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Defects are inevitably present in nanofluidic systems, yet the role they play in nanofluidic transport remains poorly understood. Here, we report ab initio molecular dynamics (AIMD) simulations of the friction of liquid water on defective graphene and boron nitride sheets. We show that water dissociates at certain defects and that these "reactive" defects lead to much larger friction than the "nonreactive" defects at which water molecules remain intact. Furthermore, we find that friction is extremely sensitive to the chemical structure of reactive defects and to the number of hydrogen bonds they can partake in with the liquid. Finally, we discuss how the insight obtained from AIMD can be used to quantify the influence of defects on friction in nanofluidic devices for water treatment and sustainable energy harvesting. Overall, we provide new insight into the role of interfacial chemistry on nanofluidic transport in real, defective systems.
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http://dx.doi.org/10.1021/acs.jpclett.6b00280 | DOI Listing |
Nano Lett
September 2025
State Key Laboratory of Materials Low-Carbon Recycling, College of Materials Science and Engineering, Beijing University of Technology, Beijing 100124, P. R. China.
Two-dimensional (2D) nanofluidic architectures with nanoconfined interlayer channels and excess surface charges have revolutionized membrane-based reverse electrodialysis systems, demonstrating highly efficient osmotic energy collection through strong electrostatic screening of electric double layer (EDL). However, the ion-transport dynamics in 2D nanofluidic anion-selective membranes (2D-NAMs) still remain unexplored. Here, we combine density functional theory and molecular dynamics (MD) simulations to systematically explore ion transport in the 2D-NAMs.
View Article and Find Full Text PDFACS Nano
September 2025
College of Energy, Soochow Institute for Energy and Materials InnovationS (SIEMIS), Jiangsu Provincial Key Laboratory for Advanced Carbon Materials and Wearable Energy Technologies, Soochow University, Suzhou 215006, China.
The confining walls made by 2D materials are often considered solid boundary conditions in studies of fluid transport through nanochannels, while the atomically thin walls inherently exhibit thermal fluctuations at a finite temperature. In this work, we investigate the solid-liquid interfacial friction properties of water confined within flexible nanochannels using machine-learning-potential molecular dynamics. Surprisingly, we find that the friction coefficient (λ) increases with lateral size in the flexible nanochannels, following a linear relationship with 1/, which is absent in rigid channels.
View Article and Find Full Text PDFJ Am Chem Soc
September 2025
Key Laboratory of Functional Inorganic Materials Chemistry, Ministry of Education of the People's Republic of China, Heilongjiang University, Harbin 150080, China.
Nanofluidics-based reverse electrodialysis offers a promising approach for harnessing the osmotic energy that exists between saline and fresh water, thereby providing a sustainable source of power. Nevertheless, the key obstacle to realizing a commercially viable power output stems from inadequate ion permselectivity in nanofluidics. Here, we engineer dual asymmetric MXene-based composite nanofluidics (DA-MXCNs) composed of a negatively charged, porous MXene layer and a positively charged, confined MXene layer, which strategically incorporates asymmetric channel dimensions and opposing charge distributions.
View Article and Find Full Text PDFElectromagn Biol Med
September 2025
Department of Mathematics and Statistics, Collage of Science, Taif University, Taif, Saudi Arabia.
This work investigates the electroosmotic peristaltic transport of a Casson (blood)-based hybrid nanofluid via an asymmetric channel embedded inside a porous medium. The model takes into consideration electric and magnetic field effects, Ohmic heating, as well as velocity and thermal slip conditions. The governing equations are simplified and solved by employing unsupervised sigmoid-based neural networks (SNNs), Fibonacci-based neural networks (FNNs), and their hybrid model (FSNNs) under the assumptions of low Reynolds number and long wavelength.
View Article and Find Full Text PDFNat Commun
August 2025
Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, PR China.
Lithium metal negative electrodes are highly promising for high-specific-energy batteries due to their low electrochemical potential and high capacity. However, dendrite growth due to limited Li transport at the interface hinder their performance and safety. Enhancing interfacial Li transport can prevent Li depletion and ensure uniform Li deposition.
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