Article
Chemistry, Physical
Ahmad Boudaghi, Masumeh Foroutan
Summary: This study investigated the wettability of polydimethylsiloxane (PDMS) surfaces using molecular dynamics simulation and found that the constituent atoms and their number influenced the contact angle and droplet radius, with surfaces containing more carbon atoms offering better hydrophobicity. Additionally, rough surfaces rich in carbon increased the surface hydrophobicity.
JOURNAL OF MOLECULAR LIQUIDS
(2022)
Article
Engineering, Mechanical
Chongpu Zhai, Shuwen Zhang, Hui Ji, Deheng Wei, Hengxu Song, Kaiyuan Liu, Minglong Xu
Summary: This study quantifies the impact of surface roughness on interfacial flexoelectricity during normal compression and oscillation. Through examining 3D-printed surfaces with different roughness features, the researchers found that the flexoelectric charge follows a power-law relationship with the compression load, and the exponent is positively correlated with the fractal dimension. Contact analyses reveal that the flexoelectric charge concentrates on larger microcontacts as compression continues, and rougher surfaces show less heterogeneity in flexoelectric polarizations. This study provides experimental measurements and explanations for interfacial flexoelectricity, highlighting its connection to surface structures and suggesting new approaches for contact evaluation and flexoelectricity enhancement.
EXTREME MECHANICS LETTERS
(2023)
Article
Physics, Fluids & Plasmas
Thijs de Goede, Karla de Bruin, Noushine Shahidzadeh, Daniel Bonn
Summary: This paper investigates the influence of surface roughness on droplet splashing, showing that rough surfaces can change the splashing velocity of droplets. When the droplet roughness is large enough, it changes the droplet splashing mechanism from corona to prompt splashing. The study also demonstrates that the measured splashing velocity for water and ethanol on surfaces with different roughnesses can be collapsed onto a single curve, indicating that the droplet splashing velocity on rough surfaces scales with the Ohnesorge number defined with the surface roughness length scale.
PHYSICAL REVIEW FLUIDS
(2021)
Article
Chemistry, Applied
Zhihua Zhang, Qiuhua Xie, Tanyu Chao, Li Cui, Ping Wang, Yuanyuan Yu, Qiang Wang
Summary: Cotton fabric was functionalized with zein and rosin, resulting in increased water resistance and hydrophobicity, as well as excellent antibacterial activity. The functionalized fabrics maintained their mechanical properties, air permeability, and water vapor permeability.
PROGRESS IN ORGANIC COATINGS
(2023)
Article
Engineering, Mechanical
Jianjun Bian, Lucia Nicola
Summary: Results from molecular dynamics simulations show that covering the rough copper surface with a wrinkled graphene layer is the best solution for reducing friction.
TRIBOLOGY INTERNATIONAL
(2021)
Article
Engineering, Mechanical
Lin Li, Jinyuan Tang, Han Ding, Dongri Liao, Duncai Lei
Summary: The linear filtering model is commonly used to control the areal autocorrelation function (AACF), but it has limitations in handling anisotropic surfaces and cross-textured surfaces. A new AACF constraint function is proposed in this paper, which can reconstruct isotropic, anisotropic, and cross-textured surfaces more accurately and efficiently. Numerical experiments show that the proposed constraint function improves the fit for isotropic and anisotropic surfaces, but there are still errors for cross-textured surfaces, suggesting room for further improvement in the linear filtering model.
TRIBOLOGY INTERNATIONAL
(2021)
Article
Chemistry, Physical
Fanfan Zhang, Haichang Yang, Xiahui Gui, Han Guo, Yijun Cao, Yaowen Xing
Summary: The morphology of interfacial nanobubbles (INBs) on different hydrophobic surfaces was investigated using TIRF and AFM. The interaction between particles in the presence and absence of INBs was measured using a hydrophobic AFM colloid cantilever. The results show that the formation of INBs is closely related to the hydrophobicity of the substrates, and the size of INBs is positively correlated with the magnitude and range of the hydrophobic interaction force between particles.
APPLIED SURFACE SCIENCE
(2022)
Article
Polymer Science
Takuya Ohzono, Emiko Koyama
Summary: In this study, a photosensitive nematic main-chain liquid crystal elastomer (LCE) with switchable adhesion properties on rough surfaces was demonstrated. The LCE can deform to adapt to rough surfaces under light, resulting in enhanced adhesion ability. By proper light irradiation, the LCE exhibits rubber elasticity, leading to reduced adhesion on rough surfaces. This LCE with switchable elasticity is of great significance for treating objects with rough surfaces.
Review
Mechanics
Daniel Chung, Nicholas Hutchins, Michael P. Schultz, Karen A. Flack
Summary: Reliable full-scale prediction of drag due to rough wall-bounded turbulent fluid flow remains a challenge, with at least 10% uncertainty. Recent advances have lowered barriers and are beginning to impact other multiphysical areas, promising increased predictive reliability.
ANNUAL REVIEW OF FLUID MECHANICS, VOL 53
(2021)
Article
Mechanics
Sahaj Jain, Y. Sudhakar
Summary: Due to the challenges in accurately predicting interface velocities and computing drag components on rough surfaces, an effective model, called the Transpiration-Resistance model, has been developed. This model introduces shear and pressure correction factors as constitutive parameters to accurately predict interface velocities and partition the total drag into viscous and pressure components.
Article
Engineering, Aerospace
Hui Wu, Weifang Chen, Zhongzheng Jiang
Summary: The velocity slip and temperature jump for a two-dimensional rough plate under hypersonic conditions were analyzed using the DSMC method. The effects of relative roughness height on the slip coefficients were discussed, and a new slip model for rough surfaces was established. The modified slip model improves the accuracy of macroscopic properties, especially the heat transfer coefficient.
CHINESE JOURNAL OF AERONAUTICS
(2023)
Article
Materials Science, Coatings & Films
Charisse Marie D. Cagomoc, Michiro Isobe, Eric A. Hudson, Satoshi Hamaguchi
Summary: Molecular dynamics simulations were carried out to investigate the deviation of angular distribution of reflected ions from ideal specular reflection in the scattering of neon, argon, and xenon ions on silicon and silicon dioxide surfaces at grazing incidence. The deviation depends on ion mass, incident angle, and surface material and roughness. This study provides insights into the interaction of energetic ions with the sidewalls of high-aspect-ratio (HAR) channels during reactive ion etching (RIE) in semiconductor manufacturing. The results showed that the angular distribution of reflected ions increases with higher ion mass, smaller incident angle, or rougher surface, which can be used to predict the profile evolution of HAR channels in RIE processes.
JOURNAL OF VACUUM SCIENCE & TECHNOLOGY A
(2023)
Article
Optics
Subiao Bian, Oriol Arteaga
Summary: This work expands the use of spectroscopic ellipsometry to surfaces with roughness that is similar to or larger than the wavelength of the incident light. By using a custom-built spectroscopic ellipsometer and varying the angle of incidence, we were able to differentiate between the diffusely scattered and specularly reflected components. Our findings demonstrate that measuring the diffuse component at specular angles is highly beneficial for ellipsometry analysis, as its response is equivalent to that of a smooth material. This allows for accurate determination of the optical constants in materials with extremely rough surfaces. Our results have the potential to broaden the scope and utility of the spectroscopic ellipsometry technique.
Article
Computer Science, Software Engineering
O. Clausen, Y. Chen, A. Fuhrmann, R. Marroquim
Summary: This study sheds light on the reflectance variations caused by surface roughness in the simulation of light-matter interaction in computer graphics. It provides a thorough analysis of wavelength shifts that lead to reddish and blueish appearances, which have been scarcely reported in previous literature. By measuring spectral in-plane BRDF and surface topography, the researchers confirm that these shifts are diffraction-based effects dominating the overall appearance of rough samples. They propose a linear model and develop a simple BRDF model for these wavelength shifts in light interaction simulations.
COMPUTER GRAPHICS FORUM
(2023)
Article
Chemistry, Physical
Man Wang, Yi Wan, Gongming Xin
Summary: In this study, the influence of vibration on the evaporation and boiling performance of water nanofilm on rough surfaces was investigated using molecular dynamics method. The results showed that vibration suppressed the atomization of water nanofilm, and the atomization modes varied with the amplitude and frequency of the vibration. For rough surfaces, the weakening of vibration-induced evaporation and boiling performance of water nanofilm was attributed to the reduction of surface hydrophilicity.
APPLIED SURFACE SCIENCE
(2023)
Article
Chemistry, Physical
Da Wan Kim, Hyunseung Kim, Geon-Tae Hwang, Sung Beom Cho, Seung Hwan Jeon, Hyeon Woo Kim, Chang Kyu Jeong, Sungwoo Chun, Changhyun Pang
Summary: Researchers have designed an octopus-inspired pattern that enables a wearable device to have a close contact interface with the human body, resulting in improved energy harvesting efficiency. The pattern achieves stable adhesion to the skin through cohesive forces among liquid molecules, even on wet skin, leading to efficient energy generation.
ACS ENERGY LETTERS
(2022)
Article
Chemistry, Multidisciplinary
Myung Woo Na, Se Yun Jeong, Yoon-Joo Ko, Dong-Min Kang, Changhyun Pang, Mi-Jeong Ahn, Ki Hyun Kim
Summary: Evodiae Fructus, the fruit of Tetradium ruticarpum, has antibacterial activity against Helicobacter pylori and can be used to treat gastric and duodenal ulcers. Compound 3 (1-methyl-2-(8E)-8-tridecenyl-4(1H)-quinolinone) exhibited the most potent antibacterial activity and showed potential for the development of novel antibiotics against H. pylori.
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
Chemistry, Multidisciplinary
Gui Won Hwang, Heon Joon Lee, Da Wan Kim, Tae-Heon Yang, Changhyun Pang
Summary: This article introduces a highly adaptive soft microstructured switchable adhesion device inspired by the surface characteristics of octopus suckers. It can stably attach to objects with curved, rough, and irregular surfaces and reliably grasp and transport complex objects.
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
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
Engineering, Environmental
Yeon Soo Lee, Gyun Ro Kang, Min-Seok Kim, Da Wan Kim, Changhyun Pang
Summary: In this study, a double-layered adhesive patch with an octopus inspired architecture (d-OIA) coated with a soft elastomer was proposed, showing enhanced adhesive performance. The patch demonstrated improved adhesion against dry and rough underwater surfaces in the pulling direction. The soft elastomer coated on the elastic octopus-inspired patterns enabled high adaptability to rough surfaces. The patch maintained a vacuum state on rough skin even during frequent bending and stretching, and it successfully detected electrocardiograms (ECG) and electromyograms (EMG) signals in dry and sweaty conditions.
CHEMICAL ENGINEERING JOURNAL
(2023)
Article
Plant Sciences
Se Yun Jeong, Akida Alishir, Shuxiang Zhang, Yinglao Zhang, Sohyeong Choi, Changhyun Pang, Han Yong Bae, Won Hee Jung, Ki Hyun Kim
Summary: Actinomycetes S. neopeptinius BYF101 was isolated from the body surface of the termite and 20 metabolites were identified, including previously unreported obscurolide-type metabolites. The study also discovered a compound with antifungal activity.
JOURNAL OF NATURAL PRODUCTS
(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)
