, and optical films with enhanced performance and sustainability.

복합 유체 및 수송 현상 연구실은 수송 현상의 분석 및 이해에 대한 혁신적인 연구에 중점을 둔다. 실험적, 이론적 및 계산적 접근 방식을 통해 고급 제조 분야에서 복합 유체의 응용에 집중한다. 액체/기체 계면 및 입자 간의 복잡한 상호 작용을 포함하는 미세 규모 흐름 현상을 해독하기 위한 수치 및 실험 기술을 개발하며, 이는 배터리, 연료 전지 및 광학 필름 생산에 중추적인 역할을 한다. 목표는 복합 유체의 고유한 특성을 활용하여 고성능 필름 생산의 효율성과 효과를 향상시키고 주요 에너지 저장 및 생성 장치에 대한 제조 공정을 재정의하는 새로운 공정을 개발하는 것이다. 복합 유체 사용의 혁신 최전선에서 차세대 제조 기술을 개척하여 성능과 지속 가능성이 향상된 배터리, 연료 전지 및 광학 필름 생산을 위한 새로운 표준을 설정하는 것을 목표로 한다.

Physics-informed neural networks for learning fluid flows with symmetry

Percolation threshold of curved linear objects

Analysis of pulsatile shear-thinning flows in rectangular channels

Reconstruction of particle size distribution from cross-sections

Optimizing a Physics-Informed Machine Learning Model for Pulsatile Shear-Thinning Channel Flow

Analysis of low-speed blade coating flows

Pore Classification Algorithm for Quantitative Analysis in Microstructures

Passive Mixing of Thixotropic Fluids in a C-Shaped Serpentine Channel: A Numerical Analysis

Thermocapillary flows on heated substrates with sinusoidal topography

ViscNet: Vision-Based In-line Viscometry for Fluid Mixing Process

서울대학교 고분자 관련 학과 소개

AIChE 2017 참관기

Overcoming the “coffee-stain” effect by compositional Marangoni-flow-assisted drop-drying

A roll-to-roll welding process for planarized silver nanowire electrodes

Carbon nanotube–nanocup hybrid structures for high power supercapacitor applications

Particle margination and its implications on intravenous anticancer drug delivery

Two-dimensional atomic-layered alloy junctions for high-performance wearable chemical sensor

Alloyed 2D metal–semiconductor atomic layer junctions

Fluidic self-assembly for MicroLED displays by controlled viscosity

Conductance stable and mechanically durable bi-layer EGaIn composite-coated stretchable fiber for 1D bioelectronics

Chabazite-Type Zeolite Membranes for Effective CO 2 Separation: The Role of Hydrophobicity and Defect Structure

Healing of Microdefects in SSZ-13 Membranes via Filling with Dye Molecules and Its Effect on Dry and Wet CO 2 Separations

An oriented, siliceous deca-dodecasil 3R (DDR) zeolite film for effective carbon capture: insight into its hydrophobic effect

Transient stress‐based and strain‐based hemolysis estimation in a simplified blood pump

A multiscale, biophysical model of flow‐induced red blood cell damage

Mid-gap invasion in two-layer slot coating

Computational prediction of mechanical hemolysis in aortic valved prostheses

Systematic analysis for electrical conductivity of network of conducting rods by Kirchhoff's laws and block matrices

Effect of shim configuration on flow dynamics and operability windows in stripe slot coating process

Flow in tensioned-web-over-slot die coating: Effect of die lip design

Curving silver nanowires using liquid droplets for highly stretchable and durable percolation networks

Microfluidics and Coating Process Laboratory - MCPL

교수님 소개

남재욱

연구실 소개

연구실 키워드

알럼나이가 간 회사

연구실 지원 방법

대우 조건

연도별 논문 인용수

저널 & 학회 논문 출판 수

연구실 논문 목록

ViscNet: Vision-Based In-line Viscometry for Fluid Mixing Process

Optimizing a Physics-Informed Machine Learning Model for Pulsatile Shear-Thinning Channel Flow

Analysis of low-speed blade coating flows

연구실 보유 특허

대학별 입시끈

우리 연구실 모집

교수님 소개

남재욱

연구실 키워드

알럼나이가 간 회사

연구실 지원 방법

대우 조건

연도별 논문 인용수

저널 & 학회 논문 출판 수

연구실 논문 목록

ViscNet: Vision-Based In-line Viscometry for Fluid Mixing Process

Optimizing a Physics-Informed Machine Learning Model for Pulsatile Shear-Thinning Channel Flow

Analysis of low-speed blade coating flows

연구실 보유 특허

최근 3년간 연구실적 높은 연구실

대학별 입시끈

우리 연구실 모집