Article
Chemistry, Multidisciplinary
Hongying Wang, Yajuan Cheng, Zheyong Fan, Yangyu Guo, Zhongwei Zhang, Marc Bescond, Massahiro Nomura, Tapio Ala-Nissila, Sebastian Volz, Shiyun Xiong
Summary: This study reveals how introducing imperfections such as vacancy defects, mass mismatch, and alloy disorder in pillared nanostructures can affect phonon resonance mechanisms and alter the thermal conductivity characteristics.
Review
Materials Science, Multidisciplinary
Muhammad Atiq Ur Rehman, Qianq Chen, Annabel Braem, Milo S. P. Shaffer, Aldo R. Boccaccini
Summary: Electrophoretic deposition (EPD) is a powerful technique for assembling carbon nanotube (CNT) coatings and composite films with controlled architectures. This review focuses on achievements and challenges within the last 15 years, emphasizing the importance of stable CNT suspensions for successful EPD. The advantages of EPD processing include the ability to prepare CNT films and composites with controlled structures, but there are also some disadvantages to consider.
INTERNATIONAL MATERIALS REVIEWS
(2021)
Article
Chemistry, Multidisciplinary
Yubing Hu, Xinyang Liu, Fan Ji, Jie Wei, Wei Jiang, Yanan Zhang
Summary: The study enhanced the interfacial performance of Ti/carbon fiber-reinforced polymer composite laminates by depositing CNTs on a titanium surface through EPD, resulting in improved mechanical properties and reduced delamination damage under dynamic impact.
Article
Chemistry, Multidisciplinary
Harikrishnan N. Nambiar, Francis P. Zamborini
Summary: The hybrid alginate-Au nanoparticle films were prepared by electrophoretic deposition, which was caused by the localized pH drop at the electrode surface due to the oxidation of hydroquinone (HQ) catalyzed by citrate-coated gold nanoparticles (cit-Au NPs) with different diameters. The EPD of alginate occurred at different voltages depending on the size of the cit-Au NPs and the presence of cit-Au NPs resulted in higher catalytic activity for the oxidation of HQ. The post-treatment with Ca2+ solution led to the formation of hybrid Ca-Alg-Au NP hydrogel films.
Article
Materials Science, Ceramics
Daixiong Zhang, Qing Xiang
Summary: This study successfully prepared Bi2O3-MWCNTs coating using Nafion-assisted electrophoretic co-deposition method in ethanol solvent. Compared with coatings prepared with other additives, Nafion-assisted electrophoretic co-deposition showed better capacitance performance. The introduction of MWCNTs significantly enhanced the mass-specific capacitance of the coating, and it exhibited good cyclic stability.
JOURNAL OF THE AMERICAN CERAMIC SOCIETY
(2022)
Article
Chemistry, Physical
Ritwick Kali, Wezi D. Mkandawire, Scott T. Milner
Summary: This study investigates the impact of PAP pore diameter on water mobility and ion rejection using atomistic molecular dynamics simulations, and identifies the limiting PAP geometry that has the highest water permeability while still rejecting ions.
MOLECULAR SYSTEMS DESIGN & ENGINEERING
(2023)
Article
Biotechnology & Applied Microbiology
Adina Sauciuc, Blasco Morozzo della Rocca, Matthijs Jonathan Tadema, Mauro Chinappi, Giovanni Maglia
Summary: Nanopores can be used for protein identification and fingerprinting, and the introduction of spaced charges in the nanopore lumen can generate an electroosmotic flow to induce the unidirectional transport of proteins. This approach allows for the translocation and stretching of natural polypeptides, which can be used for enzymatic and non-enzymatic protein identification and sequencing.
NATURE BIOTECHNOLOGY
(2023)
Article
Polymer Science
Soubhik De, Abhinav Omprakash Fulmali, Krishna Chaitanya Nuli, Rajesh Kumar Prusty, B. Gangadhara Prusty, Bankim Chandra Ray
Summary: This article explores the modification of carbon fiber surface using carbon based nanofillers to improve the mechanical performance of carbon fiber reinforced polymer composites. The study indicates that laminate reinforced with CNT grafted carbon fibers exhibited the highest delamination resistance among all composites at extreme in-situ temperatures.
JOURNAL OF APPLIED POLYMER SCIENCE
(2021)
Article
Physics, Fluids & Plasmas
Xiang Yang, Sahin Buyukdagli, Alberto Scacchi, Maria Sammalkorpi, Tapio Ala-Nissila
Summary: EP mobility reversal refers to the phenomenon where the direction of polymer drift driven by an external electric field is reversed due to the change in sign of the counterion-dressed surface charge. In order to understand this counterintuitive effect, a strong-coupling-dressed Poisson-Boltzmann approach is applied to the cylindrical geometry of the polyelectrolyte-salt system. The derived analytical polymer mobility formula predicts that the increment of monovalent salt, the decrease of multivalent counterion valency, and the increase of the dielectric permittivity of the solvent suppress charge correlations and increase the concentration of multivalent bulk counterions required for EP mobility reversal. Coarse-grained molecular dynamics simulations support these predictions and show the induction of mobility inversion by multivalent counterions at dilute concentrations.
Article
Chemistry, Physical
Fatemeh Mazhari Mousavi, Rouhollah Farghadan
Summary: This study investigates the influence of electric fields on the spin-dependent thermoelectric properties of graphene nanoribbons with asymmetric zigzag edge extensions. The results show that the electric field significantly reduces the spin gap and lowers the threshold temperature, while inducing higher spin currents in the nanoribbons.
PHYSICAL CHEMISTRY CHEMICAL PHYSICS
(2022)
Article
Chemistry, Physical
Haiqi Gao, Jing Wang, Yuzhen Liu, Yannan Xie, Petr Kral, Ruifeng Lu
Summary: Molecular dynamics simulations have shown the significant influence of hydration shells on ions passing through ultrathin carbon nanotubes. Electrically-driven ions tend to drag their hydration shells, while pressure-driven ions can be actively driven by their hydration shells. The different binding strengths of hydration shells to ions of various sizes affect the entry rates and driving speeds of ions in CNTs.
JOURNAL OF CHEMICAL PHYSICS
(2021)
Article
Energy & Fuels
Majid EL Kassaoui, Mohammed Loulidi, Abdelilah Benyoussef, Abdallah El Kenz, Omar Mounkachi
Summary: This study investigates the adsorption affinity of hydrogen on lithium and sodium decorated carbon honeycomb (C-h) structures using dispersion-corrected density functional theory (DFT-D2). The results show that Li- and Na-decorated C-h can adsorb hydrogen molecules with at least 2 times stronger adsorption energy compared to pure C-h (-0.135 eV per H-2). At saturation, 4Li@C-h and 4Na@C-h channels can adsorb 22 and 20 H-2 molecules, respectively, with theoretical gravimetric densities of 5.95 and 5.00 wt %. The activation barriers indicate rapid migration of H-2 molecules within the C-h channels during storage/release cycles. The study suggests that Li-decorated C-h can be an efficient solid-state material for hydrogen storage.
Article
Biochemistry & Molecular Biology
Patryk Bezkosty, Elzbieta Dlugon, Maciej Sowa, Jacek Niziol, Piotr Jelen, Jakub Marchewka, Marta Blazewicz, Maciej Sitarz
Summary: Nanocomposites based on siloxanes modified with carbon nanoforms have great potential in the electronics industry, medicine and environmental protection. This study shows that polysiloxane and carbon nanotube nanocomposite coatings produced by electrophoretic deposition exhibit electrical conductivity and protect metals from corrosion, although their corrosion resistance differs slightly from that of pure polymeric coatings.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2022)
Article
Materials Science, Multidisciplinary
Bruno Alderete, Timothy MacLucas, Douglas Espin, Sonia P. Bruehl, Frank Muecklich, Sebastian Suarez
Summary: The study suggests using carbon nanotube coating as a protective layer for sucker rods to withstand harsh environmental conditions. Three different coating systems were tested, with the duplex coating combining the advantages of both additives for enhanced stability and hydrophobicity.
ADVANCED ENGINEERING MATERIALS
(2021)
Article
Chemistry, Multidisciplinary
Shao-Tuan Chen, Megan N. Renny, Liliana C. Tome, Jorge L. Olmedo-Martinez, Esther Udabe, Elise P. W. Jenkins, David Mecerreyes, George G. Malliaras, Robert R. McLeod, Christopher M. Proctor
Summary: This study successfully reduces passive drug leakage in electrophoretic drug delivery devices by changing the choice of drug co-ions. The method can decrease the steady-state drug leakage rate by up to sevenfold with minimal impact on the active drug delivery rate. Numerical simulations further demonstrate the potential of this approach and provide guidance for new material systems to suppress passive drug leakage in these devices.
Article
Engineering, Multidisciplinary
Sergio M. Martin, Daniel Waelchli, Georgios Arampatzis, Athena E. Economides, Petr Karnakov, Petros Koumoutsakos
Summary: Korali is an open-source framework for large-scale Bayesian uncertainty quantification and stochastic optimization, which efficiently utilizes parallel architectures and surpasses related software frameworks in performance.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2022)
Article
Chemistry, Physical
Pantelis R. Vlachas, Julija Zavadlav, Matej Praprotnik, Petros Koumoutsakos
Summary: The study introduces a novel framework to enhance simulation time scales by learning the effective dynamics of molecular systems. By utilizing mixture density networks and long short-term memory networks, the framework can effectively capture the structural evolution of molecular systems and generate all-atom molecular trajectories.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2022)
Article
Chemistry, Physical
Ermioni Papadopoulou, Constantine M. Megaridis, Jens H. Walther, Petros Koumoutsakos
Summary: The extreme liquid transport properties of carbon nanotubes provide new opportunities for surpassing conventional water filtration and purification technologies. By using carbon nanotubes with wettability surface patterns, we demonstrate the ultrafast transport of water droplets without external pressure gradients. Molecular dynamics simulations reveal unprecedented speeds and accelerations in droplet propulsion caused by interfacial energy gradients. We present a scaling law for water transport based on droplet dynamic contact angle and friction coefficient. These results show that patterned nanotubes can be energy-efficient nanopumps for ultrafast water nanofiltration and precision drug delivery.
JOURNAL OF PHYSICAL CHEMISTRY B
(2022)
Article
Multidisciplinary Sciences
Petr Karnakov, Sergey Litvinov, Petros Koumoutsakos
Summary: The multilayer volume-of-fluid method (Multi-VOF) is an advanced technique for simulating foamy flows. It introduces a scheme to handle multiple non-coalescing bubbles, and has been verified and validated using experimental results. This method allows for accurate simulations of large-scale flows with multiple interfaces.
Article
Multidisciplinary Sciences
H. Jane Bae, Petros Koumoutsakos
Summary: Researchers propose a multi-agent reinforcement learning approach to discover wall models for large-eddy simulations, solving the challenge of capturing near-wall dynamics in turbulent flow simulations.
NATURE COMMUNICATIONS
(2022)
Article
Mechanics
Michail Chatzimanolakis, Pascal Weber, Petros Koumoutsakos
Summary: Direct numerical simulations of flow past an impulsively started cylinder at high Reynolds numbers reveal a cascade of separation events and vortical structures, which are closely related to the forces experienced by the cylinder. This finding provides important references for reduced-order models of flow separation and flow control in high Reynolds number flows.
JOURNAL OF FLUID MECHANICS
(2022)
Article
Biophysics
Lucas Amoudruz, Athena Economides, Georgios Arampatzis, Petros Koumoutsakos
Summary: In this study, a data-driven approach is employed to quantify the stress-free state shape and visco-elastic properties of red blood cells (RBCs) for the first time. A transferable RBC model is introduced based on these quantifications, and its effectiveness is demonstrated through accurate predictions of blood flows under unseen experimental conditions.
BIOPHYSICAL JOURNAL
(2023)
Article
Engineering, Multidisciplinary
Ivica Kicic, Pantelis R. Vlachas, Georgios Arampatzis, Michail Chatzimanolakis, Leonidas Guibas, Petros Koumoutsakos
Summary: Predictive simulations are crucial for various applications, but their accuracy relies on capturing effective system dynamics. Massively parallel simulations are expensive, while reduced order models have limitations. AdaLED is a novel framework that combines large-scale simulations and reduced order models to extract and forecast effective dynamics of multiscale systems. It employs autoencoders and probabilistic recurrent neural networks for fast and adaptable learning, achieving net speed-ups and detecting unseen dynamics regimes. AdaLED is a powerful tool for computationally expensive simulations.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2023)
Article
Chemistry, Physical
Petr Karnakov, Sergey Litvinov, Petros Koumoutsakos
Summary: We introduce a potent computational method for solving inverse problems in fluid mechanics, which accelerates the convergence of gradient-based optimization methods for problems with parameters on a grid. By incorporating a multigrid decomposition technique, we achieve significant improvement in both computational efficiency and the avoidance of local minima. Our results demonstrate that this method, called mODIL, outperforms the popular Physics-Informed Neural Networks (PINNs) method in terms of computational cost, with three to five orders of magnitude lower cost in benchmark problems.
EUROPEAN PHYSICAL JOURNAL E
(2023)
Review
Physics, Applied
Yarin Gal, Petros Koumoutsakos, Francois Lanusse, Gilles Louppe, Costas Papadimitriou
Summary: Five researchers discuss the quantification of uncertainty in machine-learned models, focusing on issues relevant to physics problems. It is crucial to be able to measure uncertainty when comparing theoretical or computational models with observations in order to conduct sound scientific investigations. With the increasing popularity of data-driven modeling, understanding different sources of uncertainty and developing methods to estimate them has become a renewed area of interest.
NATURE REVIEWS PHYSICS
(2022)
Article
Multidisciplinary Sciences
Jana Lipkova, Bjoern Menze, Benedikt Wiestler, Petros Koumoutsakos, John S. Lowengrub
Summary: Increased intracranial pressure is a major source of critical symptoms and death in patients with glioma. Existing models are unable to simulate pressure distribution accurately due to the complexity of model parameters. This study presents a novel model that directly derives pressure from tumor dynamics and patient-specific anatomy, providing non-invasive insights into the patient's condition.
JOURNAL OF THE ROYAL SOCIETY INTERFACE
(2022)
Article
Computer Science, Artificial Intelligence
Pantelis R. Vlachas, Georgios Arampatzis, Caroline Uhler, Petros Koumoutsakos
Summary: In this study, a novel approach is introduced to learn the effective dynamics of complex systems by bridging large-scale simulations and reduced-order models. By combining nonlinear machine learning algorithms and equation-free methodologies, the computational effort of large-scale simulations can be significantly reduced while maintaining the prediction accuracy of the full system dynamics.
NATURE MACHINE INTELLIGENCE
(2022)
Article
Automation & Control Systems
Lucas Amoudruz, Petros Koumoutsakos
Summary: Artificial bacteria flagella (ABFs) are magnetic helical microswimmers that can be remotely controlled via a uniform, rotating magnetic field. The results demonstrate the effectiveness of reinforcement learning in achieving minimal travel time to a target for independent navigation of realistic microswimmers with a uniform magnetic field in a viscous flow field.
ADVANCED INTELLIGENT SYSTEMS
(2022)
Correction
Computer Science, Artificial Intelligence
Guido Novati, Hugues Lascombes de laroussilhe, Petros Koumoutsakos
NATURE MACHINE INTELLIGENCE
(2021)
Correction
Computer Science, Artificial Intelligence
Guido Novati, Hugues Lascombes de laroussilhe, Petros Koumoutsakos
NATURE MACHINE INTELLIGENCE
(2021)