Article
Chemistry, Physical
Jinming Zhang, Wei Ding, Uwe Hampel
Summary: This study deconstructs a complex surface defect into three primary surface defects and uses large-scale Molecular Dynamics simulations to investigate the mechanisms of droplet-solid static friction forces induced by these defects. Three element-wise static friction forces related to the primary surface defects are revealed, and it is found that the static friction force induced by chemical heterogeneity is contact line length dependent while the static friction force induced by atomic structure and topographical defect is contact area dependent. The latter causes energy dissipation and leads to a wiggle movement of the droplet during the static-kinetic friction transition.
JOURNAL OF COLLOID AND INTERFACE SCIENCE
(2023)
Article
Chemistry, Physical
Ecem Yelekli Kirici, Mayssam Naji, Selim Canakci, E. Yegan Erdem
Summary: Droplet-based microfluidic systems offer a method of manipulating and transporting droplets using surface texture and local energy gradients. This study has made significant progress in controlling and manipulating oil droplets, with potential applications in biochemistry, smart surface development, and microsystem packaging.
SURFACES AND INTERFACES
(2023)
Article
Mechanics
Yujuan Chen, Xianmin Xu
Summary: Theoretical study on the self-propulsion dynamics of a small droplet on general curved surfaces leads to a new reduced model that quantitatively describes the motion of droplets. The model includes a scaling law for droplet displacement with respect to time on the outside surface of a cone. The theoretical results are in good agreement with experimental data without adjusting the friction coefficient in the model.
Article
Physics, Multidisciplinary
Jing Lou, SongLin Shi, Chen Ma, CunJing Lv, QuanShui Zheng
Summary: In this study, a new wetting state called the suspended penetration wetting state was identified, where the droplet can penetrate the micropillars on textured surfaces without touching the base. Experimental results showed that the droplet can spontaneously recover to the initial wetting state when the external pressure is removed.
SCIENCE CHINA-PHYSICS MECHANICS & ASTRONOMY
(2021)
Article
Chemistry, Physical
Q. Legrand, S. Benayoun, S. Valette
Summary: This study investigates the anisotropic wetting on textured surfaces. Three stripe-like textures with different heights were created using three different polymers. The contact angle in all directions was measured using a lab-built goniometer. Two different behaviors, correlated to the wetting state, were observed. The Wenzel state showed strong anisotropy, with the contact angle following a Gaussian evolution. The Cassie-Baxter state, on the other hand, exhibited no anisotropy, with the contact angle remaining constant and close to the predicted value. This study deepens our understanding of droplet anisotropy by linking it to surface textures and chemistry.
APPLIED SURFACE SCIENCE
(2023)
Article
Mechanics
Shi-Zheng Wang, Xianfu Huang, Longquan Chen, Ying-Song Yu
Summary: Water droplets impinging on micro-grooved polydimethylsiloxane surfaces were investigated, and various phenomena including no bouncing, complete rebound, bouncing occurring with droplet breakup, partial rebound, and sticky state were observed depending on the impact velocity and surface roughness. The lower limit of impact velocity for bouncing droplets was determined by balancing the droplet's kinetic energy with the energy barrier caused by contact angle hysteresis. The upper limit of impact velocity was predicted by recording droplet impact at an ultrahigh speed and correlating the transition from complete rebound to bouncing with the wetting state transition. A theoretical model was developed to predict the upper limit of impact velocity by considering the liquid penetration into the micro-grooves. Additionally, the contact time of bouncing droplets decreased with decreasing Weber number, while surface roughness had a minor influence on the contact time in the experiments.
Article
Multidisciplinary Sciences
Dieter A. Baumgartner, Samira Shiri, Shayandev Sinha, Stefan Karpitschka, Nate J. Cira
Summary: This study explores the rich dynamics of fully miscible, three-component droplets composed of water, ethanol, and propylene glycol on completely wetting glass substrates. The research finds that evaporation changes the composition and shape of the droplet, altering its spreading behavior. This research has practical significance in the collection, aggregation, and removal of contaminants.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2022)
Review
Engineering, Multidisciplinary
Peng Xu, Yurong Zhang, Lijun Li, Zhen Lin, Bo Zhu, Wenhui Chen, Gang Li, Hongtao Liu, Kangjian Xiao, Yunhe Xiong, Sixing Yang, Yifeng Lei, Longjian Xue
Summary: This review provides an overview of the research progress on the adhesion behaviors of droplets on surfaces. It covers the construction of bioinspired superhydrophobic surfaces with different adhesion states, the fundamental theories of droplet adhesion, techniques to characterize droplet adhesion, wetting behaviors and the switching between different adhesion states, applications of bioinspired surfaces, and future research challenges and applications.
BIOINSPIRATION & BIOMIMETICS
(2022)
Article
Chemistry, Physical
Xiaoyi Hu, Zhen Wang, David J. Hwang, Carlos E. Colosqui, Thomas Cubaud
Summary: The spreading and receding behavior of small water droplets immersed in viscous oils on grid-patterned surfaces were experimentally investigated. It was found that droplets in partial Cassie state on planar microfluidic grids could capture oil patches that further evolved into trapped oil droplets. The natural retraction velocity of thin water films was examined based on external phase velocity, and regime maps of trapped droplets were delineated based on control parameters.
Article
Thermodynamics
Shusheng Zhang, Li-Zhi Zhang
Summary: The article introduces the effectiveness of superhydrophobic surface modifications in minimizing heat exchange between impacting droplets and solid surfaces. By developing a multiple distribution function phase-field lattice Boltzmann model, the dynamic behaviors and heat transfer during droplet impact are studied, with a detailed discussion on the effects of textured surface structural parameters. The numerical results reveal four possible bouncing modes of impacting droplets, depending on the surface energy stored in microstructure cavities. Additionally, the synergistic effects of contact time and contact area impact the heat transfer performance.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2024)
Article
Chemistry, Physical
Xiang Zhang, Azhen Du, Yongsheng Luo, Cunjing Lv, Yu Shrike Zhang, Shujie Yan, Yuanda Wu, Jingjiang Qiu, Yong He, Lixia Wang, Qian Li
Summary: Controlling the morphology and spreading behavior of liquids on solid surfaces can be achieved by designing hydrophilic micropillar arrays. The arrangement and shape of the micropillars play a crucial role in determining the shape of the liquid droplet and the spreading pattern. Surface energy barriers caused by micropillar edges were found to be key factors influencing the anisotropic spreading of the liquid.
SURFACES AND INTERFACES
(2022)
Article
Engineering, Mechanical
Jia Luo, Shuang-Ying Wu, Lan Xiao, Zhi-Li Chen
Summary: This study investigated the mechanism and parameters affecting the contact time of droplet impacting on solid surfaces using numerical simulation method and water spring theory. The results showed that increasing Weber number or decreasing cylinder diameter effectively reduced contact time, with surface wettability having the greatest impact on contact time.
INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES
(2021)
Article
Chemistry, Physical
Chenlei Chu, Yinggang Zhao, Pengfei Hao, Cunjing Lv
Summary: By varying the contact angle and geometry of the pillared textures, the wetting transition of individual droplets during condensation has been quantified. Four different wetting state transition modes have been identified and classified in a phase diagram. Simple theories correlating the critical conditions of the wetting state transition to the wettability and geometry of the textures have been constructed and experimentally verified.
Article
Engineering, Chemical
Himanshu Pathak, Tibin M. Thomas, Pallab Sinha Mahapatra
Summary: This study investigated the condensation processes of liquid droplets on soft surfaces and found that lower shear modulus of the soft surface led to higher droplet coverage and larger condensate droplet size. Regardless of the shear moduli of the substrates, the relaxation time of coalescing droplets followed a linear trend with the drop equilibrium size, with softer substrates exhibiting higher relaxation time.
CHEMICAL ENGINEERING SCIENCE
(2022)
Article
Materials Science, Multidisciplinary
Hamed Vahabi, Sravanthi Vallabhuneni, Mohammadhasan Hedayati, Wei Wang, Diego Krapf, Matt J. Kipper, Nenad Miljkovic, Arun K. Kota
Summary: This study presents a systematic design of non-textured, all-solid, hydrophilic slippery surfaces by covalently grafting polyethylene glycol brushes to smooth substrates. The SLIC surfaces demonstrate outstanding performance in condensation and fouling resistance compared to non-slippery hydrophilic surfaces and slippery hydrophobic surfaces.
Article
Chemistry, Physical
Ji Young Kim, Eun Soo Park, Taegu Lee, Seunghwa Ryu, Seung-Eon Kim, Seong-Woong Kim
Summary: The study investigated the effect of tensile loading direction and additional elements on the deformation mechanisms of TiAl alloys, revealing that enhanced room temperature ductility can be achieved with the addition of Nb.
JOURNAL OF ALLOYS AND COMPOUNDS
(2022)
Article
Nanoscience & Nanotechnology
Hyunggwi Song, Suman Timilsina, Jiyoung Jung, Taek-Soo Kim, Seunghwa Ryu
Summary: In recent years, considerable effort has been put into the development and improvement of mechanoluminescence (ML)-based stress sensing as a nondestructive inspection technique. This study presents a novel approach to increase the sensitivity of ML composites made of an epoxy resin matrix and functionalized SrAl2O4:Eu2+, Dy3+ particles. The results show that surface modification of ML particles can enhance the sensitivity and introduce new chemical bonds, leading to a larger stress transfer through interfacial bonding.
ACS APPLIED MATERIALS & INTERFACES
(2022)
Article
Mechanics
Stefano Signetti, Seunghwa Ryu, Nicola M. Pugno
Summary: An analytical model is developed to study the ballistic behavior of multilayer composite armors subjected to high-velocity impact. The model considers the effect of thickness compaction and curing pressure on impact toughness, and is validated through experiments and simulations. The study finds that graded multilayer configurations can enhance the toughness of armor, and have potential applications in the design and optimization of shielding structures.
COMPOSITE STRUCTURES
(2022)
Article
Computer Science, Artificial Intelligence
Jiyoung Jung, Kundo Park, Byungjin Cho, Jinkyoo Park, Seunghwa Ryu
Summary: In this paper, two systematic data-driven optimization frameworks for the injection molding process are proposed, using multi-objective Bayesian optimization and constrained generative inverse design network frameworks. These methods can efficiently obtain optimal process parameters and are demonstrated to be applicable in the manufacturing process of a door trim part.
JOURNAL OF INTELLIGENT MANUFACTURING
(2023)
Article
Materials Science, Multidisciplinary
Donggeun Park, Jiyoung Jung, Grace X. Gu, Seunghwa Ryu
Summary: This study proposes a multiscale kernel neural network (MNet) for predicting the strain field within a grid composite. Compared to current DNN architectures, MNet accurately predicts the strain field in new configurations and exhibits lower error rates. The results also demonstrate that MNet maintains excellent performance with smaller datasets and can be applied to larger grid composites.
MATERIALS & DESIGN
(2022)
Article
Energy & Fuels
Wabi Demeke, Yongtae Kim, Jiyoung Jung, Jaywan Chung, Byungki Ryu, Seunghwa Ryu
Summary: In this study, a systematic approach leveraging deep learning is proposed to efficiently explore and optimize the design of segmented thermoelectric legs. By combining finite element analysis and neural network modeling with a genetic optimization algorithm, high-performance design candidates are identified and the model is updated using validation results to achieve optimization of thermoelectric legs.
Article
Materials Science, Multidisciplinary
Donggyu Kim, Seunghwa Ryu
Article
Multidisciplinary Sciences
Wonbeom Lee, Hyunjun Kim, Inho Kang, Hongjun Park, Jiyoung Jung, Haeseung Lee, Hyunchang Park, Ji Su Park, Jong Min Yuk, Seunghwa Ryu, Jae-Woong Jeong, Jiheong Kang
Summary: An elastic printed circuit board (E-PCB) is a conductive framework used for the assembly of stretchable electronics. This study presents a method using a liquid metal particle network (LMPNet) as an elastic conductor, which satisfies all the requirements for E-PCBs. The LMPNet enables the fabrication of high-density E-PCBs, allowing the integration of numerous electronic components to create highly stretchable skin electronics.
Article
Materials Science, Multidisciplinary
Hyunggwi Song, Eunjeong Park, Hong Jae Kim, Chung-Il Park, Taek-Soo Kim, Yoon Young Kim, Seunghwa Ryu
Summary: Medical concentric tubes with auxetic structures have been designed to improve mechanical performance by reducing snapping instability. This study presents a novel free-form optimization method using the multi-objective Bayesian optimization (MBO) to design the bending and torsional stiffness of tubular structures. Compared to conventional tubes with rectangular holes, the optimized design achieves a significant improvement in key factor and torsional stiffness by expanding the design space.
MATERIALS & DESIGN
(2023)
Article
Chemistry, Multidisciplinary
Dongwook Yang, Han Ku Nam, Truong-Son Dinh Le, Jinwook Yeo, Younggeun Lee, Young-Ryeul Kim, Seung-Woo Kim, Hak-Jong Choi, Hyung Cheoul Shim, Seunghwa Ryu, Soongeun Kwon, Young-Jin Kim
Summary: Personal wearable devices are important in advanced healthcare, military, and sports applications. E-textiles are considered the best candidates due to their conformability and ease of manufacturing. This study demonstrates the direct laser writing of e-textiles, converting Kevlar textiles to electrically conductive laser-induced graphene (LIG). Different types of Kevlar textiles are used to fabricate wearable multimodal e-textile sensors and supercapacitors, catering to their specific structural characteristics.
Article
Materials Science, Multidisciplinary
Donggeun Park, Jaemin Lee, Kundo Park, Seunghwa Ryu
Summary: This study introduces a powerful tool called the hierarchical generative network (HGNet) for exploring novel materials using deep learning. By training three customized convolutional neural networks, this method accurately predicts complex stress distributions and fracture patterns, and discovers superior designs in vast design spaces using genetic algorithms.
ADVANCED ENGINEERING MATERIALS
(2023)
Article
Multidisciplinary Sciences
Donggeun Park, Minwoo Park, Seunghwa Ryu
Summary: This study proposes a novel approach to designing digital composite materials with desired mechanical properties by exploring the spatial arrangements of binary constituents. The advanced multi-input deep learning approach with transfer learning and a multi-kernel method accurately predicts the stress field for both seen and unseen configurations, making it an efficient tool for composite design and optimization. The incorporation of multiscale kernels in the model enables better capture of local and global features, resulting in more precise predictions. This research underscores the potential of deep learning models in advancing composite materials.
ADVANCED THEORY AND SIMULATIONS
(2023)
Review
Chemistry, Multidisciplinary
Junhyeong Lee, Donggeun Park, Mingyu Lee, Hugon Lee, Kundo Park, Ikjin Lee, Seunghwa Ryu
Summary: In the past few decades, the field of materials science has been greatly influenced by machine learning, which has accelerated the discovery and production of new materials by accurately predicting complex physical processes. However, the availability of a variety of machine learning algorithms poses the challenge of selecting the most appropriate one. This review provides a comprehensive evaluation of common machine learning algorithms used for materials design and offers guidelines for selecting the suitable model based on the nature of the design problem.
MATERIALS HORIZONS
(2023)
Article
Nanoscience & Nanotechnology
Juhee Lee, Taegu Lee, Ha Neul Lee, Hyoungsoo Kim, Yoo Kyung Kang, Seunghwa Ryu, Hyun Jung Chung
Summary: In this study, we developed a membrane assay for multiplexed detection of nucleic acid targets based on two-dimensional fluorescent ring patterns. The assay showed specific and sensitive detection in the subpicomole range, as well as multiplexed detection even in complex solutions. Deep learning analysis of fluorescence images allowed for accurate classification and prediction of target amounts. This technique provides a novel approach for the rapid detection of infectious pathogens.
ACS APPLIED MATERIALS & INTERFACES
(2023)
Article
Nanoscience & Nanotechnology
In Ho Kim, Subi Choi, Jieun Lee, Jiyoung Jung, Jinwook Yeo, Jun Tae Kim, Seunghwa Ryu, Suk-kyun Ahn, Jiheong Kang, Philippe Poulin, Sang Ouk Kim
Summary: Researchers have developed artificial muscle fibers and bundles that mimic the strong and contractive actuation of mammalian skeletal muscles. By incorporating graphene fillers and a liquid crystalline matrix, the fibers exhibit photothermal actuation and dynamic percolation behavior, enabling reliable reversible actuation similar to mammalian muscles.
NATURE NANOTECHNOLOGY
(2022)